The fourth edition of the ‘’WHO Classification of Head and Neck Tumours’’ was published in January 2017 and includes a classification of odontogenic tumours. This review aims to examine the changes made in this new classification in comparison with the previous classification of 2005. An electronic search was conducted in the PubMed, Scopus and Cochrane databases with the keywords “odontogenic tumor”, “WHO classification” and “update”. Studies published from January 2009 to April 2019 with a high level of scientific evidence were included, but studies not published in English, epidemiological studies and studies with a low level of evidence were excluded. The initial search found 457 articles and after eliminating duplicates, 8 studies were selected for full-text assessment. After excluding 3 epidemiological studies, 5 articles were finally included. These studies were stratified by their level of scientific evidence using SORT criteria (Strength of Recommendation Taxonomy). The new odontogenic tumour list has been simplified with the objective of improving its role as an international guide for diagnosis. Some changes have been possible thanks to the application of immunohistochemistry and molecular genetic techniques that allow better characterization of certain tumours. Further clinicopathological and molecular studies are needed so that this new classification can be consolidated and/or amended. Key words:Odontogenic tumour, WHO classification, update. Odontogenic tumours are defined as a neoplasms exclusively of the maxillary bones and oral mucosa, which derive from odontogenic epithelial tissue, odontogenic ectomesenchymal tissue or both . OdontogIn 1971, the World Health Organization (WHO) published the first odontogenic tumour classification with the aim of structuring and clarifying this type of pathology . This clThe 2005 classification  needed aThe main aim of the 2017 classification  and to pThe new odontogenic tumour classification distinguishes between benign and malignant tumours, as did the previous version . In 2005Regarding malignant odontogenic tumours, both classifications maintain the distinction between carcinomas and sarcomas ,4.This review aims to analyse the main changes made in the new 2017 WHO odontogenic tumour classification .A bibliographical search was performed in the Cochrane, Scopus and PubMed-MEDLINE databases using the search terms “odontogenic tumour”, “WHO classification” and “update”. Search terms were combined using the Boolean operator “AND” with the aim of obtaining different articles that include two or more of the terms used for the search.We included all studies published between January 2009 and April 2019 that were written in English and had level 1 or 2 scientific evidence according to SORT criteria (Strength of Recommendation Taxonomy) . StudiesWe obtained 457 articles from the initial search in the different databases, and 420 after removing duplicates, corresponding to 214 studies from PubMed-MEDLINE, 243 from Scopus and none from Cochrane. 371 studies were then discarded after reading the title and the 49 remaining articles were screened by reading the abstract. Of these, 41 were discarded because they only concerned odontogenic cysts or odontogenic tumour treatment or did not contribute any relevant information relating to the new classification. From the remaining 8 articles assessed for full-text eligibility, 3 studies were excluded because they were epidemiological studies and did not meet the inclusion criteria. Finally, 5 studies were included for this review: three systematic reviews, one retrospective study and a review. Fig. The studies were stratified according to their scientific evidence level using SORT criteria , resultiFirst of all, it is recognized that the malignant tumour list presented in the new classification has been simplified compared with the previous one. The list of tumours is reduced from 12 entities in 2005 to 7 entities in 2017 . As a coThe new classification also acknowledges one new type of malignant tumour, sclerosing odontogenic carcinoma, based on previous publications concerning this tumour -12.Regarding benign tumours, the 2005 classification has likewise been simplified with the disappearance of some entities . There iWith odontogenic cysts incorporated into the new 2017 WHO text  Epithelial originThere have been changes to the terminology and classification of ameloblastomas based on new discoveries about the genetic profile of this tumour . In the Regarding unicystic ameloblastoma, there are currently three histopathological types: luminal, intraluminal and mural. The mural variant is controversial since it is considered to be more of a conventional ameloblastoma with cystic degeneration rather than a true unicystic ameloblastoma . As in cMetastasizing ameloblastoma is an odontogenic tumour that was classified in 2005  as a malIn aggressive relapsing and/or metastatic ameloblastoma cases, apart from surgery, anti-BRAF biotherapy can be used. These are tyrosine kinase inhibitors (vemurafenib or dabrafenib + trametinib) ,26.There have been no major changes to squamous odontogenic tumour, calcifying epithelial odontogenic tumour or adenomatoid odontogenic tumour .In 2005 , odontogb) Epithelial-mesenchymal originOdontoameloblastoma, which has ameloblastic proliferation and dental tissue formation, was added to this group in the 2005 classification . In the In the new edition , calcifyIn 2005 , ameloblThe first 6 cases of primordial odontogenic tumour were published in 2014 . This tuThere have been no major changes to the odontoma group in this new edition  comparedGhost cell dentinogenic tumour has been updated as well as its immunohistochemistry profile .c) Mesenchymal originThe previous edition  listed tNeither odontogenic myxoma/myxofibroma nor cementoblastoma have undergone any substantial changes in this new edition .Cemento-ossifying fibroma is a neoplasm that was not included in the 2005 edition  but has The current WHO odontogenic tumours classification has been simplified in comparison with the 2005 edition with the aim of improving its use as an international guide for the diagnosis and management of this pathology.Many of these changes in classification have been possible thanks to better genetic and immunohistochemistry characterization of some tumours, which was not possible in the last edition.It is important to point out that this classification process is far from complete because there are entities such as metastasizing ameloblastoma and sclerosing odontogenic carcinoma that do not yet have enough scientific evidence to be characterized appropriately. In this regard, we would find odontogenic carcinoma with dentinoid as well as another evaluation of tumoral entities deleted in this classification.


Management of volume status, arterial blood pressure, and cardiac output are core elements in approaching the patients with aneurysmal subarachnoid hemorrhage (SAH). For the prevention and treatment of delayed cerebral ischemia (DCI), euvolemia is advocated and caution is made towards the avoidance of hypervolemia. Induced hypertension and cardiac output augmentation are the mainstays of medical management during active DCI, whereas the older triple-H paradigm has fallen out of favor due to lack of demonstrable physiological or clinical benefits and serious concern for adverse effects such as pulmonary edema and multiorgan system dysfunction. Furthermore, insight into clinical hemodynamics of patients with SAH becomes salient when one considers the frequently associated cardiac and pulmonary manifestations of the disease such as SAH-associated cardiomyopathy and neurogenic pulmonary edema. In terms of fluid and volume targets, less attention has been paid to dynamic markers of fluid responsiveness despite the well-established, in the general critical care literature, superiority of these as compared to traditionally used static markers such as central venous pressure (CVP). Based on this literature and sound pathophysiologic reasoning, reliance on static markers (such as CVP) is unjustified when one attempts to assess strategies augmenting stroke volume (SV), arterial blood pressure, and oxygen delivery. There are several options for continuous bedside cardiorespiratory monitoring and optimization of SAH patients. We, here, review a noninvasive monitoring technique based on thoracic bioreactance and focusing on continuous cardiac output and fluid responsiveness markers. Delayed cerebral ischemia (DCI), after aneurysmal subarachnoid hemorrhage (SAH), affects approximately 30% of patients . HypovolEmploying thoracic electrical bioimpedance/reactance for deriving hemodynamic variables is based on the assumption that changes in intrathoracic blood volume, during the cardiac cycle, induce changes in the electrical conductivity of the thorax that are mainly related to changes in aortic volume  environments, e.g., extraneous electrical interference). Conductivity changes are detected by skin electrodes assessing the difference between input and output voltage after applying a low-amplitude high-frequency current to the thorax . BioreacWe pilot-trialed the Starling-SV monitor in 10 prospective adult patients with SAH  were performed. Hemodynamic variables collected included cardiac index, blood pressure, central venous pressure (CVP) (as available), and stroke volume variation (SVV), as well as transcranial Doppler (TCD) mean flow velocities (as available). Volume management variables followed included daily I/O status, hourly urine output (UOP), and type and frequency of fluids and vasoactive medication support provided. Transthoracic echocardiography (TTE) was also performed as part of standard examination in SAH patients on admission and when clinically indicated by changing hemodynamics. Fluid responsiveness was tested by passive leg raise testing (PLR); PLR is a well-described positional maneuver that mobilizes fluid