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SUVmax of 18FDG PET/CT Predicts Histological Grade of Lung Adenocarcinoma

医学 置信区间 腺癌 标准摄取值 核医学 接收机工作特性 病态的 恶性肿瘤 切断 放射科 内科学 正电子发射断层摄影术 癌症 量子力学 物理
作者
Xiaoyan Sun,Tianxiang Chen,Cheng Chang,Haohua Teng,Chun Xie,Maomei Ruan,Bei Lei,Liu Liu,Lihua Wang,Yunhai Yang,Wenhui Xie
出处
期刊:Academic Radiology [Elsevier BV]
卷期号:28 (1): 49-57 被引量:41
标识
DOI:10.1016/j.acra.2020.01.030
摘要

Objectives The relationship between the 18FDG PET-CT maximum standard uptake value (SUVmax) and the type of lung adenocarcinoma is still not established. The aim of this study was to investigate the relationship between SUVmax value and histological grade and pathological subtype of lung adenocarcinoma, and to determine the optimum SUVmax cutoffs for distinguishing different histological grades. Materials and Methods The data of 618 lung adenocarcinoma patients were retrospectively analyzed. The relationship between SUVmax measured on preoperative 18FDG-PET-CT and the histological grade and pathological subtype was examined. The Kruskal-Wallis test was used to compare differences among groups, and the Bonferroni-Dunn test for pairwise comparison among groups. ROC analysis was applied to determine the optimal cut-off values for distinguishing different groups. In addition, the cut-off value was verified in an independent cohort of 85 consecutive lung adenocarcinoma cases. Results The SUVmax was significantly different between the low, intermediate, and high-grade groups(p < .001). SUVmax value increased with increase in the degree of malignancy. The optimal cut-off value for identifying low-grade tumors was 2.01 (sensitivity 90.4%, specificity 86.9%, area under the curve [AUC] = 0.928, 95% confidence interval: 0.91–0.95; p < .001). The optimal cutoff SUVmax value for identifying high-grade tumors was 7.41 (sensitivity 79.8%, specificity 73.5%, AUC = 0.830, 95% confidence interval: 0.79–0.87; p < .001). The validation experiment showed that the coincidence rate was 88.89% in the low-level group, 64.15% in the middle-level group, and 78.57% in the high-level group. Conclusion SUVmax can be used to predict pathological subtype and histological grade of lung adenocarcinoma. Thus, 18FDG PET-CT can serve as a noninvasive tool for precise diagnosis and help in the preoperative formulation of patient-specific treatment strategies. The relationship between the 18FDG PET-CT maximum standard uptake value (SUVmax) and the type of lung adenocarcinoma is still not established. The aim of this study was to investigate the relationship between SUVmax value and histological grade and pathological subtype of lung adenocarcinoma, and to determine the optimum SUVmax cutoffs for distinguishing different histological grades. The data of 618 lung adenocarcinoma patients were retrospectively analyzed. The relationship between SUVmax measured on preoperative 18FDG-PET-CT and the histological grade and pathological subtype was examined. The Kruskal-Wallis test was used to compare differences among groups, and the Bonferroni-Dunn test for pairwise comparison among groups. ROC analysis was applied to determine the optimal cut-off values for distinguishing different groups. In addition, the cut-off value was verified in an independent cohort of 85 consecutive lung adenocarcinoma cases. The SUVmax was significantly different between the low, intermediate, and high-grade groups(p < .001). SUVmax value increased with increase in the degree of malignancy. The optimal cut-off value for identifying low-grade tumors was 2.01 (sensitivity 90.4%, specificity 86.9%, area under the curve [AUC] = 0.928, 95% confidence interval: 0.91–0.95; p < .001). The optimal cutoff SUVmax value for identifying high-grade tumors was 7.41 (sensitivity 79.8%, specificity 73.5%, AUC = 0.830, 95% confidence interval: 0.79–0.87; p < .001). The validation experiment showed that the coincidence rate was 88.89% in the low-level group, 64.15% in the middle-level group, and 78.57% in the high-level group. SUVmax can be used to predict pathological subtype and histological grade of lung adenocarcinoma. Thus, 18FDG PET-CT can serve as a noninvasive tool for precise diagnosis and help in the preoperative formulation of patient-specific treatment strategies.
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