Crosslinking MRI with Histopathology: Cross-Sectional Analysis to Assess the Effectiveness in the Identification of Benign and Malignant Tumors
DOI:
https://doi.org/10.31580/pjmls.v7i3.3144Keywords:
Benign pathology on the orbit, Diagnostic reality, Histopathological examination, Magnetic resonance imaging, Orbital massesAbstract
Background: Orbital masses including benign and malignant tumors are still an important diagnostic and therapeutic problem. Magnetic Resonance Imaging MRI has played a crucial role in the non-invasive assessment of these lesions, on account of its better soft tissue resolution and planar detail. The association between MRI and histopathological characteristics is still vital in reaching the correct management decisions.
Objective: In this study, MRI was assessed for its ability to diagnose the location of orbital masses specifically distinguishing between malignant and benign forms of tumors histopathological results were used as a standard of reference.
Methods: After study approval, this cross-sectional prospective study (June- November 2022) was done inter-collaboratively at Teaching Hospital, University of Lahore, Shalimar Hospital Lahore in affiliation with private medical diagnostic centers in Lahore. Using non-probability sequential sampling technique, 145 patients diagnosed with clinical symptoms pointing at orbital mass, who were to undertake surgery or biopsy, were selected. MRI scans were done using a 1.5 enhanced MR machine. The overall accuracy of MRI in diagnosing the orbital masses was assessed using the following parameters; sensitivity, specificity, PPV, NPV, and diagnostic accuracy all in comparison to histopathological prognostications.
Results: While 145 admitted patients were involved in the study, 55.2% of the patients were females while the remainder (44.8%) were male, and the patient ages were mostly 18-30 years (87.6%). MRI successfully detected 77.2 percent of cancer cases as malignant, and 22.8 percent as benign, whereas histopathological examination revealed 83.4 percent as malignant, and 16.6 percent as benign. Diagnostic performance assessment of MRI for benign masses revealed 81.82% sensitivity, 96.43% specificity, 87.10% of PPV, 94.74% of NPV, and an overall 93.10% accuracy. MRI in malignant masses showed sensitivity 90.16%, specificity 86.90%, PPV 83.33%, NPV 92.41% and diagnostic efficiency 88.28%.
Conclusion: In this study, high diagnostic accuracy is shown for MRI in distinguishing benign from malignant orbital masses, but this study is limited by its single center design and a relatively homogeneous patient population, not allowing generalization of these results. These findings need further studies across different centers with different demographics to be confirmed and the applicability of MRI diagnostics to further be improved in the settings of other clinical teams.
References
Lee MJ, Verma R, Hamilton BE, Pettersson D, Choi D, Kim ES, Korn BS, Kikkawa DO, Rosenbaum JT. The utility of orbital imaging in the evaluation of orbital disease. Plos one. 30;19(8):e0308528.
Luo S, Sha Y, Wu J, Lin N, Pan Y, Zhang F, Huang W. Differentiation of malignant from benign orbital tumours using dual-energy CT. Clinical Radiology. 2022;77(4):307-13.
Tanenbaum RE, Lobo R, Kahana A, Wester ST. Advances in magnetic resonance imaging of orbital disease. Canadian Journal of Ophthalmology. 2022;57(4):217-27.
Samad A, Shoukat S, Nisar P, Bibi A, Tabassum S, Aleem SA. Diagnostic Accuracy of MRI in Detecting Orbital Masses Keeping Histopathology as Gold Standard. Journal of Health and Rehabilitation Research. 2024;4(1):1148-52.
Castelnuovo P, Lambertoni A, Sileo G, Valentini M, Karligkiotis A, Battaglia P, Turri-Zanoni M. Critical review of multidisciplinary approaches for managing sinonasal tumors with orbital involvement. Acta Otorhinolaryngologica Italica. 2021;41(2 Suppl 1): S76.
Mukherjee B, Backiavathy V, Umadevi C, Noronha OV. Radiopathological Correlation in Orbital Lesions. Middle East African Journal of Ophthalmology. 2023;30(2):98-102.
Ang T, Juniat V, Patel S, Selva D. Evaluation of orbital lesions with DCE-MRI: a literature review. Orbit. 2024;43(3):408-16.
Bacorn C, Gokoffski KK, Lin LK. Clinical correlation recommended: accuracy of clinician versus radiologic interpretation of the imaging of orbital lesions. Orbit. 2021;40(2):133-7.
Zhang H, Lu T, Liu Y, Jiang M, Wang Y, Song X, Fan X, Zhou H. Application of quantitative MRI in thyroid eye disease: imaging techniques and clinical practices. Journal of Magnetic Resonance Imaging. 2024;60(3):827-47.
Gahrmann R, Gardeniers M. Orbital Imaging. InOculoplastic, Lacrimal and Orbital Surgery: The ESOPRS Textbook: Volume 2 2024 May 1 (pp. 151-177). Cham: Springer Nature Switzerland.
Asilturk M, Abdallah A, Sofuoglu E. Radiologic–Histopathologic correlation of adult spinal tumors: A retrospective study. Asian Journal of Neurosurgery. 2020;15(02):354-62.
SKhan SN, Sepahdari AR. Orbital masses: CT and MRI of common vascular lesions, benign tumors, and malignancies. Saudi Journal of Ophthalmology. 2012;26(4):373-83.
Pradeep T, Ravipati A, Melachuri S, Rajaii F, Campbell AA, Hodgson N, Zhang M, Pillai JJ, Nunery WR, Fu R. Utility of diffusion-weighted imaging to differentiate benign and malignant solid orbital tumours. Canadian Journal of Ophthalmology. 2023;58(5):455-60.
O'Shaughnessy E, Senicourt L, Mambour N, Savatovsky J, Duron L, Lecler A. Toward precision diagnosis: machine learning in identifying malignant orbital tumors with multiparametric 3 T MRI. Investigative Radiology. 2024;59(10):737-45.
Hunink MG, De Slegte RG, Hoogesteger MF. ROC analysis of the clinical, CT and MRI diagnosis of orbital space-occupying lesions. Orbit. 1989;8(3):173-87.
Shields JA, Bakewell B, Augsburger JJ, Flanagan JC. Classification and incidence of space-occupying lesions of the orbit: a survey of 645 biopsies. Archives of ophthalmology. 1984;102(11):1606-11.
Bastola P, Koirala S, Pokhrel G, Ghimire P, Adhikari RK. A clinico-histopathological study of orbital and ocular lesions; a multicenter study. Journal of Chitwan Medical College. 2013;3(2):40-4.
Vogele D, Sollmann N, Beck A, Haggenmüller B, Schmidt SA, Schmitz B, Kapapa T, Ozpeynirci Y, Beer M, Kloth C. Orbital tumors—clinical, radiologic and histopathologic correlation. Diagnostics. 2022;12(10):2376.
Kalemaki MS, Karantanas AH, Exarchos D, Detorakis ET, Zoras O, Marias K, Millo C, Bagci U, Pallikaris I, Stratis A, Karatzanis I. PET/CT and PET/MRI in ophthalmic oncology. International journal of oncology. 2020;56(2):417-29.
Bacorn C, Gokoffski KK, Lin LK. Clinical correlation recommended: accuracy of clinician versus radiologic interpretation of the imaging of orbital lesions. Orbit. 2021;40(2):133-7.
Ramesh S. Survey of 1264 patients with orbital tumors and simulating lesions. InFoundational Papers in Oculoplastics. Cham: Springer International Publishing. 2022;359-365.
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