IntroductionMiscommunication during patient handoff contributes to an estimated 80% of serious medical errors and, consequently, plays a key role in the estimated five million excess deaths annually from poor quality of care in low- and middle-income countries (LMICs).ObjectiveThe objective of this study was to assess signout communication during patient handoffs between prehospital personnel and hospital staff.MethodsThis is a cross-sectional study, with a convenience sample of 931 interfacility transfers for pregnant women across four states from November 7 to December 13, 2016. A complete signout, as defined for this study, contains all necessary signout elements for patient care exchanged verbally or in written form between an emergency medical technician (EMT) and a physician or nurse.ResultsEnrollment of 786 cases from 931 interfacility transfers resulted in 1572 opportunities for signout. EMTs and a physician or nurse signed out in 1549 cases (98.5%). Signout contained all elements in 135 cases (8.6%). The mean percentage of signout elements included was 45.2% . Physician involvement was correlated with a higher mean percent  compared to nurse involvement . With respect to the frequency of signout communication, 63.1% of EMTs reported often or always giving signout, and 60.5% reported often or always giving signout; they reported feeling moderately to very comfortable with signout (73.7%) and 34.1% requested further training.ConclusionsPhysicians, nurses, and the EMTs conducted signout 99% of the time but often fell short of including all elements required for optimal patient care. Interventions aimed at improving the quality of patient care must include strengthening signout communication. There are an estimated 5 million excess deaths annually in developing countries due to poor quality of care . HandoveThe World Health Organization (WHO), National Health Services (NHS), Joint Commission, and the Agency for Healthcare Research and Quality (AHRQ) have emphasized the importance of communication. They have laid out specific guidelines for safe handovers ,8. TheseTo date, most research on the impact of inadequate signout communication has been in-hospital studies . Yet, siA study of the signout process in an LMIC between prehospital and hospital healthcare providers is imperative given its importance to quality patient care. This study aims to assess the quality of signout during the patient handoff between prehospital and in-hospital providers.OverviewThis is a cross-sectional study of a convenience sample of pregnancy-related interfacility transfers (IFTs) by an Indian emergency medical services (EMS) provider between November 7th, 2016 and December 13th, 2016 (Monday to Saturday 8 AM to 5 PM for five weeks) across four states: Assam, Gujarat, Himachal Pradesh, and Karnataka. Research assistants’ availability defined data collection hours. IFTs were the focus of the study as they require EMTs to both receive and give signout, resulting in two data points per call. Further, the sample was confined to a single chief complaint because a) it required a uniform set of signout elements and b) calls for pregnancy-related transfers are a major focus for EMS agencies in LMICs - pregnancy-related transfers comprise over 30% of total transfers by the Indian EMS agency studied with over 30% of these being IFTs ), community health centers (283 [36%]), and sub-divisional hospitals (137 [17.4%]). District hospitals received a majority of the cases (357 [45.4%]). The medical college hospitals and sub-divisional hospitals received a major part of the rest .Signout characteristics - complete signoutFrom 786 IFTs, there were 1572 occasions of signout as signout occurs both at the referring and the receiving facility. The EMT and hospital personnel interacted either verbally or in written form or both on 1549 (98.5%) occasions. All required elements were included in signout on 135 (8.6%) occasions. A nurse or a physician at the referring facility gave a complete signout to the EMT on 69 (8.8%) occasions and the EMT gave a complete signout to a nurse or a physician at the receiving facility at a similar frequency (64 [8.1%]). Overall, signout was complete on 133 (8.4%) occasions - on two occasions all elements were included but signout was not performed by a physician or nurse. Least frequently included elements were length of stay in referring facility (269 [17.1%]), interventions during transport (171 [21.8%]) and referring facility interventions (374 [23.8%]) , whereas, in Himachal Pradesh, it was physicians (213 (95.9%)). In Himachal Pradesh, personnel predominantly exchanged written forms (220 [99.1%]) without verbal interaction. The included signout elements varied between states and inclusion of a particular element varied across the states. Providers in Karnataka most often included obstetric history (601 [93%]), whereas those in Assam and Gujarat regularly included primary diagnosis (379 [94.8%] and 295 [97%]) and past medical history (341 [85.2%] and 243 [79.9%])  compared to nursing staff involvement (23.7% [95% CI 22.5-24.8]) . Referring facility signout on an average had 42.8% (95% CI 40.9-44.8) of elements compared to 47.7% (95% CI 45.8-49.5) at receiving facilities . The majority of EMTs reported giving (494 [63.1%]) and receiving (474 [60.5%]) signout "most of the time" or "always”. A minority of EMTs, 267 (34.1%), felt they require further training in signout practices. However, EMTs in Assam differ in their opinions compared to other states. Most report feeling only slightly comfortable giving signout (174 [87.9%]), and they give and receive signout only some of the time (179 [90.4%] and 178 [89.4%]). Moreover, Assam EMTs near-universally felt they require further training (192 [96.5%])  signout elements from a total of 16 ) was comparable to earlier studies performed in countries with mature emergency care systems. In a study by Carter al of 16 . In a stal signs .Reviews on prehospital signout have identified multiple factors that influence signout. Busy emergency departments (ED) with overloaded staff forced to handle multiple tasks at the same time in a chaotic environment offer a greater potential for multiple interruptions and passive listening during handoff ,14,22. Iet al. in their 2008 systematic review identified 24 signout mnemonics used in and out of hospital settings [et al. in their study on changes in medical errors after implementation of the I-PASS system noted a 23% decrease in the rate of medical-errors  and a 30% decrease in the rate of preventable adverse events  [From among these factors, structured signout is afforded much importance, and multiple signout tools have been developed and studied. Despite not having a formal process or utilizing a specific signout tool, at the state level an innate structure has developed to support the signout process as evidenced by the distinct interstate variation identified in this study. Further, states are fairly consistent with the type of provider involved in signout, the method used, and the number and type of signout elements included. Use of checklists; standardization of signout components with the use of mnemonics; and computerization of such checklists have been shown to improve signout efficiency in other settings and may improve the quality of signout in LMICs as well ,26-27. Usettings . Despitep<0.001) .Standardization with mnemonics alone may be insufficient for improving communication and the quality of emergency care in India and other countries. Reviews on prehospital signout suggest shared mental models that achieve a common language and understanding between prehospital and hospital care providers as important for strengthening communication -12. A shOf note, the EMT-B training program has a session on communication across the states included in the study. Furthermore, based on a review of the literature and direct observation, they are also developing a novel continuing education module to promote consistent signout communication. In the future, integrated sessions for EMTs and hospital care providers in LMICs, and potentially elsewhere, should cultivate the development of a shared mental model and team-based learning.LimitationsThis study provides a snapshot of signout practices but does not identify the cause for the low frequency of a complete signout. Further, the signout elements included were identified at a broad level and lacked specific details. This study was based on EMT’s self-report as a screening of the written documents and direct observation of the handover was not possible at the time of this study. Moreover, another potential limitation would be the Hawthorne effect. EMTs were aware that data collection would occur which may influence the reporting of signout elements. We believe the recall bias is limited as the EMT was called immediately after the patient was transferred. Finally, the reason for the transfer was included in referring facility signout and missed in receiving facility signout during data collection.Physicians or the nurses and the EMT communicated on 99% of signout opportunities and included 45.2% of recommended signout content. The rate of a complete signout by EMTs was comparable to the rate of a complete signout by physicians and nurses. Improvement requires a multifactorial interdisciplinary approach - one that accounts for the unique ambulance hospital interface. Recognition by ambulance and hospital-based providers on the critical nature of signout in providing quality care is imperative. Interventions should include a standardized signout process, coordinated training that fosters a shared mental model, and integrated information systems.


Pulmonary artery (PA) sarcoma is an extremely rare malignant tumor of pulmonary artery. It is often misdiagnosed as pulmonary thromboembolism (PTE) because of its clinical and imaging features which are quite similar to PTE. Multimodality diagnostic imaging and recognition of specific imaging characteristics with appropriate clinical suspicion are required to make correct diagnosis. In this report, we present a case of PA sarcoma with imaging and clinical features as well as emphasize significance of using multimodality imaging. Pulmonary artery (PA) sarcoma is a rare tumor originating from mesenchymal cells of pulmonary artery. Patients with PA sarcoma usually present with nonspecific pulmonary symptoms such as dyspnea, cough and haemoptysis. In addition, main manifestation of PA sarcoma on computed tomography pulmonary angiography (CTPA) is filling defect, which mimics PTE. Due to its nonspecific clinical and imaging features, early diagnosis is tough preoperatively . Delays A 64-year-old woman admitted to our hospital with a 1 month history of dyspnea. Her medical history also revealed that she received antibiotic and anticoagulant therapy for diagnosis of PTE and pneumonia in the past 2 weeks but had no clinical improvement. Physical examination was unremarkable. Laboratory test showed elevated D-dimer level (1990 ng/ml) and C-reactive protein (16.6 mg/dl). Levels of tumor markers were normal. Transthoracic echocardiography showed high pulmonary artery pressure (65 mmHg). She underwent CTPA with suspicion of pulmonary emboli. Thrombus at the lower extremities was not detected on venous Doppler ultrasound. CTPA demonstrated intraluminal filling defect at the pulmonary trunk extending right and left pulmonary arteries. Expansion of the involved pulmonary arteries and extension to segmental-subsegmental branches were also noted . In addiet al. as 100% specific to PA sarcoma on magnetic resonance imaging (MRI). Moreover, the authors believed that this feature shows malignant nature of sarcoma, which grows rapidly and invades to segmental-subsegmental branches of PA [Pulmonary artery (PA) sarcoma arises from the intimal layer of pulmonary trunk and main pulmonary arteries. It has very poor prognosis and only chance of survival is early diagnosis with radical surgical resection. However, clinical manifestations of PA sarcoma are nonspecific and imaging features are very similar to those of PTE. In a study, based on imaging and clinical criteria, 47% of the patients were initially considered to have PE including 39% receiving anticoagulant therapy . CTPA ises of PA . In the es of PA . CompareIn spite of its less prevalence, PA sarcoma should be considered in differential diagnosis of the patients presenting with PTE particularly in those with inadequate response to thrombolytic therapy. Combining various imaging modalities and recognizing of characteristic CTPA features associated with high suspicion are important in precise diagnosis of PA sarcoma and preventing delays.


