Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes.

BACKGROUND AND PURPOSE: Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories. MATERIALS AND METHODS: We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status. RESULTS: For isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas, tumor size (hazard ratio, 3.82; 95% CI, 1.94-7.75; P < .001), number of involved lobes (hazard ratio, 1.70; 95% CI, 1.28-2.27; P < .001), hydrocephalus (hazard ratio, 4.43; 95% CI, 1.12-17.54; P = .034), midline shift (hazard ratio, 1.16; 95% CI, 1.03-1.30; P = .013), margins (P = .031), and contrast enhancement (hazard ratio, 0.34; 95% CI, 0.13-0.90; P = .030) were associated with overall survival. For IDH-mutant 1p/19q-codeleted lower-grade gliomas, tumor size (hazard ratio, 2.85; 95% CI, 1.06-7.70; P = .039) and ependymal extension (hazard ratio, 6.34; 95% CI, 1.07-37.59; P = .042) were associated with overall survival. CONCLUSIONS: MR imaging metrics offers prognostic information for patients with lower-grade gliomas within molecularly defined classes, with the greatest prognostic value for IDH wild-type lower-grade gliomas.

Retropharyngeal ectopic parathyroid adenoma versus lymph node: Problem solving with CT neck angiogram.

A 66-year-old female underwent preoperative evaluation for primary hyperparathyroidism. Ultrasound (US) neck and technetium (Tc)-99m-sestamibi planar scintigraphy were negative, but single photon emission computed tomography/computed tomography (SPECT/CT) demonstrated a tracer-avid retropharyngeal nodule compatible with parathyroid adenoma (PTA). A retrospective review of CT neck angiogram (CTA) and neck magnetic resonance imaging (MRI) performed 4 months earlier for stroke evaluation revealed arterial phase hyperenhancing retropharyngeal tissue, which had been dismissed as a nonpathological lymph node. "Polar vessel sign" seen in two-thirds of PTA was also present on retrospective review of the CTA. The concordant findings between SPECT/CT and CTA were indicative of a solitary undescended ectopic PTA in the retropharyngeal space, an uncommon location. A successful surgical cure was achieved after minimally invasive parathyroidectomy. This case highlights the retropharyngeal space as an important ectopic site of PTA, limitation of US, and Tc-99m-sestamibi planar scintigraphy in identifying retropharyngeal PTA. We also discuss the role of CT and MRI and the challenge in differentiating retropharyngeal PTA from a lymph node.

Molecular Subtype Classification in Lower-Grade Glioma with Accelerated DTI.

BACKGROUND AND PURPOSE: Image-based classification of lower-grade glioma molecular subtypes has substantial prognostic value. Diffusion tensor imaging has shown promise in lower-grade glioma subtyping but currently requires lengthy, nonstandard acquisitions. Our goal was to investigate lower-grade glioma classification using a machine learning technique that estimates fractional anisotropy from accelerated diffusion MR imaging scans containing only 3 diffusion-encoding directions. MATERIALS AND METHODS: Patients with lower-grade gliomas (n = 41) (World Health Organization grades II and III) with known isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status were imaged preoperatively with DTI. Whole-tumor volumes were autodelineated using conventional anatomic MR imaging sequences. In addition to conventional ADC and fractional anisotropy reconstructions, fractional anisotropy estimates were computed from 3-direction DTI subsets using DiffNet, a neural network that directly computes fractional anisotropy from raw DTI data. Differences in whole-tumor ADC, fractional anisotropy, and estimated fractional anisotropy were assessed between IDH-wild-type and IDH-mutant lower-grade gliomas with and without 1p/19q codeletion. Multivariate classification models were developed using whole-tumor histogram and texture features from ADC, ADC + fractional anisotropy, and ADC + estimated fractional anisotropy to identify the added value provided by fractional anisotropy and estimated fractional anisotropy. RESULTS: ADC (P = .008), fractional anisotropy (P < .001), and estimated fractional anisotropy (P < .001) significantly differed between IDH-wild-type and IDH-mutant lower-grade gliomas. ADC (P < .001) significantly differed between IDH-mutant gliomas with and without codeletion. ADC-only multivariate classification predicted IDH mutation status with an area under the curve of 0.81 and codeletion status with an area under the curve of 0.83. Performance improved to area under the curve = 0.90/0.94 for the ADC + fractional anisotropy classification and to area under the curve = 0.89/0.89 for the ADC + estimated fractional anisotropy classification. CONCLUSIONS: Fractional anisotropy estimates made from accelerated 3-direction DTI scans add value in classifying lower-grade glioma molecular status.

