Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma

Advances in diffuse glial tumors diagnosis

In recent decades, there have been significant advances in the diagnosis of diffuse gliomas, driven by the integration of novel technologies. These advancements have deepened our understanding of tumor oncogenesis, enabling a more refined stratification of the biological behavior of these neoplasms. This progress culminated in the fifth edition of the WHO classification of central nervous system (CNS) tumors in 2021. This comprehensive review article aims to elucidate these advances within a multidisciplinary framework, contextualized within the backdrop of the new classification. This article will explore morphologic pathology and molecular/genetics techniques (immunohistochemistry, genetic sequencing, and methylation profiling), which are pivotal in diagnosis, besides the correlation of structural neuroimaging radiophenotypes to pathology and genetics. It briefly reviews the usefulness of tractography and functional neuroimaging in surgical planning. Additionally, the article addresses the value of other functional imaging techniques such as perfusion MRI, spectroscopy, and nuclear medicine in distinguishing tumor progression from treatment-related changes. Furthermore, it discusses the advantages of evolving diagnostic techniques in classifying these tumors, as well as their limitations in terms of availability and utilization. Moreover, the expanding domains of data processing, artificial intelligence, radiomics, and radiogenomics hold great promise and may soon exert a substantial influence on glioma diagnosis. These innovative technologies have the potential to revolutionize our approach to these tumors. Ultimately, this review underscores the fundamental importance of multidisciplinary collaboration in employing recent diagnostic advancements, thereby hoping to translate them into improved quality of life and extended survival for glioma patients.

The T2-FLAIR mismatch sign in oncologic neuroradiology: History, current use, emerging data, and future directions

The T2-Fluid-Attenuated Inversion Recovery (T2-FLAIR) mismatch sign is a radiogenomic marker that is easily discernible on preoperative conventional MR imaging. Application of strict criteria (adult population, cerebral hemisphere location, and classic imaging morphology) permits the noninvasive preoperative diagnosis of isocitrate dehydrogenase (IDH)-mutant 1p/19q-non-codeleted diffuse astrocytoma with near-perfect specificity, albeit with variably low sensitivity. This leads to improved preoperative planning and patient counseling. More recent research has shown that the application of less strict criteria compromises the near-perfect specificity of the sign but remains adequate for ruling out IDH-wildtype (glioblastoma) phenotype, which bears a far grimmer prognosis compared to IDH-mutant diffuse astrocytic disease. In this review, we elaborate on the various definitions of the T2-FLAIR mismatch sign present in the literature, illustrate these with images obtained at a comprehensive cancer center, discuss the potential of the mismatch sign for application to certain pediatric-type brain tumors, namely dysembryoplastic neuroepithelial tumor and diffuse midline glioma, and elaborate upon the clinical, histologic, and molecular associations of the T2-FLAIR mismatch sign as recognized to date. Finally, the sign's correlates in diffusion- and perfusion-weighted imaging are presented, and opportunities to further maximize the diagnostic and prognostic applications of the sign in the context of the 2021 revision of the WHO Classification of Central Nervous System Tumors are discussed.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium

PURPOSE

While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas.

METHODS

Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS).

RESULTS

One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS.

CONCLUSION

Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Importance of Age and Noncontrast-Enhancing Tumor as Biomarkers for Isocitrate Dehydrogenase-Mutant Glioblastoma: A Multicenter Study

PURPOSE

This study aimed to investigate the most useful clinical and magnetic resonance imaging (MRI) parameters for differentiating isocitrate dehydrogenase (IDH)-mutant and -wildtype glioblastomas in the 2016 World Health Organization Classification of Tumors of the Central Nervous System.

METHODS

This multicenter study included 327 patients with IDH-mutant or IDH-wildtype glioblastoma in the 2016 World Health Organization classification who preoperatively underwent MRI. Isocitrate dehydrogenase mutation status was determined by immunohistochemistry, high-resolution melting analysis, and/or IDH1/2 sequencing. Three radiologists independently reviewed the tumor location, tumor contrast enhancement, noncontrast-enhancing tumor (nCET), and peritumoral edema. Two radiologists independently measured the maximum tumor size and mean and minimum apparent diffusion coefficients of the tumor. Univariate and multivariate logistic regression analyses with an odds ratio (OR) were performed.