Cardiac pumping depends on the morphological structure of the heart, but also on its subcellular  architecture, which enables cardiac contraction. In cases of congenital heart defects, localized ultrastructural disruptions that increase the risk of heart failure are only starting to be discovered. This is in part due to a lack of technologies that can image the three-dimensional (3D) heart structure, to assess malformations; and its ultrastructure, to assess organelle disruptions. We present here a multiscale, correlative imaging procedure that achieves high-resolution images of the whole heart, using 3D micro-computed tomography (micro-CT); and its ultrastructure, using 3D scanning electron microscopy (SEM). In a small animal model (chicken embryo), we achieved uniform fixation and staining of the whole heart, without losing ultrastructural preservation on the same sample, enabling correlative multiscale imaging. Our approach enables multiscale studies in models of congenital heart disease and beyond. The heart is our hardest-working organ and beats around 100,000 times a day, pumping blood through a vast system of vessels to all areas of the body. Specialized heart cells make the heart contract rhythmically, enabling it to work efficiently. Contractile molecules inside these cells, called myofibrils, align within the heart cells, and heart cells align to each other, so that the heart tissue contracts effectively.However, when the heart has defects or is diseased this organization can be lost, and the heart may no longer pump blood efficiently, leading to sometimes life-threatening complications. For example, around one in a hundred newborn babies suffer from congenital heart defects, and despite medical advances, these conditions remain the main cause of non-infectious mortality in children.Many cases of congenital heart disease are diagnosed before a baby is born during an ultrasound scan. However, these scans, as well as subsequent diagnostic tools, lack the precision to detect problems within the heart cells. Now, Rykiel et al. used two complementary imaging techniques known as micro-computed tomography and scanning electron microscopy to acquire pictures of the whole heart as well as of the organization inside the heart cells.This made it possible to capture the structure of the heart tissue at both micrometer (the whole heart) and nanometer resolution (the inside of the cells), and to study what happens within the heart and its cells when the heart has a defect.Rykiel et al. tested the imaging technology on the hearts of chicken embryos, at stages equivalent to a five to six-month-old human fetus, and compared a healthy heart with a heart with a defect called tetralogy of Fallot. They found that the tissues in the heart with a defect had a sponge-like appearance, with increased space in between cells. Moreover, the myofibrils of the heart with a defect were aligned differently compared to those in the normal heart.More research is needed to fully understand what happens when the heart has a defect. However, the imaging technology used in this study offers the possibility of examining the heart at an unprecedented level of detail. This will deepen our understanding of how structural heart defects arise and how they affect the pumping of the heart, and will give us clues to design better treatments for patients with heart defects and other heart anomalies. Congenital heart disease (CHD), which manifests as a morphologically defective heart, affects about 1% of newborn babies, and remains the primary cause of non-infectious children mortality in the developed world . While CImaging approaches have been employed to study cardiac function in normal and CHD hearts . In humaThe structural  characteristics of heart malformations, including changes in cardiac wall architecture, have been extensively studied. However, the mechanisms that lead to an anomalous cardiac architecture in CHD and the clinical consequences of it are unknown. Recent studies have revealed an abnormal orientation of myocardial cells (the heart muscle cells) within CHD hearts . Myocard3). The methodology we present herein improves upon previous protocols by achieving uniform staining of a relatively large heart sample (4-5 mm wide), circumventing micro-CT X-ray penetration issues, and allowing sample screening and selection prior to full SEM sample preparation. Our multiscale imaging, further, enables mapping of structural and ultrastructural heart features.We describe here a proof-of-concept correlative multiscale procedure that combines imaging of whole heart morphology and its subcellular organization . Our multiscale procedure uses micro computed tomography (micro-CT) imaging to capture heart morphology at micrometer resolution, and scanning electron microscopy (SEM) to capture cardiac tissue ultrastructure at nanometer resolution. Current SEM technologies allow for three-dimensional (3D) imaging, enabling reconstruction and quantification of ultrastructural features within a tissue volume . Among 3As proof of concept, we applied our developed multiscale imaging procedure to two embryonic chick hearts. These hearts were collected at stages corresponding to about 5–6 months of human fetal development, when the heart is already formed but maturing in preparation for birth/hatching. We imaged: (1) a control heart with no structural defects and (2) a heart with tetralogy of Fallot (TOF), a combination of structural heart malformations found in humans . Our resStep 1 the heart was excised, homogeneously fixed and stained for micro-CT. Initial staining followed a modified ferrocyanide-reduced osmium–thiocarbohydrazide–osmium (ROTO) protocol  section of the block, which also determined ultrastructural quality and enabled registration to micro-CT images. In Step 3, a slab of the sample was cut and sectioned around a specific region of interest  from which sub-ROIs for 3D SBF-SEM imaging (~40×60 μm2) were selected. In Step 4, 3D SBF-SEM datasets were acquired .To achieve multiscale imaging, we followed a four-step protocol  a normal heart and (2) a heart exhibiting TOF malformation. In a normal heart, blood in the left ventricle (LV) and right ventricle (RV) is separated by an interventricular septum; the pulmonary valve and pulmonary artery connect to the RV, which pumps blood to the lungs; and the aortic valve and aorta connect to the LV, which pumps blood to the body. TOF is characterized by a combination of four defects: (i) ventricular septal defect, which is a hole in the interventricular septum; (ii) overriding aorta, a change in the position of the aorta such that it sits in the middle of the two ventricles, on top of the ventricular septal defect; (iii) pulmonary stenosis or atresia, a narrowing or closure of the pulmonary artery or pulmonary valve; and (iv) RV hypertrophy, a thickening and enlargement of the RV wall. RV hypertrophy in TOF, however, develops over time as the stenosis of the pulmonary artery increases pressure in the RV after birth  and was From micro-CT images of the two hearts, we quantified cardiac structural features for illustration purposes. It is important to mention, however, that these quantifications only pertain to the two hearts compared in this study, and thus are not necessarily representative of normal nor TOF heart populations. For the two hearts compared, we found that the LV volume was about the same in the normal, control (CON) heart and TOF hearts. However, in the CON heart the RV volume was 40% smaller than the LV volume (RV volume/LV volume ~0.6), while in the TOF heart RV volume was 30% larger than the LV volume (RV volume/LV volume ~1.3). Overall the volume of the TOF RV was about twice as big as the CON RV, suggesting functional impairment of the TOF RV.ultrastructural architecture of the selected hearts at approximately the transverse section at which the heart width  is maximal, also referred to as the equatorial plane. Images of semithin cross-sections for each heart (Step 2 in We chose to characterize the Step 3 in 2) were imaged at 10 nm lateral resolution, and we acquired 800–1000 images in depth . These high-resolution images showed the conservation of ultrastructural features , ultrastructural features could be visualized from any angle of view within the reconstructed images see . Thus SBTo more easily visualize and quantify cardiac ultrastructure, we segmented (delineated) from SBF-SEM images the cell nuclei, myofibrils, mitochondria, and the extracellular space. To this end, we used a combination of deep learning algorithms and tools available on the Dragonfly 4.1 software . When independently tested against carefully annotated images , the segmentation accuracy from the deep learning algorithm was at least 90% for myofibrils, 94% for mitochondria, and 98% for nuclei. Additional manual segmentation ‘clean up’ was thus required to improve the accuracy of organelle depictions. These segmentations, however, reveal the detailed 3D ultrastructural architecture of the heart wall e.g. see .Ultrastructural quantifications of the two hearts were performed for illustration purposes. To control the accuracy of segmentations for quantification, we used subsets of the full SBF-SEM datasets by selecting images and regions within images from the complete dataset. From these selected image regions, we quantified the percentage of the cell occupied by nuclei, myofibrils, and mitochondria. That is, we quantified selected organelle density within cells. We found that, for our two hearts, the density of nuclei, myofibrils and mitochondria was similar between the CON and TOF hearts see . We alsoVisualization of segmentations of the entire sub-ROIs from region A of the CON and TOF hearts revealed a slightly different orientation of myocardial cells between samples . QuantifHeart function relies on a multiscale, finely orchestrated contractile machinery. Efficient heart pumping requires a highly organized cardiac architecture linked to the cell metabolism . StructuThe heart walls contain myocardial cells, which are elongated, cylindrical-like muscle cells that are aligned in patterns that optimize cardiac contractility . In humaThe correlative, multiscale imaging approach presented here was implemented and optimized in a chicken embryo model of heart development and CHD . Heart dThe correlative multiscale imaging approach presented here could provide new insights into the underpinnings of heart development, and on cardiac mechanical changes in CHD. For example, analysis of multiscale cardiac images over developmental stages could be used to unravel how cardiac tissues progressively assemble and mature at diverse scales to form a functional heart. When cardiac development is perturbed  multiscale images can be used to reveal how the natural maturation and assembly of cardiac components  are altered, sometimes in irreversible ways that lead to CHD. Multiscale images, furthermore, promise to reveal differences and similarities among CHD hearts with different phenotypes, as well as among hearts with similar phenotypes resulting from diverse insults. Moreover, the combination of morphological and ultrastructural cardiac imaging data can predict the mechanical function of the heart. Indeed myocardial disarray or marked reductions in myofibrils, for example, will decrease the contraction efficiency (and force) of cardiac tissues. In turn, decrease contractility affects cardiac efficiency, including compromised ejection fraction and stroke volume.Researchers have used EM techniques, including SEM, for decades to visualize the organization of organelles within cells . In the 3), which facilitates proper sample preparation. In preparing samples, portions of the heart are typically excised, carefully prepared for imaging (fixed and stained) . Because the ultrastructural features analyzed are at the nanometer scale, samples used for EM are typically very small (<1 mmstained) , and thestained) . Using tstained) . Our metWhole animals and organs have been scanned with computed tomography (CT), a 3D X-ray imaging modality, to determine the internal and external structure of organs, including the heart. For small animal models, micro-CT, a high-resolution CT, is typically employed . To enhaThe discrepancy in the scale at which we acquire micro-CT and SBF-SEM images introduces fundamental differences in the requirements for sample preparation. Due to diverse fixation and staining protocols , tissuesApplications combining micro-CT and EM technologies have recently begun to emerge, for example . HoweverSample preparation for SBF-SEM required strong, immediate fixation to preserve the ultrastructure of the heart tissue. We used a modified Karnovsky’s fixative with equal parts glutaraldehyde and paraformaldehyde. The paraformaldehyde rapidly penetrated and temporarily stabilized the tissue, and the slower-penetrating glutaraldehyde, a superior cross-linker, more permanently preserved the tissue sample . An obviFor 3D SBF-SEM images, heart samples were further stained with a combination of heavy metals. This is because SEM images are acquired via the detection of secondary and backscattered electrons that are emitted as the tissue is scanned with a high energy beam of primary electrons . Soft biFor whole-heart samples, we found that staining with uranyl acetate and lead aspartate rendered resin-embedded hearts opaque to micro-CT imaging (data not shown). Our multiscale multimodality imaging procedure overcame these difficulties by performing micro-CT imaging after ROTO (see above) but prior to the lead and uranium staining steps, such that correlative 3D micro-CT and 3D SBF-SEM could be implemented. This initial modified ROTO post-fixing and staining provided tissue contrast for micro-CT while also ensuring that the sample was preserved and stabilized before final SBF-SEM sample preparation and imaging see . In addiDue to the size of the hearts and slow diffusion (penetration) of heavy metals into the tissue, achieving uniform staining during further SBF-SEM tissue processing was not straightforward. Initial iterations of the procedure (data not shown) resulted in a strong gradient of staining into the heart tissue, a manifestation of poor stain penetration . ApplicaWhile the focus of this study was to demonstrate homogeneous staining and fixation, our procedure enables correlative microscopy. One way to achieve accurate localization of ultrastructures within the heart structure, is to register semithin transverse sections to micro-CT images, and then SBF-SEM images to the semithin images  , togetheMicro-CT images reveal the microstructural characteristics of hearts. Not only could we classify the hearts based on phenotype , but cardiac characteristics, such as heart size and wall thickness could be visualized and quantified. For example, it was noted from our analysis that the RV of the TOF heart exhibited a larger volume than that of the CON heart examined here see . During Another difference between the two hearts was that the ventricles of the TOF heart exhibited less dense tissue and a more extended trabecular architecture compared with the control heart. This is consistent with reduced myocardial compaction in TOF . The heaWe noticed differences in SBF-SEM image sharpness, which are attributable to excessive ‘charging’ (accumulation of static charge on a sample’s surface) when scanning the TOF heart . The incWhile 2D EM images have been invaluable in deciphering ultrastructural features of myocardial cells and tissues, 3D images can unravel more details in the spatial organization of the ultrastructural architecture . As an ePrevious studies have detailed the congenital heart anomalies associated with outflow tract banding (OTB) Direct application of the proposed multiscale imaging method to human hearts is limited. The method presented here is destructive, and thus can only be applied to human samples of deceased individuals. Moreover, the larger size of the human heart will lead to difficulties in attaining homogeneous fixation and staining. To circumvent fixation and stain homogeneity issues, increased timing for diffusion of fixative and heavy metal stains is certainly a possibility as is microwave steps (to accelerate diffusion). In addition, changes in processing, such as sectioning of hearts after micro-CT to facilitate diffusion of heavy metal stains and control imaging are also possible. As presented, using our methods, multiscale imaging of human hearts is limited.Our correlative, multiscale imaging procedure allowed us to acquire detailed micro-CT images of an entire embryonic chicken heart see , followeWhile our multiscale imaging approach was implemented and optimized using embryonic chicken hearts, we expect it will be straightforward to adapt it for use in mouse and other small animal models of cardiac malformations. It will be advantageous to use complementary models, as typically genetic insults are studied using mouse models, while environmental perturbations are studied using avian models. Heart dimensions in those species (mouse and chicken) are very similar, and we anticipate that tissue processing will not differ significantly. Slight increases in heart size may just require an increase in protocol staining times. Extending the approach to different species and models of congenital heart disease will likely enable us to understand in detail the similarities and differences between cardiac defects, and the underpinnings of malformations that result from genetic and environmental insults.ILAR News 1991; 33(4):68–70), the NIH’s ‘Office for Protection from Research Risks has interpreted ‘live vertebrate animal’ to apply to avians only after hatching.’ Our Institutional animal care and use committee (IACUC) follows NIH interpretation. Therefore, chicken embryos are not considered animals and our research did not require approval. Incubator logs in the lab were monitored daily to ensure there were no eggs near the hatching time of 21 incubation days. Nevertheless, we used the minimum possible number of embryos to achieve our goals.Our research used chicken embryos. According to the US National Institutes of Health (NIH) Office of Laboratory Animal Welfare , and applied to a chick animal model of congenital heart disease. Chicken embryos were prepared as described previously . BrieflyAt HH38, embryonic whole hearts were excised and fixed as follows. The chest cavity was opened and the pericardial sac around the heart gently removed with forceps. Each heart was arrested by injecting 500 µL of chick ringer solution containing 60 mM KCl, 0.5 mM verapamil, and 0.5 mM EGTA  into theStep 1). Each heart was placed in a 5 mL glass scintillation vial and we used 3 mL of solution per vial for each incubation/wash. First, the fixed hearts were washed in 0.1M Sodium Cacodylate (pH 7.4) for 20 min with 4 exchanges of fresh buffer. Next, the hearts were incubated in 0.1% (w/v) of tannic acid in 0.1M Sodium Cacodylate (pH 7.4) for 15 min at room temperature. Samples were then washed in 0.1M Sodium Cacodylate (pH 7.4) for 20 min with 4 exchanges of fresh buffer. Since the reducing agents used in subsequent steps (modified ROTO protocol) were light-sensitive, the sample vials were covered in aluminum foil from this point on. The whole hearts were post-fixed in 2% (v/v) Osmium Tetroxide (OsO4) and 1.5% (w/v) Potassium Ferricyanide (K₃[Fe(CN)₆]) in distilled water (dH2O) for 2 hr at room temperature on a rotating platform. The samples were then extensively washed in dH2O for 20 min with four exchanges of fresh dH2O. Next, the samples were immersed in 0.1% (w/v) Thiocarbohydrazide (TCH) solution in dH2O, placed in an oven, and incubated for 40 min at 60°C. This step was followed by another four exchanges of fresh dH2O over 20 min. Samples were then immersed in a 2% (v/v) OsO4 solution in dH2O for 2 hr at room temperature on a rotating platform. Finally, the hearts were washed extensively in dH2O over 20 min with four exchanges of fresh water. Each heart was stored in dH2O at 4°C until imaged by micro-CT. This preparation provided excellent contrast for micro-CT scans (see Results).In order to enable both whole-heart micro-CT imaging and subsequent SBF-SEM imaging of regions of interest (ROIs), we processed fixed hearts for micro-CT using the initial portion of a Renovo Neural, Inc  protocol  designed4) water does not damage the tissues.Micro-CT images of whole hearts were acquired to assess the cardiac structure. We acquired high-resolution (~10 μm) 3D scans of each heart using a Caliper Quantum FX Micro-CT system  with 10 mm field of view, 140 μA current, 90 kV voltage, and a scan time of 3 min. We used the Amira 6.0 software platform (FEI Company) or Dragonfly 4.1 software  to visualize these scans and identify cardiac defects. Hearts were then stored in double distilled water at 4°C until further processing. Please note that at this step in the processing (cardiac tissues fixed and post-fixed with OsOStep 2), following the Renovo Neural, Inc protocol. In large samples, like the whole hearts described in this manuscript, it is necessary to extend most of the staining steps. Failure to extend the timing of staining resulted in a heterogenous stain distribution throughout the tissue (in our early iterations of the procedure). In our final, optimized procedure, we incubated