Improving the utility of 1H-MRS for the differentiation of glioma recurrence from radiation necrosis

Abstract

Proton magnetic resonance spectroscopy (H-MRS) has shown promise in distinguishing recurrent high-grade glioma from posttreatment radiation effect (PTRE). The purpose of this study was to establish objective H-MRS criteria based on metabolite peak height ratios to distinguish recurrent tumor (RT) from PTRE. A retrospective analysis of magnetic resonance imaging andH-MRS data was performed. Spectral metabolites analyzed included N-acetylaspartate, choline (Cho), creatine (Cr), lactate (Lac), and lipids (Lip). Quantitative H-MRS criteria to differentiate RT from PTRE were identified using 81 biopsy-matched spectral voxels. A receiver operating characteristic curve analysis was conducted for all metabolite ratio combinations with the pathology diagnosis as the classification variable. Forward discriminant analysis was used to identify ratio variables that maximized the correct classification of RT versus PTRE. Our results were applied to 205 records without biopsy-matched voxels to examine the percent agreement between our criteria and the radiologic diagnoses. Five ratios achieved an acceptable balance [area under the curve (AUC) ≥ 0.700] between sensitivity and specificity for distinguishing RT from PTRE, and each ratio defined a criterion for diagnosing RT. The ratios are as follows: Cho/Cr> 1.54 (sensitivity 66%, specificity 79%), Cr/Cho ≤ 0.63 (sensitivity 65%, specificity 79%), Lac/Cho ≤ 2.67 (sensitivity 85%, specificity 58%), Lac/Lip ≤ 1.64 (sensitivity 54%, specificity 95%), and Lip/Lac > 0.58 (sensitivity 56%, specificity 95%). Application of our ratio criteria in prospective studies may offer an alternative to biopsy or visual spectral pattern recognition to distinguish RT from PTRE in patients with gliomas.

Noninvasive Prediction of TERT Promoter Mutations in High‐Grade Glioma by Radiomics Analysis Based on Multiparameter MRI

“…MRS is a noninvasive MR-based imaging technique that provides data on cellular metabolism. Plenty of published studies have confirmed that MRS can not only improve the diagnostic accuracy of glioma, grade the tumor, but also identify the radioactive necrosis and recurrence and predict survival rate [34]. There was a strong connection between the Cho/Cr and Lac and TERTm in our study.…”

“…Though Lip peak was verified to be associated with the activity of tumor necrosis [38], there was no predictive value demonstrated in our research, which may be due to the Lip peak Applying radiomics nomogram for prediction, the probability of TERT promoter mutation was close to 0.9. BioMed Research International being more sensitive to the placement of voxels, thus affecting the definitive results [34]. Therefore, it is necessary to conduct a further study on the Lip feature for predicting TERT promoter mutations.…”

Cancer metabolism in a snapshot: MRS(I)

“…The problem of imbalanced classes has also been tackled with the use of AdaBoost . Supervised pattern recognition techniques such as support vector machines, linear discriminant analysis or several different algorithms, and classifier fusion, are also used in the latest literature, mainly for diagnostic questions. These methodologies are, generally too sophisticated to be put in practice by purely clinical groups, and when methodologies are tested the norm is availability of very small datasets, although there are exceptions such as Reference 113 or 109.…”

“…On the other hand, groups from clinical centres tend to use simpler approaches on larger series of patients from one clinical setting. In Reference , Crain et al measured five peak heights with ImageJ directly over the image provided by the scanner software, to apply a linear discriminant classifier on SPSS, testing different ratio combinations, to differentiate between post‐radiation effects and recurrence in gliomas, however with low success. In Reference , principal component analysis, a feature extraction method, is used to successfully visually distinguish one genetically different type of medulloblastoma of the four already accepted existing subtypes .…”

Lack of choline elevation on proton magnetic resonance spectroscopy in grade I–III gliomas

“…Proton magnetic resonance spectroscopy ( 1 H MRS) allows noninvasive assessment of metabolic alterations within a tissue of interest. 1,2 A number of studies [3][4][5][6][7][8][9] have reported the utility of 1 H MRS for studying brain tumor metabolism. These studies have reported promising results in evaluation of glioma grade, identification of glioma genotypes, differentiation of neoplasm types, differentiation of recurrent tumors from radiation injury, and assessment of the effect of whole brain radiation therapy on normal brain parenchyma in patients with metastases.…”