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Biomedical subjects

M McCombs

Publications and source records attributed to M McCombs.

4 recordsLinked to original sources
PubMed1996

Mammography fixed grid versus reciprocating grid: evaluation using cadaveric breasts as test objects.

In this study we use unfixed cadaveric breasts to obtain mammography images with fixed and reciprocating grids. Sheets of acrylic, containing one or more clusters of simulated calcifications and masses, were superimposed on two fresh cadaveric breasts (3.4 and 6.5 cm thick), and were imaged with a fixed grid and a reciprocating grid. Six radiologists, working independently, attempted to identify the number of clusters and/or masses in 114 images containing 139 clusters of simulated calcifications and 42 simulated masses. Thirty-four of these images were normal, containing no lesions. For the thinner breast, no statistically significant difference was found in the detection of clusters of calcifications in the images produced with the fixed grid compared to those produced with the reciprocating grid. However, for the detection of calcifications in images of the thicker breast, sensitivity of 74% for detection of calcifications when a fixed grid was used was significantly less than sensitivity of 86% when a reciprocating grid was used (P = 0.006). The mass detection sensitivity was 91% for images made with a fixed grid compared to 96% for images made with a reciprocating grid, but the difference was not statistically significant (P = 0.346). The use of cadaveric breasts as test objects was well accepted by radiologists. Only for the thick cadaveric breast were differences between the two grids significant, and these differences were restricted to the task of finding calcifications.

Biophysical Phenomena↗
PubMed1996

Using tissue texture surrounding calcification clusters to predict benign vs malignant outcomes.

The positive predictive value of mammography is between 20% and 25% for clustered microcalcifications. For very early cancers there is often a lack of concordance between mammographic signs and pathology. This study examines the usefulness of computer texture analysis to improve the accuracy of malignant diagnosis. Texture analysis of the breast tissue surrounding microcalcifications on digitally acquired images during stereotactic biopsy is used in this study to predict malignant vs benign outcomes. 54 biopsy proven cases (36 benign, 18 malignant) are used. The texture analysis calculates statistical features from gray level co-occurrence matrices and fractal geometry for equal probability and linear quantizations of the image data. Discriminant models are generated using linear discriminant analysis and logistic discriminant analysis. Results do not differ significantly by method of quantization or discriminant analysis. Jackknife results misclassify 2 of 18 malignant cases (sensitivity 89%) and 6 of 36 benign cases (specificity 83%) for logistic discriminant analysis. From this preliminary study, texture analysis appears to show significant discriminatory power between benign and malignant tissue, which may be useful in resolving problems of discordance between pathological and mammographic findings, and may ultimately reduce the number of benign biopsies.

Biophysical Phenomena↗
PubMed1994

Silicone breast implant ruptures in an animal model: comparison of mammography, MR imaging, US, and CT.

PURPOSE: To determine the most accurate imaging modality for detection of silicone implant ruptures. MATERIALS AND METHODS: Forty single-lumen silicone implants were surgically placed in 20 rabbits. Each rabbit received one intact and one ruptured implant and was examined with mammography, magnetic resonance (MR) imaging, ultrasound (US), and computed tomography (CT). Five radiologists reviewed all images in a random fashion and graded each for rupture. The radiologist who performed US also graded her impression during examination with US. Receiver operating characteristic (ROC) analysis was performed. RESULTS: MR imaging and CT were the most accurate modalities in detection of implant ruptures, with areas under the ROC curves (Az) of .95 and .91. Mammography and US were statistically significantly inferior, with Az of .77 for each (P < .05). CONCLUSION: MR imaging and CT are statistically more accurate than US and mammography for detection of intracapsular silicone implant ruptures when only the images are reviewed.

Animals↗