the samples in 1% (w/v) aqueous uranyl acetate for 24 hr at 4°C, after which they were washed in dH2O for 30 min with 6 exchanges of fresh dH2O. We then incubated the samples in lead aspartate for 30 min at 60°C. The samples were then extensively washed in dH2O for 20 min with 4 exchanges of dH2O. Dehydration steps were done in a series of acetone-dH2O mixtures ; each step was repeated twice for 5 min at room temperature. The whole heart sample was then embedded in an epoxy (Epon 812) resin for further manipulation and SBF-SEM sample preparation. The first infiltration step was done for 1 hr at room temperature in a mixture of 1:1 (v/v) acetone:epon followed by a 1:3 (v/v) acetone:epon incubation for 1 hr at room temperature. The hearts were subsequently incubated overnight in pure (100%) epon on a rotating platform. The following day the epoxy solution was exchanged four times, each time with 30 min incubation steps at room temperature. Samples were polymerized at 60°C for 48 hr in a conventional oven, leading to a whole heart sample embedded in an Epon block.After whole hearts were imaged with micro-CT, sample preparation of selected hearts for 3D SBF-SEM imaging was finished see ; Step 2,Step 2). This step is crucial since the SBF-SEM imaging requires samples with extremely good contrast. Semithin sections were imaged on a Teneo Volume Scope in low vacuum mode using a VS-DBS backscattered electron detector and the MAPS software (FEI Company). Imaging conditions used were 2.5 kV and 0.2 mA, dwell 3–5 µs. In some cases, the samples imaged using this method needed to be coated with a thin (5–8 nm) layer of carbon to minimize charging artifacts induced by the electron beam.Using the micro-CT images as reference, the Epon-embedded heart blocks were sectioned to reach a selected short axis (transverse) section using a diamond-wire jewelry saw. For this study we selected the mid cardiac transverse section, at a plane where the heart is wider . After this step, a semithin section (250 nm) was obtained using an ultramicrotome and mounted on a silicon chip previously glow discharged for 1 min at 15 mA . Semithin section images were used to confirm the area of interest as well as to check for both the ultrastructural quality of the sample and the success of the staining procedure see ; Step 2.Step 3). The slabs were sectioned into smaller ROIs, which were subsequently mounted on Microtome stub SEM pins (Agar Scientific 61092450) using H20E Epo-Tek silver epoxy (Ted Pella 16014) and cured overnight at 60°C in a conventional oven. The resulting small blocks were then trimmed using a Trim90 diamond knife (Diatome) to generate a pillar of 500 × 500 µm2. The block was then coated with 20 nm of gold using a Leica ACE 600 unit.The same diamond-wire jewelry saw was then utilized to generate a slab (~1.5 mm) from the sample see ; Step 3.Step 4). 3D image acquisition was done on a Teneo Volume Scope SBF-SEM in low vacuum mode (50 Pa) using a VS-DBS backscattered detector. Images were acquired at a lateral resolution of 10 nm/pixel and image sets included 800–1000 serial sections (with each section thickness measuring 40 nm in the z axis). SBF-SEM data sets were approximately 40 μm × 60 μm×32–40 μm.In the last step of our multiscale imaging procedure, 3D SBF-SEM images of sub-ROIs selected from the mounted sample were acquired see ; Step 4.All registration, of SBF-SEM data was performed with Amira 6.0 (FEI Company). First, complete image stacks (800–1000 slices) from each ROI and sub-ROIs were automatically aligned to generate a continuous 3D volume. Next, a non-local means filter was applied to every 2D slice in order to improve the signal-to-noise ratio. Due to slight differences in the intrinsic properties of the tissue, sections from the TOF heart appeared slightly lighter compared to the control heart. We adjusted the intensity of the TOF sections during post-processing to match that of the control heart.To better appreciate ultrastructural differences between the two hearts, we used Dragonfly 4.1 software to segment and quantify SBF-SEM images. We segmented: cell nuclei, mitochondria, myofibrils and the extracellular space . The segmentation used a combination of tools in Dragonfly, including deep learning algorithms. Briefly, we employed a six-level U-Net deep learning model  implemen3. For quantification purposes, we segmented and further curated smaller portions of the data sets from two corresponding regions of the control and the TOF hearts (regions A and B). Quantifications of extracellular space and nuclei were done from 17 evenly spaced images from the 800 image datasets of region A; and 21 evenly spaced images from the 1000 image datasets of region B (thus every 50th image was used for these segmentations). For quantification of mitochondria and myofibrils, we cropped images (n ≥ 10) so that we could focus on smaller regions, allowing us to manually improve the accuracy of segmentations in a more tractable manner and focusing on myocardial regions.For visualization purposes, we segmented a whole dataset from the control heart and an approximately corresponding dataset from the TOF heart , and the surface area occupied by extracellular space (SE), nuclei (SN), mitochondria (SMit) and myofibrils (SMyo). We then computed the fraction of the total surface area occupied by the extracellular space (SE/ST); and the fraction of the cell occupied by organelles , computed as the ratio of organelle surface  to the cell surface (Si/(ST - SE)). Because quantifications were performed from different portions (n ≥ 10) of the dataset, average and standard deviations were calculated to represent quantifications for the dataset .Quantifications were performed based on segmented images. We quantified, from each image or image portion, the total surface area (SMyofibril orientation (angle) quantifications were also performed. To this end, we used the myofibril segmentations in the transmural image plane (x-y), split them into individual segmentations (each myofibril was separately assessed using the multi-ROI functions in Dragonfly) and quantified the transmural angle of each myofibril, as the angle with respect to the x-direction, θ angle. Because the x-direction was approximately parallel to the wall boundary, θ = 0° represents myofibrils that are oriented parallel to the wall or in circumferential direction, and θ = 90° are myofibrils oriented towards the ventricle lumen in the radial direction. Angular quantifications were plotted as histograms showing frequency (number of myofibrils) versus an angular range. For quantifications in the x-z plane , we re-sampled the images acquired in the x-y plane, to obtain images in the x-z plane, and then performed the quantifications as before. We quantified the elliptical orientation angle of each myofibril (x-z plane) with respect to the x-direction, Φ angle. Thus Φ = 0°, represents myofibrils that are oriented circumferentially around the ventricle, and θ = 90° are myofibrils oriented longitudinally along the ventricular wall see . Results In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Your proof-of-principle article provides a very useful multi-scale approach to correlate ultrastructural and cellular findings with tissue geometry and structure relevant to cardiac morphogenesis and malformations. This general approach can be applied to a wide range of questions relevant to developmental biology and the origins of congenital malformations.Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Karthik Kodigepalli (Reviewer #3).Thank you for submitting your work entitled "Multiscale imaging of the whole heart and its internal cellular architecture: Application to congenital heart disease" for consideration by eLife.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife at this time. In addition to text edits, 2 of the 3 reviewers recommend a larger number of embryos are required to determine the accuracy of the proposed methods, including sufficient numbers for statistical analysis. The manuscript would also be strengthened by quantitative alignment analysis in addition to qualitative comments.The reviewers found the current manuscript to present an interesting approach of combining micro-CT imaging with regional histology in the avian heart, however, 2 of the 3 reviewers felt that the findings of the current manuscript are too preliminary to warrant publication in Reviewer #1:Essential revisions:1) The current title suggests that the described methods are applicable to a better understanding of congenital heart disease (CHD). However, it would be more accurate to state the current described findings in 2 non-beating chick hearts  is a "Proof of Principle" for correlating changes in macroscale abnormalities in cardiac structure with microscale changes in tissue and cell composition (as mentioned in the Introduction).2) The authors should comment on, aside from the technical accomplishments of the approach, how this data provides new insights into errors in cardiac morphogenesis, altered growth and adaptation, or the changes in mechanical function that occur in CHD.3) The authors should discuss, briefly, how changes in myofiber architecture are related to mechanical function  since changes in mechanical loading and function can result in multiscale changes in cardiac architecture.4) The paper would be strengthened by the analysis of larger number of imaged hearts  to better understand the reproducibility of the described methods. This paper uses a single normal and a single abnormal heart, and describes the results from 2 regions of interest from the LV free wall of each specimen. The only significant difference between the 2 specimens was the increase in extracellular space noted in the TOF specimen . The paper would be strengthened, for example, by the analysis of adjacent ROIs in the same heart to determine reproducibility and by comparison of specimens from both LV and RV specimens.5) The authors highlight the ability to classify phenotype, heart size, and wall thickness with their technique (subsection “Comparison of control and TOF hearts and limitations of this study”), however the paper lacks any discussion of the now readily available and less time-consuming approach of using of high-resolution echocardiography to acquire data on multiple time points from beating avian and mammalian developing hearts. It is important to explain how the multiscale data derived from this approach complements currently available data sets.6) It is important for the authors to reference the studies that detailed the congenital cardiac anomalies associated with conotruncal banding in the chick embryo which are associated with abnormal neural crest migration, altered aortic-mitral valve continuity, aortic valve override, VSDs, and abnormal conotruncal septation . This mechanism for altered conotruncal septation may be very different from the altered neural crest and conotruncal anomalies in the chick embryo produced by neural crest ablation  which may impact the changes in myocardial and myofiber orientation and maturation.The technical details of the current studies are excellent (with the exception of the lack of quantitative data on cellular orientation).Introduction:This sentence can be more clearly restructured. It would be more accurate to state that most studies of the myocardial