RESULTS

The tumors were IDH-wildtype glioblastoma in 306 cases and IDH-mutant glioblastoma in 21. Interobserver agreement for both qualitative and quantitative evaluations was moderate to excellent. The univariate analyses revealed a significant difference in age, seizure, tumor contrast enhancement, and nCET (P < 0.05). The multivariate analysis revealed significant difference in age for all 3 readers (reader 1, odds ratio [OR] = 0.960, P = 0.012; reader 2, OR = 0.966, P = 0.048; reader 3, OR = 0.964, P = 0.026) and nCET for 2 readers (reader 1, OR = 3.082, P = 0.080; reader 2, OR = 4.500, P = 0.003; reader 3, OR = 3.078, P = 0.022).

CONCLUSIONS

Age and nCET are the most useful parameters among the clinical and MRI parameters for differentiating IDH-mutant and IDH-wildtype glioblastomas.

MRI features predict tumor grade in isocitrate dehydrogenase (IDH)-mutant astrocytoma and oligodendroglioma

PURPOSE

Nearly all literature for predicting tumor grade in astrocytoma and oligodendroglioma pre-dates the molecular classification system. We investigated the association between contrast enhancement, ADC, and rCBV with tumor grade separately for IDH-mutant astrocytomas and molecularly-defined oligodendrogliomas.

METHODS

For this retrospective study, 44 patients with IDH-mutant astrocytomas (WHO grades II, III, or IV) and 39 patients with oligodendrogliomas (IDH-mutant and 1p/19q codeleted) (WHO grade II or III) were enrolled. Two readers independently assessed preoperative MRI for contrast enhancement, ADC, and rCBV. Inter-reader agreement was calculated, and statistical associations between MRI metrics and WHO grade were determined per reader.

RESULTS

For IDH-mutant astrocytomas, both readers found a stepwise positive association between contrast enhancement and WHO grade (Reader A: OR 7.79 [1.97, 30.80], p = 0.003; Reader B: OR 6.62 [1.70, 25.82], p = 0.006); both readers found that ADC was negatively associated with WHO grade (Reader A: OR 0.74 [0.61, 0.90], p = 0.002); Reader B: OR 0.80 [0.66, 0.96], p = 0.017), and both readers found that rCBV was positively associated with WHO grade (Reader A: OR 2.33 [1.35, 4.00], p = 0.002; Reader B: OR 2.13 [1.30, 3.57], p = 0.003). For oligodendrogliomas, both readers found a positive association between contrast enhancement and WHO grade (Reader A: OR 15.33 [2.56, 91.95], p = 0.003; Reader B: OR 20.00 [2.19, 182.45], p = 0.008), but neither reader found an association between ADC or rCBV and WHO grade.

CONCLUSIONS

Contrast enhancement predicts WHO grade for IDH-mutant astrocytomas and oligodendrogliomas. ADC and rCBV predict WHO grade for IDH-mutant astrocytomas, but not for oligodendrogliomas.

Conventional MRI features can predict the molecular subtype of adult grade 2-3 intracranial diffuse gliomas

Purpose

Molecular biomarkers are important for classifying intracranial gliomas, prompting research into correlating imaging with genotype (“radiogenomics”). A limitation of the existing radiogenomics literature is the paucity of studies specifically characterizing grade 2–3 gliomas into the three key molecular subtypes. Our study investigated the accuracy of multiple different conventional MRI features for genotype prediction.

Methods

Grade 2–3 gliomas diagnosed between 2007 and 2013 were identified. Two neuroradiologists independently assessed nine conventional MRI features. Features with better inter-observer agreement (κ ≥ 0.6) proceeded to consensus assessment. MRI features were correlated with genotype, classified as IDH-mutant and 1p/19q-codeleted (IDH^mut/1p19q^codel), IDH-mutant and 1p/19q-intact (IDH^mut/1p19q^int), or IDH-wildtype (IDH^wt). For IDH^wt tumors, additional molecular markers of glioblastoma were noted.

