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 肺 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:45
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Fzj发布了新的文献求助10
1秒前
Rnaissance完成签到,获得积分10
1秒前
刘舒雅关注了科研通微信公众号
1秒前
DD完成签到,获得积分10
2秒前
hh完成签到,获得积分10
2秒前
2秒前
XXX发布了新的文献求助10
2秒前
hdz发布了新的文献求助10
3秒前
XXX发布了新的文献求助10
3秒前
XXX发布了新的文献求助10
3秒前
XXX发布了新的文献求助10
3秒前
22发布了新的文献求助10
3秒前
如意的灵波完成签到,获得积分10
3秒前
4秒前
Lucas的应助被刘厚麟采纳,获得10
6秒前
6秒前
6秒前
川川发布了新的文献求助10
8秒前
Whisper完成签到,获得积分20
8秒前
8秒前
怪杰发布了新的文献求助10
9秒前
11秒前
11秒前
佟若南发布了新的文献求助10
12秒前
hzwhz完成签到,获得积分10
13秒前
zouzh发布了新的文献求助30
14秒前
大头欢欢完成签到,获得积分10
14秒前
失眠山兰发布了新的文献求助10
15秒前
16秒前
18秒前
阿达完成签到,获得积分20
18秒前
jiangqingquan完成签到,获得积分10
18秒前
19秒前
南桑完成签到 ,获得积分10
19秒前
20秒前
树池完成签到,获得积分10
21秒前
Liuz发布了新的文献求助10
23秒前
刘厚麟发布了新的文献求助10
23秒前
SQC2002完成签到,获得积分10
25秒前
斯文败类的应助被怪杰采纳,获得10
27秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Production Logging: Theoretical and Interpretive Elements 400
CLSI C56QG Examples of Hemolyzed, Icteric, and Lipemic/Turbid Samples Quick Guide 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7817493
求助须知:如何正确求助?哪些是违规求助? 9346089
关于积分的说明 20533547
捐赠科研通 7410009
什么是DOI,文献DOI怎么找? 3331743
关于科研通互助平台的介绍 2478103
邀请新用户注册赠送积分活动 2351370