architecture, including the analysis of myofiber architecture and cellular constituents have found all to be abnormal in the setting of congenital cardiac malformations. What is unknown is the mechanisms responsible and the subsequent clinical consequence…It would not be accurate to state that the results of a small number of studies on myofiber architecture have been "ignored while planning treatment strategies" and would probably be more accurate to say that those myofiber studies have not been proven to be relevant to decisions regarding treatment strategies. This sentence should simply state that emerging evidence supports the importance of myofiber disarray in CHD which may impact cardiac function before and after interventional procedures.The authors should include 1 or 2 references to other imaging approaches, such as OCT and the use of high-resolution echocardiography for cardiovascular phenotyping of CHD in developing avian and mammalian developing hearts.The authors should provide an updated pathogenesis that TOF results from abnormal neural crest cell migration and altered aortopulmonary septation which can present with a range of phenotypes including four basic features  .Figure 4. The RV and LV should be identified in the CON and TOF hearts.Subsection “Image segmentation and quantification” and Figure 8. The authors suggest that Figure 8 shows a change in the orientation of myocardial cells but no quantitative data (or data on specimen reproducibility) is provided. This impression would be strengthened by some quantitative data and some evidence that a known external reference point was used to orient the specimens prior to histologic processing.Subsection “Conclusions” The text suggests that this approach "enables analysis of both whole heart and ultrastructural architecture" however only a small segment of the ultrastructure was assessed. It is more accurate to say, "The described approach allows the correlation of macro and micro-scale architecture in selected regions of the heart".Reviewer #2:The manuscript by Rykiel reports an improved method for microCT analysis of heart anatomy followed by ultrastructural analysis of myocardial cells in the same sample. Analysis of a control and malformed embryonic chicken heart is shown as proof of principal for the utility of this technique. The main advantage of the reported method is improved fixation and imaging of the same samples. However, there are several limitations of the method as shown in the current study.Essential revisions:1) In order for this method to be useful in rigorous analysis of cardiac anatomy and cellular organization, additional quantification and evidence for reproducibility of the methods are needed. The current manuscript analyzing n=1 sample sizes is inadequate to determine if reproducible quantitative data can be obtained using these methods.2) Quantification of additional parameters in the microCT and SEM studies are needed.3) Tests of statistical significance were performed based on multiple measurements of the same samples. These tests are not appropriate for the n=1 sample sizes in the current study.4) It is difficult to appreciate the benefit of the 3D ultrastructural analysis from the images shown. It is difficult to appreciate the features of interest in Figure 6, Figure 7 and Figure 8. What are the red and green stains showing in Figure 8?5) The main conclusion related to differences in the control and TOF heart seems to be at there is increased extracellular space related to increased trabeculation. This likely would be easier to appreciate on a lower resolution analysis or ventricular myocardial architecture.6) The authors emphasize that this method could be applied to analysis of human congenital heart disease. The reported sample preparation and ultrastructural analysis is not feasible at a whole organ level for humans.7) This protocol might be useful for analysis of cardiac malformations in mice. Are there any data to support the use of this method in other animal models?Reviewer #3:This manuscript titled "Multiscale imaging of the whole heart and its internal cellular architecture: Application to congenital heart disease" by Rykiel et al., presents a multiscale and correlative imaging system that combines the 3D-micro-computed tomography and scanning electron microscopy techniques to simultaneously assess micro and ultrastructure of whole heart tissues. The authors have utilized an avian (chick) in vivo model and have satisfactorily demonstrated the applications of their novel imaging system. Micro-CT and SEM techniques have been individually well established and combining both can be challenging due different ensuing image resolutions and problems with fixation and staining. In the avian heart model, this study indicates to have overcome these problems and successfully applied this technique to larger tissues (5-6 mm wide) than the previous studies. This novel method can indeed be a powerful tool in studying the CHD and other disease models. The procedures and steps of optimized staining, fixation and imaging using micro-CT and SBF-SEM are clearly illustrated and described in good detail. There are, however, some minor issues that need to be addressed in the manuscript to improve the clarity and before the study can be published.Comments:1) Subsection “Cardiac structure analysis from 3D micro-CT images”, while analyzing the micro-CT images of control avian heart vs the TOF avian heart, authors mention that in the TOF heart, 'right' branch of the pulmonary artery was missing compared to control heart. In support of this observation, they refer to a rare human condition 'unilateral absence of pulmonary artery' seen in TOF patients. However, in Figure 3 legend, they mention that the 'left' branch of pulmonary artery was absent in the TOF heart. Was this observation made in the other sample? It is confusing to the reader and needs to be clarified.2) Article's main focus in on the multiscale imaging technique and its potential applications. The data presented in Figure 7 and Figure 8 are obtained from one control and one TOF avian heart. Although authors address this limitation in the article, one would need to be careful not to conclude much based on the observations comparing CT and TOF hearts although they are in line with previously published findings.3) In subsection “Image segmentation and quantification”, authors mention while describing the 3D visualization of SBF-SEM segmentations , that orientation of myocardial cells were 'slightly' different. This needs to be described further as to how exactly the orientation of TOF myocardial cells was different from the control.4) Other potential applications of this novel imaging technique in addition to CHDs  need to be briefly commented on. Any other cardiac ultra-structures that can potentially be studied using this technique must be mentioned briefly.5) The novel imaging technique presented here improves on the previous methods by being applicable to larger tissues (up to 5-6mm according to authors). However, this is still smaller tissue size compared to other in vivo models and human heart tissues. Do authors foresee any potential problems in translating this technology to human heart tissues? This needs to be elaborated upon. Reviewer #1:Essential revisions:1) The current title suggests that the described methods are applicable to a better understanding of congenital heart disease (CHD). However, it would be more accurate to state the current described findings in 2 non-beating chick hearts  is a "Proof of Principle" for correlating changes in macroscale abnormalities in cardiac structure with microscale changes in tissue and cell composition (as mentioned in the Introduction).Thanks for the comment. Our current title “Multiscale imaging of the whole heart and its internal cellular architecture: Application to congenital heart disease” certainly suggests that we have analyzed congenital heart disease extensively, which is not the case. Our intention was to highlight this possibility. We agree to change the title to “Multiscale cardiac imaging spanning the whole heart and its internal cellular architecture in a small animal model” to more accurately reflect the paper scope of presenting the multiscale imaging procedure, with examples supporting its use.2) The authors should comment on, aside from the technical accomplishments of the approach, how this data provides new insights into errors in cardiac morphogenesis, altered growth and adaptation, or the changes in mechanical function that occur in CHD.Thanks for making this point. We have added a paragraph explaining this in more detail. Briefly, the imaging method presented will allow us to determine how the heart adapts to hemodynamic conditions (the case presented) but also to other insults , and draw comparisons among different cases and normal hearts. The combination of structural and ultrastructural cardiac imaging data, moreover, can predict mechanical function. Indeed, myocardial disarray or marked reductions in myofibrils, for example, will decrease cardiac efficiency, including compromised ejection fraction and stroke volume.We added the following paragraph in the Discussion section of the paper:“The presented correlative multiscale imaging approach will provide new insights into the underpinnings of heart development, and on cardiac mechanical changes in CHD. Analysis of multiscale cardiac images over developmental stages, will unravel how cardiac tissues progressively assemble and mature at diverse scales to form a functional heart. When cardiac development is perturbed  multiscale images will reveal how the natural maturation and assembly of cardiac components  are altered, sometimes in irreversible ways that lead to CHD. Multiscale images, furthermore, promise to reveal possible differences and similarities among CHD hearts with different phenotypes (e.g. TOF vs DORV), as well as among hearts with similar phenotypes but that were the result of diverse insults . Moreover, the combination of morphological and ultrastructural cardiac imaging data can predict the mechanical function of the heart. Indeed, myocardial disarray or marked reductions in myofibrils, for example, will decrease the contraction efficiency (and force) of cardiac tissues. In turn, decrease contractility affects cardiac efficiency, including compromised ejection fraction and stroke volume.”3) The authors should discuss, briefly, how changes in myofiber architecture are related to mechanical function  since changes in mechanical loading and function can result in multiscale changes in cardiac architecture.Thanks for this insightful suggestion. We agree that this is missing, and we have added to this, explaining how myocardial cell architecture impacts cardiac function. Briefly, myofibers contract along their long axes and align parallel to each other, so that cardiac contraction occurs along specific directions in the heart. The normal helical architecture of myofibers ensures that the heart contracts and twists to effectively eject blood into the pulmonary and systemic circulations. If the myofiber architecture is perturbed, however, cardiac contractility is compromised. This is both because the tissue can no longer contract on a specific direction, and because contraction force may be diminished. Thus, changes in