Clinical and Magnetic Resonance Imaging Radiomics-Based Survival Prediction in Glioblastoma Using Multiparametric Magnetic Resonance Imaging.

INTRODUCTION: Survival prediction in glioblastoma remains challenging, and identification of robust imaging markers could help with this relevant clinical problem. We evaluated multiparametric magnetic resonance imaging-derived radiomics to assess prediction of overall survival (OS) and progression-free survival (PFS). METHODOLOGY: A retrospective, institutional review board-approved study was performed. There were 93 eligible patients, of which 55 underwent gross tumor resection and chemoradiation (GTR-CR). Overall survival and PFS were assessed in the entire cohort and the GTR-CR cohort using multiple machine learning pipelines. A model based on multiple clinical variables was also developed. Survival prediction was assessed using the radiomics-only, clinical-only, and the radiomics and clinical combined models. RESULTS: For all patients combined, the clinical feature-derived model outperformed the best radiomics model for both OS (C-index, 0.706 vs 0.597; P < 0.0001) and PFS prediction (C-index, 0.675 vs 0.588; P < 0.001). Within the GTR-CR cohort, the radiomics model showed nonstatistically improved performance over the clinical model for predicting OS (C-index, 0.638 vs 0.588; P = 0.4). However, the radiomics model outperformed the clinical feature model for predicting PFS in GTR-CR cohort (C-index, 0.641 vs 0.550; P = 0.004). Combined clinical and radiomics model did not yield superior prediction when compared with the best model in each case. CONCLUSIONS: When considering all patients, regardless of therapy, the radiomics-derived prediction of OS and PFS is inferior to that from a model derived from clinical features alone. However, in patients with GTR-CR, radiomics-only model outperforms clinical feature-derived model for predicting PFS.

AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.

PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-based three-class classification of glioblastoma (GBM), intracranial metastatic disease (IMD) and primary CNS lymphoma (PCNSL). METHODOLOGY: Retrospective analysis included 502 cases for training (208 GBM, 67 PCNSL and 227 IMD), with external validation on 86 cases (27:27:32). Multiparametric MRI images (T1W, T2W, FLAIR, DWI and T1-CE) were co-registered, resampled, denoised and intensity normalized, followed by semiautomatic 3D segmentation of the enhancing tumor (ET) and peritumoral region (PTR). Model performance was assessed using several ML pipelines and 3D-convolutional neural networks (3D-CNN) using sequence specific masks, as well as combination of masks. All pipelines were trained and evaluated with 5-fold nested cross-validation on internal data followed by external validation using multi-class AUC. RESULTS: Two ML models achieved similar performance on test set, one using T2-ET and T2-PTR masks (AUC: 0.885, 95% CI: [0.816, 0.935] and another using T1-CE-ET and FLAIR-PTR mask (AUC: 0.878, CI: [0.804, 0.930]). The best performing DL models achieved an AUC of 0.854, (CI [0.774, 0.914]) on external data using T1-CE-ET and T2-PTR masks, followed by model derived from T1-CE-ET, ADC-ET and FLAIR-PTR masks (AUC: 0.851, CI [0.772, 0.909]). CONCLUSION: Both ML and DL derived pipelines achieved similar performance. T1-CE mask was used in three of the top four overall models. Additionally, all four models had some mask derived from PTR, either T2WI or FLAIR.

CT Perfusion Maps Improve Detection of M2-MCA Occlusions in Acute Ischemic Stroke.

OBJECTIVES: Middle cerebral artery occlusions, particularly M2 branch occlusions are challenging to identify on CTA. We hypothesized that additional review of the CTP maps will increase large vessel occlusion (LVO) detection accuracy on CTA and reduce interpretation time. MATERIALS AND METHODS: Two readers (R1 and R2) retrospectively reviewed the CT studies in 99 patients (27 normal, 26 M1-MCA, 46 M2-MCA occlusions) who presented with suspected acute ischemic stroke (AIS). The time of interpretation and final diagnosis were recorded for the CTA images (derived from CTP data), both without and with the CTP maps. The time for analysis for all vascular occlusions was compared using McNemar tests. ROC curve analysis and McNemar tests were performed to assess changes in diagnostic performance with the addition of CTP maps. RESULTS: With the addition of the CTP maps, both readers showed increased sensitivity (p = 0.01 for R1 and p = 0.04 for R2), and accuracy (p = 0.02 for R1 and p = 0.004 for R2) for M2-MCA occlusions. There was a significant improvement in diagnostic performance for both readers for detection of M2-MCA occlusions (AUC R1 = 0.86 to 0.95, R2 = 0.84 to 0.95; p < 0.05). Both readers showed reduced interpretation time for all cases combined, as well as for normal studies (p < 0.001) when CTP images were reviewed along with CTA. Both readers also showed reduced interpretation time for M2-MCA occlusions, which was significant for one of the readers (p < 0.02). CONCLUSION: The addition of CTP maps improves accuracy and reduces interpretation time for detecting LVO and M2-MCA occlusions in AIS. Incorporation of CTP in acute stroke imaging protocols may improve detection of more distal occlusions.

