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Diagnostics
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New Trends in Musculoskeletal Imaging
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New Trends in Musculoskeletal Imaging

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2088

Special Issue Editor

Prof. Dr. Ugo Carraro

E-Mail Website
Guest Editor
School of Physical Medicine and Rehabilitation, Department of Neuroscience, University of Padova, Padua, Italy
Interests: genetic and acquired skeletal muscle disorders; mobility functional tests; skeletal muscle imaging; quantitative tissue densitometry by 3D and 2D color CT and MRI; blood and mouth fluid biomarkers; targeted management and follow-up in mobility medicine; functional electrical stimulation of denervated and reinnervating muscles; home full-body in-bed gym exercise; spa, thermal, and balneotherapy; hemi-fasting and other nutritional supplements of mobility medicine in aging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

“New Trends in Musculoskeletal Imaging” will be a special forum for specialists and sub-specialists of mobility medicine to share developments in classic and novel management techniques, particularly relevant for the world’s aging population and young people who suffer from genetic and acquired diseases of the skeletal muscles and their associated tissues (fascia, tendons, joints, and nerves).

The keywords below list the many different specialists who we hope will be interested in providing their suggestions and/or criticisms. However, it is necessary to underline that, without a correct diagnosis, any management intervention could be at risk of increasing, rather than decreasing, patient discomfort. Furthermore, this topic interests the entire population, regardless of age, because prevention measures must start from a defined knowledge of each individual. The two linked special issues below can provide further information for any interested authors.

Prof. Dr. Ugo Carraro
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • genetic and acquired skeletal muscle disorders
  • mobility functional tests
  • skeletal muscle imaging
  • light and electron microscopy
  • quantitative tissue densitometry by 3D and 2D color CT and MRI
  • blood and mouth fluid biomarkers
  • targeted management and follow-up in mobility medicine
  • functional electrical stimulation of denervated and reinnervating muscles
  • home full-body in-bed gym exercise
  • hemi-fasting and other nutritional supplements of mobility medicine in aging
  • spa, thermal, and balneotherapy

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Published Papers (3 papers)

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18 pages, 977 KB  
Article
An Explainable Radiomics-Based Classification Model for Sarcoma Diagnosis
by Simona Correra, Arnar Evgení Gunnarsson, Marco Recenti, Francesco Mercaldo, Vittoria Nardone, Antonella Santone, Halldór Jónsson, Jr. and Paolo Gargiulo
Diagnostics 2025, 15(16), 2098; https://doi.org/10.3390/diagnostics15162098 - 20 Aug 2025
Viewed by 523
Abstract
Objective: This study introduces an explainable, radiomics-based machine learning framework for the automated classification of sarcoma tumors using MRI. The approach aims to empower clinicians, reducing dependence on subjective image interpretation. Methods: A total of 186 MRI scans from 86 patients [...] Read more.
Objective: This study introduces an explainable, radiomics-based machine learning framework for the automated classification of sarcoma tumors using MRI. The approach aims to empower clinicians, reducing dependence on subjective image interpretation. Methods: A total of 186 MRI scans from 86 patients diagnosed with bone and soft tissue sarcoma were manually segmented to isolate tumor regions and corresponding healthy tissue. From these segmentations, 851 handcrafted radiomic features were extracted, including wavelet-transformed descriptors. A Random Forest classifier was trained to distinguish between tumor and healthy tissue, with hyperparameter tuning performed through nested cross-validation. To ensure transparency and interpretability, model behavior was explored through Feature Importance analysis and Local Interpretable Model-agnostic Explanations (LIME). Results: The model achieved an F1-score of 0.742, with an accuracy of 0.724 on the test set. LIME analysis revealed that texture and wavelet-based features were the most influential in driving the model’s predictions. Conclusions: By enabling accurate and interpretable classification of sarcomas in MRI, the proposed method provides a non-invasive approach to tumor classification, supporting an earlier, more personalized and precision-driven diagnosis. This study highlights the potential of explainable AI to assist in more secure clinical decision-making. Full article
(This article belongs to the Special Issue New Trends in Musculoskeletal Imaging)
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16 pages, 2228 KB  
Article
Potential Use of a New Energy Vision (NEV) Camera for Diagnostic Support of Carpal Tunnel Syndrome: Development of a Decision-Making Algorithm to Differentiate Carpal Tunnel-Affected Hands from Controls
by Dror Robinson, Mohammad Khatib, Mohammad Eissa and Mustafa Yassin
Diagnostics 2025, 15(11), 1417; https://doi.org/10.3390/diagnostics15111417 - 3 Jun 2025
Viewed by 717
Abstract
Introduction: Carpal Tunnel Syndrome (CTS) is a prevalent neuropathy requiring accurate, non-invasive diagnostics to minimize patient burden. This study evaluates the New Energy Vision (NEV) camera, an RGB-based multispectral imaging tool, to detect CTS through skin texture and color analysis, developing a machine [...] Read more.
Introduction: Carpal Tunnel Syndrome (CTS) is a prevalent neuropathy requiring accurate, non-invasive diagnostics to minimize patient burden. This study evaluates the New Energy Vision (NEV) camera, an RGB-based multispectral imaging tool, to detect CTS through skin texture and color analysis, developing a machine learning algorithm to distinguish CTS-affected hands from controls. Methods: A two-part observational study included 103 participants (50 controls, 53 CTS patients) in Part 1, using NEV camera images to train a Support Vector Machine (SVM) classifier. Part 2 compared median nerve-damaged (MED) and ulnar nerve-normal (ULN) palm areas in 32 CTS patients. Validations included nerve conduction tests (NCT), Semmes–Weinstein monofilament testing (SWMT), and Boston Carpal Tunnel Questionnaire (BCTQ). Results: The SVM classifier achieved 93.33% accuracy (confusion matrix: [[14, 1], [1, 14]]), with 81.79% cross-validation accuracy. Part 2 identified significant differences (p < 0.05) in color proportions (e.g., red_proportion) and Haralick texture features between MED and ULN areas, corroborated by BCTQ and SWMT. Conclusions: The NEV camera, leveraging multispectral imaging, offers a promising non-invasive CTS diagnostic tool using detection of nerve-related skin changes. Further validation is needed for clinical adoption. Full article
(This article belongs to the Special Issue New Trends in Musculoskeletal Imaging)
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Other