myofiber architecture  frequently lead to heart tissues with impaired contractility and thus reduced compliance.We added the following sentences in the Introduction:“This highly organized pattern ensures that cardiac contraction occurs along specific directions, so that the heart can effectively eject blood into the pulmonary and systemic circulations. Perturbations of the normal myocardial architecture affect cardiac contractility and compliance. This is both because the tissue can no longer contract on the very specific directions and patterns that optimize cardiac function, but also because cardiac contraction force may be diminished. Therefore, changes in myocardial architecture  frequently lead to heart tissues with impaired contractility and reduced compliance.”4) The paper would be strengthened by the analysis of larger number of imaged hearts  to better understand the reproducibility of the described methods. This paper uses a single normal and a single abnormal heart, and describes the results from 2 regions of interest from the LV free wall of each specimen. The only significant difference between the 2 specimens was the increase in extracellular space noted in the TOF specimen . The paper would be strengthened, for example, by the analysis of adjacent ROIs in the same heart to determine reproducibility and by comparison of specimens from both LV and RV specimens.We have developed the methods described after several iterations that optimized tissue fixation and preparation for both the microCT and SEM images. Once we found the combination of procedures to achieve the multiscale resolution presented in this paper, we chose two hearts . We applied the methods to those two hearts to show that we could successfully reproduce proper fixation and preparation of tissues required for high resolution imaging at diverse scales, even though the hearts were different. In other words, we showed that the method works not only for normal hearts, but also for malformed hearts. Indeed, the methods worked without additional optimizations or tweaks. Adding more hearts to the study will be useful for a Research paper, with the objective of understanding how abnormal hearts differ among themselves and with respect to normal; and how perturbed blood flow conditions or other insults lead to different adaptations and ultrastructure. We therefore respectfully disagree with the reviewer: we do not think we need more samples to show, in a Tools and Resources article, that our method works. Instead, more samples will be required for a full Research paper focused on comparisons of hearts and insights gained by the methods and analyses of images.We agree that the paper will be strengthened by analysis of adjacent ROIs from the same hearts, which we have performed. By analyzing SEM images that were 2 microns apart  we accomplished adjacent ROI analysis and comparison, and further found that differences among these adjacent ROIs were small (not more than 10%), emphasizing the reproducibility of our imaging and segmentation methods. Including the RV as well as the LV would be nice – however, the main objective of the analysis presented was not to do an extensive comparison of these two hearts, but show possible types of analyses, and the kind of insights that can be gained. The fact that the only difference we could find in the LV of these two hearts is increased extracellular space is not important (and not significant), the point we want to emphasize is that our approach enables cardiac multiscale imaging and quantitative analysis. A more extensive study with more hearts (a full Research paper) could then show similarities and differences among hearts at multiple scales, as well as perhaps unique adaptations in diverse regions of the same heart.5) The authors highlight the ability to classify phenotype, heart size, and wall thickness with their technique (subsection “Comparison of control and TOF hearts and limitations of this study”), however the paper lacks any discussion of the now readily available and less time-consuming approach of using of high-resolution echocardiography to acquire data on multiple time points from beating avian and mammalian developing hearts. It is important to explain how the multiscale data derived from this approach complements currently available data sets.Thanks for bringing this important point to our attention. We are well aware of the currently available echocardiography imaging . Using echocardiography we can certainly obtain data on heart function from beating avian and mammalian hearts. Echocardiography data can be further used to quantify heart size and wall thickness, but also blood flow velocities, ejection fractions and other functional cardiac parameters. However, while we can observe functional problems in hearts using echocardiography, we cannot get the ultrastructural details of the hearts. Moreover, it is also difficult to identify, using only echocardiography, subtle malformations in the heart structure . Our multiscale approach, therefore, can certainly complement echocardiography data: by providing a more detailed phenotyping of the hearts, including structural and ultrastructural characteristics that can explain and eventually predict in vivo function.We have now addressed these considerations in the Introduction: “For later stages of heart development ecochardiography is used in mice and chick. In small animal research, moreover, due to the small size of developing hearts, functional imaging techniques are frequently complemented with micro-CT or histology to more accurately phenotype the heart.”And in the Discussion section: “…combining echocardiography, which can acquire in vivo images of the heart for functional (including blood flow) analysis, together with 3D micro-CT and SEM, can reveal functional as well as detailed microstructural and ultrastructural characteristics of normal versus CHD hearts.”–6) It is important for the authors to reference the studies that detailed the congenital cardiac anomalies associated with conotruncal banding in the chick embryo which are associated with abnormal neural crest migration, altered aortic-mitral valve continuity, aortic valve override, VSDs, and abnormal conotruncal septation . This mechanism for altered conotruncal septation may be very different from the altered neural crest and conotruncal anomalies in the chick embryo produced by neural crest ablation  which may impact the changes in myocardial and myofiber orientation and maturation.This is indeed an important point for discussion and consideration. Thanks for highlighting this point. We have added a short explanation clarifying that conotruncal heart defects, similar to the ones obtained after hemodynamic interventions, can also result from neural crest ablation, adding the references mentioned by the reviewer. Our multiscale imaging method could then be useful to determine possible changes in ultrastructure and adaptation in a seemingly similar cardiac malformation phenotype but due to diverse origins.We have added the following paragraph in the Discussion section:“Previous studies have detailed the congenital heart anomalies associated with outflow tract banding (OTB) used in this study to induce TOF. Those studies found a spectrum of congenital heart defects after OTB, which originated from abnormalities in the outflow tract . These abnormalities included increased separation between the aortic and mitral valve annuli , ventricular septal defects, abnormal position of the aorta, including TOF and double outlet right ventricle (DORV), in which both the aorta and pulmonary trunks emerge from the right ventricle. Meanwhile, neural crest cell ablation also leads to conotruncal anomalies in the chick embryo. Cardiac neural crest cells are required for normal heart development (in the chick and mouse), and ablation of these cells leads to persistent truncus arteriosus (PTA), characterized by lack of separation of the aorta and pulmonary trunk, but also to TOF and DORV. Likewise, diverse genetic anomalies are also associated with conotruncal heart defects. However, the mechanisms by which anomalous genes, neural crest cell ablation, and altered hemodynamics lead to conotruncal defects may differ, and these differences may impact myocardial and myofiber orientation and maturation. Multiscale imaging studies could reveal the impact of diverse interventions on cardiac microstructure and ultrastructure, both when the same or different phenotypes are obtained. This in turn could contribute to our understanding of the underpinnings of CHD and their functional and structural consequences.”The technical details of the current studies are excellent (with the exception of the lack of quantitative data on cellular orientation).We apologize for this omission. We have added the quantification of myofibrils cell orientation from our images in the Results section and added Figure 10 to illustrate it.Introduction:This sentence can be more clearly restructured. It would be more accurate to state that most studies of the myocardial architecture, including the analysis of myofiber architecture and cellular constituents have found all to be abnormal in the setting of congenital cardiac malformations. What is unknown is the mechanisms responsible and the subsequent clinical consequence…The reviewer is correct. We have rewritten this sentence as follows: “The structural  characteristics of heart malformations, including changes in cardiac wall architecture, have been extensively studied. However, the mechanisms that lead to an anomalous cardiac architecture in CHD and the clinical consequences of it are unknown. “It would not be accurate to state that the results of a small number of studies on myofiber architecture have been "ignored while planning treatment strategies" and would probably be more accurate to say that those myofiber studies have not been proven to be relevant to decisions regarding treatment strategies. This sentence should simply state that emerging evidence supports the importance of myofiber disarray in CHD which may impact cardiac function before and after interventional procedures.Yes, we agree with the reviewer. We have edited this sentence, which now states “These emergent studies are revealing myocardial disarray in CHD  that very likely affect cardiac function before and after surgical repair.”The authors should include 1 or 2 references to other imaging approaches, such as OCT and the use of high-resolution echocardiography for cardiovascular phenotyping of CHD in developing avian and mammalian developing hearts.Thanks for pointing this out. We have included references to other methodologies employed for phenotyping. We are aware of these techniques and have used them in our work. OCT is used for earlier stages, when the heart is still small and tubular (before about 4 days of incubation in chick). For the studies presented here, when the heart already has four chambers (day 12 of incubation in chick) OCT, an optical imaging technique, cannot penetrate the tissue, and instead high-resolution echocardiography is used in avian and mammalian developing hearts. In our own studies , further, for the chick hearts echocardiography was used for phenotyping but was complemented by microCT, from which we could get a more detailed image of the heart morphology.We have added a paragraph on the use of OCT and echocardiography techniques in the context of heart development and CHD: “Imaging approaches have been employed to study cardiac function in normal and CHD hearts. 