Mesenchymal Non-Meningothelial Tumors of the CNS: Evolving Molecular Landscape and Implications for Neuroradiologists.

The World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS5) significantly revised the terminology and diagnostic criteria of "mesenchymal non-meningothelial" tumors of CNS to better align with the classification of these soft tissue tumors outside the CNS. The CNS chapter only covers the entities with distinct histological or molecular characteristics that occur exclusively or primarily in the CNS. These tumors usually arise from the meninges and are rarely intraparenchymal in origin, mainly in the supratentorial compartment. These tumors are grouped into three main categories: soft tissue, chondro-osseous, and notochordal. Soft tissue tumors, the largest group, are further divided into fibroblastic, vascular, and skeletal muscle subtypes. Notably, a new subcategory for "tumors of uncertain differentiation" has been introduced, encompassing three new histomolecular entities: FET::CREB fusion-positive, CIC-rearranged sarcoma, and primary intracranial sarcoma, DICER1-mutant. Emerging entities like dural angioleiomyomas and spindle cell neoplasms with NTRK-rearrangements have been reviewed, although not introduced in WHO CNS5. Given the often non-specific histology and immunophenotype of mesenchymal nonmeningothelial tumors of uncertain differentiation, molecular techniques have become indispensable for accurate diagnosis. This review provides a comprehensive overview of primary mesenchymal non-meningothelial CNS tumors, including their clinical, radiological, histopathological, and molecular characteristics and treatment strategies.ABBREVIATIONS: ALK: Anaplastic lymphoma kinase; ATF1: activating transcriptase factor-1; CREB: cAMP response element-binding protein; CREM: cAMP response element modulator; CIC: Capicua transcriptional receptor; EWSR1: Ewing sarcoma RNA binding protein; FUS: fused in sarcoma; NAB2: nerve growth factor-inducible protein A binding protein 2; STAT6: signal transducer and activator of transcription 6; WHO: World Health Organization WHO CNS5: World Health Organization Classification of Tumors of the Central Nervous System, fifth edition.

Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.

Background: Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhage (ICH) detection on noncontrast CT (NCCT) have shown promising results but lack prospective validation. Objective: To evaluate the impact on radiologists' real-world aggregate performance for ICH detection and report turnaround times for ICH-positive examinations of a radiology department's implementation of an AI triage and notification system for ICH detection on head NCCT examinations. Methods: This prospective single-center study included adult patients who underwent head NCCT examinations from May 12, 2021 to June 30, 2021 (phase 1) or September 30, 2021 to December 4, 2021 (phase 2). Before phase 1, the radiology department implemented a commercial AI triage system for ICH detection that processed head NCCT examinations and notified radiologists of positive results through a widget with a floating pop-up display. Examinations were interpreted by neuroradiologists or emergency radiologists, who evaluated examinations without and with AI assistance in phase 1 and phase 2, respectively. A panel of radiologists conducted a review process for all examinations with discordance between the radiology report and AI and a subset of remaining examinations, to establish the reference standard. Diagnostic performance and report turnaround times were compared using Pearson chi-square test and Wilcoxon rank-sum test, respectively. Bonferroni correction was used to account for five diagnostic performance metrics (adjusted significance threshold, .01 [α=.05/5]). Results: A total of 9954 examinations from 7371 patients (mean age, 54.8±19.8 years; 3773 female, 3598 male) were included. In phases 1 and 2, 19.8% (735/3716) and 21.9% (1368/6238) of examinations, respectively, were positive for ICH (P=.01). Radiologists without versus with AI showed no significant difference in accuracy (99.5% vs 99.2%), sensitivity (98.6% vs 98.9%), PPV (99.0% vs 99.7%), or NPV (99.7% vs 99.7%) (all P>.01); specificity was higher for radiologists without than with AI (99.8% vs 99.3%, respectively, P=.004). Mean report turnaround time for ICH-positive examinations was 147.1 minutes without AI versus 149.9 minutes with AI (P=.11). Conclusion: An AI triage system for ICH detection did not improve radiologists' diagnostic performance or report turnaround times. Clinical Impact: This large prospective real-world study does not support use of AI assistance for ICH detection.

Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is a debilitating neurodegenerative disease. Early diagnosis of AD and its precursor, mild cognitive impairment (MCI), is crucial for timely intervention and management. Radiomics involves extracting quantitative features from medical images and analyzing them using advanced computational algorithms. These characteristics have the potential to serve as biomarkers for disease classification, treatment response prediction, and patient stratification. Of note, Magnetic resonance imaging (MRI) radiomics showed a promising result for diagnosing and classifying AD, and MCI from normal subjects. Thus, we aimed to systematically evaluate the diagnostic performance of the MRI radiomics for this task. METHODS AND MATERIALS: A comprehensive search of the current literature was conducted using relevant keywords in PubMed/MEDLINE, Embase, Scopus, and Web of Science databases from inception to August 5, 2023. Original studies discussing the diagnostic performance of MRI radiomics for the classification of AD, MCI, and normal subjects were included. Method quality was evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools. RESULTS: We identified 13 studies that met the inclusion criteria, involving a total of 5448 participants. The overall quality of the included studies was moderate to high. The pooled sensitivity and specificity of MRI radiomics for differentiating AD from normal subjects were 0.92 (95% CI [0.85; 0.96]) and 0.91 (95% CI [0.85; 0.95]), respectively. The pooled sensitivity and specificity of MRI radiomics for differentiating MCI from normal subjects were 0.74 (95% CI [0.60; 0.85]) and 0.79 (95% CI [0.70; 0.86]), respectively. Also, the pooled sensitivity and specificity of MRI radiomics for differentiating AD from MCI were 0.73 (95% CI [0.64; 0.80]) and 0.79 (95% CI [0.64; 0.90]), respectively. CONCLUSION: MRI radiomics has promising diagnostic performance in differentiating AD, MCI, and normal subjects. It can potentially serve as a non-invasive and reliable tool for early diagnosis and classification of AD and MCI.

Radiomics; A Potential Next "Omics" in Psychiatric Disorders; An Introduction.

Psychiatric disorders remain one of the most debilitating conditions; however, most patients are never diagnosed and do not seek treatment. Despite its massive burden on modern society and the health system, many hurdles prevent proper diagnosis and management of these disorders. The diagnosis is primarily based on clinical symptoms, and efforts to find appropriate biomarkers have not been practical. Through the past years, researchers have put a tremendous effort into finding biomarkers in "omics" fields: genomics, transcriptomics, proteomics, metabolomics, and epigenomics. This article reviews the evolving field of radiomics and its role in diagnosing psychiatric disorders as the sixth potential "omics." The first section of this paper elaborates on the definition of radiomics and its potential to provide a detailed structural study of the brain. Following that, we have provided the latest promising results of this novel approach in a broad range of psychiatric disorders. Radiomics fits well within the concept of psychoradiology. Besides volumetric analysis, radiomics takes advantage of many other features. This technique may open a new field in psychiatry for diagnosing and classifying psychiatric disorders and treatment response prediction in the era of precision and personalized medicine. The initial results are encouraging, but radiomics in psychiatry is still in its infancy. Despite the extensive burden of psychiatric disorders, there are very few published studies in this field, with small patient populations. The lack of prospective multi-centric studies and heterogeneity of studies in design are the significant barriers against the clinical adaptation of radiomics in psychoradiology.

Radiomics Outperforms Clinical and Radiologic Signs in Predicting Spontaneous Basal Ganglia Hematoma Expansion: A Pilot Study.

Prediction of the hematoma expansion (HE) of spontaneous basal ganglia hematoma (SBH) from the first non-contrast CT can result in better management, which has the potential of improving outcomes. This study has been designed to compare the performance of "Radiomics analysis," "radiology signs," and "clinical-laboratory data" for this task. We retrospectively reviewed the electronic medical records for clinical, demographic, and laboratory data in patients with SBH. CT images were reviewed for the presence of radiologic signs, including black-hole, blend, swirl, satellite, and island signs. Radiomic features from the SBH on the first brain CT were extracted, and the most predictive features were selected. Different machine learning models were developed based on clinical, laboratory, and radiology signs and selected Radiomic features to predict hematoma expansion (HE). The dataset used for this analysis included 116 patients with SBH. Among different models and different thresholds to define hematoma expansion (10%, 20%, 25%, 33%, 40%, and 50% volume enlargement thresholds), the Random Forest based on 10 selected Radiomic features achieved the best performance (for 25% hematoma enlargement) with an area under the curve (AUC) of 0.9 on the training dataset and 0.89 on the test dataset. The models based on clinical-laboratory and radiology signs had low performance (AUCs about 0.5-0.6).

ALK-positive histiocytosis involving the cavernous sinus: A deceptive radiologic mimic of meningioma.

Anaplastic lymphoma kinase (ALK)-positive histiocytosis is an uncommon condition, recently considered a separate condition from other histiocytosis by WHO 5th edition. It can involve intracranial structures. This manuscript describes a case of ALK-positive histiocytosis of the cavernous sinus, focusing on the radiologic and pathologic presentation of the entity. Our case had MRI manifestations mimicking meningioma, metastasis, and Langerhans histiocytosis. On CT imaging, benign osseous remodeling of the cavernous sinus was detected, which can be helpful in differentiating it from more common meningioma.

Magnetic Resonance Imaging (MRI) Findings in COVID-19 Associated Encephalitis.

We conducted this study to investigate the scope of the MRI neuroimaging manifestations in COVID-19-associated encephalitis. From January 2020 to September 2021, patients with clinical diagnosis of COVID-19-associated encephalitis, as well as concomitant abnormal imaging findings on brain MRI, were included. Two board-certified neuro-radiologists reviewed these selected brain MR images, and further discerned the abnormal imaging findings. 39 patients with the clinical diagnosis of encephalitis as well as abnormal MRI findings were included. Most (87%) of these patients were managed in ICU, and 79% had to be intubated-ventilated. 15 (38%) patients died from the disease, while the rest were discharged from the hospital. On MRI, FLAIR hyperintensities in the insular cortex were the most common finding, seen in 38% of the patients. Micro-hemorrhages on the SWI images were equally common, also seen in 38% patients. FLAIR hyperintensities in the medial temporal lobes were seen in 30%, while FLAIR hyperintensities in the posterior fossa were evident in 20%. FLAIR hyperintensities in basal ganglia and thalami were seen in 15%. Confluent FLAIR hyperintensities in deep and periventricular white matter, not explained by microvascular angiopathy, were detected in 7% of cases. Cortical-based FLAIR hyperintensities in 7%, and FLAIR hyperintensity in the splenium of the corpus callosum in 7% of patients. Finally, isolated FLAIR hyperintensity around the third ventricle was noted in 2% of patients.

Subcortical signal alteration of corticospinal tracts. A radiologic manifestation of ARIA: A case report.

Patients with Alzheimer's disease who have been given monoclonal antibodies targeting amyloid-ß (Aß) (eg, gantenerumab, donanemab, lecanemab, and aducanumab) for scientific purposes may have a spectrum of imaging findings known as amyloid-related imaging abnormalities (ARIA), shown on brain magnetic resonance imaging (MRI) scans. These neuroimaging abnormalities are caused by antibody-mediated destruction of accumulated Aß aggregates in cerebral blood vessels and brain parenchyma. ARIA may demonstrate as brain edema or sulcal effusion (ARIA-E) or as hemosiderin deposits caused by brain parenchymal or pial hemorrhage (ARIA-H). The current study explores 2 cases with interval development of FLAIR hyper signal intensity along the bilateral corticospinal tracts in the motor cortex/precentral gyri after treatment by aducanumab. We believe this manifestation is a subtype of ARIA-A that has not been explored earlier. Our first case was a 72-year-old woman with a history of HTN and kidney transplant (polycystic kidney) who presented with mild cognitive impairment with clinical findings consistent with early Alzheimer's disease. After receiving 3 doses of aducunumab and experiencing cognition improvement, she underwent a brain MRI because of dizziness and vertigo. The brain MRI demonstrated new FLAIR hyper signal intensity in subcortical regions of precentral gyri (motor cortex) symmetrically as well as trace subarachnoid hemorrhage at the vertex compatible with ARIA-E and ARIA-H. Our second case was an 85-year-old woman with a history of small lymphocytic leukemia which was treated 20 years earlier. After orthopedic surgery 2 years ago, she developed dementia with anterograde amnesia. Since then, Aricept and Namenda have been started, but there have been no improvements in her subjective condition. The initial Amyloid PET/MR imaging showed diffuse cerebral Amyloid deposition. After tolerating 6 doses of aducanumab a safety MRI revealed new bilateral symmetric FLAIR hyper signal intensity in the subcortical motor cortex. Results of our study suggest that the subcortical corticospinal tract is another hotspot for ARIA findings. Hence, these regions might be an unknown site for both the action and adverse effects of aducanumab on amyloid plaques with secondary inflammation. In addition, radiologists must take this phenomenon into the account, and be cognizant that the FLAIR hyper signal intensities should not be misinterpreted as motor neuron disease (eg, amyotrophic lateral sclerosis).

Radiomics for differentiation of the posterior fossa pilocytic astrocytoma versus hemangioblastomas in adults. A pilot study.

PURPOSE: Both pilocytic astrocytoma (PA) and hemangioblastoma (HB) are common primary neoplasms of the posterior fossa with similar radiological manifestations. This study was conducted to evaluate the role of Radiomics in differentiating these two conditions in adults. MATERIALS AND METHODS: After a retrospective search of our institutional imaging archive, adult patients with a known diagnosis of PA or HB were included. We reviewed each patient's most recent preoperative brain magnetic resonance imaging (MRI). The solid enhancing nodule of each lesion on post-contrast T1 sequence was manually segmented. Multiple Radiomics features were then extracted from each nodule using the Pyradiomics library. Subsequently, the most predictive features were identified by feature selection models. Following this, different machine learning (ML) models were constructed based on these selected features to classify lesions as PA or HB. Finally, we evaluated the performance of each model by leave-one-out cross-validation. RESULTS: With inclusion and exclusion criteria, 34 enhancing PA nodules and 39 HB nodules were selected. A total of 115 features were extracted from each enhancing nodule. Twelve characteristics were detected as most predictive of histopathological diagnosis. Among various ML models, the neural network had the best performance in differentiating these two conditions with an AUC of 0.9 and an accuracy of 82%. CONCLUSIONS: In this retrospective study, Radiomics MRI techniques demonstrated high performance in distinguishing adult posterior fossa PA from HB. Future development of Radiomics models may advance presurgical diagnosis of these two conditions when added to routine clinical practice and thus improve patient management.

Radiological and Clinical Findings of Non-bifurcating Carotid Artery With Aberrant Course: A Case Report and Review of the Literature.

A non-bifurcating carotid artery is a rare variation in the carotid circulation. Here we present a rare case of a non-bifurcating carotid artery with an aberrant course of the internal carotid artery incidentally discovered in a patient who presented to the trauma center after a fall. To our knowledge, this is the first reported case of a non-bifurcating carotid artery with an aberrant course of the internal carotid artery. The embryonic mechanisms of this variation and the available literature regarding this condition are also reviewed. Knowing this variation is necessary before considering vascular intervention of the neck and ear surgery to avoid vascular injury and complications.

Clinical applications of diffusion-weighted sequence in brain imaging: beyond stroke.

Diffusion-weighted imaging (DWI) is a well-established MRI sequence for diagnosing early stroke and provides therapeutic implications. However, DWI yields pertinent information in various other brain pathologies and helps establish a specific diagnosis and management of other central nervous system disorders. Some of these conditions can present with acute changes in neurological status and mimic stroke. This review will focus briefly on diffusion imaging techniques, followed by a more comprehensive description of the utility of DWI in common neurological entities beyond stroke.

Navigating parental leave as a leader in radiology: Commentary on challenges and strategies.

Navigating parental leave can be challenging in all fields of medicine, but it can be especially challenging for leaders balancing clinical, research, and administrative duties. As women take on more leadership roles, we have the opportunity to better define the current challenges and identify potential strategies for navigating successful parental leave while balancing the demands of leadership. This manuscript provides a commentary on the challenges and strategies for navigating parental leave in leadership positions in radiology, an important topic for shaping how parental leave is both viewed and valued in the future. Specifically, we highlight challenges and strategies for administrative responsibilities, reporting personnel, emails, microaggressions, research, empowerment, and prioritization.

The Role of Machine Learning and Radiomics for Treatment Response Prediction in Idiopathic Normal Pressure Hydrocephalus.

Introduction Ventricular shunting remains the standard of care for patients with idiopathic normal pressure hydrocephalus (iNPH); however, not all patients benefit from the shunting. Prediction of response in advance can result in improved patient selection for ventricular shunting. This study aims to develop a machine learning predictive model for treatment response after shunt placement using the clinical and radiomics features. Methods In this retrospective pilot study, the medical records of iNPH patients who underwent ventricular shunting were evaluated. In each patient, the "idiopathic normal pressure hydrocephalus grading scale" (iNPHGS) and a "Modified Rankin Scale" were calculated before and after surgery. The subsequent treatment response was calculated as the difference between the iNPHGS scores before and after surgery. iNPHGS score reduction of two or more than two were considered as treatment response. The presurgical MRI scans were evaluated by radiologists, the ventricular systems were segmented on the T2-weighted images, and the radiomics features were extracted from the segmented ventricular system. Using Orange data mining open-source platform, different machine learning models were then developed based on the presurgical clinical features and the selected radiomics features to predict treatment response after shunt placement. Results After the implementation of the inclusion criteria, 78 patients were included in this study. One hundred twenty radiomics features were extracted, and the 12 best predictive radiomics features were selected. Using only clinical data (iNPHGS and Modified Rankin Scale), the random forest model achieved the best performance in treatment prediction with an area under the curve (AUC) of 0.71. Adding the Radiomics analysis to the clinical data improved the prediction performance, with the support vector machine (SVM) achieving the highest rank in treatment prediction with an AUC of 0.8. Adding age and sex to the analysis did not improve the prediction. Conclusion Using machine learning models for treatment response prediction in patients with iNPH is feasible with acceptable accuracy. Adding the Radiomics analysis to the clinical features can further improve the predictive performance. SVM is likely the best model for this task.