from the lower body towards the central circulation and is one of the recommended methods of testing fluid responsiveness in critically ill patients. If PLR could not be performed, then a fluid challenge of 250 cc of normal saline was used. Whenever fluid boluses were administered, the volume was incorporated and accounted for in the overall fluid management of these patients by adjustment of the total fluid rate provided .The median age of the 10 participants was 57 years  [2 rebreathing [I2 = 83%; p < 0.001), with a wide percentage error (47%), implying that completely noninvasive CO devices are not interchangeable with thermodilution.The CO measured by bioreactance has been shown to be highly correlated with that measured by pulse-contour analysis and thermodilution. The most frequently used analytic method for evaluating CO monitoring devices is the Bland–Altman method of plotting bias against mean CO and by determining the limits of agreement (LOA) . The per< 0.001) . A systereathing . A totalIn terms of fluid responsiveness, bioreactance-based devices have been studied in both spontaneously breathing and mechanically ventilated patients with shock in combination with the passive leg raise test (PLR). Specifically, NICOM has been validated in the assessment of fluid responsiveness by PLR –50. BenoFirst-version NICOM provided CO readings averaged over 30 seconds, creating concerns in its ability to track very rapid changes in SV (pertinent in the assessment of fluid responsiveness). Alteration of the algorithm has led to the Starling-SV device for which the averaging time of CO has been reduced to 8 seconds. Bioreactance-based measurements are limited in situations where there is no association between aortic systolic deformation and SV , severe anemia, pulmonary arterial hypertension, or due to physical limitations such as obesity and large pleural effusions. Pitfalls and limitations of using bioreactance-based noninvasive cardiac output monitoring in the critical care unit and in intraoperative settings are shown in supplementary material On the basis of the preceding discussion, alternative approaches towards hemodynamic monitoring in SAH can involve minimally invasive methods for the continuous monitoring of CI and fluid responsiveness . Such stIn this manuscript, we reviewed the use of a noninvasive device that has been reported, in different ICU populations, to have an acceptable performance in terms of estimations and tracking of CI and fluid responsiveness. Additional considerations include the ability to monitor patients without central or arterial lines, the user-friendly nature of the device, and the ability to employ it in non-ICU settings. In terms of our limited evaluation of this technology, we found CI and fluid responsiveness estimations consistent and expected as compared to the overall normal cardiac function  demonstrated by our patients with mostly low-grade SAH. The idea of monitoring fluid responsiveness in order to rationalize fluid management in patients with SAH is promising and should be further explored. However, this short report precludes any conclusions in terms of device performance in patients with high-grade SAH or patients with stress cardiomyopathy or under active hemodynamic augmentation with vasoactive medications. Future work is planned to investigate the role of such monitoring in “hemodynamically active” SAH patients.Estimation and manipulation of effective circulating volume, cardiac function, and stroke volume are central features in the critical care approach to patients with SAH. Reliance on static preload markers, fluid balances, and indiscriminate fluid loading should be discouraged in view of their unreliability and potential harm in terms of both systemic and neurologic adverse effects. Instead, accumulating evidence across critically ill populations suggests that hemodynamic optimization can be better informed by direct measurements of compartmental volumes, continuous assessment of stroke volume and cardiac performance, and testing of fluid responsiveness. A number of minimally invasive technologies can provide such monitoring; our aim, here, was to review a noninvasive bioreactance-based technique and comment on our preliminary experience as tested in a pilot cohort of SAH patients.


Hyponatremia can be developed during hysteroscopic surgery with electrolyte-free irrigation fluid. We experienced severe hyponatremia with postoperative seizures and confirmed mild brain edema.A quadragenarian female patient underwent a 2-h hysteroscopic myomectomy with electrolyte-free fluid for uterine distension under general anesthesia. Plasma sodium level of 84.1 mmol/L 100 min after the start of surgery indicated excessive absorption of the irrigation fluid. Acute severe hyponatremia was diagnosed with significant edema in the conjunctiva, lip, and extremities. She was treated with a continuous infusion of hypertonic saline. However, seizures and cerebral edema developed 7 h later. The patient recovered without neurological deficits at postoperative day 2.The electrolyte-free irrigation fluid can be absorbed rapidly during hysteroscopic surgery. Its interruption with hyponatremia should be considered against prolonged surgery. Especially under general anesthesia, caution should be exercised because the typical symptoms of hyponatremia such as nausea and confusion are blinded. Hyponatremia is a severe complication of hysteroscopic myomectomy, caused by the absorption of fluid media used for uterine distension via damaged blood vessel and myometrium –7. Absor2, 100% (FiO2 = 0.21). General anesthesia was induced with fentanyl, propofol, and rocuronium, followed by tracheal intubation and maintained with desflurane and remifentanil. The urinary catheter was not inserted as the estimated operation time was 1 h. Electrolyte-free 3% d-sorbitol solution  was used for monopolar electrosurgery. The patient was placed in a lithotomy position. The solution bag was placed at approximately 100 cm height from the surgical table without any additional pressure applied to the bag. The difference between the fluid inflow and outflow increased over time. During the latter half of the surgery, a substantial spillage was observed on the floor. A mild decrease in blood pressure was observed throughout the surgery. Approximately 100 min after the start of surgery, the plasma sodium level was estimated as 84.1 mmol/L. At the end of the 123-min surgery, the difference between the inflow (21 L) and the collected outflow (14 L) was 7 L excluding the spillage. At this time, the vital signs were as follows: blood pressure, 80/34 mmHg; heart rate, 60 bpm, SpO2, 99% (FiO2 = 0.45). Premature ventricular contractions were observed 5 to 10 times per minute. The intravenous fluid infused was 780 mL in total. The urinary catheter was inserted due to prolonged surgical time. Immediately, 1000 mL of urine was excreted. After the drapes were removed, distention of the lower abdomen and navel was noticed. No abdominal fluid wave on palpitation, and no findings of intraperitoneal fluid retention by an abdominal ultrasound exam were observed. However, there were significant edemas in the conjunctiva, lip, and fingers  was scheduled for a hysteroscopic myomectomy under general anesthesia. Her chief complaint was hypermenorrhea. Preoperative ultrasound revealed a 3.6-cm submucous uterine myoma which protruded into the uterine cavity (protrusion ratio: 60–70%). Gonadotropin-releasing hormone therapy was initiated 3 months prior to the operation to improve anemia and shrink the myoma. Her preoperative laboratory tests were normal except the serum bilirubin level of 1.3 mg/dL. Electrocardiogram, non-invasive blood pressure, and pulse oximetry were applied for intra-anesthesia monitoring. Immediately before the anesthesia induction, the vital signs were as follows: blood pressure, 114/80 mmHg; heart rate, 82 bpm; and SpOThe details of correctional treatment, and transition of plasma sodium level and urine output are described in Fig. In this case, severe hyponatremia occurred during a 2-h hysteroscopic myomectomy with electrolyte-free solution. Although a seizure attack and mild brain edema occurred, the patient fully recovered on the second postoperative day.Hysteroscopic surgery is generally less invasive than laparoscopic or open surgery when the patient selection is appropriate. As this case had 3.6 cm leiomyoma, smaller than 4–5 cm, the indication was applicable . HoweverTreatment of severe acute hyponatremia should be considered. A guideline proposes a treatment strategy for hyponatremia with severe symptoms (1D and 2D indicate strong and weak recommendations with low evidence) . BrieflyElectrolyte-free 3% d-sorbitol solution was used in this case for the monopolar electrical system. Nowadays, isotonic fluid is also used in hysteroscopic surgery to avoid dilutional hyponatremia. However, cases have been reported that isotonic fluid can result in severe hypokalemia and metabolic acidosis with arrhythmia  or severAs the significant edema and the difference between the fluid inflow and outflow indicated the absorption of irrigation fluid, we administered furosemide to excrete water from the body. It should be noted that chronic furosemide intake can develop hyponatremia , 14 due We experienced severe hyponatremia with a postoperative seizure attack and mild brain edema in a case undergoing a 2-h hysteroscopic procedure with electrolyte-free solution as irrigation fluid. During the surgery, it is essential to monitor the fluid balance closely, and the interruption of the surgery should be considered by prolonged surgery and a large difference between inflow and outflow fluid. Under general anesthesia, caution should be exercised because the typical symptoms of hyponatremia such as nausea and confusion are blinded. Hyponatremia was treated with hypertonic saline administration and left no permanent neurological deficits.


