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Imaging in Diagnosis and Treatment of Musculoskeletal Disorders

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A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nuclear Medicine & Radiology".

Deadline for manuscript submissions: closed (20 April 2026) | Viewed by 6995

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Editors

Dr. Francesco Porta

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Guest Editor

Section of Rheumatology, Interdisciplinary Pain Medicine Unit, Santa Maria Maddalena Hospital, Rovigo, Italy
Interests: rheumatology; musculoskeletal ultrasound; musculoskeletal imaging; pain medicine; ultrasound guided procedures

Prof. Dr. Florentin Ananu Vreju

E-Mail Website
Guest Editor

Faculty of Medicine, Univeristy of Medicine and Pharmacy of Craiova, Craiova, Romania
Interests: rheumatology; musculoskeletal ultrasound; arthritis; osteoarthritis
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Special Issue Information

Dear Colleagues,

In the field of musculoskeletal disorders, imaging is becoming increasingly important in diagnostic confirmation, prognostic stratification, decision-making, and follow-up. The integration of imaging into the management of rheumatological conditions enables earlier diagnosis and more accurate differential diagnosis and ultimately offers a comprehensive understanding of the disease.

On the other hand, even in musculoskeletal disorders that are not exclusively of rheumatological origin, imaging has become a crucial tool, and making decisions without it would now seem outdated. Additionally, it is now widely established that imaging plays a vital role in interventional procedures, which, over the years, have become safer and increasingly precise thanks to the ability to guide needles to a target without crossing critical structures.

This concept applies equally to ultrasound-guided procedures, which can be routinely performed in an outpatient setting, as well as to fluoroscopy- or CT-guided procedures that require access to more specialized facilities.

For this Special Issue, we encourage authors to submit papers on applications of imaging in musculoskeletal and rheumatological conditions, in both diagnosis and treatment.

Dr. Francesco Porta
Prof. Dr. Florentin Ananu Vreju
Guest Editors

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Keywords

ultrasound
ultrasound-guided injections
imaging-guided procedures

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Published Papers (4 papers)

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Research

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16 pages, 1594 KB

Open AccessArticle

Beyond Bone Density Alone: Opportunistic Identification of Vertebral Compression Fractures in Breast Cancer Survivors Using Artificial Intelligence-Derived Vertebral Bone Density and Paraspinal Muscle–Fat Metrics

by Chengxin Wan, Lingquan Kong, Jie Hao, Bin Lu, Chao Wu, Miao Wei, Zhiwei Zhang, Beibei Gong and Fajin Lv

J. Clin. Med. 2026, 15(16), 6283; https://doi.org/10.3390/jcm15166283 - 13 Aug 2026

Abstract

Background/Objectives: This study aimed to evaluate whether artificial intelligence-derived vertebral volumetric bone mineral density (AI-vBMD) and paraspinal intermuscular adipose tissue (IMAT) ratio from routine computed tomography (CT) could identify moderate-to-severe vertebral compression fractures (VCFs) in breast cancer survivors, and whether paraspinal IMAT ratio and routinely available clinical variables improved diagnostic performance. Methods: This retrospective study included 275 women with breast cancer who underwent routine non-contrast CT and lumbar quantitative computed tomography (QCT). Hounsfield unit-derived volumetric bone mineral density (HU-vBMD) was derived using a QCT-referenced HU-to-vBMD conversion equation, whereas AI-vBMD and paraspinal IMAT ratio were extracted using automated software. Moderate-to-severe VCF was defined as Genant grade ≥ 2. Agreement with QCT-vBMD was assessed using correlation, intraclass correlation coefficient (ICC), and Bland–Altman analysis. Model discrimination was evaluated using receiver operating characteristic analysis and DeLong tests. Results: Moderate-to-severe VCF was present in 75 patients (27.3%). HU-vBMD and AI-vBMD showed excellent agreement with QCT-vBMD (ICC, 0.978 and 0.987, respectively). AI-vBMD outperformed HU-vBMD for identifying VCFs (AUC, 0.738 vs. 0.714; p < 0.001). IMAT ratio showed comparable standalone discrimination to AI-vBMD (AUC, 0.760 vs. 0.738; p = 0.604). Adding IMAT ratio to AI-vBMD improved discrimination (AUC, 0.786 vs. 0.738; p = 0.038). The full model incorporating clinical covariates achieved the highest AUC (0.828; 95% CI, 0.778–0.878). Conclusions: AI-vBMD and paraspinal IMAT ratio automatically extracted from routine CT improved the diagnostic assessment of prevalent moderate-to-severe VCFs in breast cancer survivors. This study supports an automated CT-based approach that integrates vertebral bone density and paraspinal muscle–fat information for opportunistic identification of clinically relevant VCFs. Full article

