Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease.

IF 4.1 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Insights into Imaging Pub Date : 2024-10-14 DOI:10.1186/s13244-024-01826-1
Zhouyan Liao, Guanjie Yuan, Kangwen He, Shichao Li, Mengmeng Gao, Ping Liang, Chuou Xu, Qian Chu, Min Han, Zhen Li
{"title":"Body composition as a potential imaging biomarker for predicting the progression risk of chronic kidney disease.","authors":"Zhouyan Liao, Guanjie Yuan, Kangwen He, Shichao Li, Mengmeng Gao, Ping Liang, Chuou Xu, Qian Chu, Min Han, Zhen Li","doi":"10.1186/s13244-024-01826-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To investigate whether the body composition parameters can be employed as potential biomarkers for predicting the progression risk of chronic kidney disease (CKD).</p><p><strong>Materials and methods: </strong>Four hundred sixteen patients diagnosed with CKD were included in this retrospective study. Patients with a greater than 50% decline in estimated glomerular filtration rate or progression to end-stage kidney disease were in the high-risk group, otherwise, they were in a low-risk group. Body composition area, the index, and radiodensities in the Hounsfield unit (HU), which reflect the degree of X-ray absorption, were measured on abdominal CT images. Risk factors in body composition and clinical parameters of CKD were identified by Cox regression and utilized to construct the nomogram. The performance of the nomogram was assessed using time receiver operating characteristics curves, calibration curves, and decision curve analysis.</p><p><strong>Results: </strong>There were 254 patients in low-risk group and 162 in high-risk group (268 males, 148 females, mean age: 55.89 years). Urea, diabetes, 24 h-urinary protein, mean arterial pressure, and subcutaneous adipose tissue radiodensity (SATd) were valuable indicators for predicting the high-risk group. The area under curve values for the nomogram of training/validation set at 1 year, 2 years, and 3 years were 0.805/0.753, 0.784/0.783, and 0.846/0.754, respectively. For diabetic CKD patients, extra attention needs to be paid to visceral to subcutaneous fat ratio and renal sinus fat radiodensity.</p><p><strong>Conclusion: </strong>SATd was the most valuable noninvasive indicator of all body composition parameters for predicting high-risk populations with CKD. The nomogram we constructed has generalization with easily obtainable indicators, good performance, differentiation, and clinical practicability.</p><p><strong>Critical relevance statement: </strong>Radiodensity rather than an area of adipose tissue can be used as a new biomarker of prognosis for CKD patients, providing new insights into risk assessment, stratified management, and treatment for CKD patients.</p><p><strong>Key points: </strong>Obesity is an independent risk factor for the development and prognosis of CKD. Adipose tissue radiodensity is more valuable than fat area in prognosticating for kidney disease. Parameters that prognosticate in diabetic CKD patients are different from those in other CKD patients.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"15 1","pages":"247"},"PeriodicalIF":4.1000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11473763/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Insights into Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13244-024-01826-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose: To investigate whether the body composition parameters can be employed as potential biomarkers for predicting the progression risk of chronic kidney disease (CKD).

Materials and methods: Four hundred sixteen patients diagnosed with CKD were included in this retrospective study. Patients with a greater than 50% decline in estimated glomerular filtration rate or progression to end-stage kidney disease were in the high-risk group, otherwise, they were in a low-risk group. Body composition area, the index, and radiodensities in the Hounsfield unit (HU), which reflect the degree of X-ray absorption, were measured on abdominal CT images. Risk factors in body composition and clinical parameters of CKD were identified by Cox regression and utilized to construct the nomogram. The performance of the nomogram was assessed using time receiver operating characteristics curves, calibration curves, and decision curve analysis.

Results: There were 254 patients in low-risk group and 162 in high-risk group (268 males, 148 females, mean age: 55.89 years). Urea, diabetes, 24 h-urinary protein, mean arterial pressure, and subcutaneous adipose tissue radiodensity (SATd) were valuable indicators for predicting the high-risk group. The area under curve values for the nomogram of training/validation set at 1 year, 2 years, and 3 years were 0.805/0.753, 0.784/0.783, and 0.846/0.754, respectively. For diabetic CKD patients, extra attention needs to be paid to visceral to subcutaneous fat ratio and renal sinus fat radiodensity.

Conclusion: SATd was the most valuable noninvasive indicator of all body composition parameters for predicting high-risk populations with CKD. The nomogram we constructed has generalization with easily obtainable indicators, good performance, differentiation, and clinical practicability.

Critical relevance statement: Radiodensity rather than an area of adipose tissue can be used as a new biomarker of prognosis for CKD patients, providing new insights into risk assessment, stratified management, and treatment for CKD patients.

Key points: Obesity is an independent risk factor for the development and prognosis of CKD. Adipose tissue radiodensity is more valuable than fat area in prognosticating for kidney disease. Parameters that prognosticate in diabetic CKD patients are different from those in other CKD patients.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
身体成分是预测慢性肾脏病恶化风险的潜在成像生物标志物。
目的:研究身体成分参数是否可用作预测慢性肾脏病(CKD)进展风险的潜在生物标志物:这项回顾性研究共纳入了 416 名确诊为慢性肾脏病的患者。估计肾小球滤过率下降超过 50%或进展为终末期肾病的患者为高风险组,否则为低风险组。通过腹部 CT 图像测量身体成分面积、指数和反映 X 射线吸收程度的 Hounsfield 单位(HU)放射性密度。通过 Cox 回归确定了身体成分和 CKD 临床参数中的风险因素,并利用这些因素构建了提名图。利用时间接收器工作特征曲线、校准曲线和决策曲线分析评估了提名图的性能:低风险组有 254 名患者,高风险组有 162 名患者(男性 268 人,女性 148 人,平均年龄 55.89 岁)。尿素、糖尿病、24 小时尿蛋白、平均动脉压和皮下脂肪组织放射密度(SATd)是预测高风险组的重要指标。训练/验证集的提名图在 1 年、2 年和 3 年的曲线下面积值分别为 0.805/0.753、0.784/0.783 和 0.846/0.754。对于糖尿病慢性肾脏病患者,需要格外注意内脏与皮下脂肪比率和肾窦脂肪放射密度:结论:在所有身体成分参数中,SATd 是预测 CKD 高危人群最有价值的无创指标。我们构建的提名图具有通用性,指标容易获得,性能良好,区分度高,临床实用性强:放射性密度而非脂肪组织面积可用作 CKD 患者预后的新生物标志物,为 CKD 患者的风险评估、分层管理和治疗提供新的见解:要点:肥胖是慢性肾脏病发病和预后的一个独立风险因素。脂肪组织放射密度比脂肪面积对肾脏疾病的预后更有价值。糖尿病慢性肾脏病患者的预后参数与其他慢性肾脏病患者不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Insights into Imaging
Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
7.30
自引率
4.30%
发文量
182
审稿时长
13 weeks
期刊介绍: Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.
期刊最新文献
Percutaneous cryoablation in soft tissue tumor management: an educational review. Computed tomography enterography-based deep learning radiomics to predict stratified healing in patients with Crohn's disease: a multicenter study. Constructing and exploring neuroimaging projects: a survey from clinical practice to scientific research. Estimated diagnostic performance of prostate MRI performed with clinical suspicion of prostate cancer. Multimodality deep learning radiomics predicts pathological response after neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1