The primary aim was to test the hypothesis that deriving pre-treatment 3D magnetic resonance tumour volume (mrTV) quantification improves performance characteristics for the prediction of loco-regional failure compared with standard maximal tumour diameter (1D) assessment in patients with squamous cell carcinoma of the anus undergoing chemoradiotherapy.sum). Reproducibility was assessed using intraclass concordance correlation (ICC) and Bland-Altman limits of agreements. We derived receiver operating curves using logistic regression models and expressed accuracy as area under the curve (ROCAUC).We performed an early evaluation case-control study at two UK centres (2007–2014) in 39 patients with loco-regional failure (cases), and 41 patients disease-free at 3 years (controls). mrTV was determined using the summation of areas method  minutes. Intra and inter-observer reproducibilities were generally good (ICCs from 0.79 to 0.89) but with wide limits of agreement . Median mrTVs were greater for cases (32.6 IQR: 21.5–53.1 cm3) than controls . The ROCAUC for mrT-size predicting loco-regional failure was 0.74 (95% CI: 0.63–0.85) improving to 0.82 (95% CI: 0.72–0.92) when replaced with mrTV .The median time per patient for VolPreliminary results suggest that the replacement of mrTV for mrT-size improves prediction of loco-regional failure after chemoradiotherapy for squamous cell carcinoma of the anus. However, mrTV calculation is time consuming and variation in its reproducibility are drawbacks with the current technology.The online version contains supplementary material available at 10.1186/s12885-020-07613-7. Chemo-radiotherapy (CRT) is the primary treatment for patients with squamous cell carcinoma of the anus (SCCA) . The keyUntil recently, CRT for SCCA adopted a broad “one size fits all” strategy, typically comprising 5-fluorouracil and mitomycin concurrent with 50 to 55 Gy radiotherapy, despite a wide spectrum of the loco-regional disease stages at presentation. Stratified approaches are now being evaluated, as exemplified by the UK PLATO  trial  illustraAn alternative imaging approach to pre-treatment staging is magnetic resonance quantification of tumour volume (mrTV). This has been explored in other tumour sites, such as in head and neck –10 and lThe primary aim was to test the hypothesis that deriving pre-treatment 3D mrTV quantification improves performance characteristics for the prediction of LRF compared with standard maximal tumour diameter (1D) assessment in patients with SCCA undergoing CRT. We chose to quantify 3D mrTV using a summation of areas method, as conceptually, this better captures the complex 3-dimensional nature of an anal tumour compared with estimation methods derived from 1D tumour dimensions. But in turn, this method may be labour intensive and there may be considerable variation in reproducibility. Thus, secondary aims were to evaluate whether 3D mrTV quantification directly measured on scans by the summation of area method is reproducible; and whether volume estimation derived from less labour intensive 1D tumour dimensions is a valid estimation of tumour volume.In accordance with the CRUK/EORTC imaging biomarker consensus statement, this was a two-centre Domain 2 validation study evaluating performance characteristics, reproducibility and whether the biomarker is ‘fit for purpose’ .We performed a case-control study at two UK centres, the Christie NHS Foundation Trust, Manchester, and Leeds Teaching Hospitals Trust, Leeds (LTHT). Patients were included if they had histologically confirmed SCCA; T1 to T4 disease (AJCC 7th edition) ; and had2 on day 1, and continuous infusion of 5-fluorouracil (5-FU) 1000 mg/m2 on days 1–4 and days 29–32.All patients were treated between 2007 and 2014 prior to the introduction of IMRT (Intensity Modulated Radiotherapy). The treatment protocol followed that used in the ACT II trial  – namelyFrom the retrospective two-centre clinical databases, all 40 patients with LRF from 2007 to 2014 undergoing CRT and with measureable anal tumours were selected as cases (one outlier volume later excluded). Forty-one patients without LRF at 3 years were controls. Control selection was at random from those patients in the databases with available MR images satisfying criteria listed next.All tumour quantification used routinely collected pre-treatment MR imaging, performed on a 1.5 Telsa MR employing optimal pelvic phase-array body coil , left-right (LR) and cranio-caudal (CC) planes along the axis of the tumour measured on the high resolution T2W images. The AP and LR diameters were recorded on the axial plane at the point of maximal dimension. The longest diameter was noted and the next dimension was taken at an axis perpendicular to the above. CC dimension was measured in either the coronal or sagittal plane. The largest of these three diameters was considered to be the tumour size (cm). Assessors (RK and BC) were blind to LRF status.To determine mrT-size, three primary orthogonal measurements of the maximal diameters were taken in the anterior-posterior mrTV measurements were performed using World-Match (in-house written software from MvH ) that alsum), which sums-up the area contoured on serial image slices while taking into account the distance between the slices; i.e. the slice thickness of the scans  patients and compared using intra-class concordance correlations (ICC) with scores < 0.5 representing poor; 0.5 to < 0.75 moderate; 0.75 to < 0.9 good; and ≥ 0.9 excellent agreement . 95% conAP, LR and CC planes. The ellipsoid equation was: π × d1 × d2 × d3)/4. These were assessed for reproducibility as above. We also evaluated for accuracies compared with Volsum using the ROCAUC method .We tested whether volume estimation derived from 1D tumour dimensions is a valid estimate of TV, using ellipsoid and elliptical cylinder equations and measured 1D diameters  was used for all statistical analyses. Continuous data were summarised as medians with inter-quartile ranges (IQR) and categorical data were presented as proportions. Comparisons were by Chi-square and Fisher’s Exact tests and non-parametric Mann-Whitney U tests, respectively.AUC using post-estimation commands.Assessment of the discriminatory potential of the different tumour quantifications was tested with receiver operator characteristic curves (ROCs) and estimation of accuracy using the AUC and compared against each other using the method of DeLong et al. . MultivaAUC. We added 3% as case-control studies tend to overestimate performance characteristics .mrTV measurements took a median of 7 min, but with wide variation from less than 1 min to over an hour. Contours performed in the 22 preliminary patients took longer than subsequent determinations . Similarly, mrTV determined by summation of areas was greater in cases compared with controls   cm versus 3.6 (IQR: 2.9–5.2) cm, –6.2 cm vAUC for mrT-size predicting LRF was 0.74 (95% CI: 0.63–0.85).This improved to 0.82 (95% CI: 0.72–0.92) when mrTV replaced mrT-size (p = 0.024)  cm3. Agreement was excellent between Volsum and volume determined by the ellipsoid eq. [ICC scores =0.91 (95% CI: 0.86 to 0.94)] and good between Volsum and volume determined by the elliptical cylinder eq. [ICC scores =0.73 (95% CI: 0.66 to 0.80)]. From, the Bland-Altman plots, the limits of agreement for Volsum and volume determined by the ellipsoid equation were from − 20.4 (− 16%) to 20.1 (17%). For Volsum versus volume determined by the elliptical cylinder, there was a disproportionate trend with increasing volume  cmAUC for mrTV determined by the ellipsoid volume estimate was 0.79 (95% CI: 0.68 to 0.89); that for the elliptical cylinder volume estimate was identical (Table SThe ROCl Table S.sum) versus mrT-size, the IDI was 9.6% , which was statistically different (p = 0.0015). By contrast, the NRI was potentially large at 34% (se: 22%), but not statistically significant (p = 0.123).For mrTV  had imperfect levels of agreement with volume determined by summation of areas but it is unknown whether this influences performance characteristics defined by AUC on ROC analyses.To our knowledge, this is the first study to evaluate the performance characteristics of mrTV and LRF in SCCA. Many studies –29 in paMR imaging is the current standard of care for the pre-treatment staging of SCCA , providiThe study has several strengths. First, we used data from two well-characterised UK treatment centres with uniform treatment protocols. Second, to minimise the risk of heterogeneity in scanning parameters and quality over time and between centres, scan quality parameters were evaluated. Third, in-house written software was employed, which allowed contouring in multiple planes, facilitating accurate volume quantification.α < 0.001. Third, we fell just short of our target sample size. An improvement of 9% in the ROCAUC for mrTV over mrT-size was statistically significant at p = 0.024, and might be clinically meaningful. A similar 9% was noted with the IDI method, and while the NRI was potentially promising at 34%, it had much uncertainty. Fourth, as a retrospective study, there are potential biases and confounding. To mitigate against some of these, the assessors were blinded. Finally, the study recognises that ‘drawing’ tumour volume on MR is currently imprecise. It is challenging to differentiate peri-tumour oedema and fibrosis from tumour tissue and pathological validation of TV measurements was not possible. Indeed, tumour delineation is one of the most uncertain aspects of RT planning and as such, assessment of tumour volume for the purpose of prediction is subject to the same issues [The study has several limitations. First, with only 80 patients, it is a relatively small sample size. Second, to enrich for events we used a case-control study design. This approach is biased in that it overestimates performance characteristics  and hence issues –39. ThisThe findings from this study suggest that 3D MR-based tumour volume quantification may enhance prediction of LRF risk over current MR-based methods. We speculate that TV better reflects tumour biology and could facilitate risk stratification to improve the precision of personalised treatment. The main limitation is that tumour ROI definition on MR is not currently routinely performed, and can be time consuming. MR-based RT planning, currently investigated in tumours such as rectal adenocarcinoma , may becTumour regression grading has been found to predict for early local failure in SCCA . FurtherPET-CT is increasingly used in the pre-treatment assessment of anal cancer and small studies demonstrate the potential prognostic role of metabolic tumour volume (MTV) –45. LargLastly, we acknowledge that looking at a single parameter to predict LRF is simplistic and it is more realistic that a number of patient, biological, tumour and radiological features each contribute to prognostic outcomes in anal cancer , and areThese preliminary results suggest that 3D MR-based tumour volume quantification may improve prediction of LRF in patients with SCCA following CRT over currently employed measurements. Further work will be required to refine ROI contouring, both in regards to facilitating a less time consuming and more reproducible process, and to explore the role of this tumour volume within multiparametric prognostic models for LRF in SCAA.Additional file 1.


