Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.9
3.8
Journals
Diagnostics
Special Issues
Musculoskeletal Imaging in Clinical Practice: From Qualitative Diagnosis to Quantitative...
share announcement

Musculoskeletal Imaging in Clinical Practice: From Qualitative Diagnosis to Quantitative Analysis

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

Deadline for manuscript submissions: 30 June 2027 | Viewed by 1328

Editor

Dr. Seul Ki Lee

E-Mail Website
Guest Editor
Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
Interests: musculoskeletal radiology; musculoskeletal tumor imaging; radiomics; quantitative imaging analysis; orthopedic oncology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Musculoskeletal (MSK) imaging is essential for diagnosing and managing a wide spectrum of orthopedic conditions, including trauma, arthritis, sports injuries, and bone and soft tissue tumors. Traditionally, MSK imaging has relied on qualitative, morphology-based interpretation using radiography, CT, MRI, and ultrasound. With recent technological advances, however, the field is rapidly transitioning toward quantitative analysis. Techniques such as T2 mapping, diffusion-weighted imaging, dynamic enhanced MRI, and DIXON now enable objective characterization of tissue composition and microstructure.

This Special Issue aims to showcase studies that bridge qualitative diagnosis and quantitative imaging analysis in clinical practice. We welcome research that demonstrates how emerging quantitative methods enhance diagnostic accuracy, prognostication, and personalized musculoskeletal care.

Dr. Seul Ki Lee
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • musculoskeletal imaging
  • qualitative diagnosis
  • quantitative imaging
  • imaging biomarkers
  • MRI
  • CT
  • plain radiograph
  • ultrasound

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

22 pages, 3544 KB  
Article
Radiographic Angle-Based Machine Learning Models for the Diagnosis of Pes Planus and Pes Cavus: A Large-Scale Study Using Weight-Bearing Lateral Foot Radiographs
by Rabia Taşdemir, Mustafa Işık, Ahmet Hakan İnce, Ebru Sena Poyraz, Şule Baysal, Ramazan Parıldar and Nevzat Gönder
Diagnostics 2026, 16(12), 1929; https://doi.org/10.3390/diagnostics16121929 - 22 Jun 2026
Viewed by 248
Abstract
Background/Objectives: Pes planus and pes cavus are common foot deformities, which may lead to pain, functional limitations, and impairment of foot biomechanics. While calcaneal pitch, talar declination, and Meary angles, commonly used in diagnosis, provide objective information, their lack of a gold [...] Read more.
Background/Objectives: Pes planus and pes cavus are common foot deformities, which may lead to pain, functional limitations, and impairment of foot biomechanics. While calcaneal pitch, talar declination, and Meary angles, commonly used in diagnosis, provide objective information, their lack of a gold standard and the observer’s dependence on manual measurements limit their reliability. Therefore, in this study, these angles obtained from weight-bearing lateral foot radiographs were evaluated according to literature references, and the aim was to determine the model that provides the most accurate prediction in the diagnosis of pes planus using machine learning algorithms. It should be emphasized that, because the diagnostic labels were derived from literature-based thresholds of these same angles, the machine-learning task addressed here is the automated reproduction and standardization of expert, angle-threshold-based classification, rather than an independent clinical diagnosis from raw images. Methods: This retrospective study was conducted using weight-bearing lateral foot radiographs of 697 male patients obtained from the archives of public hospitals in Gaziantep. Calcaneal pitch, Meary angle, and talar declination angles were evaluated in both feet, and the data were labeled as normal, pes planus, and pes cavus. The dataset, consisting of a total of 1394 feet, was divided into training and test groups and analyzed using Random Forest, XGBoost, Logistic Regression, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) algorithms; the diagnostic performance of the models was compared using measures such as accuracy, F1 score, sensitivity, and specificity. Results: A total of 1394 feet from 697 male patients (mean age 24.8 ± 5.57 years) were analyzed using five machine learning algorithms with calcaneal pitch angle (CPA), Meary angle (MA), and talar declination angle (TDA) as reference labels. Ensemble-based methods showed superior performance, with XGBoost achieving perfect classification (Accuracy = 1.000) under all three labels for the left foot and 0.996–1.000 for the right foot, while Random Forest reached 0.986–1.000 across all experiments. Logistic Regression and SVM yielded moderate accuracies (0.905–0.973), whereas KNN consistently performed the weakest (0.905–0.964), particularly in the pes cavus subgroup. The near-perfect accuracy obtained when the labeling angle was itself included among the predictors reflects, at least in part, the algebraic reconstruction of the threshold rule from a same-source variable rather than genuine diagnostic generalization; results should therefore be interpreted with this in mind. Conclusions: This study demonstrates that machine learning, particularly ensemble methods such as XGBoost and Random Forest, provides high accuracy and consistency in diagnosing foot arch deformities based on radiographic angle measurements. Traditional models, such as Logistic Regression, still hold value in terms of clinical interpretability despite their lower performance. The findings suggest that machine learning-based approaches can offer objective, rapid, and reliable decision support tools for diagnosing pes planus and pes cavus, but external validation studies are necessary for clinical generalizability. Full article
(This article belongs to the Special Issue Musculoskeletal Imaging in Clinical Practice: From Qualitative Diagnosis to Quantitative Analysis)
►▼ Show Figures