8 In humans, ultrasound-based echocardiography, which can image the in vivo motion of cardiac walls during heart pumping and measure blood flow velocities within the heart, is used to diagnose fetal CHD in utero and assess severity. After the baby is born, echocardiography is useful to monitor cardiac function before and after interventions to repair CHD. Magnetic resonance imaging (MRI) is also employed to precisely diagnose malformations and monitor cardiac function in CHD. In heart development animal research, moreover, optical coherence tomography (OCT) and echocardiography are used with avian and mammalian models of CHD. OCT, like ultrasound, is a non-invasive technique that can image heart motion and measure blood flow velocities within the heart. OCT resolution (< 5 µm) is ideal for early avian and mouse embryos during tubular-heart developmental stages. For later stages of heart development ecochardiography is used in mice and chick. In small animal research, moreover, due to the small size of developing hearts, functional imaging techniques are frequently complemented with micro-CT or histology to more accurately phenotype the heart.”–The authors should provide an updated pathogenesis that TOF results from abnormal neural crest cell migration and altered aortopulmonary septation which can present with a range of phenotypes including four basic features  .We would like to thank the reviewer for bringing this important point out. TOF can certainly result from other mechanisms, including abnormal neural crest cell migration, which is extremely interesting. Originally, we had just focused the presentation and discussion of the paper on the model we were presenting (hemodynamic interventions), but it is fair to also mention other possible causes of TOF. Interestingly, our proposed multiscale imaging method can be used to compare hearts with TOF from perturbations in hemodynamics versus perturbations in neural crest cell migration. We have added in the Discussion section that TOF can result from abnormal neural crest cell migration as well as provide the reference cited by the reviewer.We have added the following paragraph to the Discussion section:“Previous studies have detailed the congenital heart anomalies associated with outflow tract banding (OTB) used in this study to induce TOF. Those studies found a spectrum of congenital heart defects after OTB, which originated from abnormalities in the outflow tract . These abnormalities included increased separation between the aortic and mitral valve annuli , ventricular septal defects, abnormal position of the aorta, including TOF and double outlet right ventricle (DORV), in which both the aorta and pulmonary trunks emerge from the right ventricle. Meanwhile, neural crest cell ablation also leads to conotruncal anomalies in the chick embryo. Cardiac neural crest cells are required for normal heart development (in the chick and mouse), and ablation of these cells leads to persistent truncus arteriosus (PTA), characterized by lack of separation of the aorta and pulmonary trunk, but also to TOF and DORV. Likewise, diverse genetic anomalies are also associated with conotruncal heart defects. However, the mechanisms by which anomalous genes, neural crest cell ablation, and altered hemodynamics lead to conotruncal defects may differ, and these differences may impact myocardial and myofiber orientation and maturation. Multiscale imaging studies could reveal the impact of diverse interventions on cardiac microstructure and ultrastructure, both when the same or different phenotypes are obtained. This in turn could contribute to our understanding of the underpinnings of CHD and their functional and structural consequences.”Figure 4. The RV and LV should be identified in the CON and TOF hearts.Thanks for pointing to this omission. We have re-label Figure 4, in particular labels for the right and left ventricles  have been added.Subsection “Image segmentation and quantification” and Figure 8. The authors suggest that Figure 8 shows a change in the orientation of myocardial cells but no quantitative data (or data on specimen reproducibility) is provided. This impression would be strengthened by some quantitative data and some evidence that a known external reference point was used to orient the specimens prior to histologic processing.We agree with the reviewer .We have now provided the myofibril angle quantifications, which are summarized in Figure 10 and described in the text of the manuscript .Subsection “Conclusions” The text suggests that this approach "enables analysis of both whole heart and ultrastructural architecture" however only a small segment of the ultrastructure was assessed. It is more accurate to say, "The described approach allows the correlation of macro and micro-scale architecture in selected regions of the heart".We agree with the reviewer and have amended the sentence accordingly: “The described approach allows the correlation of microstructural and ultrastructural architecture in selected regions of the heart.”Reviewer #2:The manuscript by Rykiel reports an improved method for microCT analysis of heart anatomy followed by ultrastructural analysis of myocardial cells in the same sample. Analysis of a control and malformed embryonic chicken heart is shown as proof of principal for the utility of this technique. The main advantage of the reported method is improved fixation and imaging of the same samples. However, there are several limitations of the method as shown in the current study.Thanks for your positive view of the manuscript and insightful comments. We will address study limitations pointed by the reviewer in what follows.Essential revisions:1) In order for this method to be useful in rigorous analysis of cardiac anatomy and cellular organization, additional quantification and evidence for reproducibility of the methods are needed. The current manuscript analyzing n=1 sample sizes is inadequate to determine if reproducible quantitative data can be obtained using these methods.We respectfully disagree with the reviewer on this. We do not think we need more samples to show evidence of reproducibility of the methods. We have developed the methods described after several iterations that optimized tissue fixation and preparation for both the microCT and SEM images. Once we found the combination of procedures that achieved multiscale resolution as presented in this paper , we chose two hearts  and applied the methods to those two hearts. We showed that we could nicely replicate the methods (proper fixation and preparation of tissues for imaging), even though the hearts were different . The method worked seamlessly  and we could get homogeneous fixation and staining in both hearts (as presented in the manuscript) as well as high-resolution images of heart structure and ultrastructure.We agree that adding more hearts to the study will be useful for a Research paper, in which the aim is to understand how similar/different abnormal hearts are among themselves and with respect to normal. Such paper would indeed focus on comparisons of hearts and insights gained by application of the imaging approach presented. We do not think, however, that more samples/animals are needed for a Tools and Resources paper (the article type for this manuscript), in which the focus of the paper is on the methods and procedures needed to achieve multiscale imaging of a relatively large organ, the heart.2) Quantification of additional parameters in the microCT and SEM studies are needed.We have added more quantifications from microCT and 3D SEM images in the Results. These include quantifications of ventricle sizes from microCT and myofibril alignment from SEM. We initially chose to not include too many quantifications not to mislead the readers. Given that n = 1 , we cannot make conclusions from a biological point of view, and we did not want to give the wrong impression in this Tools and Resources paper. However, more quantifications have now been included to illustrate additional data that can be obtained from our presented multiscale imaging approach, while warning the reader that data is for illustration purposes only.3) Tests of statistical significance were performed based on multiple measurements of the same samples. These tests are not appropriate for the n=1 sample sizes in the current study.Statistical tests on multiple measurements from the same samples (different locations) were only included to show whether the two samples were different. We have removed these tests not to confuse readers , and also because they are not necessary .4) It is difficult to appreciate the benefit of the 3D ultrastructural analysis from the images shown. It is difficult to appreciate the features of interest in Figure 6, Figure 7 and Figure 8. What are the red and green stains showing in Figure 8?Thanks for the comment. We apologize for not showing more clearly the advantages of 3D SEM from our figures. We have added a Figure  showing the detailed architecture obtained from SEM in a small region, that illustrates the advantages of 3D SEM.Regarding the specific figures mentioned by the reviewer. Figure 6 just shows that ultrastructural details can be appreciated on the imaging plane (x-y plane) but also on perpendicular planes (x-z and y-z planes), and that the images acquired (part of the image stack) are well aligned and homogeneous. We have added labels to the figure to make it more clear, and edited its caption. Figure 7  simply shows quantifications based on SEM images in A and B, and then a depiction of the 3D extracellular space in C and D for the control and TOF hearts, respectively. We have edited the caption to more accurately reflect this. Figure 8  shows a completely segmented 3D SEM volume. Please note that the ‘stains’ are segmentations (painted delineations) of the nuclei (red), mitochondria (blue) and myofibrils (green). These segmentations were obtained semi-automatically using a deep learning  strategy. We are very sorry we omitted to mention in the figure caption what the colors represent, and we have now added this explanation to the figure caption. In addition, as mentioned before, we have added a figure  showing detailed segmentations of ultrastructure.5) The main conclusion related to differences in the control and TOF heart seems to be at there is increased extracellular space related to increased trabeculation. This likely would be easier to appreciate on a lower resolution analysis or ventricular myocardial architecture.We agree with the reviewer: increased trabeculation could be better appreciated with other methods. However, we cannot conclude anything of biological significance from n = 1. We apologize for not being clear on this, and we have clarified this in the paper now. The analysis performed on images was not exhaustive, and was only presented as an example of possible quantifications. There are other aspects that were not fully analyzed, like lipid droplet distribution, glycogen distribution, the distribution of the mitochondria with respect to the myofibrils, etc. Our intention on selecting nuclei, mitochondria and myofibrils for