Aim: The selective BRAF and MEK inhibitors (BRAFi+MEKi) have substantially improved the survival of melanoma patients with BRAF V600 mutations. However, BRAFi+MEKi can also cause severe or fatal outcomes. We aimed to identify and compare serious adverse events (sAEs) that are significantly associated with BRAFi+MEKi. Methods: In this pharmacovigilance study, we reviewed FDA Adverse Event Reporting System (FAERS) data in order to detect sAE reporting in patients treated with the combination therapies vemurafenib+cobimetinib (V+C), dabrafenib+trametinib (D+T) and encorafenib+binimetinib (E+B). We evaluated the disproportionate reporting of BRAFi+MEKi-associated sAEs. Significant associations were further analyzed to identify combination-specific safety signals among BRAFi+MEKi. Results: From January 2018 through June 2019, we identified 11,721 sAE reports in patients receiving BRAFi+MEKi. Comparison of BRAFi+MEKi combinations demonstrates that skin toxicities, including Stevens–Johnson syndrome, were disproportionally reported using V+C, with an age-adjusted reporting odds ratio (adj. ROR) of 3.4 , whereas fever was most significantly associated with D+T treatment with an adj. ROR of 1.9 . Significant associations using E+B treatment include peripheral neuropathies  and renal disorders . Notably, we found an increase in the proportion of Guillain–Barré syndrome reports  in patients administered E+B. Conclusion: BRAFi+MEKi combinations share a similar safety profile attributed to class effects, yet concomitantly, these combinations display distinctive effects that can dramatically impact patients’ health. Owing to the limitations of pharmacovigilance studies, some findings warrant further validation. However, the possibility of an increased risk for these events should be considered in patient care. BRAFv600 mutations [Combination therapy with BRAF plus MEK inhibitors (BRAFi+MEKi) has transformed the treatment landscape and improved the clinical outcomes of patients with melanoma harboring utations ,4,5,6,7.utations , 67% forutations  and 63% utations  in BRAF-utations . Howeverutations . Moreoveutations .The safety profiles of BRAFi+MEKi monotherapy and combination therapies were evaluated during the confirmatory trials ,16,17,18Considering the similar clinical efficacy demonstrated by the three BRAFi+MEKi combinations, the therapeutic decision often relies on the safety profile that characterizes each of the combinations. However, despite numerous studies comparing different agents, there are no head-to-head clinical trials comparing the different combinations, and most safety data originate from the confirmatory phase III trials . MoreoveThe observational, retrospective, pharmacovigilance study is based on reports linked to suspect drugs in the FDA Adverse Events Reporting System (FAERS) ,36. The This study included serious events leading to death, life-threatening conditions, disability, or hospitalization from January 2018 to December 2019. Despite available reports before 2018, this period was used to compare the reports of three BRAFi+MEKi combinations during the same timeframe. Of note, reports of AEs associated with E+B started in 2018. Adverse events were classified according to the Medical Dictionary for Regular Activities (MedDRA), which organizes terms into a hierarchy . DuplicaDisproportionality analysis using the ‘case-control’ approach allows assessing whether the reporting rate of AEs is differentially elevated relative to expected rates of reporting in a pharmacovigilance database ,40. Dispp-values, as proposed by Ahmed et al. [p-value for multiple testing using the Benjamini–Hochberg (BH) correction was <0.05 [The decision rule for a potential signal generation was based on a positive IC value (>0), a minimum number of reactions of 3, and a threshold of 0.05 for the Bayesian version of the false discovery rate (FDR) . This and et al. , and a sas <0.05 . Only coas <0.05  and epiRas <0.05  packagesas <0.05 .The FAERS database included 11,721 reports of sAEs among patients receiving V+C (2345), D+T (8411) and E+B (965), corresponding to the time period (January 2018 to December 2019) . The tot−130), followed by general systems disorders not elsewhere classified (NEC) with 249 (10.6%) cases  (−20) and body temperature conditions with 496 (5.9%) cases . For patients treated with E+B, the most common sAE reports were general systems disorders with 116 (12.0%) cases , followed by gastrointestinal signs and symptoms with 68 (7.0%) cases .In order to compare reactions between different BRAFi+MEKi combinations that are also differentially elevated compared to other drugs, we first performed a disproportionality analysis compared to the background . The most common sAE reports in patients exposed to V+C were epidermal and dermal conditions with 311 (13.3%) cases  . For patThe reported frequencies of sAEs for the three BRAFi+MEKi combinations can be compared directly using ROR analysis. The detailed ROR estimates of V+C, D+T, and E+B for sAEs detected as signals are listed in We conducted further analysis and calculated the age-adjusted ROR of the identified disproportional sAEs. The adjusted ROR of the sAEs  showed sWe described the clinical characteristics of cases with sAEs occurring in patients treated with BRAFi+MEKi . Among pNovel therapeutic strategies relying on the selective inhibition of the MAPK pathway have proven to significantly prolong the survival of patients with advanced BRAF-mutated melanoma ,4,5,6,7.The results show a significant incidence of skin disorders, fever, and GI conditions associated with BRAFi+MEKi combinations, corresponding to the recognized class effects of the treatment ,13,19. AConfirmatory studies are necessary to determine therapeutic activity but are limited in providing an accurate depiction of the safety profile, as the conditions under which medicines are used post-marketing may not be reflected in clinical trials, and they also lack sufficient power to detect infrequent or rare events ,56. PharFew limitations of disproportionality analysis need to be recognized. Pharmacovigilance studies have complementary strengths in signal detection that require further validation, optimally in prospective trials. Replication of safety issues in other continental reporting agencies such as the WHO pharmacovigilance database and European Medicine Agency is biased by overlapping safety reports between databases . FurtherOne of the major limitations of the analysis involves the inability to quantify the incidence of identified risks, as the total number of patients exposed to a given product is unknown . FurtherIn conclusion, our study shows that beyond skin disorders and fever associated with V+C and D+T, respectively, BRAFi+MEKi therapy can cause other combination-specific toxicities that include gastrointestinal, renal and neurological disorders associated with E+B. Most of the serious adverse reactions commence soon after administration and resolve after dechallenge. These complications should be considered in therapeutic decision making, and careful monitoring is recommended.


