Noninvasive differentiation of molecular subtypes of adult non-enhancing glioma using MRI perfusion and diffusion parameters

Evaluation of Key Molecular Markers in Adult Diffuse Gliomas Based on a Novel Combination of Diffusion and Perfusion MRI and MR Spectroscopy

BACKGROUND

Preoperative identification of isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status could help clinicians select the optimal therapy in patients with diffuse glioma. Although, the value of multimodal intersection was underutilized.

PURPOSE

To evaluate the value of quantitative MRI biomarkers for the identification of IDH mutation and 1p/19q codeletion in adult patients with diffuse glioma.

STUDY TYPE

Retrospective.

POPULATION

Two hundred sixteen adult diffuse gliomas with known genetic test results, divided into training (N = 130), test (N = 43), and validation (N = 43) groups.

SEQUENCE/FIELD STRENGTH

Diffusion/perfusion-weighted-imaging sequences and multivoxel MR spectroscopy (MRS), all 3.0 T using three different scanners.

ASSESSMENT

The apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) of the core tumor were calculated to identify IDH-mutant and 1p/19q-codeleted statuses and to determine cut-off values. ADC models were built based on the 30th percentile and lower, CBV models were built based on the 75th centile and higher (both in five centile steps). The optimal tumor region was defined and the metabolite concentrations of MRS voxels that overlapped with the ADC/CBV optimal region were calculated and added to the best-performing diagnostic models.

STATISTICAL TESTS

DeLong's test, diagnostic test, and decision curve analysis were performed. A P value <0.05 was considered to be statistically significant.

RESULTS

Almost all ADC models achieved good performance in identifying IDH mutation status, among which ADC_15th was the most valuable parameter (threshold = 1.186; Youden index = 0.734; AUC_train = 0.896). The differential power of CBV histogram metrics for predicting 1p/19q codeletion outperformed ADC histogram metrics, and the CBV_80th-related model performed best (threshold = 1.435; Youden index = 0.458; AUC_train = 0.724). The AUCs of ADC_15th and CBV_80th models in the validation set were 0.857 and 0.733. These models tended to improve after incorporation of N-acetylaspartate/total_creatine and glutamate-plus-glutamine/total_creatine, respectively.

DATA CONCLUSION

The intersection of ADC-, CBV-based histogram and MRS provide a reliable paradigm for identifying the key molecular markers in adult diffuse gliomas.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Rethinking extent of resection of contrast-enhancing and non-enhancing tumor: different survival impacts on adult-type diffuse gliomas in 2021 World Health Organization classification

OBJECTIVES

Extent of resection (EOR) of contrast-enhancing (CE) and non-enhancing (NE) tumors may have different impacts on survival according to types of adult-type diffuse gliomas in the molecular era. This study aimed to evaluate the impact of EOR of CE and NE tumors in glioma according to the 2021 World Health Organization classification.

METHODS

This retrospective study included 1193 adult-type diffuse glioma patients diagnosed between 2001 and 2021 (183 oligodendroglioma, 211 isocitrate dehydrogenase [IDH]-mutant astrocytoma, and 799 IDH-wildtype glioblastoma patients) from a single institution. Patients had complete information on IDH mutation, 1p/19q codeletion, and O6-methylguanine-methyltransferase (MGMT) status. Cox survival analyses were performed within each glioma type to assess predictors of overall survival, including clinical, imaging data, histological grade, MGMT status, adjuvant treatment, and EOR of CE and NE tumors. Subgroup analyses were performed in patients with CE tumor.

RESULTS

Among 1193 patients, 935 (78.4%) patients had CE tumors. In entire oligodendrogliomas, gross total resection (GTR) of NE tumor was not associated with survival (HR = 0.56, p = 0.223). In 86 (47.0%) oligodendroglioma patients with CE tumor, GTR of CE tumor was the only independent predictor of survival (HR = 0.16, p = 0.004) in multivariable analysis. GTR of CE and NE tumors was independently associated with better survival in IDH-mutant astrocytoma and IDH-wildtype glioblastoma (all ps < 0.05).

CONCLUSIONS

GTR of both CE and NE tumors may significantly improve survival within IDH-mutant astrocytomas and IDH-wildtype glioblastomas. In oligodendrogliomas, the EOR of CE tumor may be crucial in survival; aggressive GTR of NE tumor may be unnecessary, whereas GTR of the CE tumor is recommended.

