Li Guangzheng, Huang Renjun, Zhu Mo, Du Mingzhan, Zhu Jingfen, Sun Zongqiong, Liu Kaili, Li Yonggang
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Department of Pathology, The First Affiliated Hospital of Soochow University, Suzhou, China.
J Thorac Dis. 2022 Feb;14(2):443-454. doi: 10.21037/jtd-22-77.
This study aimed to explore the value of native T1-mapping and diffusion-weighted imaging (DWI) in differentiating the pathological types and degree of tumor differentiation of lung cancer and their correlation with Ki-67 protein expression.
A total of 78 consecutive lung cancer patients who received chest magnetic resonance imaging (MRI) scans between May 2020 and June 2021 were enrolled in this study. Two radiologists independently analyzed the apparent diffusion coefficient (ADC) and T1 values for each lesion. The intraclass correlation coefficient (ICC) and Bland-Altman plots were generated to assess interobserver agreement of the T1 and ADC mean values in lesions. The difference in ADC and T1 values among different pathological types, as well as between high- and low-differentiated lung cancers were analyzed, and diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve analysis. The correlation between ADC value, T1 value, and Ki-67 protein expression index was determined.
The ADC and T1 values showed excellent interobserver agreement (ICC 0.820, 0.942, respectively). There was a significant difference in ADC values between small cell carcinoma and squamous carcinoma (P<0.05), and between small cell carcinoma and adenocarcinoma (P<0.05), but not between squamous carcinoma and adenocarcinoma (P>0.05). A significant difference in T1 values was observed between small cell carcinoma (P<0.05) and adenocarcinoma, and between squamous carcinoma (P<0.05) and adenocarcinoma, but not between squamous carcinoma and small cell carcinoma (P>0.05). There were statistically significant differences in ADC and T1 values between the moderately and highly differentiated group and the poorly differentiated group (P<0.05). ROC curve analysis showed that the T1 combined with ADC value had high diagnostic value for the degree of differentiation of the tumor [area under the curve (AUC) =0.912]. Pearson correlation analysis showed a significant positive correlation between T1 value and Ki-67 index (r=0.66, P<0.001) and a significant negative correlation between ADC value and Ki-67 index (r=-0.45, P<0.01).
T1 and ADC values can be used to distinguish the pathological type and differentiation degree of lung cancer.
本研究旨在探讨磁共振T1加权成像（native T1-mapping）及扩散加权成像（DWI）在鉴别肺癌病理类型、肿瘤分化程度中的价值，及其与Ki-67蛋白表达的相关性。
选取2020年5月至2021年6月期间连续收治的78例接受胸部磁共振成像（MRI）扫描的肺癌患者。两名放射科医生独立分析每个病灶的表观扩散系数（ADC）和T1值。计算组内相关系数（ICC）并绘制Bland-Altman图，以评估观察者间对病灶T1和ADC平均值的一致性。分析不同病理类型以及高、低分化肺癌之间ADC和T1值的差异，并通过受试者工作特征（ROC）曲线分析评估诊断效能。确定ADC值、T1值与Ki-67蛋白表达指数之间的相关性。
ADC和T1值显示出极好的观察者间一致性（ICC分别为0.820和0.942）。小细胞癌与鳞癌之间（P<0.05）、小细胞癌与腺癌之间（P<0.05）的ADC值存在显著差异，但鳞癌与腺癌之间无显著差异（P>0.05）。小细胞癌与腺癌之间（P<0.05）、鳞癌与腺癌之间（P<0.05）的T1值存在显著差异，但鳞癌与小细胞癌之间无显著差异（P>0.05）。中高分化组与低分化组之间的ADC和T1值存在统计学显著差异（P<0.05）。ROC曲线分析显示，T1值联合ADC值对肿瘤分化程度具有较高的诊断价值[曲线下面积（AUC）=0.912]。Pearson相关性分析显示，T1值与Ki-67指数呈显著正相关（r=0.66，P<0.001），ADC值与Ki-67指数呈显著负相关（r=-0.45，P<0.01）。
T1值和ADC值可用于鉴别肺癌的病理类型和分化程度。