Results

One hundred nineteen patients were included. T2-FLAIR mismatch (stratified as > 50%, 25–50%, or < 25%) was the most predictive feature across genotypes (p < 0.001). All 30 tumors with > 50% mismatch were IDH^mut/1p19q^int, and all seven with 25–50% mismatch. Well-defined margins correlated with IDH^mut/1p19q^int status on univariate analysis (p < 0.001), but this related to correlation with T2-FLAIR mismatch; there was no longer an association when considering only tumors with < 25% mismatch (p = 0.386). Enhancement (p = 0.001), necrosis (p = 0.002), and hemorrhage (p = 0.027) correlated with IDH^wt status (especially “molecular glioblastoma”). Calcification correlated with IDH^mut/1p19q^codel status (p = 0.003). A simple, step-wise algorithm incorporating these features, when present, correctly predicted genotype with a positive predictive value 91.8%.

Conclusion

T2-FLAIR mismatch strongly predicts IDH^mut/1p19q^int even with a lower threshold of ≥ 25% mismatch and outweighs other features. Secondary features include enhancement, necrosis and hemorrhage (predicting IDH^wt, especially “molecular glioblastoma”), and calcification (predicting IDH^mut/1p19q^codel).

Gamma distribution model of diffusion MRI for evaluating the isocitrate dehydrogenase mutation status of glioblastomas

OBJECTIVE

To determine whether the γ distribution (GD) model of diffusion MRI is useful in the evaluation of the isocitrate dehydrogenase (IDH) mutation status of glioblastomas.

METHODS

12 patients with IDH-mutant glioblastomas and 54 patients with IDH-wildtype glioblastomas were imaged with diffusion-weighted imaging using 13 b-values from 0 to 1000 s/mm2. The shape parameter (κ) and scale parameter (θ) were obtained with the GD model. Fractions of three different areas under the probability density function curve (f1, f2, f3) were defined as follows: f1, diffusion coefficient (D) < 1.0×10-3 mm2/s; f2, D > 1.0×10-3 and <3.0×10-3 mm2/s; f3, D > 3.0 × 10-3 mm2/s. The GD model-derived parameters measured in gadolinium-enhancing lesions were compared between the IDH-mutant and IDH-wildtype groups. Receiver operating curve analyses were performed to assess the parameters' diagnostic performances.

RESULTS

The IDH-mutant group's f1 (0.474  ±  0.143) was significantly larger than the IDH-wildtype group's (0.347  ±  0.122, p = 0.0024). The IDH-mutant group's f2 (0.417  ±  0.131) was significantly smaller than the IDH-wildtype group's (0.504  ±  0.126, p = 0.036). The IDH-mutant group's f3 (0.109  ±  0.060) was significantly smaller than the IDH-wildtype group's (0.149  ±  0.063, p = 0.0466). The f1 showed the best diagnostic performance among the GD model-derived parameters with the area under the curve value of 0.753.

CONCLUSION

The GD model could well describe the pathological features of IDH-mutant and IDH-wildtype glioblastomas, and was useful in the differentiation of these tumors.

ADVANCES IN KNOWLEDGE

Diffusion MRI based on the γ distribution model could well describe the pathological features of IDH-mutant and IDH-wildtype glioblastomas, and its use enabled the significant differentiation of these tumors. The γ distribution model may contribute to the non-invasive identification of the IDH mutation status based on histological viewpoint.

Gyriform infiltration as imaging biomarker for molecular glioblastomas

BACKGROUND

Molecular glioblastomas (i.e. without the histological but with the molecular characteristics of IDH-wild-type glioblastoma) frequently lack contrast enhancement, which can wrongly lead to suspect a lower-grade glioma. Herein, we aimed to assess the diagnostic value of gyriform infiltration as an imaging marker for molecular glioblastomas.

METHODS

Two independent investigators reviewed the MRI scans from patients with newly diagnosed gliomas for the presence of a gyriform infiltration defined as an elective cortical hypersignal on MRI FLAIR sequence. Diagnostic test performance of this sign for the diagnosis of molecular glioblastoma were calculated.