Skull base osteomyelitis imaging.

PURPOSE OF REVIEW: Skull base osteomyelitis (SBO) is a challenging entity to diagnose and treat. The goal of this review is to summarize the imaging findings of SBO and present these in the context of recent studies on imaging of SBO. RECENT FINDINGS: This review discusses the clinical presentation, pathophysiology and imaging appearances of SBO. The review further emphasizes the results of latest studies on imaging of SBO, and the role of different modalities in diagnosis and evaluation of disease course and treatment response. Brief discussion on differential diagnoses from an imaging standpoint is also included. SUMMARY: Various imaging modalities play different and complimentary roles in diagnosis and management of SBO, which are discussed in this review.

Epidemiology, clinical profile, management, and outcome of COVID-19-associated rhino-orbital-cerebral mucormycosis in 2826 patients in India - Collaborative OPAI-IJO Study on Mucormycosis in COVID-19 (COSMIC), Report 1.

Purpose: COVID-19-associated rhino-orbital-cerebral mucormycosis (ROCM) has reached epidemic proportion during India's second wave of COVID-19 pandemic, with several risk factors being implicated in its pathogenesis. This study aimed to determine the patient demographics, risk factors including comorbidities, and medications used to treat COVID-19, presenting symptoms and signs, and the outcome of management. Methods: This was a retrospective, observational study of patients with COVID-19-associated ROCM managed or co-managed by ophthalmologists in India from January 1, 2020 to May 26, 2021. Results: Of the 2826 patients, the states of Gujarat (22%) and Maharashtra (21%) reported the highest number of ROCM. The mean age of patients was 51.9 years with a male preponderance (71%). While 57% of the patients needed oxygen support for COVID-19 infection, 87% of the patients were treated with corticosteroids, (21% for > 10 days). Diabetes mellitus (DM) was present in 78% of all patients. Most of the cases showed onset of symptoms of ROCM between day 10 and day 15 from the diagnosis of COVID-19, 56% developed within 14 days after COVID-19 diagnosis, while 44% had delayed onset beyond 14 days. Orbit was involved in 72% of patients, with stage 3c forming the bulk (27%). Overall treatment included intravenous amphotericin B in 73%, functional endoscopic sinus surgery (FESS)/paranasal sinus (PNS) debridement in 56%, orbital exenteration in 15%, and both FESS/PNS debridement and orbital exenteration in 17%. Intraorbital injection of amphotericin B was administered in 22%. At final follow-up, mortality was 14%. Disease stage >3b had poorer prognosis. Paranasal sinus debridement and orbital exenteration reduced the mortality rate from 52% to 39% in patients with stage 4 disease with intracranial extension (p < 0.05). Conclusion: : Corticosteroids and DM are the most important predisposing factors in the development of COVID-19-associated ROCM. COVID-19 patients must be followed up beyond recovery. Awareness of red flag symptoms and signs, high index of clinical suspicion, prompt diagnosis, and early initiation of treatment with amphotericin B, aggressive surgical debridement of the PNS, and orbital exenteration, where indicated, are essential for successful outcome.

Cataract surgical reach: Falling short to catch white cataracts!

Purpose: The aim of this study was to know proportion of white cataracts from among patients coming for cataract surgery, and to find causes delaying uptake of cataract surgery. Methods: A hospital-based, prospective study enrolled patients of senile cataract between April 2018 and March 2019. The proportion of white cataract was calculated and underlying causes delaying uptake of cataract surgery studied. Results: White cataracts constituted 13.5% of total 3634 senile cataract patients, with gender disparity disfavoring women. Bilateral white cataract was presentation in 39 (8%) patients and lens-related glaucoma in 24 (5%) patients. Pseudophakia in the other eye was single most common cause of delay. Conclusion: A large proportion of white cataracts suggest that penetration of cataract surgical services in not reaching to the most eligible individual.