Rectal cancer has the eighth highest cancer incidence worldwide, and it is increasing in young individuals. However, in countries with a high human development index, mortality is decreasing, which may reflect better patient management, imaging being key. We rely on imaging to establish the great majority of clinical tumour features for therapeutic decision-making, namely tumour location, depth of invasion, lymph node involvement, circumferential resection margin status and extramural venous invasion. Despite major improvements in technique resulting in better image quality, and notwithstanding the dissemination of guidelines and examples of standardised reports, rectal cancer staging is still challenging on the day-to-day practice, and we believe there are three reasons. First, the normal posterior pelvic compartment anatomy and variants are not common knowledge to radiologists; second, not all rectal cancers fit in review paper models, namely the very early, the very low and the mucinous; and third, the key clinical tumour features may be tricky to analyse. In this review, we discuss the normal anatomy of the rectum and posterior compartment of the pelvis, systematise all rectal cancer staging key points and elaborate on the particularities of early, low and mucinous tumours. We also include our suggested reporting templates and a discussion of its comparison to the reporting templates provided by ESGAR and SAR. Imaging is the pillar upon which therapeutic decisions are made in rectal cancer patients.Knowledge of normal anatomy and variants of the posterior pelvic compartment is mandatory for rectal cancer staging.We provide a roadmap for rectal cancer staging which includes anatomy and anatomic variants of the posterior pelvis, all key staging features and the particularities of early, low and mucinous tumours.Rectal cancer is one of the best examples of success of clinical research in the past 40 years. Total mesorectal excision (TME) alone, as opposed to blunt “pelvic rape”, resulted in an increase in the 5-year cancer-specific survival rate from 38 to 68% . The intThe rectum ends distally at the anorectal transition. The anorectal transition may be defined by 2 anatomic landmarks: the first is an abrupt increase in thickness of the inner muscular layer, corresponding to the upper limit of the internal sphincter of the anus Fig. a 4]. Th. Th4]. TThe definition of the upper limit of the rectum is an intraoperative definition, corresponding to the lower limit of the large bowel that can be mobilised away from the spinal column. On MR imaging, it may correspond to the point of inflection between the more vertical rectum and the more horizontal rectosigmoid or “sigmoid take-off” –9 Fig. a. The acThe rectum may be divided into 3 segments: upper, mid and low. The upper rectum is located above the lower limit of the anterior peritoneal reflection (see below) Fig. a 8]. Th. Th8]. TFor standardization purposes, we recommend rectal cancer location measurements to be made based on the central axis of both the anal canal and rectum Fig. a. RectumAlthough peristalsis, pulsation, breathing and susceptibility from bowel air may cause image artefacts, in optimal conditions, the layers of the rectal wall should be clearly defined. The mucosa is a thin, dark regular line on T2 Fig. a. It is A small enema before MR imaging may minimise susceptibility from bowel air . SpasmolThe rectum is out of the peritoneal cavity, and its serosa—the mesorectal fascia—is displaced radially to contain a large fatty cushion—the mesorectum. The mesorectal fascia is usually described as a pencil-drawn hypointense line on T2. However, it is a multi-layered envelope that presents with gaps, particularly at its lower antero-lateral aspect, which means that at some points it may not be visible and we must extrapolate its expected position Fig. a 14]. A. A14]. AThe parietal fascias have different names according to location. Anteriorly, in between the anterolateral neurovascular bundles and extending craniocaudally from the pelvic floor to the peritoneal reflection is the trapezoidal-shaped Dennonvillier fascia Fig. c, d 15]15]; postCaudally, the mesorectal fascia is in continuity with the intersphicteric plane Fig. f 18]. C. C18]. CThe anterior peritoneal reflection can easily be identified whenever there is a small amount of free peritoneal fluid because in the supine position it will accumulate at the deepest point of the rectovesical or rectouterine pouch, exactly where the peritoneum “reflects” Fig. c. The heArterial blood arrives at the rectum through 4 routes. The main route is the superior rectal artery, which is the continuation of the inferior mesenteric artery when it crosses the left common/internal iliac artery Fig. a 22]. T. T22]. Tlevatior ani, and an inner submucosal plexus which runs through the whole extension of the rectum and continues down to the anus , 3433, 3The maximum depth of invasion tends to occur at the tumour’s centre, and in large tumours, orientation of the slices perperdicular to it may be the most useful. On the other hand, it is common for the tumour’s periphery to overhang the rectal wall into the lumen Fig. c, d, f.The circumferential margin of resection (CRM) is the plane where surgeons must dissect in order to perform a standardised total mesorectal excision (TME). It corresponds to the full circumference of the mesorectal fascia and, in tumours extending down into the anal canal, to the intersphincteric plane, with which the mesorectal fascia is in continuity inferiorly. The minimum distance between the tumour and the circumferential margin of resection on high-resolution T2-WI acquired perpendicular to its long axis should be recorded, as well as its location and extent. CRM is considered involved if the tumour lies < 1 mm from it Fig. a 38]. A. A38]. AExtramural venous invasion (EMVI) on the histopathology of rectal cancer surgery specimens is an independent predictor of local recurrence, distant recurrence and worse overall survival . MR imagIn rectal cancer patients, nearly 48% of positive lymph nodes are ≤ 5 mm. As such, size criteria to identify nodal involvement are not reliable –30, 46. For nodes in the lateral pelvis, mostly size criteria have been tested, with variable cutoffs and variable outcomes –56. AccoTumour deposits are defined according to AJCC 2018 as discrete tumour nodules in the rectal cancer pathology specimen within the lymphatic drainage area of the primary tumour without identifiable lymphatic, vascular or neural tissue, irrespective of their morphology . If a veAlthough T stage now prevails, lymph node positivity on MR imaging is still considered an indication for neoadjuvant therapy according to NCCN guidelines, whereas ESMO guidelines admit surgery upfront for N positive patients without involvement of the circumferential margin of resection or mrEMVI, preferably ≤ T3a-b , 34.In the authors’ perspective, the differentiation between positive lymph nodes with extracapsular extension, ENTDs and discontinuous EMVI on MR imaging may be difficult. Evidence suggests all of these entities entail a worse outcome compared to confined lymph node involvement. As such, pointing extranodal tumour on staging reports may be more important than matching its exact pathologic diagnosis Fig.  60].Fi.Fi60].k = 0.74) [Very early rectal cancers, defined as low grade (G1/G2) cT1 cN0 cEMVI- tumours , can be  = 0.74) . ResultsA tumour with its lower edge less than 6 cm above the anal verge is considered a low rectal cancer Fig. 19)19). Its In low rectal tumours, additional oblique axial and coronal T2-WI planes perpendicular and parallel to the long axis of the anal canal, respectively, should be acquired when needed. The anal verge may be identified on sagittal T2-WI as the lower limit of the perianal hypointense skin change Fig. .Mucinous adenocarcinomas comprise 10–20% of all rectal cancers, tend to affect younger patients and are defined histologically by the presence of extracellular mucin in more than 50% of the tumour stroma . There iWhenever in doubt, DWI b0 may be useful for the distinction between fat signal, which will be suppressed, and mucin, which will remain bright. Also, we find high-resolution T1-WI may help define the boundary between mucin and fat Fig. .Figures Our patients routinely perform a small enema shortly before MR imaging to empty the rectum, which significantly reduces susceptibility artefacts due to air content, improvement being particularly relevant for DWI . IntraveOur acquisition protocol is exhibited in Table With respect to staging key points, all of our patients are staged with MR imaging unless an absolute contraindication is known, even early tumours, and as such, we have decided to include early tumour sub-staging in our templates as by Balyasnikova et al. , which iPelvic MR imaging is the pillar of clinical rectal cancer staging and the basis for optimal multidisciplinary patient management decision-making. A thorough and systematic knowledge of the relevant normal anatomy and variants, of the key staging imaging features and of the particularities of early, low and mucinous tumours is mandatory for rectal cancer staging MR image interpretation.


