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A systematic pipeline for the objective comparison of whole-brain spectroscopic MRI with histology in biopsy specimens from grade III glioma.

ABSTRACT: The diagnosis, prognosis, and management of patients with gliomas are largely dictated by the pathological analysis of tissue biopsied from a selected region within the lesion. However, due to the heterogeneous and infiltrative nature of gliomas, identifying the optimal region for biopsy with conventional magnetic resonance imaging (MRI) can be quite difficult. This is especially true for low grade gliomas, which often are non-enhancing tumors. To improve the management of patients with these tumors, the field of neuro-oncology requires an imaging modality that can specifically identify a tumor's most anaplastic/aggressive region(s) for biopsy targeting. The addition of metabolic mapping using spectroscopic MRI (sMRI) to supplement conventional MRI could improve biopsy targeting and, ultimately, diagnostic accuracy. Here, we describe a pipeline for the integration of state-of-the-art, high-resolution whole-brain 3D sMRI maps into a stereotactic neuronavigation system for guiding biopsies in gliomas with nonenhancing components. We also outline a machine-learning method for automated histology analysis that generates normalized, quantitative metrics describing tumor infiltration in immunohistochemically-stained tissue specimens. As a proof of concept, we describe the combination of these two techniques in a small cohort of grade III glioma patients. In this work, we aim to set forth a systematic pipeline to stimulate histopathology-image validation of advanced MRI techniques, such as sMRI.

SUBMITTER: Cordova JS

PROVIDER: S-EPMC4968944 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PURPOSE:This prospective study evaluated the use of vascular, extracellular and restricted diffusion for cytometry in tumours (VERDICT) MRI to investigate the tissue microstructure in glioma. VERDICT-derived parameters were correlated with both histological features and tumour subtype and were also used to explore the peritumoural region. METHODS:Fourteen consecutive treatment-naïve patients (43.5 years?±?15.1 years, six males, eight females) with suspected glioma underwent diffusion-weighted imaging including VERDICT modelling. Tumour cell radius and intracellular and combined extracellular/vascular volumes were estimated using a framework based on linearisation and convex optimisation. An experienced neuroradiologist outlined the peritumoural oedema, enhancing tumour and necrosis on T2-weighted imaging and contrast-enhanced T1-weighted imaging. The same regions of interest were applied to the co-registered VERDICT maps to calculate the microstructure parameters. Pathology sections were analysed with semi-automated software to measure cellularity and cell size. RESULTS:VERDICT parameters were successfully calculated in all patients. The imaging-derived results showed a larger intracellular volume fraction in high-grade glioma compared to low-grade glioma (0.13?±?0.07 vs. 0.08?±?0.02, respectively; p?=?0.05) and a trend towards a smaller extracellular/vascular volume fraction (0.88?±?0.07 vs. 0.92?±?0.04, respectively; p?=?0.10). The conventional apparent diffusion coefficient was higher in low-grade gliomas compared to high-grade gliomas, but this difference was not statistically significant (1.22?±?0.13?×?10-3 mm2/s vs. 0.98?±?0.38?×?10-3 mm2/s, respectively; p?=?0.18). CONCLUSION:This feasibility study demonstrated that VERDICT MRI can be used to explore the tissue microstructure of glioma using an abbreviated protocol. The VERDICT parameters of tissue structure correlated with those derived on histology. The method shows promise as a potential test for diagnostic stratification and treatment response monitoring in the future. KEY POINTS:• VERDICT MRI is an advanced diffusion technique which has been correlated with histopathological findings obtained at surgery from patients with glioma in this study. • The intracellular volume fraction measured with VERDICT was larger in high-grade tumours compared to that in low-grade tumours. • The results were complementary to measurements from conventional diffusion-weighted imaging, and the technique could be performed in a clinically feasible timescale.

Project description:Due to the extremely intrinsic heterogeneity among glioma patients, the outcomes of these patients are tremendously different. Therefore, the exploitation of novel biomarker classification of glioma is vitally important for deep insight into the essence and predicting the prognosis of glioma. We aim to analyze the correlation between TP73 mRNA expression, DNA methylated alteration and the prognosis of WHO grade II/III glioma, utilizing bioinformatics to evaluate its significance as a risk-factor in predicting the prognosis of these glioma patients. The analysis found that TP73 expression was positively correlated with the grade of glioma, and showed a strong correlation with glioma molecular classification, which revealed significantly higher TP73 expression in IDH-wildtype than in IDH-mutant subtype of WHO grade II/III glioma. Cox regression analysis indicated that high expression of TP73 shared an independent high-risk factor impacting the prognosis of WHO grade II/III glioma. We discovered 8 DNA promoter methylation sites with prognostic significance, which were negatively associated with TP73 expression, and positively associated with beneficial overall survival (OS) and progression-free survival (PFS). Integrating with four independent glioma datasets, subsequent Meta-analysis verified that low expression of TP73 was closely related to favorable OS, especially in IDH-mutant subtype. Moreover, we found that 1p/19qCodel /TP73low subgroup shared the most favorable OS, 1p/19qNon-codel /TP73high subgroup suffered the worst OS. Meanwhile, the enrichment analysis of TP73-related differential mRNAs demonstrated that TP73 aberration in WHO grade II/III glioma might be closely related to cell cycle and P53 signaling pathways. Finally, TP73 expression of 53 glioma specimens was measured by qRT-PCR, which was consistent with the previous analytical result, and TP73 high-expression subgroup suffered worse PFS than TP73 low-expression subgroup. In summary, our funding supports that TP73 gene can perform as a reliable biomarker to evaluate the survival outcome of patients diagnosed with WHO grade II/III glioma.

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A systematic pipeline for the objective comparison of whole-brain spectroscopic MRI with histology in biopsy specimens from grade III glioma.

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