Literature DB >> 12498489

Neuropathological diagnostic accuracy.

M Murphy1, A Loosemore, I Ferrer, P Wesseling, P R Wilkins, B A Bell.   

Abstract

This study investigated variations in neuropathological diagnosis when histopathological slides are evaluated with access to all information pertinent to a case, compared with evaluation of H & E stained slides with only limited clinical information. The aim of the study is to evaluate the role of 'local' factors in reaching a definitive, neuropathological diagnosis. Each of 227 cases was reviewed by the local neuropathologist at one of three European centres with access to all clinical, radiological and histopathological data. Each case was also reviewed by a second, independent neuropathologist at another European unit, who was blinded to the local pathologist's diagnosis, and only had access to the age and sex of the patient and the location of the lesion. For the histopathological evaluation, initially he had access to H & E and GFAP stains only. Diagnoses were made using the WHO 2000 classification system and the two evaluations were classified into one of the following four categories: complete agreement; minor disagreement (not affecting treatment); minor disagreement (affecting treatment); complete disagreement. In 175 (77.1%) cases there was complete agreement between the two neuropathologists and in 18 (7.9%) cases there were non-treatment altering discrepancies in the diagnoses. Overall, there was disagreement which might potentially affect treatment in 34 (15%) of the cases. Histopathological diagnosis of the majority (85%) of brain tumours is accurate and uniform. However, histopathology is subject to a degree of interpretation. The availability of full, 'local', clinical information may be of considerable importance to the diagnostic process.

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Mesh:

Year:  2002        PMID: 12498489     DOI: 10.1080/0268869021000030267

Source DB:  PubMed          Journal:  Br J Neurosurg        ISSN: 0268-8697            Impact factor:   1.596


  7 in total

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2.  Neuroendoscopic management of posterior third ventricle and pineal region tumors: technique, limitation, and possible complication avoidance.

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Authors:  Silun Wang; Jinyuan Zhou
Journal:  J Comput Assist Tomogr       Date:  2012 Nov-Dec       Impact factor: 1.826

5.  Deep learning from multiple experts improves identification of amyloid neuropathologies.

Authors:  Daniel R Wong; Ziqi Tang; Nicholas C Mew; Sakshi Das; Justin Athey; Kirsty E McAleese; Julia K Kofler; Margaret E Flanagan; Ewa Borys; Charles L White; Atul J Butte; Brittany N Dugger; Michael J Keiser
Journal:  Acta Neuropathol Commun       Date:  2022-04-28       Impact factor: 7.578

6.  Convolutional neural networks to predict brain tumor grades and Alzheimer's disease with MR spectroscopic imaging data.

Authors:  Jacopo Acquarelli; Twan van Laarhoven; Geert J Postma; Jeroen J Jansen; Anne Rijpma; Sjaak van Asten; Arend Heerschap; Lutgarde M C Buydens; Elena Marchiori
Journal:  PLoS One       Date:  2022-08-24       Impact factor: 3.752

7.  Genetic alterations in glioma.

Authors:  Linda B C Bralten; Pim J French
Journal:  Cancers (Basel)       Date:  2011-03-07       Impact factor: 6.639

  7 in total

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