GRADING AND STAGING OF BRAIN TUMOR ON MRI AN ANALYTICAL EXAMINATION WITH HISTOPATHALOGICALCORRELATION: A DESCRIPTIVE CROSS-SECTIONAL STUDY

Authors

  • Sara Kamal Sarhad University of Science and Information Technology, Peshawar, Pakistan. Author
  • Ayesha Khan Sarhad University of Science and Information Technology, Peshawar, Pakistan. Author
  • Irsa Sikandar Ghazali Nursing College, Peshawar, Pakistan. Author
  • Waqas Ahmad Khyber Medical University Institute of Health Sciences, Swabi, Pakistan. Author
  • Muhammad Arif Khyber Medical University, Pakistan. Author
  • Musadiq Khan Sarhad University of Science and Information Technology, Peshawar, Pakistan. Author
  • Umer Majeed Sarhad  University  of Science and Information Technology, Peshawar, Pakistan Author

DOI:

https://doi.org/10.71000/dn2w7k73

Keywords:

Brain Neoplasms; Diagnostic Imaging; Histopathology; Magnetic Resonance Imaging; Neoplasm Grading; Neoplasm Staging; World Health Organization

Abstract

Background: Brain tumors remain a major contributor to neurological morbidity and mortality worldwide, with outcomes largely dependent on timely diagnosis and accurate grading. Tumor grading reflects cellular differentiation and biological aggressiveness, whereas staging evaluates anatomical extent and spread. Preoperative radiological assessment, particularly magnetic resonance imaging (MRI), plays a pivotal role in guiding clinical management. However, correlation between imaging characteristics and histopathological grading remains essential to validate non-invasive diagnostic reliability.

Objective: To evaluate the role of radiological imaging in the grading and staging of brain tumors and to determine its correlation with histopathological findings based on the World Health Organization (WHO) classification.

Methods: This descriptive cross-sectional study was conducted at selected tertiary care hospitals over a defined study period. A total of 50 patients with radiologically suspected primary brain tumors were enrolled using non-probability convenience sampling. Patients with incomplete imaging records or secondary metastatic lesions were excluded. Data were collected through structured proformas documenting demographic variables, tumor location, size, margins, contrast enhancement patterns, necrosis, peritumoral edema, and mass effect. MRI was the primary imaging modality, supplemented by computed tomography (CT) where clinically indicated. Histopathological grading was performed according to the WHO classification system (Grades I–IV) following surgical resection or biopsy. Statistical analysis was conducted using SPSS version 25. Descriptive statistics were calculated as frequencies and percentages, and imaging characteristics were compared with histopathological grades to determine correlation patterns.

Results: The study included 50 patients with a mean age of 44.2 ± 13.6 years; 28 (56%) were male and 22 (44%) were female. Supratentorial tumors accounted for 41 cases (82%), while 9 (18%) were infratentorial. Histopathological evaluation revealed 8 (16%) Grade I tumors, 10 (20%) Grade II tumors, 17 (34%) Grade III tumors, and 15 (30%) Grade IV tumors, indicating a predominance of high-grade lesions (64%). Irregular tumor margins were observed in 32 patients (64%), heterogeneous contrast enhancement in 29 (58%), central necrosis in 24 (48%), and significant peritumoral edema in 35 (70%). Among high-grade tumors (Grades III–IV), 26 of 32 cases (81.3%) demonstrated heterogeneous enhancement and 28 of 32 (87.5%) exhibited marked edema. In contrast, low-grade tumors (Grades I–II) more commonly presented with well-defined margins (12 of 18; 66.7%) and minimal or no enhancement (10 of 18; 55.6%). A strong concordance was observed between radiological grading indicators and histopathological diagnosis, supporting the predictive value of imaging characteristics in determining tumor aggressiveness.

Conclusion: Radiological imaging, particularly MRI, demonstrated substantial reliability in the preoperative grading and anatomical assessment of brain tumors. Imaging features such as enhancement pattern, necrosis, and peritumoral edema showed strong correlation with histopathological grade, underscoring MRI’s critical role as a non-invasive tool for clinical decision-making, treatment planning, and prognostic evaluation.

Author Biographies

  • Sara Kamal, Sarhad University of Science and Information Technology, Peshawar, Pakistan.

    Lecturer, Radiology Technology, Sarhad Institute of Allied Health Sciences, Sarhad University of Science and Information Technology, Peshawar, Pakistan.

  • Ayesha Khan, Sarhad University of Science and Information Technology, Peshawar, Pakistan.

    Lecturer, Radiology Technology, Sarhad Institute of Allied Health Sciences, Sarhad University of Science and Information Technology, Peshawar, Pakistan.

  • Irsa Sikandar, Ghazali Nursing College, Peshawar, Pakistan.

    Lecturer, Ghazali Nursing College, Peshawar, Pakistan.

  • Waqas Ahmad, Khyber Medical University Institute of Health Sciences, Swabi, Pakistan.

    Demonstrator, Radiology, Khyber Medical University Institute of Health Sciences, Swabi, Pakistan.

  • Muhammad Arif, Khyber Medical University, Pakistan.

    Demonstrator, Radiology, Khyber Medical University, Pakistan.

  • Musadiq Khan, Sarhad University of Science and Information Technology, Peshawar, Pakistan.

    Academic Coordinator, Sarhad Institute of Allied Health Sciences, Sarhad University of Science and Information Technology, Peshawar, Pakistan.

  • Umer Majeed, Sarhad  University  of Science and Information Technology, Peshawar, Pakistan

    Assistant  Professor,  Sarhad  Institute  of  Allied  Health  Sciences,  Sarhad  University  of Science and Information Technology, Peshawar, Pakistan

References

Brain Neoplasms; Diagnostic Imaging; Histopathology; Magnetic Resonance Imaging; Neoplasm Grading; Neoplasm Staging; World Health Organization.

Wang KY, Chen MM, Lincoln CM. Adult primary brain neoplasm, including 2016 World Health Organization classification. Neuroimaging Clinics. 2021 Feb 1;31(1):121-38.

Osborn AG, Louis DN, Poussaint TY, Linscott LL, Salzman KL. The 2021 World Health Organization classification of tumors of the central nervous system: what neuroradiologists need to know. American Journal of Neuroradiology. 2022 Jul 1;43(7):928-37.

Gritsch S, Batchelor TT, Gonzalez Castro LN. Diagnostic, therapeutic, and prognostic implications of the 2021 World Health Organization classification of tumors of the central nervous system. Cancer. 2022 Jan 1;128(1):47-58.

Berger TR, Wen PY, Lang-Orsini M, Chukwueke UN. World Health Organization 2021 classification of central nervous system tumors and implications for therapy for adult-type gliomas: a review. JAMA oncology. 2022 Oct;8(10):1493-501.

Iv M, Bisdas S. Neuroimaging in the era of the evolving WHO Classification of Brain Tumors, From the AJR Special Series on Cancer Staging. American Journal of Roentgenology. 2021 Jul 27;217(1):3-15.

Ly KI, Wen PY, Huang RY. Imaging of central nervous system tumors based on the 2016 World Health Organization Classification. Neurologic clinics. 2020 Feb 1;38(1):95-113.

Kurokawa R, Kurokawa M, Baba A, Ota Y, Pinarbasi E, Camelo-Piragua S, Capizzano AA, Liao E, Srinivasan A, Moritani T. Major changes in 2021 World Health Organization classification of central nervous system tumors. Radiographics. 2022 Sep;42(5):1474-93.

Soni N, Ora M, Bathla G, Szekeres D, Desai A, Pillai JJ, Agarwal A. Meningioma: molecular updates from the 2021 World Health Organization classification of CNS tumors and imaging correlates. American Journal of Neuroradiology. 2025 Feb 1;46(2):240-50.

McNamara C, Mankad K, Thust S, Dixon L, Limback-Stanic C, D’Arco F, Jacques TS, Löbel U. 2021 WHO classification of tumours of the central nervous system: a review for the neuroradiologist. Neuroradiology. 2022 Oct;64(10):1919-50.

