Diagnostic Accuracy of Magnetic Resonance Imaging in Detecting Malignancy in Musculoskeletal Tumors Taking Histopathology as Gold Standard
DOI:
https://doi.org/10.61919/qz59nj09Keywords:
Musculoskeletal tumors, Magnetic resonance imaging, Histopathology, Diagnostic accuracy, Sensitivity, Specificity, Oncology imagingAbstract
Background: Musculoskeletal tumors represent a diagnostic challenge due to overlapping clinical and imaging features, while histopathology remains invasive and resource intensive. Magnetic resonance imaging (MRI), with its superior soft-tissue contrast and multiplanar capabilities, is widely used for characterization and surgical planning, yet variability in diagnostic performance necessitates further validation across diverse populations. Objective: To evaluate the diagnostic accuracy of MRI in detecting malignancy in musculoskeletal tumors, using histopathology as the reference standard. Methods: In this prospective diagnostic accuracy study conducted at a tertiary-care radiology department in Peshawar, Pakistan, from June to November 2024, 97 consecutive patients aged 18–70 years with clinically suspected musculoskeletal tumors underwent MRI on 1.5T or 3T scanners followed by histopathological confirmation. Predefined MRI signal and enhancement criteria were applied to classify tumors as malignant or non-malignant. Diagnostic indices were derived from 2×2 contingency tables, and subgroup analyses were performed across demographic and clinical variables in accordance with STARD recommendations. Results: Histopathology confirmed malignancy in 56 cases (57.7%). MRI achieved a sensitivity of 92.9% (95% CI: 82.7–98.0), specificity of 82.9% (95% CI: 67.9–92.9), positive predictive value of 88.1%, negative predictive value of 89.5%, and overall diagnostic accuracy of 88.7%. Diagnostic performance was consistent across age, sex, body mass index, residence, and occupational strata. Conclusion: MRI demonstrates high diagnostic accuracy for differentiating malignant from benign musculoskeletal tumors and can serve as a reliable non-invasive adjunct to histopathology in global oncology practice. These findings support the integration of MRI into diagnostic pathways to reduce unnecessary biopsies and guide surgical decision-making, while multicenter research incorporating advanced sequences is warranted to further improve specificity and generalizability.
References
1. Tanaka K, Ozaki T. New TNM Classification (AJCC Eighth Edition) of Bone and Soft Tissue Sarcomas: JCOG Bone and Soft Tissue Tumor Study Group. J Clin Oncol. 2019;49(2):103-7.
2. Mirabello L, Troisi RJ, Savage SA. Osteosarcoma Incidence and Survival Rates from 1973 to 2004: Data from the Surveillance, Epidemiology, and End Results Program. Cancer. 2009;115(7):1531-43.
3. Esiashvili N, Goodman M, Marcus RB. Changes in Incidence and Survival of Ewing Sarcoma Patients Over the Past 3 Decades: Surveillance, Epidemiology, and End Results Data. J Pediatr Hematol Oncol. 2008;30(6):425-30.
4. Singla A, Geller DS. Musculoskeletal Tumors. Clinics. 2020;67(1):227-45.
5. Fritz B, Müller DA, Sutter R, Wurnig MC, Wagner MW, Pfirrmann CW, et al. Magnetic Resonance Imaging–Based Grading of Cartilaginous Bone Tumors: Added Value of Quantitative Texture Analysis. Radiology. 2018;289(3):663-72.
6. Lee YH. Efficiency Improvement in a Busy Radiology Practice: Determination of Musculoskeletal Magnetic Resonance Imaging Protocol Using Deep-Learning Convolutional Neural Networks. J Digit Imaging. 2018;31(4):604-10.
7. Sujlana P, Skrok J, Fayad LM. Review of Dynamic Contrast-Enhanced MRI: Technical Aspects and Applications in the Musculoskeletal System. J Magn Reson Imaging. 2018;47(4):875-90.
8. Yuceturk G, Sabah D, Kececi B, Kara AD, Yalcinkaya S. Prevalence of Bone and Soft Tissue Tumors. Acta Orthop Traumatol Turc. 2011;45(3):135-43.
9. Ali S, Maqsood S, Akhtar S, Hameed N, Ghaffar SA, Hussain M. Diagnostic Accuracy of Magnetic Resonance Imaging in Predicting Malignancy in Musculoskeletal Tumors Taking Histopathology as Gold Standard. Pak J Med Health Sci. 2021;15(7):1603-6.
10. Guirguis M, Sharan G, Wang J, Chhabra A. Diffusion-Weighted MR Imaging of Musculoskeletal Tissues: Incremental Role Over Conventional MR Imaging in Bone, Soft Tissue, and Nerve Lesions. BJR Open. 2022;4(1):20210077.
11. Azad H, Ahmed A, Zafar I. X-Ray and MRI Correlation of Bone Tumors Using Histopathology as Gold Standard. Cureus. 2022;14(7):e27262.
12. Liaquat F, Alia N, Ayub M, Sikander M. Diagnostic Accuracy of Magnetic Resonance Imaging in Diagnosing Malignant Musculoskeletal Tumours, Taking Histopathology as Gold Standard. Indus J Biosci Res. 2025;3(6):114-7.
13. Shirin M, Rahman S, Chowdhury P, Showkat MS, Karki BP, Al Azad MS. Accuracy of Diffusion-Weighted Magnetic Resonance Imaging in Diagnosing Malignant Musculoskeletal Tumours. Bangabandhu Sheikh Mujib Med Univ J. 2024;17(2):e72248.
14. Boruah DK, Gogoi B, Patni RS, Sarma K, Hazarika K. Added Value of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Musculoskeletal Tumors: A Retrospective Study and Review of Literature. Cureus. 2021;13(1):e12645.
15. Ankita G, Mannan N, Jaipal U. Diagnostic Accuracy of Contrast-Enhanced Magnetic Resonance Imaging in Bone Tumors and Its Association with Surgical Findings Assuming Histopathological Findings as Gold Standard. Int J Sci Res. 2018;6(1):56-61.
16. Hazarika M, Bhuyan RK, Bhuyan R. How Accurate is MRI in Prediction of Musculoskeletal Tumors: A Prospective Evaluation. Int J Biomed Res. 2015;6(12):942-6.
17. Hassan S, Khan MT, Ghafoor M, Raman R, Aslam N, Mumtaz A, et al. Diagnostic Accuracy of Magnetic Resonance Imaging in Detecting Parametrial Invasion in Cervical Cancer Patients, Taking Histopathology as the Gold Standard. J Soc Obstet Gynaecol Pak. 2024;14(2):102-7.
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Copyright (c) 2025 Tasleem Khan, Naila Tamkeen, Faryal Basheer, Ambreen Khan (Author)
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