ArticleDiagnostics (Basel, Switzerland)2021
Texture Features of Proton Density Fat Fraction Maps from Chemical Shift Encoding-Based MRI Predict Paraspinal Muscle Strength.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Spine muscle auto segmentation techniques in MRI imaging: a systematic review.BMC musculoskeletal disorders · 2024Pooled it
- 3D Radiomic Texture Analysis of Quantitative Muscle MRI Enhances the Distinction Between Myotonic Dystrophy Type 1 and Charcot-Marie-Tooth Neuropathy Type 1A: A Proof-of-Concept Study.European journal of neurology · 2026Article
- Clinical significance and future applications of standardized imaging parameters for assessing paraspinal muscle fatty infiltration in lumbar degenerative disease: a narrative review.Journal of orthopaedic surgery and research · 2026Review
- The effect of a multimodal exercise program on paraspinal muscle morphology and clinical outcomes in chronic low back pain.Isokinetics and exercise science · 2026Article
- Radiomics and Back Pain.Global spine journal · 2026Review
- Texture analysis of T1- and T2-weighted images identifies myofiber atrophy and grip strength decline in streptozotocin-induced type 1 diabetic sarcopenia rats.Journal of orthopaedic surgery and research · 2025Article
- Myosteatosis: diagnostic significance and assessment by imaging approaches.Quantitative imaging in medicine and surgery · 2024Review
- Magnetic Resonance Imaging of the Lumbar Spine: Recommendations for Acquisition and Image Evaluation from the BACPAC Spine Imaging Working Group.Pain medicine (Malden, Mass.) · 2023Article
- Effect of vitamin energy drinks on relieving exercise-induced fatigue in muscle group by ultrasonic bioimaging data analysis.PloS one · 2023Article
- Associations of Texture Features of Proton Density Fat Fraction Maps between Lumbar Vertebral Bone Marrow and Paraspinal Musculature.Biomedicines · 2022Article
- Editorial on Special Issue "Spine Imaging: Novel Image Acquisition Techniques and Analysis Tools".Diagnostics (Basel, Switzerland) · 2022Article
- Proton density fat fraction: magnetic resonance imaging applications beyond the liver.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Review
- Association of Cervical and Lumbar Paraspinal Muscle Composition Using Texture Analysis of MR-Based Proton Density Fat Fraction Maps.Diagnostics (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 3 countries.
Funding
Abstract
Texture analysis (TA) has shown promise as a surrogate marker for tissue structure, based on conventional and quantitative MRI sequences. Chemical-shift-encoding-based MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of paraspinal muscles has been associated with various medical conditions including lumbar back pain (LBP) and neuromuscular diseases (NMD). Its application has been shown to improve the prediction of paraspinal muscle strength beyond muscle volume. Since mean PDFF values do not fully reflect muscle tissue structure, the purpose of our study was to investigate PDFF-based TA of paraspinal muscles as a predictor of muscle strength, as compared to mean PDFF. We performed 3T-MRI of the lumbar spine in 26 healthy subjects (age = 30 ± 6 years; 15 females) using a six-echo 3D spoiled gradient echo sequence for chemical-shift-encoding-based water-fat separation. Erector spinae (ES) and psoas (PS) muscles were segmented bilaterally from level L2-L5 to extract mean PDFF and texture features. Muscle flexion and extension strength was measured with an isokinetic dynamometer. Out of the eleven texture features extracted for each muscle, Kurtosis(global) of ES showed the highest significant correlation (
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Registered trials
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 OpenQuestion graph.