CLINICAL RELEVANCE STATEMENT

Surgical strategies on contrast-enhancing (CE) and non-enhancing (NE) tumors should be reassessed considering the different survival outcomes after gross total resection depending on CE and NE tumors in the 2021 World Health Organization classification of adult-type diffuse gliomas.

KEY POINTS

The survival impact of extent of resection of contrast-enhancing (CE) and non-enhancing (NE) tumors was evaluated in adult-type diffuse gliomas. Gross total resection of both CE and NE tumors may improve survival in isocitrate dehydrogenase (IDH)-mutant astrocytomas and IDH-wildtype glioblastomas, while only gross total resection of the CE tumor improves survival in oligodendrogliomas. Surgical strategies should be reconsidered according to types in adult-type diffuse gliomas.

Identifying IDH-mutant and 1p/19q noncodeleted astrocytomas from nonenhancing gliomas: Manual recognition followed by artificial intelligence recognition

Background

The T2-FLAIR mismatch sign (T2FM) has nearly 100% specificity for predicting IDH-mutant and 1p/19q noncodeleted astrocytomas (astrocytomas). However, only 18.2%-56.0% of astrocytomas demonstrate a positive T2FM. Methods must be considered for distinguishing astrocytomas from negative T2FM gliomas. In this study, positive T2FM gliomas were manually distinguished from nonenhancing gliomas, and then a support vector machine (SVM) classification model was used to distinguish astrocytomas from negative T2FM gliomas.

Methods

Nonenhancing gliomas (regardless of pathological type or grade) diagnosed between January 2022 and October 2022 (N = 300) and November 2022 and March 2023 (N = 196) will comprise the training and validation sets, respectively. Our method for distinguishing astrocytomas from nonenhancing gliomas was examined and validated using the training set and validation set.

Results

The specificity of T2FM for predicting astrocytomas was 100% in both the training and validation sets, while the sensitivity was 42.75% and 67.22%, respectively. Using a classification model of SVM based on radiomics features, among negative T2FM gliomas, the accuracy was above 85% when the prediction score was greater than 0.70 in identifying astrocytomas and above 95% when the prediction score was less than 0.30 in identifying nonastrocytomas.

Conclusions

Manual screening of positive T2FM gliomas, followed by the SVM classification model to differentiate astrocytomas from negative T2FM gliomas, may be a more effective method for identifying astrocytomas in nonenhancing gliomas.

Glioma grading using multiparametric MRI: head-to-head comparison among dynamic susceptibility contrast, dynamic contrast-enhancement, diffusion-weighted images, and MR spectroscopy

PURPOSE

To assess the diagnostic accuracy of dynamic susceptibility contrast, dynamic contrast-enhancement, MR spectroscopy (MRS), and diffusion-weighted imaging for differentiating high-grade (HGGs) from low-grade gliomas (LGGs).

METHODS

Seventy-two patients (16 LGGs, 56 HGGs) with pathologically confirmed gliomas were retrospectively included. From three-dimensionally segmented tumor, histogram analyses of relative cerebral blood volume (rCBV), volume transfer constant (K^trans), and apparent diffusion coefficient (ADC) were performed. Choline-to-creatinine ratio (Cho/Cr) was calculated using MRS. Logistic regression analyses were performed to differentiate HGGs (grade ≥ 3) from LGGs (grade ≤ 2). Areas under the receiver operating characteristics curves (AUC) were plotted. Subgroup analysis was performed between IDH-wildtype glioblastomas and IDH-mutant astrocytomas. Pairwise Spearman's correlation coefficients (ρ) were computed.

RESULTS

HGGs had higher 95th percentile rCBV, K^trans and Cho/Cr (P < 0.01) than LGGs. AUC of 95th percentiles of rCBV and K^trans were 0.79 (95% CI, 0.67-0.91) and 0.74 (95% CI, 0.59-0.88), respectively. AUC of 5th percentile of ADC was 0.63 (95% CI, 0.48-0.79), and that of Cho/Cr was 0.67 (95% CI, 0.52-0.81). IDH-wildtype glioblastomas and IDH-mutant astrocytomas showed significantly different 95th percentile rCBV (P = 0.04) and K^trans (P < 0.01), with K^trans showing the highest AUC (0.73, 95% CI 0.57-0.89) in IDH status prediction. Moderate correlations were observed between 95th percentile rCBV and K^trans (ρ = 0.47), Cho/Cr (ρ = 0.40), and 5th percentile ADC (ρ = -0.36) (all P < 0.01).