FDG PET/CT in Neurolymphomatosis.

Online supplemental material is available for this article.

Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: a comparison of diagnostic performance across different MRI sequences and machine learning techniques.

OBJECTIVES: Despite the robust diagnostic performance of MRI-based radiomic features for differentiating between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) reported on prior studies, the best sequence or a combination of sequences and model performance across various machine learning pipelines remain undefined. Herein, we compare the diagnostic performance of multiple radiomics-based models to differentiate GBM from PCNSL. METHODS: Our retrospective study included 94 patients (34 with PCNSL and 60 with GBM). Model performance was assessed using various MRI sequences across 45 possible model and feature selection combinations for nine different sequence permutations. Predictive performance was assessed using fivefold repeated cross-validation with five repeats. The best and worst performing models were compared to assess differences in performance. RESULTS: The predictive performance, both using individual and a combination of sequences, was fairly robust across multiple top performing models (AUC: 0.961-0.977) but did show considerable variation between the best and worst performing models. The top performing individual sequences had comparable performance to multiparametric models. The best prediction model in our study used a combination of ADC, FLAIR, and T1-CE achieving the highest AUC of 0.977, while the second ranked model used T1-CE and ADC, achieving a cross-validated AUC of 0.975. CONCLUSION: Radiomics-based predictive accuracy can vary considerably, based on the model and feature selection methods as well as the combination of sequences used. Also, models derived from limited sequences show performance comparable to those derived from all five sequences. KEY POINTS: • Radiomics-based diagnostic performance of various machine learning models for differentiating glioblastoma and PCNSL varies considerably. • ML models using limited or multiple MRI sequences can provide comparable performance, based on the chosen model. • Embedded feature selection models perform better than models using a priori feature reduction.

Repeat Head CT for Neurologically Stable Patients With Mild Traumatic Subarachnoid Hemorrhage During Interfacility Transfer and Follow-Up Does Not Alter Patient Care [Formula: see text].

PURPOSE: To evaluate the impact of repeat head computed tomography (CT) during (1) interfacility transfer and (2) inpatient and/or outpatient follow-up on management, cost-effectiveness, and radiation dose in neurologically stable patients with mild traumatic subarachnoid hemorrhage (tSAH). MATERIAL AND METHODS: This is a single-center retrospective study evaluating patients with mild tSAH presenting between January 2017 and July 2019. A total of 101 and 140 patients met the eligibility criteria for the first and second subgroups, respectively. Common inclusion criteria were isolated mild tSAH, Glasgow Coma Scale between 13 and 15, and neurological stability. Additional inclusion criteria for the first subgroup were availability of brain imaging at the outside institution prior to transfer and the second subgroup was the availability of follow-up imaging. RESULTS: In the first subgroup, 76.20% of patients had stable SAH, 18.80% had reduced SAH, while 5% had an interval increase in SAH. None required any surgical intervention. Additional per-patient mean radiation exposure was 1.77 ± 0.26 mSv. In the second subgroup, all 140 patients had complete resolution of tSAH. One patient had a new tiny subdural hemorrhage, which subsequently resolved on follow-up. The additional mean radiation exposure was 2.47 ± 1.29 mSv. A total of 256 avoidable CT scans were performed resulting in excess health care costs of about US$531 696. CONCLUSION: In neurologically stable isolated tSAH patients, repeat brain imaging during interfacility transfer and inpatient and/or outpatient follow-up do not alter patient management despite increased health care costs and radiation burden.

Cerebral computed tomographic angiography using third-generation reconstruction algorithm provides improved image quality with lower contrast and radiation dose.

PURPOSE: We hypothesized that cerebral CT angiogram performed using third-generation reconstruction algorithm and lower contrast dose-low-kVp technique (LD-CTA) will provide better image quality when compared with regular contrast dose CTA at 120 kVp using a sinogram-affirmed iterative reconstruction algorithm (ND-CTA). METHODS: Retrospective imaging review of 100 consecutive patients (50 each in LD- and ND-CTA groups). Two readers independently assessed the subjective image quality across multiple vascular segments on a Likert-like scale. Differences in contrast dose, CT dose index (CTDI), and dose length product (DLP) were compared using Mann-Whitney U test. Fisher's exact test was used to compare subjective image quality. Similarly, contrast- and signal-to-noise ratios (CNR and SNR) were compared in the mid-M1 MCA vessels bilaterally and the mid-basilar artery using Mann-Whitney U test. Interclass correlation coefficient (ICC) was calculated for the SNR/CNR values. RESULTS: Both observers showed excellent correlation in subjective image quality (mean percentage agreement of 95.2% for group 1 versus 89.2% for group 2). LD-CTA group showed better SNR and CNR (p < 0.0001) for both MCA vessels and the mid-basilar artery. Interclass correlation coefficient showed moderate correlation (0.51-0.63) between readers. LD-CTA group also used lower contrast (49 cc versus 97 cc in ND-CTA) and had lower radiation exposure (DLP/CTDI for both groups 268.3/80.7 vs 519.5/36.08, both < 0.0001). CONCLUSION: Next-generation reconstruction algorithm and low-kV scanning significantly improved image quality on cerebral CTA images despite lower contrast dose and, in addition, have lower radiation exposure.

Right ventricular dysfunction in rheumatic heart valve disease: A clinicopathological evaluation.

Background: . Dysfunction of the right ventricle (RV) in rheumatic heart disease (RHD) is a poor prognostic factor. We planned to observe the clinicopathological changes in the RV of patients with RHD. Methods: . We defined RV dysfunction by a myocardial performance index value of >0.4 on transthoracic echo-cardiography and included patients with isolated severe mitral stenosis in sinus rhythm with normal left ventricular (LV) function from April 2014 to April 2016. The patients were divided into two groups based on the absence (group I, n=21) and presence (group II, n=22) of RV dysfunction. RV muscle biopsy was evaluated for the presence of apoptosis, fibrosis and fat deposition apart from other clinical and echocardiography parameters. Results: . Patients in both the groups had a similar demographic profile and LV dimensions and function. The age of the patients in the two groups was the only clinical parameter that was significantly different; older patients were in group II. A higher value for RV systolic pressure (RVSP) and the grade of tricuspid regurgitation was seen in group II. Though there was no significant difference in the presence of fibrosis and intensity of apoptosis in the RV biopsy samples, the deposition of fat in the interstitial spaces was decreased in group II. Age at presentation had no significant difference or correlation with the deposition of fibrosis or fat in the RV myocardial biopsy. Conclusions: . Patients with RV dysfunction were older in age and their RVSP was raised at operation, suggesting that earlier intervention may help in preserving RV function.

Modified technique for imaging the wrist and elbow in obese and claustrophobic patients using a non-open standard MRI scanner.

OBJECTIVE: It is challenging to image extremely obese and claustrophobic patients using a standard, non-open, magnetic resonance imaging (MRI) scanner. On the other hand, installing an additional upright or open MRI scanner may not be cost-effective for most practices. Our technique with a patient in a sitting or standing position behind the standard MRI scanner may be helpful in the MR examination of the wrist/elbow in these patients using a standard wrist/elbow coil. MATERIAL AND METHODS: We performed wrist and elbow MRI of extremely obese and claustrophobic patients by using our modified technique with the patient sitting or standing outside the standard non-open MRI scanner. A total number of 20 cases with the following diagnosis were examined: triquetral and scaphoid bone contusions and fractures, scapholunate ligament tears, triangular fibrocartilage complex tear, and biceps tear. RESULTS: Comparison of image quality for diagnostic information between the standard technique and our technique showed no significant difference, which is necessary for making the diagnosis. CONCLUSIONS: Our technique enables wrist and elbow imaging of extremely obese and claustrophobic patients who cannot otherwise be imaged using a standard MRI scanner without compromising the image quality that is essential for making a diagnosis.

Neuroimaging Findings in Intracranial Sarcoid Phlebitis: A Case Report.

INTRODUCTION: Venous phlebitis in Neurosarcoidosis (NS) is rare but is often associated with intracranial hemorrhage (ICH). Imaging findings in such cases have been recently described on susceptibility weighted imaging (SWI). CASE PRESENTATION AND OUTCOME: We report a patient who presented with ICH. Magnetic resonance imaging provided evidence for parenchymal and leptomeningeal involvement while SWI and vessel wall imaging (VWI) helped confirmed NS associated intracranial phlebitis. The patient was subsequently diagnosed with systemic sarcoidosis. DISCUSSION: The emerging role of VWI and SWI in the diagnosis of this rare entity is discussed.

Application of diffusion tensor imaging in brain lesions: A comparative study of neoplastic and non-neoplastic brain lesions.

PURPOSE: To evaluate the role of diffusion tensor imaging (DTI) in the differentiation of neoplastic and non-neoplastic brain lesions, on the basis of DTI parameters, fractional anisotropy (FA) and mean diffusivity (MD) from the lesion (L) and the perilesional edema (PE). MATERIAL AND METHODS: Patients with newly diagnosed 25 neoplastic [10 high grade gliomas (HGG), 11 metastases, 4 low grade glioma (LGG)] and 25 non-neoplastic [13 tuberculomas and 12 neurocysticercosis (NCC)] brain lesions underwent an MRI, including the DTI sequences. Fractional anisotropy from the lesion (FAL) and mean diffusivity from the lesion (MDL), as well as fractional anisotropy from the perilesional edema (FAPE), and mean diffusivity from the perilesional edema (MDPE) were calculated and quantified using region of interest (ROI) based assessment on DTI derived FA and MD parametric maps. The mean values of FAL, FAPE, MDL and MDPE from the two groups were compared by the independent sample t-test. RESULTS: In the non-neoplastic group, perilesional edema showed a significantly higher (P = 0.015) MD compared to the neoplastic group. Perilesional FA and lesional FA and MD showed no such statistically significant difference. On further subgroup analysis, MDPE was higher in metastases compared to HGG (P < 0.001), reflecting an increase in the vasogenic edema. Perilesional FA was higher in HGG compared to metastases and tuberculomas (P < 0.001) reflecting tumour infiltration in addition to vasogenic edema. FAL was higher in tuberculomas compared to metastases (P < 0.001), pointing to a more microstructural destruction in metastases. CONCLUSION: Quantitative DTI parameters, FA and MD, from the lesion and from the area of perilesional edema are helpful in the evaluation and differentiation of brain lesions.

Magnetic resonance imaging of bacterial and tuberculous spondylodiscitis with associated complications and non-infectious spinal pathology mimicking infections: a pictorial review.

Magnetic resonance (MR) imaging plays an important role in the evaluation of bacterial and tuberculous spondylodiscitis and associated complications. Owing to its high sensitivity and specificity, it is a powerful diagnostic tool in the early diagnosis of ongoing infections, and thus provides help in prompt initiation of appropriate, therapy which may be medical or surgical, by defining the extent of involvement and detection of complications such as epidural and paraspinal abscesses. More specifically, MR imaging helps in differentiating bacterial from tuberculous infections and enables follow up of progression or resolution after appropriate treatment. However, other non-infectious pathology can demonstrate similar MR imaging appearances and one should be aware of these potential mimickers when interpreting MR images. Radiologists and other clinicians need to be aware of these potential mimics, which include such pathologies as Modic type I degenerative changes, trauma, metastatic disease and amyloidosis. In this pictorial review, we will describe and illustrate imaging findings of bacterial and tuberculous spondylodiscitis, their complications and non-infectious pathologies that mimic these spinal infections.

Perfusion MR imaging of enhancing brain tumors: Comparison of arterial spin labeling technique with dynamic susceptibility contrast technique.

OBJECTIVE: Arterial spin labeling (ASL) magnetic resonance (MR) perfusion is a noninvasive and repeatable method for quantitatively measuring cerebral blood flow (CBF). This study aims to compare measurements of ASL-derived CBF with dynamic susceptibility contrast (DSC) MRI in the assessment of enhancing brain tumors (primary and metastatic), with an aim to use ASL as an alternative to DSC. MATERIALS AND METHODS: Thirty patients with newly diagnosed brain tumors (16 meningiomas, 6 gliomas, 3 metastases, 2 cerebellopontine angle schwannoma, 1 central neurocytoma, and 2 low-grade gliomas) were examined using a 3T MR scanner. Values of CBF, regional cerebral blood flow (rCBF), and regional cerebral blood volume (rCBV) were determined in the tumor (T) as well as in the contralateral normal gray matter (GM) and white matter (WM). Tumor-to-GM or WM CBF, rCBF, and rCBV ratios were calculated to estimate normalized perfusion values (i.e., ASL normalized tumor blood flow [nTBF], DSC nTBF, and DSC normalized tumor blood volume [nTBV]) from the ASL and DSC techniques. ASL and DSC MRI derived perfusion parameters were compared using paired t-test and correlated using Pearson correlation coefficient. RESULTS: Mean values for ASL nTBF and DSC nTBF using contralateral GM as the reference point were 2.98 ± 1.67and 2.91 ± 1.43, respectively. A very strong correlation coefficient was found between ASL nTBF and DSC nTBF with contralateral GM as the reference region (r = 0.903; R2= 0.813). Mean DSC nTBF and DSC nTBV also showed strong correlation (r = 0.83; R2= 0.701). CONCLUSION: Our study results suggested that measurement of CBF from ASL possesses the potential for a noninvasive assessment of blood flow in intracranial tumors as an alternate to DSC MRI, in those patients requiring multiple follow-up imaging and in patients with impaired renal functions.

Arterial spin labeling magnetic resonance perfusion study to evaluate the effects of age and gender on normal cerebral blood flow.

PURPOSE: Arterial spin labeling (ASL) is a noninvasive magnetic resonance (MR) perfusion technique to detect changes in blood flow. This study was undertaken to obtain a reference set of normal values of cerebral blood flow (CBF) in different age groups using three-dimensional pseudocontinuous ASL (3D PCASL) technique. The existence of an age-related decline in the gray matter (GM) and white matter (WM) CBF was evaluated. The gender-related CBF was also analyzed. MATERIALS AND METHODS: One hundred and sixty normal volunteers of varying age (6-72 years), arranged in 4 age groups, underwent MR perfusion imaging using 3D PCASL technique at 3 Tesla (T). Mean CBF values in global and regional GM and WM in different age groups were extracted from the quantitative perfusion map. RESULTS: A significant negative correlation was observed between the age and mean GM and WM CBF values (r = -0.80, P = 0.001; r = -0.59, P = 0.001, respectively). Similar results were also observed between age and various regional mean GM and WM CBF values (P = 0.001). No significant effect of gender on the GM CBF and WM CBF was found in any age group (P > 0.05). CONCLUSION: PCASL technique provides reliable quantitative parameters for the precise mapping of age-related perfusion changes occurring in the normal brain.

Ependymal Tumors: Overview of the Recent World Health Organization Histopathologic and Genetic Updates with an Imaging Characteristic.

The 2021 World Health Organization Classification of Tumors of the Central Nervous System (CNS5), introduced significant changes, impacting tumors ranging from glial to ependymal neoplasms. Ependymal tumors were previously classified and graded based on histopathology, which had limited clinical and prognostic utility. The updated CNS5 classification now divides ependymomas into 10 subgroups based on anatomic location (supratentorial, posterior fossa, and spinal compartment) and genomic markers. Supratentorial tumors are defined by zinc finger translocation associated (ZFTA) (formerly v-rel avian reticuloendotheliosis viral oncogene [RELA]), or yes-associated protein 1 (YAP1) fusion; posterior fossa tumors are classified into groups A (PFA) and B (PFB), spinal ependymomas are defined by MYCN amplification. Subependymomas are present across all these anatomic compartments. The new classification kept an open category of "not elsewhere classified" or "not otherwise specified" if no pathogenic gene fusion is identified or if the molecular diagnosis is not feasible. Although there is significant overlap in the imaging findings of these tumors, a neuroradiologist needs to be familiar with updated CNS5 classification to understand tumor behavior, for example, the higher tendency for tumor recurrence along the dural flap for ZFTA fusion-positive ependymomas. On imaging, supratentorial ZFTA-fused ependymomas are preferentially located in the cerebral cortex, carrying predominant cystic components. YAP1-MAMLD1-fused ependymomas are intra- or periventricular with prominent multinodular solid components and have significantly better prognosis than ZFTA-fused counterparts. PFA ependymomas are aggressive paramedian masses with frequent calcification, seen in young children, originating from the lateral part of the fourth ventricular roof. PFB ependymomas are usually midline, noncalcified solid-cystic masses seen in adolescents and young adults arising from the fourth ventricular floor. PFA has a poorer prognosis, higher recurrence, and higher metastatic rate than PFB. Myxopapillary spinal ependymomas are now considered grade II due to high recurrence rates. Spinal-MYCN ependymomas are aggressive tumors with frequent leptomeningeal spread, relapse, and poor prognosis. Subependymomas are noninvasive, intraventricular, slow-growing benign tumors with an excellent prognosis. Currently, the molecular classification does not enhance the clinicopathologic understanding of subependymoma and myxopapillary categories. However, given the molecular advancements, this will likely change in the future. This review provides an updated molecular classification of ependymoma, discusses the individual imaging characteristics, and briefly outlines the latest targeted molecular therapies.

Newly Recognized Genetic Tumor Syndromes of the CNS in the 5th WHO Classification: Imaging Overview with Genetic Updates.

The nervous system is commonly involved in a wide range of genetic tumor-predisposition syndromes. The classification of genetic tumor syndromes has evolved during the past years; however, it has now become clear that these syndromes can be categorized into a relatively small number of major mechanisms, which form the basis of the new 5th edition of the World Health Organization book (beta online version) on genetic tumor syndromes. For the first time, the World Health Organization has also included a separate chapter on genetic tumor syndromes in the latest edition of all the multisystem tumor series, including the 5th edition of CNS tumors. Our understanding of these syndromes has evolved rapidly since the previous edition (4th edition, 2016) with recognition of 8 new syndromes, including the following: Elongator protein complex-medulloblastoma syndrome, BRCA1-associated protein 1 tumor-predisposition syndrome, DICER1 syndrome, familial paraganglioma syndrome, melanoma-astrocytoma syndrome, Carney complex, Fanconi anemia, and familial retinoblastoma. This review provides a description of these new CNS tumor syndromes with a focus on imaging and genetic characteristics.

Molecular GBM versus Histopathological GBM: Radiology-Pathology-Genetic Correlation and the New WHO 2021 Definition of Glioblastoma.

Given the recent advances in molecular pathogenesis of tumors, with better correlation with tumor behavior and prognosis, major changes were made to the new 2021 WHO (CNS5) classification of CNS tumors, including updated criteria for diagnosis of glioblastoma. Diagnosis of GBM now requires absence of isocitrate dehydrogenase and histone 3 mutations (IDH-wildtype and H3-wildtype) as the basic cornerstone, with elimination of the IDH-mutated category. The requirements for diagnosis were conventionally histopathological, based on the presence of pathognomonic features such as microvascular proliferation and necrosis. However, even if these histological features are absent, many lower grade (WHO grade 2/3) diffuse astrocytic gliomas behave clinically similar to GBM (grade 4). The 2021 WHO classification introduced new molecular criteria that can be used to upgrade the diagnosis of such histologically lower-grade, IDH-wildtype, astrocytomas to GBM. The three molecular criteria include: concurrent gain of whole chromosome 7 and loss of whole chromosome 10 (+7/-10); TERT promoter mutation; epidermal growth factor receptor (EGFR) amplification. Given these changes, it is now strongly recommended to have molecular analysis of WHO grade 2/3 diffuse astrocytic, IDH-wildtype, gliomas in adult patients, as identification of any of the above mutations allows for upgrading the tumor to WHO grade 4 ("molecular GBM") with important prognostic implications. Despite at an early stage, there is active ongoing research on the unique MRI features of molecular GBM. This paper highlights the differences between "molecular" and "histopathological" GBM, with the aim of providing a basic understanding about these changes.ABBREVIATIONS: GBM=Glioblastoma; TERT=telomerase reverse transcriptase; EGFR=epidermal growth factor receptor; MGMT= methylguanine-DNA methyltransferase; NGS= next-generation sequencing; IDH= isocitrate dehydrogenase.

Light-chain Deposition Diseases of the CNS: Review of Pathogenesis, Imaging Features and Radiographic Mimics.

