Correlation study of three-dimensional measurements based on artificial intelligence of pulmonary ground-glass nodule and measurements of pathologic digital sections
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.
国家科技期刊平台
NSTL
万方数据
