# Accurate Paediatric Brain Tumour Classification Through Improved Quantitative Analysis of 1H MR Imaging and Spectroscopy

## TL;DR

This study improves pediatric brain tumor diagnosis by combining MRI and MRS data with noise suppression, achieving 100% accuracy in tumor classification.

## Contribution

A novel method combining noise-suppressed 1H-MRS and dMRI for accurate pediatric brain tumor classification is introduced.

## Key findings

- Combining dMRI and noise-suppressed 1H-MRS achieved 100% cross-validated accuracy in tumor classification.
- Key radiomic biomarkers like ADC fifth percentile and myo-inositol showed high diagnostic performance (mAUC > 0.95).
- The method outperformed single-modality approaches and non-noise-suppressed 1H-MRS.

## Abstract

Multimodality imaging is an emerging research topic in neuro‐oncology for its potential of being able to demonstrate tumours in a more comprehensive manner. Diffusion‐weighted magnetic resonance imaging (dMRI) and proton magnetic resonance spectroscopy (1H‐MRS) allow inferring tissue cellularity and biochemical properties, respectively. Combining dMRI and 1H‐MRS may provide more accurate diagnosis for paediatric brain tumours than only one modality. This retrospective study collected 1.5‐T clinical 1H‐MRS and dMRI from 32 patients to assess paediatric brain tumour classification with combined dMRI and 1H‐MRS. Specifically, spectral noise of 1H‐MRS was suppressed before calculating metabolite concentrations. Extracted radiomic features were apparent diffusion coefficient (ADC) histogram features through dMRI and metabolite concentrations through 1H‐MRS. These features were put together and then ranked according to the multiclass area under the curve (mAUC) and selected for tumour classification through machine learning. Tumours were precisely typed by combining noise‐suppressed 1H‐MRS and dMRI, and the cross‐validated accuracy was improved to be 100% according to naïve Bayes. The finally selected radiomic biomarkers, which showed the highest diagnostic ability, were ADC fifth percentile (mAUC = 0.970), myo‐inositol (mAUC = 0.952), combined glutamate and glutamine (mAUC = 0.853), total creatine (mAUC = 0.837) and glycine (mAUC = 0.815). The study indicates combining MR imaging and spectroscopy can provide better diagnostic performance than single‐modal imaging.

This study presents a method of quantitative analysis in 1.5‐T short‐T
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1H‐MRS and dMRI for paediatric brain tumour classification. Accurate diagnostic accuracy of ependymomas, medulloblastomas and pilocytic astrocytomas can be achieved through combining the two modalities, which is significantly better than only one modality or without 1H‐MRS noise suppression.