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肺癌人工智能细胞病理诊断系统的研发及诊断价值探讨

王华南 郭明学 孙亚楠 张彩云 龙莉 梁志欣

解放军医学院学报2024,Vol.45Issue(5):463-468,6.
解放军医学院学报2024,Vol.45Issue(5):463-468,6.DOI:10.12435/j.issn.2095-5227.2024.049

肺癌人工智能细胞病理诊断系统的研发及诊断价值探讨

Development and diagnostic value of artificial intelligence cytopathological diagnosis system for lung cancer

王华南 1郭明学 2孙亚楠 2张彩云 3龙莉 4梁志欣2

作者信息

  • 1. 解放军总医院第一医学中心呼吸与危重症医学科,北京 100853||联勤保障部队第990医院呼吸内科,河南驻马店 463000
  • 2. 解放军总医院第一医学中心呼吸与危重症医学科,北京 100853
  • 3. 解放军总医院第六医学中心呼吸与危重症医学科,北京 100048
  • 4. 武汉兰丁智能医学股份有限公司,湖北武汉 430000
  • 折叠

摘要

Abstract

Background Although traditional cytopathological diagnosis of lung cancer has its advantages,it is greatly influenced by doctors'subjective experience and workload.The new generation of artificial intelligence,represented by deep learning algorithm models,can automatically extract and summarize features from medical images,demonstrating significant advantages in intelligent diagnosis.Objective To develop an artificial intelligence cytopathological diagnosis system for lung cancer and explore its diagnostic value by combining the artificial intelligence and digital pathology.Methods From May 2021 to July 2023,533 patients with suspected lung cancer were selected from the First Medical Center of Chinese PLA General Hospital.Among them,354 cases were finally diagnosed with lung cancer(including 98 cases of adenocarcinoma,140 cases of squamous carcinoma,and 116 cases of small-cell carcinoma),and another 179 cases were non-lung cancer.The bronchoscopic biopsy specimens and pleural effusion specimens from the selected cases were smeared,stained,and scanned.Using the digital pathological slices from 340 randomly selected samples(including 229 lung cancer cases and 111 non-lung cancer cases),the candidate detection models and classification models were trained,validated,and tested,respectively.Based on the test results,the YOLO v7 detection model and Vision Transformer classification model were selected as the basic structure to initially establish the Artificial Intelligence Cytopathological Diagnosis System for lung cancer.Then the trained Artificial Intelligence Cytopathological Diagnosis System was used to diagnose the remaining 193 untrained samples for validation,and the interpretation results were compared with the pathological diagnosis results as the standard.Results The accuracy of the developed Artificial Intelligence Cytopathological Diagnosis System in lung cancer diagnosis was 91.2%(176/193),with sensitivity of 98.4%(123/125),specificity of 77.9%(53/68),positive predictive value of 89.1%(123/138),and negative predictive value of 96.4%(53/55).The Youden index was 0.763,and Kappa statistic was 0.798.Conclusion The Artificial Intelligence Cytopathological Diagnosis System has high sensitivity and accuracy in the diagnosis of lung cancer,which can effectively improve the efficiency of lung cancer diagnosis.However,the system still needs to be further optimized to enhance its diagnostic specificity.

关键词

人工智能/深度学习/肺癌/细胞病理/诊断

Key words

artificial intelligence/deep learning/lung cancer/cytopathology/diagnosis

分类

医药卫生

引用本文复制引用

王华南,郭明学,孙亚楠,张彩云,龙莉,梁志欣..肺癌人工智能细胞病理诊断系统的研发及诊断价值探讨[J].解放军医学院学报,2024,45(5):463-468,6.

基金项目

国家重点研发计划(2022YFA1104704) (2022YFA1104704)

解放军医学院学报

OACSTPCD

2095-5227

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