Related factors with diagnostic yield and intracranial hemorrhagic complications in frame-based stereotactic biopsy. Review

Safety and efficacy of brain biopsy: Results from a single institution retrospective cohort study

Introduction

Brain biopsy provides important histopathological diagnostic information for patients with new intracranial lesions. Although a minimally invasive technique, previous studies report an associated morbidity and mortality between 0.6% and 6.8%. We sought to characterise the risk linked to this procedure, and to establish the feasibility of instigating a day-case brain biopsy pathway at our institution.

Materials and methods

This single-centre retrospective case series study included neuronavigation guided mini craniotomy and frameless stereotactic brain biopsies carried out between April 2019 and December 2021. Exclusion criteria were interventions performed for non-neoplastic lesions. Demographic data, clinical and radiological presentation, type of biopsy, histology and complications in the post-operative period were recorded.

Results

Data from 196 patients with a mean age of 58.7 years (SD+/-14.4 years) was analysed. 79% (n=155) were frameless stereotactic biopsies and 21% (n=41) neuronavigation guided mini craniotomy biopsies. Complications resulting in acute intracerebral haemorrhage and death, or new persistent neurological deficits were observed in 2% of patients (n=4; 2 frameless stereotactic; 2 open). Less severe complications or transient symptoms were noted in 2.5% of cases (n=5). 8 patients had minor haemorrhages in the biopsy tract with no clinical ramifications. Biopsy was non-diagnostic in 2.5% (n=5) of cases. Two cases were subsequently identified as lymphoma. Other reasons included insufficient sampling, necrotic tissue, and target error.

Discussion and conclusion

This study demonstrates that brain biopsy is a procedure with an acceptably low rate of severe complications and mortality, in line with previously published literature. This supports the development of day-case pathway allowing improved patient flow, reducing the risk of iatrogenic complications associated with hospital stay, such as infection and thrombosis.

MRI-Based Radiomics and Radiogenomics in the Management of Low-Grade Gliomas: Evaluating the Evidence for a Paradigm Shift

Low-grade gliomas (LGGs) are tumors that affect mostly adults. These neoplasms are comprised mainly of oligodendrogliomas and diffuse astrocytomas. LGGs remain vexing to current management and therapeutic modalities although they exhibit more favorable survival rates compared with high-grade gliomas (HGGs). The specific genetic subtypes that these tumors exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of an LGG pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). The introduction of radiomics as a high throughput quantitative imaging technique that allows for improved diagnostic, prognostic and predictive indices has created more interest for such techniques in cancer research and especially in neurooncology (MRI-based classification of LGGs, predicting Isocitrate dehydrogenase (IDH) and Telomerase reverse transcriptase (TERT) promoter mutations and predicting LGG associated seizures). Radiogenomics refers to the linkage of imaging findings with the tumor/tissue genomics. Numerous applications of radiomics and radiogenomics have been described in the clinical context and management of LGGs. In this review, we describe the recently published studies discussing the potential application of radiomics and radiogenomics in LGGs. We also highlight the potential pitfalls of the above-mentioned high throughput computerized techniques and, most excitingly, explore the use of machine learning artificial intelligence technologies as standalone and adjunct imaging tools en route to enhance a personalized MRI-based tumor diagnosis and management plan design.