Fast-track development and multi-institutional clinical validation of an artificial intelligence algorithm for detection of lymph node metastasis in colorectal cancer
Modern Pathology(2024)
摘要
Lymph node metastasis (LNM) detection can be automated using artificial intelligence-based diagnostic tools. Only limited studies have addressed this task for colorectal cancer. The aim of this study was to develop of a clinical-grade digital pathology tool for LNM detection in colorectal cancer (CRC) using the original fast-track framework.The training cohort included 432 slides from one department. A segmentation algorithm detecting 8 relevant tissue classes was trained. The test cohorts consisted of materials from five pathology departments digitized by four different scanning systems.A high-quality, large training dataset was generated within 7 days, and a minimal amount of annotation work using fast-track principles. The AI tool showed very high accuracy for LNM detection in all cohorts, with sensitivity, negative predictive value, and specificity ranges of 0.980-1.000, 0.997-1.000, and 0.913-0.990, correspondingly. Only 5 of 14460 analyzed test slides with tumor cells over all cohorts were classified as false negative (3/5 representing clusters of tumor cells in lymphatic vessels).A clinical-grade tool was trained in a short time using fast-track development principles and validated using the largest international, multi-institutional, multi-scanner cohort of cases to date, showing very high precision for LNM detection in CRC. We are releasing a part of the test datasets to facilitate academic research.
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关键词
Lymph node,metastasis detection,AI,colorectal cancer,validation,digital pathology
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