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Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen–Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists' scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists' ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists' scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists' scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland–Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform's low inter-user variability and the high accuracy of its T1c and FLAIR AI models. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) of the brain has been implemented to evaluate multiple intracranial pathologies. Non-contrast T2-weighted images are a routinely acquired sequence in almost all neuroimaging protocols. It is not uncommon to encounter various cerebrovascular lesions incidentally on brain imaging. Neuroradiologists should evaluate the routine T2-weighted images for incidental cerebrovascular lesions, irrespective of the primary indication of the study. Vascular structures typically demonstrate a low signal flow-void on the T2-weighted images. In our experience, large cerebrovascular abnormalities are easily visible to a typical neuroradiologist. In this article, we present the spectrum of the characteristic imaging appearance of various intracranial cerebrovascular lesions on routine non-contrast T2-weighted MRI. These include aneurysm, arteriovenous malformation, arterial occlusion, capillary telangiectasia, cavernous malformation, dural arteriovenous fistula, moyamoya, proliferative angiopathy, and vein of Galen malformation. [ABSTRACT FROM AUTHOR]

Previous neuroimaging studies have suggested that obsessive–compulsive disorder (OCD) is associated with altered resting-state functional connectivity of the cerebellum. In this study, we aimed to describe the most significant and reproducible microstructural abnormalities and cerebellar changes associated with obsessive–compulsive disorder (OCD) using diffusion tensor imaging (DTI) investigations. PubMed and EMBASE were searched for relevant studies using the PRISMA 2020 protocol. A total of 17 publications were chosen for data synthesis after screening titles and abstracts, full-text examination, and executing the inclusion criteria. The patterns of cerebellar white matter (WM) integrity loss, determined by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) metrics, varied across studies and symptoms. Changes in fractional anisotropy (FA) values were described in six publications, which were decreased in four and increased in two studies. An increase in diffusivity parameters of the cerebellum (i.e., MD, RD, and AD) in OCD patients was reported in four studies. Alterations of the cerebellar connectivity with other brain areas were also detected in three studies. Heterogenous results were found in studies that investigated cerebellar microstructural abnormalities in correlation with symptom dimension or severity. OCD's complex phenomenology may be characterized by changes in cerebellar WM connectivity across wide networks, as shown by DTI studies on OCD patients in both children and adults. Classification features in machine learning and clinical tools for diagnosing OCD and determining the prognosis of the disorder might both benefit from using cerebellar DTI data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simple Summary: Progression/recurrence, pseudoprogression, and radionecrosis are all scenarios that can be expected during the treatment course of glioma and GBM. Although MRI, PET, CT, and MRS have shown some capabilities in differentiating these conditions, there is still a considerable need for the emergence of state-of-the-art techniques to assist field professionals. Here, we introduce radiomics, a process that extracts many features from medical images using data characterization algorithms and a promising tool to differentiate these scenarios. The results could significantly impact patients' care by enhancing the understanding and accuracy of post-treatment follow-ups in brain cancer patients. Glioma and glioblastoma multiform (GBM) remain among the most debilitating and life-threatening brain tumors. Despite advances in diagnosing approaches, patient follow-up after treatment (surgery and chemoradiation) is still challenging for differentiation between tumor progression/recurrence, pseudoprogression, and radionecrosis. Radiomics emerges as a promising tool in initial diagnosis, grading, and survival prediction in patients with glioma and can help differentiate these post-treatment scenarios. Preliminary published studies are promising about the role of radiomics in post-treatment glioma/GBM. However, this field faces significant challenges, including a lack of evidence-based solid data, scattering publication, heterogeneity of studies, and small sample sizes. The present review explores radiomics's capabilities in following patients with glioma/GBM status post-treatment and to differentiate tumor progression, recurrence, pseudoprogression, and radionecrosis. [ABSTRACT FROM AUTHOR]

Simple Summary: Low-grade gliomas (LGGs) are relatively slow-growing primary brain tumors where the clinical criteria for tumor diagnosis and progression assessment include both qualitative and quantitative analytics. The Response Assessment in Neuro-Oncology (RANO) criteria for LGGs define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator's discretion of the perpendicular diameter of the largest tumor cross-section. However, sources of error exist, including the limitation of 2D quantification, operator selection of both the tumor cross-section and perpendicular diameters, and the inability to quantify satellite tumor components. The aim of this retrospective study was to assess the accuracy and reproducibility of RANO in LGGs. In a heterogeneous population of 63 participants with different subtypes of LGGs, we showed that the accuracy of RANO compared to visual and volumetric gold standards was, at best, 67% and 57%, respectively. Reproducibility varied widely, even between board-certified neuroradiologists. Our results suggest that advanced approaches, such as computer-assisted tumor segmentation and annotation tools, are necessary to accurately assess LGG progression by reducing human variability. Purpose: The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator's discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG. Materials and Methods: A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment. Results: RANO product measurements had poor-to-moderate inter-operator reproducibility (r2 = 0.28–0.82; coefficient of variance (CV) = 44–110%; mean percent difference (diff) = 0.4–46.8%) and moderate-to-excellent intra-operator reproducibility (r2 = 0.71–0.88; CV = 31–58%; diff = 0.3–23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02). Conclusion: RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management. [ABSTRACT FROM AUTHOR]

A 30-year-old woman with idiopathic intracranial hypertension experienced worsening headaches and decreasing vision in her left eye. She underwent an uncomplicated ventriculoperitoneal shunt procedure but the following day was found to have cerebral venous sinus thrombosis. Treatment included venous sinus thrombectomy and anticoagulation. She had a favourable clinical outcome. Extensive evaluation including testing for thrombophilia was unremarkable. Potential causes for this rare association are discussed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Radiomics now has significant momentum in the era of precision medicine. Glioma is one of the pathologies that has been extensively evaluated by radiomics. However, this technique has not been incorporated into clinical practice. In this systematic review, we selected and reviewed the published studies about glioma grading by radiomics to evaluate this technique's feasibility and its challenges. Material and Methods: Using seven different search strings, we considered all published English manuscripts from 2015 to September 2020 in PubMed, Embase, and Scopus databases. After implementing the exclusion and inclusion criteria, the final papers were selected for the methodological quality assessment based on our in-house Modified Radiomics Standard Scoring (RQS) containing 43 items (minimum score of 0, maximum score of 44). Finally, we offered our opinion about the challenges and weaknesses of the selected papers. Results: By our search, 1,177 manuscripts were found (485 in PubMed, 343 in Embase, and 349 in Scopus). After the implementation of inclusion and exclusion criteria, 18 papers remained for the final analysis by RQS. The total RQS score ranged from 26 (59% of maximum possible score) to 43 (97% of maximum possible score) with a mean of 33.5 (76% of maximum possible score). Conclusion: The current studies are promising but very heterogeneous in design with high variation in the radiomics software, the number of extracted features, the number of selected features, and machine learning models. All of the studies were retrospective in design; many are based on small datasets and/or suffer from class imbalance and lack of external validation data-sets. [ABSTRACT FROM AUTHOR]

As human life expectancy increases, there is an increased prevalence of neurodegenerative disorders and dementia. There are many ongoing research trials for early diagnosis and management of dementia, and neuroimaging is a critical part of such studies. However, conventional neuroimaging often fails to provide enough diagnostic findings in patients with neurodegenerative disorders. In this context, different MRI sequences are currently under investigation to facilitate the accurate diagnosis of such disorders. Susceptibility‐weighted imaging (SWI) is an innovative MRI technique that utilizes "magnitude" and "phase" images to produce an image contrast that is sensitive for the detection of susceptibility differences of the tissues. As many neurodegenerative disorders are associated with accelerated iron deposition and/or microhemorrhages in different parts of the brain, SWI can be applied to detect these diagnostic clues. For instance, in cerebral amyloid angiopathy, SWI can demonstrate cortical microhemorrhages, which are predominantly in the frontal and parietal regions. Or in Parkinson disease, abnormal swallow‐tail sign on high‐resolution SWI is highly diagnostic. Also, SWI is a useful sequence to detect the low signal intensity of precentral cortices in patients with amyotrophic lateral sclerosis. Being familiar with SWI findings in neurodegenerative disorders is critical for an accurate diagnosis. In this paper, the authors review the technical parameters of SWI, physiologic, and pathologic iron deposition in the brain, and the role of SWI in the evaluation of neurodegenerative disorders in daily practice. [ABSTRACT FROM AUTHOR]