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5 pages, 1661 KB  
Interesting Images
Uncovering Sternoclavicular Arthritis, Suspected Pseudogout, in a Fever of Unknown Origin by Whole-Body MRI
by Maho Hayashi, Koji Hayashi, Mamiko Sato, Toshiko Iwasaki and Yasutaka Kobayashi
Diagnostics 2025, 15(16), 2032; https://doi.org/10.3390/diagnostics15162032 - 13 Aug 2025
Viewed by 459
Abstract
An 89-year-old male developed a persistent high fever (around 39 °C) approximately two weeks following endoscopic reduction of sigmoid volvulus. He had no history of hypercalcemia but was using diuretics and proton pump inhibitors. Renal and thyroid status were normal. He was largely [...] Read more.
An 89-year-old male developed a persistent high fever (around 39 °C) approximately two weeks following endoscopic reduction of sigmoid volvulus. He had no history of hypercalcemia but was using diuretics and proton pump inhibitors. Renal and thyroid status were normal. He was largely bedridden and asymptomatic except for fever. Laboratory tests demonstrated elevated C-reactive protein (4.75 mg/dL), but some tumor markers (including CEA, CA19-9, and CA125), anti-nuclear antibodies, MPO-ANCA, PR3-ANCA, β-D-glucan, and interferon-gamma release assay were all negative. Urinalysis was unremarkable. Blood cultures obtained from two sets were negative. Chest–abdomen–pelvis contrast-enhanced computed tomography (CT), and echocardiography did not reveal any evident neoplastic lesions or focal sites of infection. Despite various antibiotic therapies, the patient’s spike fever persisted for nearly one month, leading to a diagnosis of fever of unknown origin (FUO). The patient experienced partial symptomatic relief with corticosteroid therapy, though mild fever continued. Two months after the volvulus onset, diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) was performed, revealing hyperintensities at the right sternoclavicular joint, leading to a diagnosis of sternoclavicular arthritis. Neck CT revealed calcification in this joint. Despite difficulty in joint fluid analysis, low infection risk and the patient’s prolonged bedridden state and advanced age led to suspicion of pseudogout. Nonsteroidal anti-inflammatory drugs relieved fever and normalized inflammatory markers. DWIBS may be a valuable tool for detecting potential focus sites in FUO. Full article
(This article belongs to the Special Issue New Trends in Musculoskeletal Imaging)
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