Quantitative Measurement on Contrast-Enhanced CT Distinguishes Small Clear Cell Renal Cell Carcinoma From Benign Renal Tumors: A Multicenter Study

医学 肾细胞癌 队列 肾皮质 肾透明细胞癌 逻辑回归 清除单元格 核医学 泌尿科 放射科 内科学
作者
Shiwei Luo,Wanxian Lin,Jialiang Wu,Wanli Zhang,Xiaoyan Kui,Shengsheng Lai,Ruili Wei,Xinrui Pang,Ye Wang,Chutong He,Jun Liu,Ruimeng Yang
出处
期刊:Academic Radiology [Elsevier BV]
卷期号:31 (4): 1460-1471 被引量:6
标识
DOI:10.1016/j.acra.2023.10.014
摘要

Rationale and Objectives To evaluate the potential of quantitative measurements on contrast-enhanced CT (CECT) in differentiating small (≤4 cm) clear cell renal cell carcinoma (ccRCC) from benign renal tumors, including fat-poor angiomyolipoma (fpAML) and renal oncocytoma (RO). Materials and Methods 244 patients with pathologically confirmed ccRCC (n = 184) and benign renal tumors (fpAML, n = 50; RO, n = 10) were randomly assigned into training cohort (n = 193) and test cohort 1 (n = 51), while external test cohort 2 (n = 50) was from another hospital. Quantitative parameters were obtained from CECT (unenhanced phase, UP; corticomedullary phase, CMP; nephrographic phase, NP; excretory phase, EP) by measuring attenuation of renal mass and cortex and subsequently calculated. Univariable and multivariable logistic regression analyses were performed to evaluate the association between these parameters and ccRCC. Finally, the constructed models were compared with radiologists' diagnoses. Results In univariable analysis, UP-related parameters, particularly UPC-T (cortex minus tumor attenuation on UP), demonstrated AUC of 0.766 in training cohort, 0.901 in test cohort 1, 0.805 in test cohort 2. The heterogeneity-related parameter SD (standard deviation) showed AUC of 0.781, 0.834, and 0.875 respectively. In multivariable analysis, model 1 incorporating UPC-T, NPC-T (cortex minus tumor attenuation on NP), CMPT-UPT (tumor attenuation on CMP minus UP), and SD yielded AUC of 0.866, 0.923, and 0.949 respectively. When compared with radiologists, multivariate models demonstrated higher accuracy (0.800–0.860) and sensitivity (0.794–0.971) than radiologists' assessments (accuracy: 0.700–0.720, sensitivity: 0.588–0.706). Conclusion Quantitative measurements on CECT, particularly UP- and heterogeneity-related parameters, have potential to discriminate ccRCC and benign renal tumors (fpAML, RO). To evaluate the potential of quantitative measurements on contrast-enhanced CT (CECT) in differentiating small (≤4 cm) clear cell renal cell carcinoma (ccRCC) from benign renal tumors, including fat-poor angiomyolipoma (fpAML) and renal oncocytoma (RO). 244 patients with pathologically confirmed ccRCC (n = 184) and benign renal tumors (fpAML, n = 50; RO, n = 10) were randomly assigned into training cohort (n = 193) and test cohort 1 (n = 51), while external test cohort 2 (n = 50) was from another hospital. Quantitative parameters were obtained from CECT (unenhanced phase, UP; corticomedullary phase, CMP; nephrographic phase, NP; excretory phase, EP) by measuring attenuation of renal mass and cortex and subsequently calculated. Univariable and multivariable logistic regression analyses were performed to evaluate the association between these parameters and ccRCC. Finally, the constructed models were compared with radiologists' diagnoses. In univariable analysis, UP-related parameters, particularly UPC-T (cortex minus tumor attenuation on UP), demonstrated AUC of 0.766 in training cohort, 0.901 in test cohort 1, 0.805 in test cohort 2. The heterogeneity-related parameter SD (standard deviation) showed AUC of 0.781, 0.834, and 0.875 respectively. In multivariable analysis, model 1 incorporating UPC-T, NPC-T (cortex minus tumor attenuation on NP), CMPT-UPT (tumor attenuation on CMP minus UP), and SD yielded AUC of 0.866, 0.923, and 0.949 respectively. When compared with radiologists, multivariate models demonstrated higher accuracy (0.800–0.860) and sensitivity (0.794–0.971) than radiologists' assessments (accuracy: 0.700–0.720, sensitivity: 0.588–0.706). Quantitative measurements on CECT, particularly UP- and heterogeneity-related parameters, have potential to discriminate ccRCC and benign renal tumors (fpAML, RO).
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
胡彦乱语的咖啡豆完成签到,获得积分10
刚刚
刚刚
cdercder应助飞飞采纳,获得30
刚刚
zhhl2006发布了新的文献求助10
1秒前
1秒前
2秒前
hl完成签到,获得积分10
2秒前
认真的不评应助hongw1980采纳,获得10
2秒前
李健的粉丝团团长应助wyx采纳,获得30
3秒前
有你完成签到 ,获得积分10
3秒前
怡然夏瑶完成签到,获得积分10
4秒前
jerry完成签到,获得积分10
4秒前
change发布了新的文献求助30
6秒前
Nature发布了新的文献求助10
6秒前
打打应助梦见秋采纳,获得10
6秒前
Yh_alive应助留胡子的黑夜采纳,获得10
7秒前
Lis完成签到,获得积分10
7秒前
7秒前
有你关注了科研通微信公众号
8秒前
小智发布了新的文献求助10
8秒前
清脆的惜芹完成签到,获得积分10
9秒前
10秒前
11秒前
11秒前
医一直悟完成签到,获得积分10
11秒前
金荣发布了新的文献求助10
11秒前
南乔星完成签到 ,获得积分10
12秒前
科目三应助MRchen采纳,获得30
13秒前
沉淀发布了新的文献求助10
13秒前
愉快的真发布了新的文献求助10
14秒前
Selina完成签到 ,获得积分10
14秒前
闲之野鹤发布了新的文献求助10
14秒前
LmyHusband发布了新的文献求助10
14秒前
阳光的雪碧完成签到,获得积分10
15秒前
mmmm完成签到,获得积分20
16秒前
byyyy完成签到,获得积分0
16秒前
卡乐李发布了新的文献求助10
16秒前
美满的如霜完成签到,获得积分10
17秒前
AN应助科研通管家采纳,获得30
17秒前
JamesPei应助科研通管家采纳,获得10
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
日本現代怪異事典 副読本 700
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 650
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
Models for the coupled atmosphere and ocean 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7378522
求助须知:如何正确求助?哪些是违规求助? 8986064
关于积分的说明 19110057
捐赠科研通 7018505
什么是DOI,文献DOI怎么找? 3226368
关于科研通互助平台的介绍 2389621
邀请新用户注册赠送积分活动 2207007