ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2021
Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations.
Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.Multidisciplinary respiratory medicine · 2026Article
- Emerging Strategies in the Diagnosis and Treatment of Pleural Mesothelioma: An Overview.Thoracic cancer · 2026Review
- MesoRet: a reticulin stain-based deep learning algorithm to assist diffuse mesothelioma subtyping.Pathologica · 2026Article
- A histomorphological atlas of resected mesothelioma discovered by self-supervised learning from 3446 whole-slide images.Nature communications · 2025Article
- Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).Journal of imaging informatics in medicine · 2025Article
- Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review.BMC medical research methodology · 2025Article
- Sarcomatoid Mesothelioma With New Pancreatic Lesions Presenting As Acute Pancreatitis: A Case Report.Cureus · 2024Article
- Deep learning model to differentiate Crohn's disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens.Virchows Archiv : an international journal of pathology · 2024Article
- MesoGraph: Automatic profiling of mesothelioma subtypes from histological images.Cell reports. Medicine · 2023Article
- The state of the art for artificial intelligence in lung digital pathology.The Journal of pathology · 2022Review
- Predicting Mesothelioma Using Artificial Intelligence: A Scoping Review of Common Models and Applications.Technology in cancer research & treatmentArticle
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12 authors.
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Abstract
Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning based classifier may be able to aid pathologists in making this critical diagnostic distinction. SpindleMesoNET was trained on cases of malignant sarcomatoid mesothelioma and benign spindle cell mesothelial proliferations. Performance was assessed through cross-validation on the training set, on an independent set of challenging cases referred for expert opinion ('referral' test set), and on an externally stained set from outside institutions ('externally stained' test set). SpindleMesoNET predicted the benign or malignant status of cases with AUC's of 0.932, 0.925, and 0.989 on the cross-validation, referral and external test sets, respectively. The accuracy of SpindleMesoNET on the referral set cases (92.5%) was comparable to the average accuracy of 3 experienced pathologists on the same slide set (91.7%). We conclude that SpindleMesoNET can accurately distinguish sarcomatoid mesothelioma from benign spindle cell mesothelial proliferations. A deep learning system of this type holds potential for future use as an ancillary test in diagnostic pathology.
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