CONCLUSIONS

The 95th percentile rCBV may be most helpful in discriminating HGGs from LGGs. The 95th percentile K^trans may aid predicting IDH status of diffuse gliomas.

Microvasculature Features Derived from Hybrid EPI MRI in Non-Enhancing Adult-Type Diffuse Glioma Subtypes

In this study, we used the vessel size imaging (VSI) MRI technique to characterize the microvasculature features of three subtypes of adult-type diffuse glioma lacking enhancement. Thirty-eight patients with confirmed non-enhancing glioma were categorized into three subtypes: Oligo (IDH-mut&1p/19q-codeleted), Astro (IDH-mut), and GBM (IDH-wt). The VSI technique provided quantitative maps of cerebral blood volume (CBV), microvasculature (µCBV), and vessel size for each patient. Additionally, tissue samples of 21 patients were histopathologically analyzed, and microvasculature features were quantified. Both MRI- and histology-derived features were compared across the three glioma subtypes with ANOVA or Kruskal–Wallis tests. Group averages of CBV, μCBV, and vessel size were significantly different between the three glioma subtypes (p < 0.01). Astro (IDH-mut) had a significantly lower CBV and µCBV compared to Oligo (IDH-mut&1p/19q-codeleted) (p = 0.004 and p = 0.001, respectively), and a higher average vessel size compared to GBM (IDH-wt) (p = 0.01). The histopathological analysis showed that GBM (IDH-wt) possessed vessels with more irregular shapes than the two other subtypes (p < 0.05). VSI provides a good insight into the microvasculature characteristics of the three adult-type glioma subtypes even when lacking enhancement. Further investigations into the specificity of VSI to differentiate glioma subtypes are thus warranted.

Visualising spatial heterogeneity in glioblastoma using imaging habitats

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.

Correlation of T1- to T2-weighted signal intensity ratio with T1- and T2-relaxation time and IDH mutation status in glioma

The current study aimed to test whether the ratio of T1-weighted to T2-weighted signal intensity (T1W/T2W ratio: rT1/T2) derived from conventional MRI could act as a surrogate relaxation time predictive of IDH mutation status in histologically lower-grade gliomas. Strong exponential correlations were found between rT1/T2 and each of T1- and T2-relaxation times in eight subjects (rT1/T2 = 1.63exp^{-0.0005T1-relax} + 0.30 and rT1/T2 = 1.27exp^{-0.0081T2-relax} + 0.48; R² = 0.64 and 0.59, respectively). In a test cohort of 25 patients, mean rT1/T2 (mrT1/T2) was significantly higher in IDHwt tumors than in IDHmt tumors (p < 0.05) and the optimal cut-off of mrT1/T2 for discriminating IDHmt was 0.666-0.677, (AUC = 0.75, p < 0.05), which was validated in an external domestic cohort of 29 patients (AUC = 0.75, p = 0.02). However, this result was not validated in an external international cohort derived from TCIA/TCGA (AUC = 0.63, p = 0.08). The t-Distributed Stochastic Neighbor Embedding analysis revealed a greater diversity in image characteristics within the TCIA/TCGA cohort than in the two domestic cohorts. The failure of external validation in the TCIA/TCGA cohort could be attributed to its wider variety of original imaging characteristics.

Conventional MRI-Derived Biomarkers of Adult-Type Diffuse Glioma Molecular Subtypes: A Comprehensive Review

The introduction of molecular criteria into the classification of diffuse gliomas has added interesting practical implications to glioma management. This has created a new clinical need for correlating imaging characteristics with glioma genotypes, also known as radiogenomics or imaging genomics. Although many studies have primarily focused on the use of advanced magnetic resonance imaging (MRI) techniques for radiogenomics purposes, conventional MRI sequences remain the reference point in the study and characterization of brain tumors. A summary of the conventional imaging features of glioma molecular subtypes should be useful as a tool for daily diagnostic brain tumor management. Hence, this article aims to summarize the conventional MRI features of glioma molecular subtypes in light of the recent literature.