Suppr超能文献

氟代脱氧葡萄糖正电子发射断层扫描/计算机断层扫描标准摄取值最大预测肺腺癌的组织学分级。

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

机构信息

Department of Nuclear Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241# West Huaihai Road, Shanghai 200030, China.

Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

出版信息

Acad Radiol. 2021 Jan;28(1):49-57. doi: 10.1016/j.acra.2020.01.030. Epub 2020 Feb 26.

Abstract

OBJECTIVES

The relationship between the FDG 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 FDG-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, FDG PET-CT can serve as a noninvasive tool for precise diagnosis and help in the preoperative formulation of patient-specific treatment strategies.

摘要

目的

FDG PET-CT 最大标准摄取值(SUVmax)与肺腺癌类型之间的关系尚未确定。本研究旨在探讨 SUVmax 值与肺腺癌组织学分级和病理亚型之间的关系,并确定区分不同组织学分级的最佳 SUVmax 截断值。

材料与方法

回顾性分析 618 例肺腺癌患者的资料。检测术前 FDG-PET-CT 测量的 SUVmax 与组织学分级和病理亚型之间的关系。采用 Kruskal-Wallis 检验比较组间差异,并用 Bonferroni-Dunn 检验进行组间两两比较。应用 ROC 分析确定区分不同组的最佳截断值。此外,在 85 例连续肺腺癌病例的独立队列中验证了该截断值。

结果

SUVmax 在低、中、高级别组之间差异有统计学意义(p <.001)。SUVmax 值随恶性程度的增加而增加。鉴别低级别肿瘤的最佳截断值为 2.01(敏感性 90.4%,特异性 86.9%,曲线下面积 [AUC] = 0.928,95%置信区间:0.91-0.95;p <.001)。鉴别高级别肿瘤的最佳 SUVmax 截断值为 7.41(敏感性 79.8%,特异性 73.5%,AUC = 0.830,95%置信区间:0.79-0.87;p <.001)。验证实验显示,在低级别组中,符合率为 88.89%,在中级别组中为 64.15%,在高级别组中为 78.57%。

结论

SUVmax 可用于预测肺腺癌的病理亚型和组织学分级。因此,FDG PET-CT 可作为一种无创工具用于精确诊断,并有助于制定针对患者的术前治疗策略。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验