RESULTS

A total of 426 patients were included, corresponding to 31 molecular glioblastoma, 294 IDH-wild-type glioblastoma, 50 IDH-mutant astrocytoma, and 51 IDH-mutant 1p19q-codeleted oligodendroglioma. A gyriform infiltration was observed in 16/31 (52%) molecular glioblastoma, 40/294 (14%) IDH-wild-type glioblastoma, and none of the IDH-mutant glioma. All the 56 gyriform-infiltration-positive tumors were IDH-wild-type and all but two had a TERT promoter mutation. The inter-rater agreement was good (κ = 0.69, p < 0.001). The sensitivity, specificity, positive predictive value and negative predictive value of the presence of a gyriform infiltration for the diagnosis of molecular glioblastoma were 52%, 90%, 29%, 96%, respectively. The median overall survival was better for gyriform-infiltration-negative patients compared to gyriform-infiltration-positive patients in the whole series and in patients with non-enhancing lesions (n = 95) (25.6 vs 16.9 months, p = 0.005 and 20.2 months vs not reached, p < 0.001).

CONCLUSION

Gyriform infiltration is a specific imaging marker of molecular glioblastomas that can help distinguishing these tumors from IDH-mutant lower-grade gliomas.

Predictive Accuracy of T2-FLAIR mismatch sign for the IDH-mutant, 1p/19q non-codeleted Low Grade Glioma: An updated Systematic Review and Meta-analysis

Background

The T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, has been considered a highly specific imaging biomarker of IDH-mutant, 1p/19q noncodeleted low-grade glioma. This systematic review and meta-analysis aimed to evaluate the diagnostic performance of T2-FLAIR mismatch sign for prediction of a patient with IDH-mutant, 1p/19q noncodeleted low-grade glioma, and identify the causes responsible for the heterogeneity across the included studies.

Methods

A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies reporting the relevant topic before November 17, 2020. The pooled sensitivity and specificity values with their 95% confidence intervals were calculated using bivariate random-effects modeling. Meta-regression analyses were also performed to determine factors influencing heterogeneity.

Results

For all the 10 included cohorts from 8 studies, the pooled sensitivity was 40% (95% confidence interval [CI] 28–53%), and the pooled specificity was 100% (95% CI 95–100%). In the hierarchic summary receiver operating characteristic curve, the difference between the 95% confidence and prediction regions was relatively large, indicating heterogeneity among the studies. Higgins I² statistics demonstrated considerable heterogeneity in sensitivity (I² = 83.5%) and considerable heterogeneity in specificity (I² = 95.83%). Among the potential covariates, it seemed that none of factors was significantly associated with study heterogeneity in the joint model. However, the specificity was increased in studies with all the factors based on the differences in the composition of the detailed tumors.

Conclusions

The T2-FLAIR mismatch sign is near-perfect specific marker of IDH mutation and 1p/19q noncodeletion.

The T2-FLAIR Mismatch Sign as an Imaging Indicator of IDH-Mutant, 1p/19q Non-Codeleted Lower Grade Gliomas: A Systematic Review and Diagnostic Accuracy Meta-Analysis

The study's objective was the evaluation of the diagnostic accuracy of the T2-FLAIR mismatch sign in terms of diagnosing IDH-mutant non-codeleted (IDHmut-Noncodel) lower grade gliomas (LGG) of the brain. We searched the MEDLINE, Scopus and Cochrane Central databases. The last database search was performed on 12 April 2021. Studies that met the following were included: MRI scan assessing the presence of T2-FLAIR mismatch sign, and available IDH mutation and 1p/19q codeletion status. The quality of studies was assessed using the QUADAS-2 tool. Twelve studies involving 14 cohorts were included in the quantitative analysis. The diagnostic odds ratio [DOR (95% confidence interval; CI)] was estimated at 34.42 (20.95, 56.56), P_z < 0.01. Pooled sensitivity and specificity (95% CI) were estimated at 40% (31-50%; P_z = 0.05) and 97% (93-99%; P_z < 0.01), respectively. The likelihood ratio (LR; 95% CI) for a positive test was 11.39 (6.10, 21.29; P_z < 0.01) and the LR (95% CI) for a negative test was 0.40 (0.24, 0.65; P_z < 0.01).The T2-FLAIR mismatch sign is a highly specific biomarker for the diagnosis of IDHmut-Noncodel LGGs. However, the test was found positive in some other tumors and had a high number of false negative results. The diagnostic accuracy of the mismatch sign might be improved when combined with further imaging parameters.