The brain lacks a conventional lymphatic system to remove metabolic waste. It has been proposed that directional fluid movement through the arteriolar paravascular space (PVS) promotes metabolite clearance. We performed simulations to examine if arteriolar pulsations and dilations can drive directional CSF flow in the PVS and found that arteriolar wall movements do not drive directional CSF flow. We propose an alternative method of metabolite clearance from the PVS, namely fluid exchange between the PVS and the subarachnoid space (SAS). In simulations with compliant brain tissue, arteriolar pulsations did not drive appreciable fluid exchange between the PVS and the SAS. However, when the arteriole dilated, as seen during functional hyperemia, there was a marked exchange of fluid. Simulations suggest that functional hyperemia may serve to increase metabolite clearance from the PVS. We measured blood vessels and brain tissue displacement simultaneously in awake, head-fixed mice using two-photon microscopy. These measurements showed that brain deforms in response to pressure changes in PVS, consistent with our simulations. Our results show that the deformability of the brain tissue needs to be accounted for when studying fluid flow and metabolite transport. The brain is surrounded by cerebrospinal fluid (CSF), and the movement of CSF can clear metabolites from the central nervous system (CNS) –7. The nAn important approach for understanding fluid movement in the brain and the PVS is simulation of fluid dynamics. Calculations based on fluid mechanics , 19, 28 The study is organized into three parts. In the first part, we investigated the possibility of directional fluid movement in the PVS driven by the movement of arteriolar walls. We found that neither arteriolar pulsations, nor functional hyperemia could drive appreciable directional flow of CSF through the PVS. Next, we examined the possibility of metabolite clearance from the PVS through exchange of fluid between the PVS and SAS. Our simulations showed that functional hyperemia, but not arteriolar pulsations, can drive large fluid exchange between the PVS and the SAS. This fluid exchange could help remove metabolites from the CNS. Our simulations predicted that the difference in fluid exchange driven by pulsations and hyperemia are partly because of the deformation of brain tissue in response to the pressure changes in the PVS. We verified this prediction by using in vivo two-photon microscopy to measure the deformation of the brain tissue and arteriolar diameter during functional hyperemia. Our measurements revealed that the brain tissue can in-fact deform from pressure changes in the PVS, as suggested by our model. These results suggest that in addition to its involvement in other processes, functional hyperemia can aid metabolite clearance in the brain through the exchange of CSF between the SAS and PVS.We first explain our modeling choices and parameters before diving into the results of our simulations. We are interested in understanding how the motions of the arteriolar walls drive fluid exchange between the PVS and SAS. We performed fluid mechanics simulations of the CSF in the PVS surrounding penetrating arterioles in adult mice. There is great deal of ambiguity regarding several key parameters governing the fluid flow of the PVS, namely the permeability of the PVS, channel width of the PVS, and the flow resistance of the surrounding spaces (the brain parenchyma and the SAS). These ambiguities pertaining to flow in the PVS within the subarachnoid space  and the −15 m2, the measured permeability of the brain tissue ) of 1.8 × 10−3 µm/s. To make the movements clearly visible, we scaled the displacements by a factor of 10 in post-processing. b. Fluid pressure in the PVS corresponding to the flow shown in a. Pressure changes due to fluid flow in the PVS reach several mmHg. These pressures will deform the soft brain tissue, which has a shear modulus of 1–8 kPa ) of 2.9 × 10-3 µm/s. To make the movements clearly visible, we scaled the radial displacements by a factor of 10 in post-processing. b. Fluid pressure in the PVS corresponding to the flow shown in a. Pressure changes due to fluid flow in the PVS reach several mmHg. These pressures will deform the soft brain tissue, which has a shear modulus of 1–8 kPa [1a). This shows the deformability of brain tissue cannot be neglected. 1–8 kPa , 145  and axial (z) directions for viewing convenience. a. Plot of the fluid velocity induced in the PVS by arteriolar pulsation in the non-compliant brain model, where the length of the PVS is equal to one wavelength of the peristaltic wave  of 143.2µm/s, but this would be accompanied by large velocity oscillations in the range of 20,000 µm/s and large pressure changes in the range of 200,000 mmHg. Note: Arteriolar and brain tissue displacements induced by arteriolar pulsations are very small (< 0.1 µm). To make the movements clearly visible, we scaled the radial displacements by 10 times in post-processing. b. Plot of the pressure induced in the PVS by arteriolar pulsation in the non-compliant brain model, where the length of the PVS is equal to one wavelength of the peristaltic wave  and axial (z) directions for viewing convenience. a. The imposed heartbeat-driven pulsations in arteriolar radius (±0.5% of mean radius [i) at 10 Hz, the heartrate of an un-anesthetized mouse. The pulse wave travels at 1 meter per second along the arteriolar wall, into the brain [b. Colors showing the axial velocity (velocity in the z-direction) in a cross section of the PVS, when the arteriolar wall movement is given by periodic pulsations. Fluid velocity vectors (arrows) are provided to help the reader interpret the flow direction from the colors. The white region is stationary. These plots  (magenta) and a completely incompressible, Neo-Hookean models (blue) were nearly identical.n radius ,Ri) at 1he brain , 58. b. Additional file 6: Figure S7. Vasodilation-induced PVS fluid flow in a completely incompressible, Neo-Hookean model was very similar to the compressible SVK model. Note the geometry is depicted with an unequal aspect ratio in the radial (r) and axial (z) directions for viewing convenience. a. Plot of the prescribed arteriolar wall movement, which is identical to the one shown in Fig b. Plot showing the axial (z-direction) fluid velocity a cross section of the PVS, when the arteriolar wall movement is given by neural activity-driven vasodilation. A portion of the vessel lumen is shown in red to provide a sense of vasodilation. Fluid velocity vectors (arrows) are provided to help the reader interpret the flow direction from the colors. The region in white has little to no flow. These plots  brain tissue (magenta) and a completely incompressible, Neo-Hookean model (blue) are very similar.Additional file 7: Figure S5. Pulsation-driven flows are small in simulations when the subarachnoid space (SAS) is modeled as a porous, fluid-filled region. Note the geometry is depicted with an unequal aspect ratio in the radial (r) and axial (z) directions for viewing convenience. a. Schematic showing the model of the penetrating arteriole used in this simulation. The brain tissue is modelled as a compliant solid. Subarachnoid space is modelled as a fluid filled region (SAS “geometry” model). b. Schematic showing the alternative model of the penetrating arteriole  at the end of the PVS (SAS “resistance” model). The results for the SAS “resistance” model are shown in Fig c. The imposed heartbeat-driven pulsations in arteriolar radius (±0.5% of mean radius [i) at 10 Hz, the heartrate of an un-anesthetized mouse. The pulse wave travels at 1 meter per second along the arteriolar wall, into the brain. d. Plot showing the axial velocity (velocity in the z-direction) in a cross section of the PVS and the connected SAS, when the arteriolar wall movement is given by periodic pulsations. Fluid velocity vectors (arrows) are provided to help the reader interpret the flow direction from the colors. Because the fluid is incompressible, the flow speed decreases when flowing into the SAS, which has a larger area of cross section compared to the PVS. The region in white has little to no flow. These plots show that there is no significant flow into the PVS driven by arteriolar pulsations. Note: Arteriolar and brain tissue displacements induced by arteriolar pulsations are very small (< 0.1 µm). To make the movements clearly visible, we scaled the displacements by 10 times in post-processing. e. Plot of the fluid flow through the top face of the PVS into the SAS. The flow rates predicted by the SAS “resistance” model (magenta) and the SAS “geometry” model (blue) are very similar.n radius ,Ri) at 1Additional file 8: Figure S8. Arteriolar dilations during functional hyperemia drive fluid exchange between the PVS and SAS in the SAS “geometry” model. Note the geometry is depicted with an unequal aspect ratio in the radial (r) and axial (z) directions for viewing convenience. a. The arteriolar wall movement is prescribed by a typical neural activity-driven vasodilation response, the same one shown in Fig b. Plot showing the axial velocity (velocity in the z-direction) in a cross section of the PVS and the connected SAS, when the arteriolar wall movement is given by neural activity-driven vasodilation. A portion of the vessel lumen is shown in red to provide a sense of vasodilation. Fluid velocity vectors (arrows) are provided to help the reader interpret the flow direction from the colors. Because the fluid is incompressible, the flow speed decreases when flowing into the SAS, which has a larger area of cross section compared to the PVS. The region in white has little to no flow. These plots  and the SAS “geometry” model (blue) are almost identical.Additional file 9: Figure S9. Heartbeat drives 0.5–4% (peak-to-peak) changes in arteriolar diameter. a. Sample image of the in-vivo fluorescence measured by two-photon microscopy following intravenous injection of FITC conjugated dextran (150 kDa) shows the cerebral vasculature near the surface of the brain . Inset  shows a smaller region containing a segment of the arteriole, that is scanned at 30Hz to obtain arteriolar diameter changes in the typical heartrate frequencies (4-14 Hz). b. Sample plot of the diameter