Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization

医学 双重能量 表征(材料科学) 病变 放射科 对偶(语法数字) 核医学 病理 光学 物理 文学类 艺术 骨质疏松症 骨矿物
作者
Mathias Meyer,Rendon C. Nelson,Federica Vernuccio,F. González,Alfredo E. Farjat,Bhavik N. Patel,Ehsan Samei,Thomas Henzler,Stefan O. Schoenberg,Daniele Marin
出处
期刊:Radiology [Radiological Society of North America]
卷期号:291 (2): 381-390 被引量:56
标识
DOI:10.1148/radiol.2019181100
摘要

Background Dual-energy (DE) CT allows reconstruction of virtual noncontrast (VNC) images from a single-phase contrast agent–enhanced examination, potentially reducing the need for multiphasic CT to characterize renal lesions. However, data regarding diagnostic performance of VNC images for the characterization of renal lesions are limited. Purpose To determine whether renal mass CT performed by using VNC images allows for reliable identification of renal lesions and differentiation of contrast-enhanced from unenhanced lesions, compared with unenhanced images. Materials and Methods This is a retrospective study of 293 patients (105 women [mean age, 65 years; age range, 18–91 years] and 188 men [mean age, 66 years; age range, 23–90 years] with 379 renal lesions [craniocaudal diameter, 1.0–4.0 cm]) who underwent a single-energy unenhanced CT examination followed by a nephrographic-phase DE CT between June 2013 and October 2017 by using one of four different DE CT platforms from two vendors. VNC images were calculated by using vendor-specific algorithms. Each lesion was classified in a blinded and independent fashion by using the VNC or unenhanced image in combination with the nephrographic images. Attenuation measurements were obtained on the VNC, unenhanced, and nephrographic images. Unenhanced images and pathologic or imaging follow-up for more than 24 months served as reference standard. Results There was strong overall agreement between VNC and unenhanced images for renal lesion characterization (Cramer V = 0.85). VNC images yielded a high diagnostic performance (area under the receiver operating characteristic curve, 0.91; 95% confidence interval: 0.86, 0.95) for facilitation of differentiation of contrast-enhanced from unenhanced renal lesions. However, there was a reduction in diagnostic performance for depicting contrast-enhanced renal lesions by using VNC compared with unenhanced images (area under the receiver operating characteristic curve, 0.91 [95% confidence interval: 0.86, 0.95] vs 0.96 [95% confidence interval: 0.93, 0.99]; P < .001). Mean absolute difference between the VNC and unenhanced attenuation was 9.2 HU ± 8.7. Conclusion Virtual noncontrast images enabled accurate renal lesion characterization, albeit with a reduction in diagnostic performance for contrast-enhanced lesion characterization. © RSNA, 2019 Online supplemental material is available for this article.

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
麦麦爸完成签到,获得积分10
刚刚
大魁完成签到,获得积分10
1秒前
Cheny完成签到 ,获得积分10
1秒前
1秒前
赵烧完成签到,获得积分10
1秒前
平淡孤萍发布了新的文献求助10
1秒前
核桃应助逆流的鱼采纳,获得30
2秒前
Nole应助逆流的鱼采纳,获得10
2秒前
一念通则万达完成签到 ,获得积分10
3秒前
3秒前
orixero应助帅气雪糕采纳,获得10
3秒前
星辰大海应助帅气雪糕采纳,获得10
3秒前
4秒前
wangxiaoyating完成签到,获得积分0
4秒前
seed完成签到 ,获得积分10
4秒前
4秒前
海带拳大力士完成签到,获得积分10
4秒前
lkxpsy完成签到,获得积分10
4秒前
15919229415完成签到,获得积分10
4秒前
赵爽完成签到,获得积分10
6秒前
七月不远完成签到,获得积分10
6秒前
6秒前
6秒前
lulu发布了新的文献求助10
7秒前
阳佟之槐完成签到,获得积分10
7秒前
激情的冰绿完成签到 ,获得积分10
8秒前
今后应助周周猴采纳,获得10
8秒前
Irene完成签到,获得积分10
9秒前
谦让白亦发布了新的文献求助10
9秒前
brick2024发布了新的文献求助10
9秒前
张天宝真的爱科研完成签到,获得积分10
11秒前
11秒前
Harden完成签到,获得积分10
11秒前
HH应助Doc_d采纳,获得10
12秒前
钟贵泉完成签到,获得积分10
12秒前
Tal完成签到 ,获得积分0
12秒前
zkygmu发布了新的文献求助10
12秒前
七月不远发布了新的文献求助10
12秒前
小马甲应助miemie66采纳,获得10
12秒前
充电宝应助333采纳,获得10
12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
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 2500
Atlas of Aligner Treatment and Planning A Case-Based Approach 1000
Rocket Propulsion Elements, 10th Edition 800
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 700
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 7441147
求助须知:如何正确求助?哪些是违规求助? 9042100
关于积分的说明 19271015
捐赠科研通 7066035
什么是DOI,文献DOI怎么找? 3238090
关于科研通互助平台的介绍 2401885
邀请新用户注册赠送积分活动 2222031