人工智能辅助肺结节筛查及定性诊断的应用研究

李娟娟; 刘敏; 杨斌; 杜伟; 杨鸿开; 廖艳全; 李峻杭; 王君

doi:10.7619/jcmp.20214698

人工智能辅助肺结节筛查及定性诊断的应用研究

李娟娟¹,
刘敏^1, ,,
杨斌²,
杜伟³,
杨鸿开¹,
廖艳全¹,
李峻杭¹,
王君¹

1.
云南省祥云县人民医院/大理大学第九附属医院影像科, 云南大理, 672100
2.
云南省昆明市第一人民医院医学影像中心, 云南昆明, 650000
3.
大理大学第一附属医院放射科, 云南大理, 671000

基金项目:

国家自然科学基金资助项目 82160348

云南大理祥云科研立项项目 DX2020SF15

详细信息

通讯作者:
刘敏, E-mail: 450755932@qq.com

中图分类号: R563;R445
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出版历程
- 收稿日期: 2021-11-28
- 网络出版日期: 2022-04-27
- 发布日期: 2022-04-27

Application of artificial intelligence-assisted pulmonary nodule screening and qualitative diagnosis

1.
Department of Medical Imaging, Xiangyun County People′s Hospital of Yunnan Province, the Ninth Affiliated Hospital of Dali University, Dali, Yunnan, 672100
2.
Medical Imaging Center, Kunming First People′s Hospital of Yunnan Province, Kunming, Yunnan, 650000
3.
Department of Radiology, the First Affiliated Hospital of Dali University, Dali, Yunnan, 671000

摘要

摘要:
目的探讨人工智能(AI)辅助诊断软件在胸部低剂量CT肺结节筛查及定性诊断的临床研究与应用价值。
方法回顾性分析病理确诊的103例肺结节患者的临床资料，将103例肺结节患者术前的胸部低剂量CT图像导入杏脉锐影肺结节AI分析软件中，采用AI及放射医师阅片的方法筛查肺结节并进行良恶性诊断，将AI辅助诊断软件与放射医师对肺结节的筛查情况进行比较，并以病理诊断为金标准，分析AI辅助诊断软件与放射医师诊断的准确性。
结果 103例患者胸部低剂量CT共筛查出258个结节, AI辅助软件与放射医师检出肺结节的敏感度分别为96.12%、89.53%, 阳性预测值分别为95.00%、100.00%; AI辅助诊断软件筛查检出肺结节的假阳性率为5.00%, 放射医师未检查出假阳性肺结节。AI辅助诊断软件与放射医师对肺结节的筛查能力比较，差异有统计学意义(P < 0.05)。103例肺结节患者病理检查共诊断出108个肺结节, AI辅助诊断软件及放射医师诊断肺结节的敏感度分别为95.35%、91.86%，特异度分别为72.73%、81.82%。
结论 AI辅助诊断软件在肺结节筛查检出及恶性结节诊断方面具有较高的准确性，但肺结节良恶性鉴别准确率低于放射医师。因此, AI辅助诊断软件可作为一种辅助手段与放射医师诊断相结合来提高肺结节的总体诊疗效能。
- 人工智能辅助诊断软件 /
- 低剂量计算机断层扫描 /
- 肺结节 /
- 良恶性 /
- 筛查 /
- 定性诊断
Abstract:
Objective To explore the clinical research and application value of artificial intelligence (AI) aided diagnosis software in lung nodule screening and qualitative diagnosis of CT screening of chest low-dose CT.
Methods The clinical data of 103 patients with pulmonary nodules diagnosed by pathology were analyzed retrospectively. The preoperative chest low-dose CT images of 103 patients with pulmonary nodules were imported into the AI analysis software of apricot pulse sharp shadow pulmonary nodules. The methods of AI and radiologists′film reading were used to screen pulmonary nodules and make benign and malignant diagnosis. The AI aided diagnosis software was compared with the screening of pulmonary nodules by radiologists, and the pathological diagnosis was taken as the gold standard, the accuracy of AI aided diagnosis software and radiologist diagnosis was analyzed.
Results A total of 258 nodules were detected by chest low-dose CT in 103 patients. The sensitivity of pulmonary nodules detected by AI assistant software and radiologist were 96.12% and 89.53%, respectively, the positive predictive values were 95.00% and 100.00%, respectively, the false positive rate of pulmonary nodules detected by AI assisted diagnostic software was 5.00%, and radiologists did not detect false positive pulmonary nodules. There was significant difference between AI aided diagnosis software and radiologists in screening ability of pulmonary nodules (P < 0.05). A total of 108 nodules were diagnosed by pathological examination in 103 patients with pulmonary nodules, the sensitivity of AI aided diagnosis software and radiologists in diagnosing pulmonary nodules were 95.35% and 91.86%, respectively, and the specificities were 72.73% and 81.82%, respectively.
Conclusion AI aided diagnosis software has high accuracy in the screening and detection of pulmonary nodules and the diagnosis of malignant nodules, but the accuracy of differentiating benign from malignant pulmonary nodules is lower than that of radiologists. Therefore, AI aided diagnosis software as an auxiliary approach can be combined with diagnosis of radiologists to improve the overall diagnosis and treatment efficiency of pulmonary nodules.
- artificial intelligence-assisted diagnosis software /
- low-dose computed tomography /
- pulmonary nodules /
- benign and malignant /
- screening /
- qualitative diagnosis

HTML全文

图 1 典型病例CT图像

A: 左肺上叶舌段血管聚集处(男，44岁, AI诊断为假阳性); B: 左肺上叶舌段胸膜增厚(女, 46岁, AI诊断为假阳性); C: 右肺下叶磨玻璃结节(女, 51岁，结节直径约4 mm, 放射医师漏诊，由AI检出); D: 左肺斜裂侧壁胸膜近血管旁结节(直径约4 mm, 放射医师漏诊，由AI检出)。

下载: 全尺寸图片幻灯片

图 2 典型病例CT图像、HE染色病理图

A、B: 右肺下叶良性结节(女，48岁, AI辅助软件误诊为高危，病理学检查确诊为错构瘤, HE染色病理图放大40倍); C、D: 左肺上叶恶性结节(女, 68岁, AI辅助软件诊断准确，病理学检查确诊为腺癌, HE染色病理图放大40倍)。

下载: 全尺寸图片幻灯片

表 1 AI与放射医师对真性肺结节筛查能力的比较[n(%)]

阅片方式	阳性	阴性
AI辅助诊断软件阅片	248(96.12)	10(3.88)
放射医师阅片	231(89.53)^*	27(10.47)^*
与AI阅片比较, *P < 0.05。

下载: 导出CSV

表 2 AI与放射医师对肺结节诊断效能比较 %

阅片方式	敏感度	特异度	阳性预测值	阴性预测值	χ²	P
AI辅助诊断软件阅片	95.35	72.73	93.18	80.00	0.100	0.752
放射医师阅片	91.86	81.82	95.18	72.00	0.364	0.547

下载: 导出CSV

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