Enhancing Brain Tumour Detection
Jörg Mauler, Philipp Lohmann, Andrew A. Maudsley, Sulaiman Sheriff, Moritz Hoevels, Anna-Katharina Meissner, Christina Hamisch, Anna Brunn, Martina Deckert, Christian P. Filss, Gabriele Stoffels, Jürgen Dammers, Maximillian I. Ruge, Norbert Galldiks, Felix M. Mottaghy, Karl-Josef Langen, and N. Jon Shah
9th November 2023
Precise tumour localisation through imaging is crucial for the diagnosis and treatment of brain tumours and is especially critical in challenging biopsy scenarios, such as those involving the brainstem.
In this context, although contrast-enhanced MRI is a common tool for brain tumour detection, its specificity for tumour tissue is limited. Amino acid PET, using radiolabelled amino acid is O-(2-[18F]fluoroethyl)-L-tyrosine (FET), on the other hand, has demonstrated significant ability to improve the diagnosis of brain tumours, especially with regard to biopsy guidance. Nevertheless, its accessibility remains restricted.
An alternative approach for the precise detection of cancerous tissue involves utilising metabolic markers, such as elevated choline (Cho) to N-acetyl aspartate (NAA) ratios, acquired through MR spectroscopic imaging (MRSI). However, the accuracies of the findings given by elevated Cho to NAA ratios in MRSI and FET uptake has not been widely compared.
Based on data acquired from 30 untreated patients with suspected glioma, the aim of this study was to assess the diagnostic accuracy of FET PET and MRSI, both individually and in combination, for the detection of tumour tissue. The gold standard for validation was histopathology. To validate the imaging findings, the findings of preoperative stereotactic biopsies were mapped into the imaging data via their coordinates.
After evaluating tissue from 88 biopsies and analysing FET PET and MRSI data from 20 areas on the healthy side of the brain, the study found that FET PET was the most accurate in identifying gliomas (area under the curve (AUC) 0.89 of the Receiver Operating Characteristic plot). Among MRS metabolites, Cho/NAA normalised to normal brain tissue was also effective (AUC 0.81). However, combining FET PET and normalised Cho/NAA was not found to improve accuracy.
This study underscores the value of supplementing MRI-based glioma delineation with FET PET, but in its absence, the Cho/NAA signal measured by MRSI offers a promising alternative.
Origional publication: Diagnostic Accuracy of MRSI and FET PET for Detecting Suspected Glioma - A Biopsy-Controlled Hybrid PET/MRI Study