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基于人工智能的肺磨玻璃密度结节三维测量与病理切片测量的相关性研究

Correlation study of three-dimensional measurements based on artificial intelligence of pulmonary ground-glass nodule and measurements of pathologic digital sections
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摘要 目的:分析肺磨玻璃密度结节人工智能测量、半自动测量与病理数字切片测量之间的相关性。方法:收集91例表现为磨玻璃密度结节的T1a期肺腺癌的CT图像及病理切片资料。使用人工智能肺部影像分析系统(AILIAS)及半自动分割技术(SLLS)测量CT图像上结节的平均直径和体积,并在病理数字切片上测量结节的平均直径与面积。AILIAS及SLLS与病理数字切片平均直径测量值、AILIAS与SLLS体积测量值两两比较行Wilcoxon符号秩检验。采用Spearman秩相关分析AILIAS及SLLS体积测量值与病理数字切片面积测量值的相关性。结果:AILIAS与SLLS所测平均直径均大于病理数字切片(Z=-7.310,-8.557;均P<0.001)。AILIAS与SLLS所测直径间差异无统计学意义(Z=-0.744,P=0.457)。SLLS所测体积小于AILIAS(Z=-6.218,P<0.001)。AILIAS和SLLS体积测量值与病理数字切片面积测量值均显著相关(rs=0.729,0.727;均P<0.001)。结论:人工智能可多维度测量肺磨玻璃结节的直径和体积,与病理数字切片面积测量值有良好的相关性及一致性,可为磨玻璃结节的良恶性判定及临床疗效评估提供数据支持。 Objective:To analyze the correlation between artificial intelligence measurements,semi-automated measurements and pathologic paraffin section measurements of pulmonary ground-glass nodule(GGN).Methods:The CT and pathological sections data of 91 patients of T1a lung adenocarcinoma confirmed by operation and pathology were collected.Using artificial intelligence lung image analysis system(AILIAS)and subsolid lung lesion segmentation(SLLS)method,the average diameter and volume of GGN were measured on CT images,and the average diameter and area of GGN on pathological sections were measured.Wilcoxon signed rank test was used to compare the average diameter measured by AILIAS,SLLS method and pathological digital section,and the volume measured by AILIAS and SLLS method.The correlation between the volume measured by AILIAS and SLLS method and the area measured by pathological digital section was analyzed by Spearman correlation analysis.Results:The diameter measured by AILIAS and SLLS method was larger than the diameter measured by pathological digital section(Z=-7.310,-8.577;both P<0.001).There was no significant difference between the diameter measured by SLLS and AILIAS method(Z=-0.744,P=0.457).The volume measured by SLLS method was less than that by AILIAS method(Z=-6.218,P<0.001).There was a significant correlation between the volume measured by AILIAS and SLLS and the area measured by pathological digital section(rs=0.729,0.727;both P<0.001).Conclusions:Artificial intelligence can measure the diameter and volume of GGN in multiple dimensions,which has a good correlation and consistency with pathological section measurement.It can provide reliable data support for the diagnosis of benign and malignant GGN and the evaluation of clinical curative effect.
作者 吴瑜 张莲 杨玉婵 丁晓青 张冬晴 陈永其 詹松华 张敏 WU Yu;ZHANG Lian;YANG Yuchan;DING Xiaoqing;ZHANG Dongqing;CHEN Yongqi;ZHAN Songhua;ZHANG Min;无(Department of Medical Imaging,Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China;Department of Radiology,Shanghai Jiading District Hospital of TCM,Shanghai 201800,China;Department of Pathology,Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China)
出处 《中国中西医结合影像学杂志》 2024年第4期371-374,378,共5页 Chinese Imaging Journal of Integrated Traditional and Western Medicine
基金 上海中医药大学附属曙光医院四明基金项目(4204)。
关键词 肺腺癌 磨玻璃密度结节 体层摄影术 X线计算机 肺结节分割 肺结节三维测量 Lung adenocarcinoma Ground-glass nodule Tomography,X-ray computed Lung nodule segmentation Lung nodule three-dimensional measurements
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