Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Papillary Thyroid Carc inoma is the subject of a report. According to news reporting from Milan, Italy, by NewsRx journalists, research stated, “The diagnostic assessment of thyroid n odules is hampered by the persistence of uncertainty in borderline cases, and fu rther complicated by the inclusion of non-invasive follicular tumor with papilla ry-like nuclear features (NIFTP) as a less aggressive alternative to papillary t hyroid carcinoma (PTC). In this setting, computational methods might facilitate the diagnostic process by unmasking key nuclear characteristics of NIFTPs.” The news correspondents obtained a quote from the research from the University o f Milano Bicocca, “The main aims of this work were to (1) identify morphometric features of NIFTP and PTC that are interpretable for the human eye, and (2) deve lop a deep learning model for multi-class segmentation as a support tool to redu ce diagnostic variability. Our findings confirmed that nuclei in NIFTP and PTC s hare multiple characteristics, setting them apart from hyperplastic nodules (HP) . The morphometric analysis identified 15 features that can be translated into n uclear alterations readily understandable by pathologists, such as a remarkable inter-nuclear homogeneity for HP in contrast to a major complexity in the chroma tin texture of NIFTP, and to the peculiar pattern of nuclear texture variability of PTC. A few NIFTP cases with available NGS data were also analyzed to initial ly explore the impact of RAS-related mutations on nuclear morphometry. Finally, a pixel-based deep learning model was trained and tested on whole slide images ( WSIs) of NIFTP, PTC, and HP cases. The model, named NUTSHELL (NUclei from Thyroi d tumors Segmentation to Highlight Encapsulated Low-malignant Lesions), successf ully detected and classified the majority of nuclei in all WSIs’ tiles, showing comparable results with already well-established pathology nuclear scores. NUTSH ELL provides an immediate overview of NIFTP areas and can be used to detect micr ofoci of PTC within extensive glandular samples or identify lymph node metastase s.”
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