Assessment of the impact of glioma diagnostic reclassification following the new 2016 WHO classification on a series of cases. / Evaluación del impacto del cambio diagnóstico de los gliomas aplicando la nueva clasificación de la OMS de 2016 sobre una serie de casos.

BACKGROUND AND OBJECTIVES: The aim of this project is to assess diagnostic reclassification based on molecular data over morphology in a series of glial tumours since the introduction of the 2016 WHO classification of brain tumours. MATERIALS AND METHODS: Retrospective review of glial tumours (oligodendrogliomas and astrocytomas) treated in our centre between January 2012 and June 2016 in which a review of diagnosis was performed when molecular studies were added. Statistical analysis included evaluation of variables of epidemiology, morphology and molecular data (mainly IDH mutation and 1p19q codeletion), diagnostic changes after new classification was considered, and clinical impact in cases of diagnostic reclassification. RESULTS: From a total of 147 glial tumours reviewed in our centre, molecular diagnosis was obtained in 74 cases (50.3%). Initial diagnosis changed in 23 cases (31%), and 20 (87%) of them had a prior histological diagnosis of oligodendroglioma (69.6% grade ii and 17.4% grade iii). Only 3 of these 23 cases diagnosis changed from astrocytoma to oligodendroglioma. Among reclassified tumours, there was a common molecular pattern, as findings showed mutant IDH in 16 cases (69.6%) and no codeletion in 20 cases (87%). According to the cell of origin, of the whole group of 27 oligodendrogliomas in our series (reclassified and non-reclassifed), 20 cases (74%) became astrocytomas, despite typical oligodendroglial morphology, due to absence of 1p19q codeletion. There was a trend for diagnosis reclassification in younger patients (<40 years), P=.065, mainly in those with a prior diagnosis of oligodendroglioma, with no statistical differences based on gender or clinical data. Besides, reclassification was more common among tumours with mutant IDH (69.6%), P=.003, than those with wild type IDH. In terms of survival, despite receiving different treatments, no significant changes were detected between reclassified and non-reclassified tumours after a mean follow-up of 16 months, partly related to lower grade of these lesions. CONCLUSIONS: Within the spectrum of the glial tumours treated in our institution, this new classification including molecular genetics over morphological data has provided marked diagnostic changes. These changes appear mainly in tumours previously diagnosed as oligodendrogliomas and in younger patients, with molecular patterns of mutant IDH and 1p19q codeletion. Although diagnosis reclassification may affect clinic, prognosis or therapeutic management of these tumours, deeper and prospective studies on these specific aspects are needed.

Causal probabilistic modeling for malignancy grading in pathology with explanations of dependency to the related histological features.

This work demonstrates that histological grading of brain tumors and astrocytomas can be accurately predicted and causally explained with the help of causal probabilistic models, also known as Bayesian networks (BN). Although created statistically, this allows individual identification of the grade of malignancy as an internal cause that has enabled the development of the histological features to their observed state. The BN models are built from data representing 794 cases of astrocytomas with their malignant grading and corresponding histological features. The computerized learning process is improved when pre-specified knowledge (from the pathologist) about simple dependency relations to the histological features is taken into account. We use the BN models for both grading and causal analysis. In addition, the BN models provide a causal explanation of dependency between the histological features and the grading. This can offer the biggest potential for choice of an efficient treatment, since it concentrates on the malignancy grade as the cause of pathological observations. The causal analysis shows that all ten histological features are important for the grading. The histological features are causally ordered, implying that features of first order are of higher priority, e.g. for the choice of treatment in order not to allow the malignancy to progress to a higher degree. Due to the explanations of feature relations, the causal analysis can be considered as a powerful complement to any malignancy classification tool and allows reproducible comparison of malignancy grading.

A comparative survival evaluation and assessment of interclassification concordance in adult supratentorial astrocytic tumors.

Classification and grading of astrocytic tumors has been the subject of several controversies and no universally accepted classification system is yet available. Nevertheless, acceptance of a common system is important for assessing prognosis as well as easy comparative evaluation and interpretation of the results of multi-center therapeutic trials. We report the results of a single center study on comparative survival evaluation along with assessment of inter-classification concordance in 102 cases of supratentorial astrocytic tumors in adults ((3) (3)16 years of age). Hematoxylin and eosin (H&E) stained slides of these 102 cases were reviewed independently by two pathologists and each case classified or graded according to four different classification systems viz. Kernohan, Daumas-Duport (SAM-A), TESTAST-268 and WHO. The histological grading was then correlated with the survival curves as estimated by the Kaplan-Meier method. The most important observation was that similar survival curves were obtained for any one grade of tumor by all the four classification systems. Fifty three of the 102 cases (51.9%) showed absolute grading concordance using all 4 classifications with maximum concordant cases belonging to grades 2 and 4. Intra-classification grade-wise survival analysis revealed a statistically significant difference between grade 2 and grades 3 or 4, but no difference between grades 3 and 4 in any of the classification systems. It is apparent from the results of this study that if specified criteria related to any of the classification systems is rigorously adhered to, it will produce comparable results. Hence, preferential adoption of any one classification system in practice will be guided by the relative ease of histologic feature value evaluation with maximum possible objectivity and reproducibility. We recommend the Daumas-Duport (SAM-A) system since it appears to be the simplest, most objectivized for practical application and highly reproducible with relative ease.

Assessment of the pathological grade of astrocytic gliomas using an MRI score.

To evaluate the usefulness of an MRI score for identifying tumour tissue characteristics, 41 histologically verified supratentorial astrocytic gliomas, including 13 low-grade astrocytomas (LGA) 14 anaplastic astrocytomas (AA) and 14 glioblastoma multiformes (GBM), were examined with a 0.5T superconductive MR imager. Nine MRI criteria were used: heterogeneity (HET), cyst formation or necrosis (CN), haemorrhage (HEM), crossing the midline (CM), oedema or mass effect (EM), border definition (BD), flow void (FV), degree (CE-D) and heterogeneity (CE-HET) of contrast enhancement; Gd-enhanced T1-weighted images were obtained in 32 cases (10 LGA, 10 AA, and 12 GBM). Each of the criteria was scored and analysed statistically. The mean values of LGA, AA and GBM were 0.45 +/- 0.31, 1.18 +/- 0.20, and 1.47 +/- 0.22, respectively. The MRI score increased with the pathological grades (P < 0.01-0.001). LGA had significantly lower values than AA in five (HET, CN, EM, BD, CE-D) of the nine criteria (55.6%) and lower values than GBM in all except HEM (88.9%). Three criteria (33.3%): HET, CN, and FV were significantly higher in GBM than AA. CE-D, HET, EM, CN, and CE-HET proved to be related to the pathological grade by a multiple regression analysis (P < 0.001).