(This article belongs to the Special Issue Imaging in Diagnosis and Treatment of Musculoskeletal Disorders)

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11 pages, 1280 KB

Open AccessArticle

Prediction of Osteoporosis at the Sacrum Using Opportunistic CT of the Abdomen and Pelvis: A Retrospective Feasibility Study in 277 Patients Comparing CT and QCT Data

by Yan Xiao, Wen Li, Wenqin Zhou, Miao Wei, Bangyuan Long, Jiayi Pu and Fajin Lv

J. Clin. Med. 2026, 15(9), 3473; https://doi.org/10.3390/jcm15093473 - 1 May 2026

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Abstract

Summary This study assessed the use of opportunistic abdominopelvic computed tomography (CT) for the evaluation of the sacrum as a predictive tool for osteoporosis. Sacral spine Hounsfield unit (HU) values measured by CT showed good correlation with mean bone mineral density (BMD) for L1–L2 measured by quantitative computed tomography (QCT), and good diagnostic performance for the identification of osteoporosis. The results of this study suggest that it is possible to obtain comprehensive information on bone health in individuals who undergo CT of pelvic. Objectives To examine the distribution pattern of bone density in the L1–S3 vertebrae using opportunistic abdominopelvic imaging. QCT was employed as a reference to establish HU thresholds for the sacral vertebrae facilitating the prediction of osteoporosis and the exclusion of bone abnormalities. Methods A total of 277 subjects aged 19 to 81 years who underwent abdominopelvic CT were evaluated. Bone mineral density (BMD) measurements for the L1–S3 vertebrae and HU values for the S1–S3 vertebrae were collected. The study analyzed the correlation between sacral spine HU values and sacral spine BMD, along with the clinically utilized mean BMD for L1–L2, was analyzed. Receiver operating characteristic (ROC) curves were generated to identify the optimal diagnostic thresholds. Results The BMD of the lumbosacral vertebrae displayed a gradual decrease from L1 to L3, followed by an increase from L4 to S1, and a subsequent decline from S1 to S3. HU values of the sacral vertebrae across all planes were strongly correlated with both sacral spine BMD and the mean BMD values for L1–L2 (r = 0.830 to 0.905, p < 0.05). For individual vertebrae, the area under the curve (AUC) of HU values for predicting osteoporosis ranged from 0.909 to 0.977, while the AUC for excluding bone abnormalities ranged from 0.933 to 0.950, with S1 demonstrating the highest predictive efficacy. The optimal threshold for S1 was >165.17 HU, yielding a specificity of 91.5% and a sensitivity of 83.0% for excluding bone abnormalities. Conversely, an S1 threshold of <130.50 HU resulted in a diagnostic specificity of 90.0% and a sensitivity of 96.6% for osteoporosis. Additionally, a predictive model that incorporated sex, age, and vertebral cancellous bone HU values achieved an AUC of 0.981. Conclusions Our data demonstrate a strong correlation between the HU values of the sacral spine and the clinically used BMD values for L1–L2, supporting the prediction of osteoporosis based on sacral spine HU values. Moreover, a predictive model that includes sex, age, and vertebral measurements offers improved diagnostic accuracy. Full article

