MRI-Derived Vertebral Bone Marrow Fat Fraction for Osteoporosis Prediction in Type 2 Diabetes: Evaluation of Inter-Device Consistency and Clinical Risk Predictors DOI

Yan Xi,

Jing Wang, Feng Sun

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 15, 2025

Abstract Introduction: This study investigates the association between lumbar spine bone marrow fat fraction (FF) on MRI and clinical risk factors in patients with type 2 diabetes mellitus (T2DM). Additionally, it evaluates inter-device consistency of FF measurements determines predictive value for osteoporosis. Materials method: A total 109 T2DM were enrolled, quantified using T1-VIBE-DIXON sequences a Siemens 3.0T mDIXON-Quant Philips MRI. Inter-device agreement was assessed. Bone mineral density (BMD) assessed dual-energy X-ray absorptiometry (DXA), participants stratified into normal, osteopenic, or osteoporotic categories based T-score thresholds. ROC analysis conducted to establish optimal cutoff osteoporosis prediction, while linear regression identified associated FF, including gender, age, BMI, duration, diabetic peripheral neuropathy (DPN) biochemical parameters. Results: demonstrated strong agreement, no significant bias scanners (P > 0.05). determined an threshold 61.4% prediction (AUC = 0.87, 95% CI: 0.73-0.95, sensitivity: 72.5%, specificity: 87.1%) 55.2% osteopenia 0.77, 0.67–0.88, 78.9%, 64.5%). Regression female gender (B 7.13, P < 0.001), advanced age 0.38, LDL-C 2.6 mmol/L 309, =0.02), DPN 3.03, =0.02) as independent predictors increased FF. Conclusion: Lumbar emerges reliable biomarker patients, demonstrating robust comparability. Identifying key enhances stratification, supporting MRI-based assessment adjunct DXA early diagnosis personalized health management.

Язык: Английский

Longitudinal assessment of changes in muscle composition using proton density fat fraction and T2* in patients with and without incidental vertebral compression fractures DOI Creative Commons

Yannick Stohldreier,

Yannik Leonhardt,

Jannik Ketschau

и другие.

Frontiers in Endocrinology, Год журнала: 2025, Номер 16

Опубликована: Март 3, 2025

Objective Chemical shift encoded-based water-fat separation magnetic resonance imaging (CSE-MRI) is an emerging noninvasive tool for the assessment of bone and muscle composition. This study aims to examine both predictive value longitudinal change proton density fat fraction (PDFF) T2* in paraspinal muscles (PSM) patients with without development incidental vertebral compression fracture (VCFs) after 6 months follow-up. Methods Patients (N=56) CT 3T CSE-MRI lumbar spine at baseline follow-up were included this retrospective study. who, on average, developed VCF one year MRI (VCF: N=14, 9 males, 66.8 ± 7.9 years) frequency matched by age sex VCFs (non-VCF) (non-VCF: N=42, 27 64.6 13.3 years). Mean PDFF, T2*, cross-sectional area (CSA) values from autochthonous PSM thoracolumbar (T11-L4) opportunistic CT-based mineral (BMD) measurements obtained each individual. The associations between measurements, changes CSA occurrence evaluated using linear logistic multivariable regression models. ROC analyses used assess cutoff predicting VCFs. Results No significant difference PDFF was found non-VCF group (VCF/non-VCF 8.5 13.8% vs. 5.0 4.6%; p=0.53). In models adjusted sex, BMD, increased significantly over (2.4 2.8% -1.0 2.3%, p&lt;0.001), while showed a decrease (p ≤ 0.01). identified increase 0.2% as optimal distinguish (AUC 0.86, 95% CI [0.74-0.98], p&lt;0.001). Conclusion Longitudinal PDFF-based composition may be useful indicator prediction fractures.

Язык: Английский

Процитировано

0
MRI-Derived Vertebral Bone Marrow Fat Fraction for Osteoporosis Prediction in Type 2 Diabetes: Evaluation of Inter-Device Consistency and Clinical Risk Predictors DOI

Yan Xi,

Jing Wang, Feng Sun

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 15, 2025

Abstract Introduction: This study investigates the association between lumbar spine bone marrow fat fraction (FF) on MRI and clinical risk factors in patients with type 2 diabetes mellitus (T2DM). Additionally, it evaluates inter-device consistency of FF measurements determines predictive value for osteoporosis. Materials method: A total 109 T2DM were enrolled, quantified using T1-VIBE-DIXON sequences a Siemens 3.0T mDIXON-Quant Philips MRI. Inter-device agreement was assessed. Bone mineral density (BMD) assessed dual-energy X-ray absorptiometry (DXA), participants stratified into normal, osteopenic, or osteoporotic categories based T-score thresholds. ROC analysis conducted to establish optimal cutoff osteoporosis prediction, while linear regression identified associated FF, including gender, age, BMI, duration, diabetic peripheral neuropathy (DPN) biochemical parameters. Results: demonstrated strong agreement, no significant bias scanners (P > 0.05). determined an threshold 61.4% prediction (AUC = 0.87, 95% CI: 0.73-0.95, sensitivity: 72.5%, specificity: 87.1%) 55.2% osteopenia 0.77, 0.67–0.88, 78.9%, 64.5%). Regression female gender (B 7.13, P < 0.001), advanced age 0.38, LDL-C 2.6 mmol/L 309, =0.02), DPN 3.03, =0.02) as independent predictors increased FF. Conclusion: Lumbar emerges reliable biomarker patients, demonstrating robust comparability. Identifying key enhances stratification, supporting MRI-based assessment adjunct DXA early diagnosis personalized health management.

Язык: Английский

Процитировано

0