values measured for the arteriole shown in a. The plot shows that heartbeat drives 1.4% peak-to-peak change in diameter for this arteriole. c. Spectrogram shows the log power of diameter changes for the sample arteriole shown in a. There is a clear peak in spectral power at 5.59 Hz, which is the frequency of the heartbeat. d. Scatter plot shows the relation between the percentage changes in diameter  and the mean diameter at heartrate frequencies. To measure the pulsations in arterioles (diameter < 40 µm), we had to anesthetize the mice (green). The pulsations in awake animals could only be measured in large arteries (blue). Isoflurane anesthesia helped with reducing motion artifacts in measuring the small magnitude pulsations. No statistical tests were performed between the anesthetized and awake data due to the small sample size.Additional file: Movie SV1. SV1_heartbeat_50s.avi; Particle tracking simulation for heartbeat driven pulsations. Duration: 50s.Additional file: Movie SV2. SV2_vasodilation_50s.avi; Particle tracking simulation for functional hyperemia. Duration: 50s.Additional file 12: Figure S10. The lack of negative radial displacement in the brain tissue can be attributed to the non-linear elastic response of the connective tissue in the PVS. a. The connective tissue in the PVS is possibly made up of extracellular matrix fibers (collagen) and fibroblasts. b. When arterioles dilate, the connective tissue is under compression (middle) and the fibers buckle (bend) rather than compress due to the low energy cost of bending. Therefore, there are very low elastic forces and our assumption that the forces in the PVS originate mainly from the fluid pressure is valid. c. When the arterioles constrict or return to their original size, the connective tissue is in tension and the fibers stretch, creating significantly larger elastic forces. In this case, our assumption that the forces in the PVS originate mainly from the fluid pressure does not hold and the fluid-structure interaction model cannot predict the behavior accurately.Additional file 13: Figure S6. Deformation of the brain tissue due to the pressure changes in the PVS. Note the geometry is depicted with an unequal aspect ratio in the radial (r) and axial (z) directions for viewing convenience. a. Radial displacement contours in the brain tissue . The brain tissue can deform by upto 1.2 µm, when the arteriole  increases its radius by 1.8 µm. b. Plot shows the change of radial displacement at the PVS-Brain interface with time. These deformations can be explained by the pressure changes in the PVS. When there is fluid outflow from the PVS, the increase in the pressure causes the brain tissue to deforms radially outward and when there is fluid influx, the brain tissue deforms radially inward. The smallest tissue displacement is at the pial surface (z = 250µm), which is the location of smallest pressure changes, as it is connected to the SAS flow resistance. The brain tissue is fixed at r = 150µm. c. Plot shows the change of radial displacement in the brain tissue at different distances from the centerline of the vessel.Additional file: Movie SV3. SV3_Sample_dilation.avi; Sample imaging data showing blood vessel and brain tissue displacement. Brain tissue is marked in green (Thy1-YFP). Blood vessels are marked in magenta (Texas Red).Additional file 15: Figure S11. The procedure for measuring brain tissue displacement from in-vivo imaging data collected with a two-photon laser scanning microscope. a. Flow chart depicting the complete procedure used to calculate displacements in the brain tissue. The procedure can be broken down into 4 major sub-sections as shown in the figure. For a full description of the procedure, see methods. b. A depiction of the iterative method in calculating displacements. The figure on the left shows a reference image. The intensity is shown by a Parula colormap (Matlab). The images on the right show two cases of displaced images. The one on the top is rotated by 2°, and can be matched to the reference image (shown in gray) by a simple displacement. After the first calculation of the displacement and correcting the displaced image, the reference and the displaced image match and further iterations of displacement calculation yield a zero value, showing that the displacement calculation has converged. The one on the bottom is rotated by 45°, and cannot be matched to the reference image (shown in gray) by a simple displacement. In this case, every iteration of displacement calculation yields a non-zero value and the calculation is not converged.Additional file 16: Figure S12. The displacement calculation method is robust to noise. a. A computer generated image (512 ×  512 pixels) with randomly oriented lines. b. The radially-outward displacement given to the image shown in a. c. An image showing the radially-outward displacement at peak displacement (frame number 13). The initial position of the lines is shown in white and the displaced position is shown in blue. d. The displacement extraction procedure  is robust to noise and predicts correct displacement. On the left, a case with low signal-to-noise ratio (0.59) is shown. The calculated displacements are very close to the actual displacement. The accuracy is comparable to the case with high signal-to-noise ratio (4.14) on the right. However, high noise results in a detection of displacement at fewer locations. The plot in the center shows that at low signal to noise ratio only 30% of the possible locations can be used for displacement calculations. Signal-to-noise ratio is calculated as the ratio of the mean signal value to the standard deviation in the noise.


In the funding statement, the grant number from the funder Spanish JCyL cofinanced with the European Union FEDER funds 2017 is listed incorrectly. The correct grant number is: SA070P17.


Owing to its severe hydrophobicity, graphene (G) as on dispersed in a fluid usually deposits therein after a short interval of time. Understanding the G-behavior and the factors affecting its deposition could pave a way for creating a substantially stable nanofluid (NF). In this work, a novel method of stabilizing a G-NF is described with selective examples. The results can be extended to develop the science and technology of G-NFs in general. Electrohydrodynamic forces are used as a controlling factor in the presence of magnetic nanoparticles (MNPs). Contrary to common chemical methods employed for preparing G-NFs, which depend on establishing bonds between the components, the physical method introduced in this article could be used as a novel approach not only to dispersing G in a fluid carrier but also to resolve the common problems originating from utilizing such chemical methods as increasing thermal resistance through adding various types of surfactants. The effects of various factors on the stability of the G-NFs are described. By increasing 50%, 100% and 170% of G, the G sitting rate increased by 43%, 82%, and 109%, respectively. With the addition of one, two and three layers to a G-monolayer, the G sitting rate grew by 77%, 153%, and 263%, respectively. Further, the G-behavior in the presence of MNPs and varied intensive electric fields were studied to optimize an electric field that could stabilize a single-layer G sheet in aqueous NFs. Adding MNPs promptly stabilizes a water/ethylene glycol/G NF in an applied electric field of 0.05 V/Å. There are several reports on nanoparticles (NPs) reinforced nanofluids (NFs) disregarding challenges concerning dispersion of NPs in a suitable liquid carrier3. The advent of nanomaterials with improved properties, particularly higher thermal conductivity, enables researchers to develop NFs with improved thermophysical properties. Graphene (G), an important member of the carbon nanomaterials3, is made of C-atoms arranged in a two-dimensional (2D) hexagonal network, where each atom having a strong covalent bond with other three C-atoms of an average 1.42 Å bond length. Having the highest thermal conductivity among different NPs, G could be considered as one of the prime candidates to be combined with conventional heat-transfer fluids to obtain NFs with higher thermophysical properties12. Researches have outlined the advancement on preparation and assessment methods and the techniques to enhance the stability of G-NFs and outlook prospects. The strong hydrophobicity of G and the influence of gravitational forces are considerable obstacles to producing such NFs with long-term stabilities. Several methods are employed to disperse not only G but also other NPs in aqueous solutions14. One such technique is adding surfactants and the other being modifying the G surfaces, which could reduce the thermophysical properties of the prepared NFs, although they hardly produce long-term stable NFs. For instance, Kim et al.15 found that a blend of dodecyl betaine (DB) surfactant and a 0.1 wt% G in water, with a ratio of G: surfactant greater than 1:1, not only does not improve the stability but also makes it more unstable compared to that having no any surfactant.Producing fluids with improved thermophysical properties has been a challenge for researchers for many yearset al.16 showed that hydrofurfuryl polyethylene glycol-functionalized G-NPs settled down after 15 days in NFs in pure water, methanol, ethanol, ethylene glycol, and 1-hexanol fluids at rates of 11, 25, 38, 18 and 47%. Kim et al.17 added three types of surfactants Sodium dodecyl sulfate (SDS), poly(propylene glycol)-block-poly(ethylene glycol) (P123) and triton X-100 to NFs containing 0.05 wt % RG (reduced G) in water and observed that, after a month, an NF containing triton X-100 was more unstable in comparison with the other ones. Shahrul et al.18 found that, after 90 min of ultrasonic stirring, water-magnetite NFs become unstable and deposited within a few min. Innovative designs of different types of stable ferrofluids (magnetic or ferroelectric NPs) dispersed in a suitable carrier liquid are well described with well-known chemical synthesis routes, and basic physics of functionalized medicals, biosensors, and other applications20. In order to investigate the surface modification of G on its stability, Uddin20 conducted a study in GO that was reduced using hydrazine monohydrate at 100 °C. That hardly disperses in a water-based NF and rather settles down rapidly. Askari et al.21 added cetyltrimethylammonium bromide (CTAB), triton X-100, and terpolymer surfactants to a water-nanoporous-G NF and observed that NPs had deposited after 3 days in the CTAB present. The NPs in the triton X-100 and terpolymer NFs deposited after two weeks and two months, respectively. Dehkordi et al.22 found that an increasing surfactant concentration in the base fluid alters its structure so as to result in foam and bubble formation, reducing the conductivity of the NFs. The additives finely modulate local structure and rheology in the NFs23.Shazali 28. This can be described in Newton’s differential equations for such NPs under an electric field30Reviewing the literature on different kinds of NFs and studies of effects of an electric field on their thermophysical properties reveals that thermophysical properties of NFs could be improved through blending MNPs, and applying an electric fieldThis study uses the hydroelectrodynamic force as Eqs.  show as 31. The ReaxFF potential was used to simulate the intermolecular forces, angles, and charge equilibrium of the system32. The ReaxFF potential calculates the force exerted on an atom at each time step using the bond order or bond distance method introduced by Tersoff36,In this study, all simulations were conducted using the LAMMPS  simulator, and the images were created utilizing an Ovito softwareIn this paper, the effects of angle of G-sheets in a dispersive phase in an NF, its temperature, the weight fraction of G by resizing, and the number of G-layers added to a base fluid are studied with an example of hybrid water (60%)-ethylene glycol (40%) heat transfer fluid. Besides, the feasibility of its stabilization was studied by adding MNPs and applying an electric field E. All systems were subject to constant pressure and volume to reach an equilibrium of 300 ps and then 700 ps, respectively. The simulation process was then pursued by applying a gravitational force of 2.2 Newton (N) with a time step of Additionally, to study the effects of G-fraction, a basic fluid structure with different modes of monolayer and multilayer G was studied. All primary structures include 4800 water molecules and 929 molecules of ethylene glycol as base fluid and G with a size of 3.5 nm × 3.5 nm at 30 °C. To study the effects of the G-content, first, the dimensions of the single-layer G-plates were increased and then the effects of fraction changes with an increasing number of layers were considered. To investigate temperature effects on G-deposition, the system was designed to contain a monolayer G with a size of 3.5 × 3.5 nm separately equilibrated at temperatures of 30, 45, 60 and 75 °C.Figure The surface tension of the G is reduced by tilting its orientation so as it deposits faster. In other words, a zero-degree of its orientation creates a continuous shell of fluid molecules on the XY plane, which would be in contact with its largest possible area and thus creates the strongest resistance against its sedimentation. On tilting its orientation angle, the shell loses its contact area until its position to 90°, creating a surface tensile phenomenon on the YZ plane, as illustrated in Fig. The mean displacement is rather increasing in the x-direction for the G-sheet at a 70° angle on a decreasing surface tension over a reduced contact area. This makes the atoms at the G’s most rear row readily break down the interfacial forces and penetrate the base fluid more easily, leading to be depositing faster compared to that at larger angles. As mentioned earlier, in the 90° case, the surface tension on the YZ plane impeded the free G-movement in this direction. The curvature radius, as on diminished in the said angle is enhanced, reflects in a drop in the wrinkle effect through rising this angle. As this angle is raised up, a decreased surface tension eases the G settle down more rapidly rather than forming a wrinkle.2, 3×3 nm2, 3.5×3.5 nm2, and 4×4 nm2 sizes were prepared and studied. According to Fig. To investigate the effects of G-fraction by resizing the sheets, four samples containing G of 2.5×2.5 nm37. Fig. In principle, a corrugation of a G-surface can be divided into three categories: wrinkle, ripple, and crumple, where the aspect ratio of the wrinkle is higher than that of ripple and its height is less than 15 nmAs noted above, a decrease in the surface tension promotes the G-sitting rate in a non-linear relationship of it over its effective contents. Here, as the G-content rises-up on increasing the G-size and as the prepared NFs contain the same base-fluid in a fixed number of molecules, more base-fluid moieties would trap in G-sheets of larger sizes. In other words, in this case, G-could is considered as a barrier to the movement of the base-fluid entities on reduced freedom of local motion, resulting in an intermolecular force growth. As a result, the surface tension under G rises-up and leads to a nonlinear relationship between its content and sitting rate. However, a growing wrinkling overcomes the increasing surface tension and, ultimately, the G settles down faster in the NFs over its increasing sizes.To investigate the effects of G-contents by increasing the number of G-layers, the samples containing one, two, three, and four G-layers were considered. Figure As portrayed in Fig. 2 orbitals in which the bonds in the orbitals overlap head-to-head are rich in the electron density along the bond axis, so-called σ-bonds. Electrons in unhybridized C-orbitals in the other bonds form π-bonds in the side-by-side (edgewise) overlap of the parallel p orbitals. As less overlapping than σ-bonds, the π-bonds are rather weaker38. Zhang et al.39 showed that the binding-energy, for a specific radius of curvature, arises-up as the number of G-layers growing and it promotes their bending strain. A monolayer can easily curve only by introducing a π-orbital misalignment between adjacent pairs of C-atoms. However, in the case of a multilayer, the van der Waals forces mediate the load transfer between layers in its bending involves extension or compression of a σ-bond. Thus, as the number of G-layers increases, the effects of σ-bonding are strengthened. This, in turn, enhances the amplitude of the valley created in the G-surface, which leads to more G-layers entering the fluid under G. Such growth reduced the surface tension and fluid resistance to the G-sitting, resulting in its faster deposition in this example.As mentioned earlier, G has unique properties of its hybrid spFigure Figure To study the hypothesis of stabilizing NFs by adding MNPs (magnetite) in an applied electric field, MNPs (of a diameter 16 Å) were added to an NF of an ethylene glycol/G in water, where the G-sheet was placed horizontally (Ө = 0), at an initial 25 °C temperature. The basic structure of the NF is shown in Fig. Applying an electric field as large as 0.5 V/Å, MNPs overcome the intermolecular forces of the base fluid, rapidly approaching and colliding with the G, creating a G-shell on the surface of the MNPs. Considering the Columbus forces are larger over all the resistive forces, the G-binds over the MNPs in a core-shell. However, as the number of G-atoms is not same on either side of the magnetic core, it exerts a net upward force on the G-side of the NP and, on the opposite side, the downward weight forces of G-atoms create a torque on the G and let G-shell detach from the surface of the MNPs over a due time interval, causing them to coagulate in the upper part of the NF. This eventuates in a dramatic instability of the NF as described in Fig. It is observed that in an electric field of 0.1 V/Å, the NPs no longer overcome completely the intermolecular forces of the base fluid and rapidly adsorb over a nearby G-sheet. As a result, a G-shell is not seen on the surface of MNPs. However, as soon as the Columbus forces exceed the resistive forces, upward pressure is built up at the contact surface of the fluid, leading to coagulation of the NPs in the upper part of the sample of an unstable NF.To investigate the interaction of base fluid molecules with MNPs, an atom at the NP surface, as a reference point, and molecules inside the base fluid at δ = 2.46, 6.30 and 15.08 Å were randomly selected. Figure As a result, a local displacement of the NPs creates an empty cavity in a dispersed phase, while the application of a weaker electric field causes the fluid around the NPs to gently rebond one another in a network, displacing the NPs upward and reducing the average electrostatic force. Therefore, a vacuum cavity no longer forms within a dispersing phase in a stable NF, as described with the models in Fig. In this paper, the factors affecting the stability of a water/ethylene glycol NF containing G-sheets are studied by reactive molecular dynamics, wherein as the G-angle on the base fluid grows, the effects of G-surface tension decreasing until the G is oriented up to 90° in the base fluid. The studies of G-behavior at different angles suggest that a wrinkling phenomenon creates at a zero-degree angle of orientation toward the z-axis in a resistant factor against G-settling. As the size of the G-sheet increases, a corrugation created on the G-surface changes from a ripple to the wrinkle. As a result, the G settles faster and causes NF instability. On increasing the number of G-layers, the resistance force against the G-settling eventually shrinks and results in a more unstable NF. A nonlinear relationship is observed between the G-sitting rate and G-content owing to an increase of its effective sizes. NFs produced by higher G-contents through an increasing G-size appears to be more stable than those created by an increasing number of G-layers. As warming the sample, the velocity of wrinkle movement arises on the G-surface as on the fluidity increases in the fluid, resulting in a decrease in the intermolecular forces on the bottom of the G-layers, which ultimately eventuates in a poor NF stability. Finally, an electrohydrodynamic force can be employed as a controlling force to stabilize NFs and control NPs dynamics in a manner that through adding MNPs and applying an electric field, such as 0.05 V/Å, a water/ethylene glycol/G NF could be completely stable.Supplementary Video.