(This article belongs to the Special Issue Imaging in Diagnosis and Treatment of Musculoskeletal Disorders)

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Review

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28 pages, 612 KB

Open AccessReview

Shear Wave Elastography in Musculoskeletal Imaging: A Narrative Review

by Enes Gurun, Mesut Ozturk, Mustafa Basaran and Ahmet Emin Okutan

J. Clin. Med. 2026, 15(12), 4843; https://doi.org/10.3390/jcm15124843 - 22 Jun 2026

Cited by 1 | Viewed by 726

Abstract

Shear wave elastography (SWE) is an increasingly investigated ultrasound-based technique in musculoskeletal imaging that provides quantitative information on tissue stiffness and biomechanical properties. This narrative review aims to summarize the basic principles, technical considerations, current clinical applications, limitations, and future perspectives of SWE in musculoskeletal imaging. Unlike conventional grayscale and Doppler ultrasonography, which mainly assess morphology and vascularity, SWE may provide additional functional information in major musculoskeletal tissues, including tendons and ligaments, skeletal muscles, peripheral nerves, fibrocartilaginous structures, plantar fascia, and selected soft tissue lesions. Current evidence suggests potential roles for SWE in detecting early biomechanical alterations, assessing disease severity, differentiating symptomatic from asymptomatic tissues, and monitoring response to treatment or rehabilitation. However, musculoskeletal tissues are anisotropic, viscoelastic, and position-dependent; as a result, SWE measurements are influenced by acquisition-related factors, tissue biomechanics, positioning and loading conditions, region of interest (ROI) placement, tissue depth, and device-related variability. For this reason, SWE findings should not be interpreted as standalone diagnostic criteria but should be considered together with clinical findings, conventional ultrasonography, MRI, electrophysiology, histopathology, and patient-centered outcomes when appropriate. This review highlights the need for tissue-specific measurement protocols, standardized reporting, normative reference data, inter-vendor harmonization, and longitudinal validation against clinically meaningful outcomes before SWE can be more reliably integrated into routine musculoskeletal imaging and rehabilitation practice. Full article

(This article belongs to the Special Issue Imaging in Diagnosis and Treatment of Musculoskeletal Disorders)

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18 pages, 4138 KB

Open AccessReview

Fibromyalgia in the Era of Brain PET/CT Imaging

by Elisabetta Abenavoli, Valentina Berti, Matilde Nerattini, Piercarlo Sarzi-Puttini, Georgios Filippou, Alessandro Lucia, Gilberto Pari, Stefano Pallanti, Fausto Salaffi, Marina Carotti, Silvia Sirotti and Francesco Porta

J. Clin. Med. 2025, 14(12), 4166; https://doi.org/10.3390/jcm14124166 - 12 Jun 2025

Cited by 7 | Viewed by 5083

Abstract

Fibromyalgia syndrome (FMS) is a complex, heterogeneous disorder characterized by chronic widespread pain, fatigue, and cognitive disturbances. The multifactorial nature of FMS, with the involvement of central and peripheral mechanisms, hampers diagnosis and effective treatment. In recent years, positron emission tomography (PET) imaging has emerged as a valuable tool for exploring the neurobiological underpinnings of FMS. Several studies have investigated alterations in glucose metabolism, neurotransmitter systems (including opioid, dopamine, and GABAergic pathways), and neuroinflammation using various PET tracers. These findings have revealed distinct brain metabolic and molecular patterns in FMS patients compared to healthy controls, particularly in pain-related regions such as the thalamus, insula, and anterior cingulate cortex (ACC). Moreover, preliminary data suggest that PET imaging may help identify FMS subgroups with different pathophysiological profiles, potentially allowing for tailored therapeutic approaches. This review summarizes the current evidence on PET applications in FMS and discusses the potential role of molecular imaging in improving patient stratification and predicting treatment response. Full article

(This article belongs to the Special Issue Imaging in Diagnosis and Treatment of Musculoskeletal Disorders)

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