Figure 1

12 pages, 1156 KB  
Article
Phalangeal Bone Mineral Density Mapping Using Quantitative CT: Implications for Hand Surgery Fixation Planning
by Zoe K. Papadopoulou, Konstantinos N. Malizos, Filippos Filippou, Vasileios Raoulis, Alexis T. Kermanidis, Michail E. Klontzas and Aristidis H. Zibis
Diagnostics 2026, 16(12), 1843; https://doi.org/10.3390/diagnostics16121843 - 15 Jun 2026
Viewed by 313
Abstract
Objective: To quantify and map bone mineral density (BMD) at the bases of human finger phalanges using computed tomography (CT) with a calibration phantom and to compare BMD both between and within digits. Methods: Ten cadaveric hands (H1 to H10) were CT scanned [...] Read more.
Objective: To quantify and map bone mineral density (BMD) at the bases of human finger phalanges using computed tomography (CT) with a calibration phantom and to compare BMD both between and within digits. Methods: Ten cadaveric hands (H1 to H10) were CT scanned with a Model 3 CT Calibration Phantom (Mindways). All data were processed in the Horos software (Version 4.0.0) and the regions of interest (ROIs) at each phalangeal base were delineated. Hounsfield Units (HU) were converted to BMD (mg/cm3) per the phantom framework. Descriptive statistics and repeated-measures ANOVA analyses were performed for each digit and corresponding phalangeal level (proximal, middle, distal). Inter-digital comparisons were performed at corresponding phalanx levels and intra-digital variations were analyzed within digits across phalangeal levels. Results: Mean BMD varied across digits and phalangeal levels. At the proximal phalanx base, the thumb and index fingers exhibited the highest values, whereas at the middle phalanx base the middle and ring fingers demonstrated the highest mean BMD values. At the distal phalanx base, the little finger demonstrated the highest BMD value, while the lowest value was observed at the distal phalanx of the index finger. Intra-digital analysis revealed distinct distribution patterns: BMD decreased distally in the thumb and index fingers, peaked at the middle phalanx in the middle and ring fingers, and was highest distally in the little finger. Repeated-measures ANOVA demonstrated statistically significant intra-digital differences in the thumb and index fingers, whereas no statistically significant inter-digital differences were observed across corresponding phalangeal levels. Conclusions: CT-based, phantom-calibrated BMD mapping at the bases of the phalanges demonstrates substantial intra-digital variability and descriptive inter-digital differences. These site-specific findings may provide additional information relevant to implant selection and preoperative planning for fixation in phalangeal fractures and tendon- or ligament-to-bone insertion injuries in hand surgery. Full article
(This article belongs to the Special Issue Musculoskeletal Imaging in Clinical Practice: From Qualitative Diagnosis to Quantitative Analysis)
►▼ Show Figures

Figure 1

Review

Jump to: Research

23 pages, 60721 KB  
Review
Malignant Transformation and Progression of Musculoskeletal Lesions with Imaging–Pathology Correlation—Part 2: Soft Tissue Lesions
by Hyang Sook Jeong, Seul Ki Lee, Jee-Young Kim, Changyoung Yoo and Min Wook Joo
Diagnostics 2026, 16(12), 1782; https://doi.org/10.3390/diagnostics16121782 - 9 Jun 2026
Viewed by 336
Abstract
Background/Objectives: Malignant transformation of soft tissue lesions is uncommon but represents a significant diagnostic challenge with substantial clinical consequences. This spectrum encompasses four interrelated processes but biologically distinct processes: (1) true malignant transformation of benign lesions; (2) dedifferentiation of low-grade or intermediate malignancies; [...] Read more.
Background/Objectives: Malignant transformation of soft tissue lesions is uncommon but represents a significant diagnostic challenge with substantial clinical consequences. This spectrum encompasses four interrelated processes but biologically distinct processes: (1) true malignant transformation of benign lesions; (2) dedifferentiation of low-grade or intermediate malignancies; (3) secondary malignancy arising in chronic inflammatory or non-neoplastic conditions; and (4) apparent progression related to tumor heterogeneity and sampling error. Although these four entities involve biologically distinct mechanisms, they are grouped under “malignant progression” for conceptual clarity. While this umbrella approach has limitations due to biological heterogeneity, this unified radiologic framework aims to supplement, rather than oversimplify, their distinct biological behaviors. Representative examples include neurofibroma and epidermal inclusion cyst among benign lesions; atypical lipomatous tumor/well-differentiated liposarcoma, dermatofibrosarcoma protuberans, and solitary fibrous tumor among lesions showing dedifferentiation or malignant progression; and chronic inflammatory or scar-related conditions and previously irradiated tissue associated with secondary malignancy. Some lesions that appear to progress during follow-up may represent initial underdiagnosis rather than true biologic progression. Methods: This narrative review summarizes current imaging features, underlying pathologic mechanisms, and clinical risk factors associated with these processes in soft tissue lesions. Particular emphasis is placed on radiologic–pathologic correlation and conditions prone to histopathologic misinterpretation. Results: Imaging red flags—including interval or rapid growth, deep fascial invasion, heterogeneous enhancement, perilesional edema, and necrosis—should raise concern for malignant progression across these categories. However, overlapping imaging features and sampling errors may result in pathologic misdiagnosis and delayed treatment. Particularly, atypical lipomatous tumors are frequently misdiagnosed as simple lipomas, while fibrosarcomas may be erroneously interpreted as aggressive fibromatosis. Advanced imaging and multidisciplinary review may help reduce diagnostic errors. Patients with predisposing factors such as genetic syndromes, chronic inflammation, prior burns, or previous radiation exposure warrant close surveillance. Conclusions: Accurate diagnosis of soft tissue lesions with true malignant transformation, dedifferentiation, or secondary malignancy—as well as recognition of diagnostic pitfalls—is essential for appropriate management. Integrated radiologic–pathologic assessment may help improve diagnostic accuracy and clinical decision-making in soft tissue oncology. Full article
(This article belongs to the Special Issue Musculoskeletal Imaging in Clinical Practice: From Qualitative Diagnosis to Quantitative Analysis)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop