| REVIEW ARTICLE |
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| Year : 2022 | Volume
: 65
| Issue : 5 | Page : 99-110 |
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Evaluating neurosurgical biopsies for CNS tumor diagnoses: An algorithmic and pattern based approach
M Adelita Vizcaino, Aditya Raghunathan
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
Correspondence Address:
Aditya Raghunathan
Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First St SW, Rochester, MN 55905
USA
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijpm.ijpm_1081_21
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The 2016 and 2021 World Health Organization (WHO) Classifications of Tumors of the Central Nervous System (CNS) reflect the importance of integrating molecular analysis into CNS tumor diagnosis and classification, adding to the complexity of any surgical neuropathology practice. On the other hand, our evolving understanding of genomic alterations across the spectrum of CNS tumors highlights the importance of utilizing traditional histological and immunohistochemical approaches to first establish as accurate a diagnosis as possible. Such an approach is also essential to recognizing the most appropriate ancillary test(s) needed for accurate classification and grading of CNS tumors. Here, we present an algorithmic approach to be considered while evaluating surgical neuropathology biopsies, which includes a recognition of main histological patterns, and incorporates clinical and radiologic features, to assist with accurate diagnosis and optimal selection of subsequent ancillary testing.
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