segmentation, and to perform an initial quantification of them, was to show possible quantitative outcomes, and merely as an example. More detailed quantifications could be performed – and would indeed be appropriate for a paper analyzing differences between normal or control hearts and CHD hearts, in which also appropriate number of animals, and careful selection of SEM ROIs including both the left and right ventricles, are considered. The fact that for these two hearts there was no difference in myocardial cell volume fraction of nuclei, myofibrils and mitochondria, in their left ventricles was coincidental. Thus, while it seems that the main conclusion from the analysis is that left ventricle trabeculation and the extracellular space is increased in TOF, and that therefore other techniques are more suitable (and cheaper) to analyze these two hearts, this conclusion is misleading, as there is more information from 3D SBF-SEM images that we have not analyzed that cannot be obtained from low resolution images of the ventricular myocardial architecture. Further, this conclusion could pertain exclusively to these two hearts, with other hearts perhaps showing differences.We have added the following in the Discussion section: “To be biologically meaningful, however, these studies need to include more animals. The quantifications and comparisons presented here for one control and one TOF heart (thus n=1) pertain only to these two hearts, and are presented as an illustration of possible ways of extracting information from the proposed multiscale imaging method. “6) The authors emphasize that this method could be applied to analysis of human congenital heart disease. The reported sample preparation and ultrastructural analysis is not feasible at a whole organ level for humans.We agree. Sorry the text was misleading. The method is not intended for human hearts, it is intended for small animal models of congenital heart disease, which could inform human congenital heart disease. We have now clarified this more emphatically in the manuscript.We have added the following paragraph to the Discussion section:“Direct application of the proposed multiscale imaging method to human hearts is limited. The method presented here is destructive, and thus can only be applied to human samples of diseased individuals. Moreover, the larger size of the human heart will lead to difficulties in attaining homogeneous fixation and staining. To circumvent fixation and stain homogeneity issues, increased timing for diffusion of fixative and heavy metal stains is certainly a possibility as is microwave steps (to accelerate diffusion). In addition, changes in processing, such as sectioning of hearts after microCT to facilitate diffusion of heavy metal stains and control imaging are also possible. As presented, using our methods, multiscale imaging of human hearts is limited.”7) This protocol might be useful for analysis of cardiac malformations in mice. Are there any data to support the use of this method in other animal models?Thanks for bringing this important point. In fact, mice hearts are very similar in size to chicken hearts, and we mentioned in the manuscript that we could apply the same techniques to mice. Unfortunately, while we have some microCT images of fetal mice hearts, and others have acquired 2D EM images of mouse hearts, we have not yet performed a full multiscale image as described in the manuscript on a mouse heart. However, we anticipate that the techniques will translate seamlessly to mice hearts with perhaps only a few (if any) small optimizations.Reviewer #3:This manuscript titled "Multiscale imaging of the whole heart and its internal cellular architecture: Application to congenital heart disease" by Rykiel et al., presents a multiscale and correlative imaging system that combines the 3D-micro-computed tomography and scanning electron microscopy techniques to simultaneously assess micro and ultrastructure of whole heart tissues. The authors have utilized an avian (chick) in vivo model and have satisfactorily demonstrated the applications of their novel imaging system. Micro-CT and SEM techniques have been individually well established and combining both can be challenging due different ensuing image resolutions and problems with fixation and staining. In the avian heart model, this study indicates to have overcome these problems and successfully applied this technique to larger tissues (5-6 mm wide) than the previous studies. This novel method can indeed be a powerful tool in studying the CHD and other disease models. The procedures and steps of optimized staining, fixation and imaging using micro-CT and SBF-SEM are clearly illustrated and described in good detail. There are, however, some minor issues that need to be addressed in the manuscript to improve the clarity and before the study can be published.We greatly appreciate your positive view of our work, and we would like to thank you for taking the time to review our manuscript. We have addressed issues in the manuscript as detailed below.Essential revisions:1) Subsection “Cardiac structure analysis from 3D micro-CT images”, while analyzing the micro-CT images of control avian heart vs the TOF avian heart, authors mention that in the TOF heart, 'right' branch of the pulmonary artery was missing compared to control heart. In support of this observation, they refer to a rare human condition 'unilateral absence of pulmonary artery' seen in TOF patients. However, in Figure 3 legend, they mention that the 'left' branch of pulmonary artery was absent in the TOF heart. Was this observation made in other samples? It is confusing to the reader and needs to be clarified.We apologize for the typo. Observations were made from the same heart, and the left branch is missing. We have amended this mistake.2) Article's main focus in on the multiscale imaging technique and its potential applications. The data presented in Figure 7 and Figure 8 are obtained from one control and one TOF avian heart. Although authors address this limitation in the article, one would need to be careful not to conclude much based on the observations comparing CT and TOF hearts although they are in line with previously published findings.Thanks for pointing this important aspect of our work . We completely agree with the reviewer. Indeed, we cannot conclude anything of biological significance from just comparing one control and one TOF heart. We have performed some quantifications and analyses merely to show possibilities, but by no means suggesting we could make conclusions from them. We have now emphasized in the manuscript that the main focus is on the multiscale imaging, and the analysis performed on the imaging is to illustrate possibilities.3) In subsection “Image segmentation and quantification”, authors mention while describing the 3D visualization of SBF-SEM segmentations , that orientation of myocardial cells were 'slightly' different. This needs to be described further as to how exactly the orientation of TOF myocardial cells was different from the control.Thanks for pointing this out. The orientation of myocardial cells can be quantified, and because the ROIs are corresponding, these quantifications can be compared. We tried to do this visually in Figure 8  but we agree this is not enough. We have added to the explanation and have now included quantifications of myofibril orientation from both samples. These quantifications are summarized in Figure 10 but also described in the text .4) Other potential applications of this novel imaging technique in addition to CHDs  need to be briefly commented on. Any other cardiac ultra-structures that can potentially be studied using this technique must be mentioned briefly.Thanks for making this important point, which we have not carefully discussed. Indeed, other applications of our imaging approach are possible, including the analysis of hearts that look normal but were subjected to insults early during development . As the reviewer points out, other applications of the multiscale imaging method are studies of extracellular matrix disorganization, fibrosis, and degeneration of valves. Moreover, in addition to studying nuclei, mitochondria and myofibrils (which we have emphasized in this manuscript as an example) we could also study the distribution (and amount) of lipid droplets, glycogen, as well as the ultrastructural organization within myocardial, endothelial, fibroblast and conduction cells.We have added these points to the Discussion section.“Outside the scope of this paper, but relevant to the comparison of normal versus CHD hearts, would be an extensive analysis of left and right ventricular wall microstructure and ultrastructure, including the distribution of lipid droplets, glycogen, and mitochondria with respect to the myofibrils. In addition, studies of the ultrastructural organization within myocardial, endocardial, fibroblast and conduction cells, in normal and CHD hearts, would be relevant to decipher the impact of CHD on cell and cardiac function.”And the following to the Conclusions: “Importantly, multiscale studies can be used to decipher the imprints that early alterations in the environment in which the heart is growing have on cardiac formation and function. In addition, other potential applications to CHD and beyond are determinations of extracellular matrix organization/disorganization, cardiac fibrosis, glycogen distribution and myxomatous degeneration of valve tissues in response to different insults and aging.”5) The novel imaging technique presented here improves on the previous methods by being applicable to larger tissues (up to 5-6mm according to authors). However, this is still smaller tissue size compared to other in vivo models and human heart tissues. Do authors foresee any potential problems in translating this technology to human heart tissues? This needs to be elaborated upon.Thanks for this insightful comment. The method presented here is destructive, and as such (as presented) can only be applied to human samples of deceased individuals. Moreover, the larger size of the human heart will lead to difficulties in attaining homogeneous fixation and staining. To achieve fixation and stain homogeneity, increased timing for diffusion of fixative and heavy metal stains is certainly a possibility as is microwave steps (to accelerate diffusion). In addition, changes in processing, such as sectioning of hearts after microCT to facilitate diffusion of heavy metal stains and control imaging are also an option.We have added the following paragraph to the Discussion section:“Direct application of the proposed multiscale imaging method to human hearts is limited. The method presented here is destructive, and thus can only be applied to human samples of diseased individuals. Moreover, the larger size of the human heart will lead to difficulties in attaining homogeneous fixation and staining. To circumvent fixation and stain homogeneity issues, increased timing for diffusion of fixative and heavy metal stains is certainly a possibility as is microwave steps (to accelerate diffusion). In addition, changes in processing, such as sectioning of hearts after microCT to facilitate diffusion of heavy metal stains and control imaging are also possible. As presented, using our methods, multiscale imaging of human hearts is limited.”