Researchers from the Indian Institute of Technology, Hyderabad, have developed an Artificial Intelligence-based tool that enables cancer specialists to diagnose and analyse brain tumours without relying on invasive procedures like a surgical biopsy. The ground-breaking computational platform, named RadGLO, extracts crucial genetic-level insights directly from a normal MRI scan, paving the way for personalised, non-invasive treatment planning.
In the study, published in the prestigious Precision Oncology (October 2025) journal, the IIT Hyderabad researchers said that the AI tool has the potential to revolutionise brain tumour diagnosis, especially gliomas (common primary brain tumours).
At present, oncologists rely on standard brain MRI to locate a tumour. Subsequently, they conduct a surgical biopsy to understand the complexity and aggressiveness of the tumour.
While a biopsy is informative, it carries risks because of its invasive nature. The procedure required the surgeon to drill a hole in the skull to collect a small part of the suspected tumour for lab testing.
With advancements in computational technology, the field of radiomics has emerged as a non-invasive alternative that can extract high-dimensional quantitative information from MRI scans. These radiomic features are derived from tumour texture, shape, and intensity patterns that provide insights comparable to those obtained from genetic analyses. These features help in identifying tumour grade, assessing treatment response, and predicting survival outcomes.
The IIT-H team leveraged radiomics to come up with the unique platform. These radiomic features are proving to offer insights comparable to those obtained from full genetic analyses, helping to identify the tumour’s grade (aggressiveness), predict how a patient will respond to treatment, and forecast survival outcomes, researchers said.
As part of the study, the IIT-H researchers have developed RaSPr (Radiomic Survival Predictor) and RadGLO ((Glioma Radiomics Analysis Platform).
The RaSPr uses the radiomic features to sort patients into high-risk (poor survival) and low-risk (better survival) groups, allowing doctors to make informed decisions.
The RadGLO is an interactive web platform that allows doctors and researchers to find radiomic markers that can distinguish between dangerous high-grade and less aggressive low-grade gliomas.
Furthermore, RadGLO enables linking each subtle MRI feature to nearly 20,000 genes, helping scientists understand the tumour’s genetic basis for progression, the researchers in the study said.
The platform allows doctors to upload the patient’s MRI scan to receive automated risk predictions and detailed molecular/genetic correlations. The technology empowers the medical community to incorporate non-invasive techniques in cancer prognosis and paving the way for personalised treatment planning for brain tumour patients, the research team, comprising Kavita Kundal, Dr K Divya Rani, Vinodini D, Dr Neeraj Kumar, and Dr Rahul Kumar, said.
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