Miller DC. The world health organization classification of tumors of the central nervous system, 2021: a critical analysis. InAdvances and Technical Standards in Neurosurgery: Volume 46 2023 Jun 16 (pp. 1-21). Cham: Springer International Publishing.

Razek AA, Gamaleldin OA, Elsebaie NA. Peripheral nerve sheath tumors of head and neck: imaging-based review of World Health Organization classification. Journal of Computer Assisted Tomography. 2020 Nov 1;44(6):928-40.

Pons-Escoda A, Naval-Baudin P, Velasco R, Vidal N, Majós C. Imaging of lymphomas involving the CNS: an update-review of the full spectrum of disease with an emphasis on the World Health Organization classifications of CNS tumors 2021 and hematolymphoid tumors 2022. American Journal of Neuroradiology. 2023 Apr 1;44(4):358-66.

Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, Hawkins C, Ng HK, Pfister SM, Reifenberger G, Soffietti R. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro-oncology. 2021 Aug 1;23(8):1231-51.

Park YW, Vollmuth P, Foltyn‐Dumitru M, Sahm F, Ahn SS, Chang JH, Kim SH. The 2021 WHO classification for gliomas and implications on imaging diagnosis: part 1—Key points of the fifth edition and summary of imaging findings on Adult‐Type diffuse gliomas. Journal of Magnetic Resonance Imaging. 2023 Sep;58(3):677-89.

Martucci M, Russo R, Schimperna F, D’Apolito G, Panfili M, Grimaldi A, Perna A, Ferranti AM, Varcasia G, Giordano C, Gaudino S. Magnetic resonance imaging of primary adult brain tumors: state of the art and future perspectives. Biomedicines. 2023 Jan 26;11(2):364.

Ugga L, Franca RA, Scaravilli A, Solari D, Cocozza S, Tortora F, Cavallo LM, De Caro MD, Elefante A. Neoplasms and tumor-like lesions of the sellar region: imaging findings with correlation to pathology and 2021 WHO classification. Neuroradiology. 2023 Apr;65(4):675-99.

Srinivasan S, Bai PS, Mathivanan SK, Muthukumaran V, Babu JC, Vilcekova L. Grade classification of tumors from brain magnetic resonance images using a deep learning technique. Diagnostics. 2023 Mar 17;13(6):1153.

Park YW, Vollmuth P, Foltyn‐Dumitru M, Sahm F, Choi KS, Park JE, Ahn SS, Chang JH, Kim SH. The 2021 WHO classification for gliomas and implications on imaging diagnosis: part 3—summary of imaging findings on glioneuronal and neuronal tumors. Journal of Magnetic Resonance Imaging. 2023 Dec;58(6):1680-702.

Rigsby RK, Brahmbhatt P, Desai AB, Bathla G, Ebner BA, Gupta V, Vibhute P, Agarwal AK. Newly recognized CNS tumors in the 2021 World Health Organization classification: imaging overview with histopathologic and genetic correlation. American Journal of Neuroradiology. 2023 Apr 1;44(4):367-80.

Sejda A, Grajkowska W, Trubicka J, Szutowicz E, Wojdacz T, Kloc W, Iżycka-Świeszewska E. WHO CNS5 2021 classification of gliomas: A practical review and road signs for diagnosing pathologists and proper patho-clinical and neuro-oncological cooperation. Folia neuropathologica. 2022 Jan 1;60(2):137-52.

Gilanie G, Bajwa UI, Waraich MM, Anwar MW. Risk-free WHO grading of astrocytoma using convolutional neural networks from MRI images. Multimedia Tools and Applications. 2021 Jan;80(3):4295-306.

Pons-Escoda A, Majos C, Smits M, Oleaga L. Presurgical diagnosis of diffuse gliomas in adults: Post-WHO 2021 practical perspectives from radiologists in neuro-oncology units. Radiología (English Edition). 2024 May 1;66(3):260-77.

Downloads

Published

2025-12-15