Background and Objective:Prostate cancer is one of the most common diseases affecting men worldwide. The Gleason scoring system is the primary diagnostic and prognostic tool for prostate cancer. Furthermore, recent reports indicate that the presence of patterns of the Gleason scale such as the cribriform pattern may also correlate with a worse prognosis compared to other patterns belonging to the Gleason grade 4. Current clinical guidelines have indicated the convenience of highlight its presence during the analysis of biopsies. All these requirements suppose a great
Background and objective: Prostate cancer is one of the most common male tumors. The increasing use of whole slide digital scanners has led to an enormous interest in the application of machine learning techniques to histopathological image classification. Here we introduce a novel family of morphological descriptors which, extracted in the appropriate image space and combined with shallow and deep Gaussian process based classifiers, improves early prostate cancer diagnosis. Method: We decompose the acquired RGB image in its RGB and optical density hematoxylin and eosin components. Then, we define two novel granulometry-based descriptors which work in both, RGB and optical density, spaces but perform better when used on the latter. In this space they clearly encapsulate knowledge used by pathologists to identify cancer lesions. The obtained features become * Corresponding author. The first two authors contributed equally.
To analyze the presence of mature and immature vessels as a prognostic factor in patients with renal cell carcinoma and propose a classification of renal cancer tumor blood vessels according to morphometric parameters. Tissue samples were obtained from 121 renal cell carcinoma patients who underwent radical nephrectomy. Staining with CD31 and CD34 was used to differentiate between immature (CD31+) and mature (CD34+) blood vessels. We quantified the microvascular density, microvascular area and different morphometric parameters: maximum diameter, minimum diameter, major axis, minor axis, perimeter, radius ratio and roundness. We found that the microvascular density was higher in CD31+ than CD34+ vessels, but CD34+ vessels were larger than CD31+ vessels, as well as being strongly correlated with the ISUP tumor grade. We also identified four vascular patterns: pseudoacinar, fascicular, reticular and diffuse. Pseudoacinar and fascicular patterns were more frequent in clear cell renal cell carcinoma (37.62 and 35.64% respectively), followed by reticular pattern (21.78%), while in chromophobe tumors the reticular pattern predominated (90%). The isolated pattern was present in all papillary tumors (100%). In healthy renal tissue, the pseudoacinar and isolated patterns were differentially found in the renal cortex and medulla respectively. We defined four distinct vascular patterns significantly related with the ISUP tumor grade in renal cell carcinomas. Further studies in larger series are needed in order to validate these results. Analysis of both mature and immature vessels (CD34+ and CD31+) provides additional information when evaluating microvascular density.
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