Evidence map›Paper›PMID 41466191›Full record

ArticleBMC medical imaging2025

Quantitative assessment of renal and perirenal adipose tissue distribution at 5 T: a feasibility study.

Yichao Xu, Zhenxing Jiang, Runyu Tang, Shaofeng Duan, Jinggang Zhang, Tingting Zha, Wei Xing

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Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yichao XuDepartment of Radiology, The Third Affiliated Hospital of Soochow University, 185 Juqian Street, Changzhou, China.
Zhenxing JiangDepartment of Radiology, The Third Affiliated Hospital of Soochow University, 185 Juqian Street, Changzhou, China.
Runyu TangCollaborative Innovation Department, Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China.
Shaofeng DuanCollaborative Innovation Department, Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China.
Jinggang ZhangDepartment of Radiology, The Third Affiliated Hospital of Soochow University, 185 Juqian Street, Changzhou, China.
Tingting ZhaDepartment of Radiology, The Third Affiliated Hospital of Soochow University, 185 Juqian Street, Changzhou, China.
Wei XingDepartment of Radiology, The Third Affiliated Hospital of Soochow University, 185 Juqian Street, Changzhou, China. suzhxingwei@suda.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the feasibility and accuracy of Fat Analysis Calculation Technique (FACT), a multi-echo Dixon-like sequence, for quantifying renal and perirenal adipose distribution at 5 T.

methodsAccuracy of FACT-based Proton density fat fraction (FACT-PDFF) was assessed by comparing with magnetic resonance spectroscopy-based PDFF (MRS-PDFF) in phantom study. In vivo FACT images from 24 volunteers (13 males and 11 females) without kidney-related diseases were acquired at 5 T and evaluated independently by two readers. Repeatability of FACT-PDFF was assessed through three consecutive scans. Spearman correlation examined associations between averaged FACT-PDFF and clinical characteristics. Linear regression, intraclass correlation coefficients (ICCs), and Bland-Altman plots assessed consistency and deviations between fat quantification methods and field strengths. The Wilcoxon signed-rank test compared image quality scores between radiologists. The paired t test compared FACT-PDFF differences across all regions of interest between bilateral kidneys and between renal cortex and medulla. Analysis of covariance compared gender-related renal fat differences.

resultsIn phantom study, FACT-PDFF showed excellent agreement with MRS-PDFF at both fields (ICCs ≥ 0.995). Linear regression revealed strong correlations (R² ≥ 0.998), and Bland-Altman plots indicated minimal bias. In clinical study, FACT images achieved high quality. Repeatability was excellent (ICCs: 0.837–0.991; CVs: 0.78–4.49%). Significant PDFF differences existed between bilateral kidneys (cortex/medulla: P < 0.001; sinus fat: P = 0.003), cortex vs. medulla (P < 0.001), and genders (right cortex, left medulla, and left perirenal fat: P ≤ 0.044). PDFF was correlated positively with age, weight, body mass index, waist/hip circumference, and waist-to-height ratio (r = 0.412–0.797, P ≤ 0.046).

conclusionsFACT at 5 T reliably quantifies renal and perirenal adipose distribution. It can offer a non-invasive alternative to biopsy, and may facilitate the understanding of renal adipose distribution and its clinical associations.

Indexed as

Adipose TissueKidneyMagnetic Resonance ImagingAdultFeasibility StudiesFemaleHumansMagnetic Resonance SpectroscopyMaleMiddle AgedPhantoms, ImagingReproducibility of ResultsAdipose tissueMagnetic resonance imagingPerirenal fatProton density fat fractionRenal fatUltra-high field

Identifiers

PMID41466191
PMCPMC12859936

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.