Extent of Surgical Resection in Lower-Grade Gliomas: Differential Impact Based on Molecular Subtype.

BACKGROUND AND PURPOSE: Diffuse lower-grade gliomas are classified into prognostically meaningful molecular subtypes. We aimed to determine the impact of surgical resection on overall survival in lower-grade glioma molecular subtypes. MATERIALS AND METHODS: For 172 patients with lower-grade gliomas (World Health Organization grade II or III), pre- and postsurgical glioma volumes were determined using a semiautomated segmentation software based on FLAIR or T2-weighted MR imaging sequences. The association of pre- and postsurgical glioma volume and the percentage of glioma resection with overall survival was determined for the entire cohort and separately for lower-grade glioma molecular subtypes based on isocitrate dehydrogenase (IDH) and 1p/19q status, after adjustment for age, sex, World Health Organization grade, chemotherapy administration, and radiation therapy administration. RESULTS: For the entire cohort, postsurgical glioma volume (hazard ratio, 1.80; 95% CI, 1.18-2.75; P = .006) and the percentage of resection (hazard ratio, 3.22; 95% CI, 1.79-5.82; P < .001) were associated with overall survival. For IDH-mutant 1p/19q-codeleted oligodendrogliomas, the percentage of resection (hazard ratio, 6.69; 95% CI, 1.57-28.46; P = .01) was associated with overall survival. For IDH-mutant 1p/19q-noncodeleted astrocytomas, presurgical glioma volume (hazard ratio, 3.20; 95% CI, 1.22-8.39; P = .018), postsurgical glioma volume (hazard ratio, 2.33; 95% CI, 1.32-4.12; P = .004), and percentage of resection (hazard ratio, 4.34; 95% CI, 1.74-10.81; P = .002) were associated with overall survival. For IDH-wild-type lower-grade gliomas, pre-/postsurgical glioma volume and percentage of resection were not associated with overall survival. CONCLUSIONS: The extent of surgical resection has a differential survival impact in patients with lower-grade gliomas based on their molecular subtype. IDH-mutant lower-grade gliomas benefit from a greater extent of surgical resection, with the strongest impact observed for IDH-mutant 1p/19q-noncodeleted astrocytomas.

Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas.

BACKGROUND AND PURPOSE: Isocitrate dehydrogenase (IDH)-mutant lower grade gliomas are classified as oligodendrogliomas or diffuse astrocytomas based on 1p/19q-codeletion status. We aimed to test and validate neuroradiologists' performances in predicting the codeletion status of IDH-mutant lower grade gliomas based on simple neuroimaging metrics. MATERIALS AND METHODS: One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. To validate the classification model, 2 different independent neuroradiologists analyzed a separate cohort of 106 institutional IDH-mutant lower grade gliomas. RESULTS: Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lower grade gliomas, (n = 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (κ = 0.56-0.79). CONCLUSIONS: We have validated a classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas.

Features of diffuse gliomas that are misdiagnosed on initial neuroimaging: a case control study.

PURPOSE: The neuroimaging diagnosis of diffuse gliomas can be challenging owing to their variable clinical and radiologic presentation. The purpose of this study was to identify factors that are associated with imaging errors in the diagnosis of diffuse gliomas. METHODS: A retrospective case-control analysis was undertaken. 18 misdiagnosed diffuse gliomas on initial neuroimaging (cases) and 108 accurately diagnosed diffuse gliomas on initial neuroimaging (controls) were collected. Clinical, pathological, and imaging metrics were tabulated for each patient. The tabulated metrics were compared between cases and controls to determine factors associated with misdiagnosis. RESULTS: Cases of misdiagnosed diffuse glioma (vs controls) were more likely to undergo initial triage as a stroke workup [OR 14.429 (95% CI 4.345, 47.915), p < 0.0001], were less likely to enhance [OR 0.283 (95% CI 0.098, 0.812), p = 0.02], were smaller (mean diameter 4.4 vs 6.0 cm, p = 0.0008), produced less midline shift (median midline shift 0.0 vs 2.0 mm, p = 0.003), were less likely to demonstrate necrosis [OR 0.156 (95% CI 0.034-0.713), p = 0.008], and were less likely to have IV contrast administered on the initial MRI [OR 0.100 (95% CI 0.020, 0.494), p = 0.008]. CONCLUSION: Several clinical and radiologic metrics are associated with diffuse gliomas that are missed or misdiagnosed on the initial neuroimaging study. Knowledge of these associations may aid in avoiding misinterpretation and accurately diagnosing such cases in clinical practice.