ENHANCING MORPHOLOGICAL ANALYSIS OF PERIPHERAL BLOOD CELLS IN CHRONIC LYMPHOCYTIC LEUKEMIA WITH AN ARTIFICIAL INTELLIGENCE‐BASED TOOL
نویسندگان
چکیده
Background: Real-time monitoring of chronic lymphocytic leukemia (CLL) is crucial for effective patient management. Peripheral blood (PB) the preferred source obtaining CLL cells due to its ease access and lower cost. However, traditional methods evaluating PB films have several drawbacks, such as lack automation, reliance on personal experience, low repeatability reproducibility. To address these limitations, we developed an artificial intelligence-based tool that objectively evaluates morphologic features in patients from a clinical perspective. Methods: We conducted retrospective study 284 newly diagnosed with at Jiangsu Province Hospital December 1, 2013 31, 2020. train test our machine-learning algorithm, randomly split cohort into training set (75%) testing (25%). obtained high-quality whole-slide images using Bionovation CSFA-80 scanner, automated algorithm deep convolutional neural network (CNN) precisely identify regions interest. Additionally, used well-established Visual Geometry Group-16 CNN encoder segment extract morphological features. This enabled us precise all lymphocytes subsequent analysis. Results: Our study's lymphocyte identification had recall 0.96 F1 score 0.97, making it suitable future applications. Cluster analysis identified three clear, groups reflect distinct stages disease development some extent. investigate longitudinal evolution lymphocyte, extracted cellular morphology parameters various time points same patient. These included initial diagnosis period without treatment indications, pretreatment indications beginning appear, phase large cell transformation. The results showed similar trends those observed aforementioned cluster Correlation further supports prognostic potential morphology-based parameters. research was funded by: National Natural Science Foundation China [82100211]; Beijing Xisike Clinical Oncology Research [Y-Roche2019/2-0090]; Project Ili & Joint Institute Health [yl2021ms04]; Technology Development Fund Pukou branch People's hospital [KJ2021-4]. Keywords: diagnostic biomarkers, Imaging Early Detection - Other, No conflicts interests pertinent abstract.
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ژورنال
عنوان ژورنال: Hematological Oncology
سال: 2023
ISSN: ['1099-1069', '0278-0232']
DOI: https://doi.org/10.1002/hon.3165_506