CAJ | 학술논문

目的使用纤维支气管镜刷片细胞形态学定量参数建立基于人工神经网络(ANN)的诊断模型,并验证其在辅助诊断肺癌中的价值.方法利用HMIAS-2000医学图像分析系统,对组织病理学确诊的138例患者纤维支气管镜刷片细胞的细胞核进行形态定量研究,包括肺腺癌48例、肺鳞癌28例、肺小细胞癌22例,肺良性病变40例.取系统误差阈值为10-8,随机数字法选取22例肺癌、8例肺良性病变对获得的22项参数进行ANN建模及模型训练,并用盲法测试验证模型对肺癌诊断的敏感性和特异性.结果所建立的ANN模型经过18次训练后即可达到误差要求.ANN模型诊断肺癌的敏感性为94.7％(72/76),特异性为96.9％(31/32).结论使用纤维支气管镜刷片细胞形态学定量参数成功建立了基于ANN的诊断模型,对肺癌的鉴别诊断具有一定的应用价值.
목적 사용섬유지기관경쇄편세포형태학정량삼수건립기우인공신경망락(ANN)적진단모형,병험증기재보조진단폐암중적개치.방법 이용HMIAS-2000의학도상분석계통,대조직병이학학진적138례환자섬유지기관경쇄편세포적세포핵진행형태정량연구,포괄폐선암48례、폐린암28례、폐소세포암22례,폐량성병변40례.취계통오차역치위10-8,수궤수자법선취22례폐암、8례폐량성병변대획득적22항삼수진행ANN건모급모형훈련,병용맹법측시험증모형대폐암진단적민감성화특이성.결과 소건립적ANN모형경과18차훈련후즉가체도오차요구.ANN모형진단폐암적민감성위94.7％(72/76),특이성위96.9％(31/32).결론 사용섬유지기관경쇄편세포형태학정량삼수성공건립료기우ANN적진단모형,대폐암적감별진단구유일정적응용개치.
Objective To establish an ANN-based diagnostic model which uses morphology quantitative parameters of bronchoscopic brush-off cells,and to evaluate its value in adjunctive diagnosis of lung cancer.Methods By using HMIAS-2000 medical image analytical system, a quantitative morphological study was conducted in the nuclei of bronchoscopic brush-off cells from 138 patients with histopathologically confirmed pulmonary lesions,including 48 cases of adenocarcinoma,28 of squamous carcinoma,22 of small cell lung cancer and 40 of benign lesions.ANN modeling and training were completed by using 22 parameters obtained from random-digit selected cases of lung cancer (n=22) and pulmonary benign lesion (n=8),with the threshold of systemic error being 10-8.A blind-test set was used to test the sensitivity and specificity of the model in diagnosing lung cancer.Results The error level of ANN model was achieved after 18 cycles of training.The ANN model had a sensitivity of 94.7％ (72/76) and a specificity of 96.9％ (31/32) in diagnosing lung cancer.Conclusion An ANN-based diagnostic model which uses morphology quantitative parameters of bronchoscopic brush-off cells is successfully established,and appears valuable in differential diagnosis of lung cancer.