Transmission acoustic microscopy of tissue sections (1 GHz)
SummaryThe acoustic microstructure of mouse small intestine has been studied with a transmission acoustic microscope working at 1 GHz and the influence of the histologic processing on the microacoustic pattern has been tested. Unstained thin sections provide pictures rich in details and highly contrasted. Gelatin has been used as hydrosoluble embedding medium and has been compared to paraffin. The former embedding procedure retained the viscoelastic properties of the specimen far more and provided the most detailed pictures. Osmiun tetroxide has been used to demonstrate acoustic staining.
Effects of tissue processing techniques in acoustical (1.2 GHz) and light microscopy
SummaryIn this study the influence of various tissue processing and staining techniques on the acoustical properties of liver tissue was investigated. A qualitative study was performed using ultrasound attenuation as the imaged parameter of a combined optical/acoustical microscope with a 1.2 GHz transducer. Images were made of three sets of adjacent liver sections (6 μm in thickness) which were prepared in ten different ways: fixed by alcohol or formalin; stained by hematoxylineosin (HE), toluidine blue (TB) or non-stained; sectioned by a cryostat or by a paraffin microtome. It was concluded that the images obtained from cryostat sections were of much higher quality than those from paraffin sections. Images obtained from sections that were sectioned while embedded in paraffin displayed no detail at all. No consistent effect was noticed with respect to staining by HE or TB. Alcohol fixed sections gave more detailed images than formalin fixed sections. Formalin fixation in combination with cryostat sectioning yielded many cytoplasmic vacuoles.
Application of Pattern Recognition Techniques to Breast Cancer Detection: Ultrasonic Analysis of 100 Pathologically Confirmed Tissue Areas
Ultrasonic pulse-echo rf waveform analysis and selected pattern recognition methods were applied to classification of breast tissue. Emphasis was placed on the classification of solid tissue areas since fluid areas are easily identified by present B-scan techniques. Pattern recognition techniques such as the Fisher Linear Discriminant (FLD), Probability Density Function (PDF) curves, jackknife estimate and committee vote were used to construct and evaluate a two class algorithm, malignant versus benign tissue areas. A data base consisting of frequency domain features from 100 pathologically confirmed tissue areas from 87 patients were used to train the algorithm. Algorithm performance was acquired via the generalized jackknife procedure to significantly reduce the bias frequently encountered in algorithm evaluation. Estimated values of algorithm performance are sensitivity and specificity values of 96 percent and 68 percent, respectively.