Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases

医学 核医学 图像质量 放射科 前瞻性队列研究 内科学 计算机科学 图像(数学) 人工智能
作者
Corey T. Jensen,Shiva Gupta,Mohammed Saleh,Xinming Liu,Vincenzo K. Wong,Usama Salem,Wei Qiao,Ehsan Samei,Nicolaus A. Wagner‐Bartak
出处
期刊:Radiology [Radiological Society of North America]
卷期号:303 (1): 90-98 被引量:67
标识
DOI:10.1148/radiol.211838
摘要

Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate liver metastases and image quality between reduced-dose deep learning image reconstruction (DLIR) and standard-dose filtered back projection (FBP) contrast-enhanced abdominal CT. Materials and Methods In this prospective Health Insurance Portability and Accountability Act–compliant study (September 2019 through April 2021), participants with biopsy-proven colorectal cancer and liver metastases at baseline CT underwent standard-dose and reduced-dose portal venous abdominal CT in the same breath hold. Three radiologists detected and characterized lesions at standard-dose FBP and reduced-dose DLIR, reported confidence, and scored image quality. Contrast-to-noise ratios for liver metastases were recorded. Summary statistics were reported, and a generalized linear mixed model was used. Results Fifty-one participants (mean age ± standard deviation, 57 years ± 13; 31 men) were evaluated. The mean volume CT dose index was 65.1% lower with reduced-dose CT (12.2 mGy) than with standard-dose CT (34.9 mGy). A total of 161 lesions (127 metastases, 34 benign lesions) with a mean size of 0.7 cm ± 0.3 were identified. Subjective image quality of reduced-dose DLIR was superior to that of standard-dose FBP (P < .001). The mean contrast-to-noise ratio for liver metastases of reduced-dose DLIR (3.9 ± 1.7) was higher than that of standard-dose FBP (3.5 ± 1.4) (P < .001). Differences in detection were identified only for lesions 0.5 cm or smaller: 63 of 65 lesions detected with standard-dose FBP (96.9%; 95% CI: 89.3, 99.6) and 47 lesions with reduced-dose DLIR (72.3%; 95% CI: 59.8, 82.7). Lesion accuracy with standard-dose FBP and reduced-dose DLIR was 80.1% (95% CI: 73.1, 86.0; 129 of 161 lesions) and 67.1% (95% CI: 59.3, 74.3; 108 of 161 lesions), respectively (P = .01). Lower lesion confidence was reported with a reduced dose (P < .001). Conclusion Deep learning image reconstruction (DLIR) improved CT image quality at 65% radiation dose reduction while preserving detection of liver lesions larger than 0.5 cm. Reduced-dose DLIR demonstrated overall inferior characterization of liver lesions and reader confidence. Clinical trial registration no. NCT03151564 © RSNA, 2022 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
1秒前
2秒前
起飞发布了新的文献求助10
3秒前
3秒前
4秒前
Miranda完成签到,获得积分10
4秒前
didihe发布了新的文献求助10
4秒前
5秒前
科研通AI6.4应助zhanghuiqian采纳,获得10
5秒前
单薄静枫发布了新的文献求助10
5秒前
Jameson完成签到,获得积分10
5秒前
冰冰发布了新的文献求助10
5秒前
5秒前
QDU发布了新的文献求助10
7秒前
爱听歌的听云完成签到,获得积分10
7秒前
回望完成签到 ,获得积分10
8秒前
yiyeshanren完成签到,获得积分10
8秒前
大大怪发布了新的文献求助10
8秒前
lwy发布了新的文献求助10
9秒前
牛牛发布了新的文献求助10
9秒前
兰战非完成签到 ,获得积分10
9秒前
10秒前
11秒前
11秒前
科研通AI6.4应助一一采纳,获得10
12秒前
13秒前
核桃发布了新的文献求助20
14秒前
大大怪完成签到,获得积分10
15秒前
隐形曼青应助scufgy采纳,获得10
15秒前
凉风送信完成签到,获得积分10
15秒前
15秒前
16秒前
zzz发布了新的文献求助10
17秒前
17秒前
牟弼完成签到,获得积分10
18秒前
18秒前
爆米花应助Gao采纳,获得10
18秒前
19秒前
雪雪完成签到,获得积分10
19秒前
maoyf完成签到,获得积分10
20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
HYDROLYSE ACIDE DE QUELQUES DIOXASPIROCYCLANES 1314
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 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 7746217
求助须知:如何正确求助?哪些是违规求助? 9294057
关于积分的说明 20223479
捐赠科研通 7326111
什么是DOI,文献DOI怎么找? 3308079
关于科研通互助平台的介绍 2460091
邀请新用户注册赠送积分活动 2319634