Light-chain deposition disease (LCDD) is a rare CNS disorder characterized by the extracellular accumulation of monoclonal immunoglobulin light chains in various organs. LCDD typically arises secondary to an underlying plasma cell dyscrasia, such as monoclonal gammopathy of undetermined significance (MGUS) or multiple myeloma. However, rare cases can occur in the absence of a demonstrable plasma cell disorder. The kidneys, liver, lungs, and heart are the most affected organs. Intracerebral LCDD, particularly without an underlying plasma cell neoplasm, represents an exceedingly uncommon entity with limited documented cases in literature. This review article explores the pathogenesis, histopathological features, and characteristic neuroimaging findings of intracerebral LCDD. We emphasize the diverse imaging presentations of this disease, which can closely resemble other neurological pathologies. Recognizing these potential mimics is crucial for avoiding misdiagnosis, especially in the absence of a known underlying plasma cell disorder. This article aims to provide a comprehensive overview from a neuroradiological perspective, facilitating the recognition and differentiation of this challenging entity.ABBREVIATIONS: LCDD, light chain deposition disease; ALD, amyloidoma.

Meningioma: Molecular Updates from the 2021 WHO Classification of CNS Tumors and Imaging Correlates.

Meningiomas, the most common primary intracranial neoplasms, account for over a third of primary CNS tumors. While traditionally viewed as benign, meningiomas can be associated with considerable morbidity, and specific meningioma subgroups display more aggressive behavior with higher recurrence rates. The risk stratification for recurrence has been primarily associated with the World Health Organization (WHO) histopathological grade and extent of resection. However, a growing body of literature has highlighted the value of molecular characteristics in assessing recurrence risk. While maintaining the previous classification system, the 5th edition of the 2021 WHO CNS tumor (CNS5) book expands upon the molecular information in meningiomas to help guide management. The WHO CNS5 stratifies meningioma into three grades (1-3) based on histopathology criteria and molecular profile. pTERT mutations and CDKN2A/B deletions now signify a grade 3 meningioma with increased recurrence risk. Tumor location also correlates with underlying mutations. Convexity and most spinal meningiomas carry 22q deletion and/or NF2 mutations, while skull base meningiomas have AKT1, TRAF7, SMO, and/or PIK3CA mutations. MRI is the primary imaging modality for diagnosing and treatment planning of meningiomas, while DOTATATE-PET imaging offers supplementary information beyond anatomical imaging. Herein, we review the evolving molecular landscape of meningiomas, emphasizing imaging/genetic biomarkers, and treatment strategies relevant to neuroradiologists.ABBREVIATIONS: AKT1=AKT serine/threonine kinase 1; BAP1=BRCA1-associated protein 1; CDK4/6=Cyclin-dependent kinases 4 and 6; KLF4=Krüppel-like factor 4; NF2=Neurofibromatosis type 2; PIK3CA=Phosphatidylinositol-4,5-Bisphosphate 3-Kinase catalytic subunit alpha; POLR2A=RNA polymerase II subunit A; SMO: Smoothened, frizzled class receptor; SMARCB1=SWItch/sucrose non-fermentable related, matrix associated, actin dependent regulator of chromatin, subfamily b, member 1; TERT=Telomerase reverse transcriptase; TRAF7=TNF receptor-associated factor 7.

Updates from the International League Against Epilepsy Classification of Epilepsy (2017) and Focal Cortical Dysplasias (2022): Imaging Phenotype and Genetic Characterization.

The International League Against Epilepsy (ILAE) is an organization of 120 national chapters providing the most widely accepted and updated guidelines on epilepsy. In 2022, the ILAE Task Force revised the prior (2011) classification of focal cortical dysplasias to incorporate and update clinicopathologic and genetic information, with the aim to provide an objective classification scheme. New molecular-genetic information has led to the concept of "integrated diagnosis" on the same lines as brain tumors, with a multilayered diagnostic model providing a phenotype-genotype integration. Major changes in the new update were made to type II focal cortical dysplasias, apart from identification of new entities, such as mild malformations of cortical development and cortical malformation with oligodendroglial hyperplasia. No major changes were made to type I and III focal cortical dysplasias, given the lack of significant new genetic information. This review provides the latest update on changes to the classification of focal cortical dysplasias with discussion about the new entities. The ILAE in 2017 updated the classification of seizure and epilepsy with 3 levels of diagnosis, including seizure type, epilepsy type, and epilepsy syndrome, which are also briefly discussed here.