Parapharyngeal space (PPS) masses are relatively rare lesions of the head and neck, and account for 0.5–1.5% of head and neck lesions. The most common lesion to occur in the PPS is a benign salivary neoplasm, typically pleomorphic adenoma either from the deep parotid or from ectopic parotid tissue rests within the PPS. A calcified or ossified mass in this location is exceedingly rare, but a calcified variant of pleomorphic adenoma has been reported. In this study, we present a patient with a heavily calcified PPS mesenchymal chondrosarcoma with an unusual presentation. We discuss the imaging and pathologic findings followed by a review of the current literature. [ABSTRACT FROM AUTHOR]

Intraventricular melanoma is a very rare and highly malignant disease. Safe resection is the mainstay of treatment, but no standard guidelines exist for adjuvant therapy. Early histologic and molecular diagnosis is key for improved survival. [ABSTRACT FROM AUTHOR]

The skeleton is the third most common site for metastasis overall, after the lungs and liver. Accurate diagnosis of osseous metastasis is critical for initial staging, treatment planning, restaging, treatment monitoring, and survival prediction. Currently, 99mTc-methylene diphosphonate whole-body scanning is the cornerstone of imaging to detect osseous metastasis. Although 18F-sodium fluoride (18F-NaF) was one of the oldest medical tracers for this purpose, it was replaced by other tracers because of their better physical properties, until recently. Continued development of PET scanners has opened a new era for 18F-NaF, and given its higher sensitivity, there have been increasing applications in imaging. In this review, we will discuss the history, technical aspects, radiobiology, and biodistribution of this tracer. Finally, we compare the accuracy of 18F-NaF PET with other conventional imaging methods for detection of osseous metastasis. [ABSTRACT FROM AUTHOR]

Leptomeningeal metastasis is extremely rare in patients with ovarian cancer, but should be considered in patients presenting with neurologic deficits such as cauda equine syndrome. Given its poor prognosis and lack of data currently on management, additional studies are needed to optimize treatment regimens and improve outcomes. [ABSTRACT FROM AUTHOR]

The RAPID© software is the most commonly used computed tomography perfusion (CTP) software in stroke centers. It is estimated that about 1300 hospitals in the world are using this software for decision-making in ischemic stroke. The software provides the estimated volume of infarction and ischemic penumbra, so it is the backbone of treatment planning in these patients. In this manuscript, we present two cases of subacute infarction with misleading CTP using RAPID© software. We believe that given the popularity of this software and increasing application of CTP in subacute infarction, this pitfall is likely underdiagnosed in many patients. In a subacute phase of infarction, we recommend diffusion-weighted imaging magnetic resonance imaging (DWI-MRI) for estimation of infarction to avoid this pitfall and possible mismanagement. [ABSTRACT FROM AUTHOR]

Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple disciplines including medicine. Clinical medicine suffers from a lack of AI-based applications, potentially due to lack of awareness of AI methodology. Future collaboration between computer scientists and clinicians is critical to maximize the benefits of transformative technology in this field for patients. To illustrate, we describe AI-based advances in the diagnosis and management of gliomas, the most common primary central nervous system (CNS) malignancy. Methods: Presented is a succinct description of foundational concepts of AI approaches and their relevance to clinical medicine, geared toward clinicians without computer science backgrounds. We also review novel AI approaches in the diagnosis and management of glioma. Results: Novel AI approaches in gliomas have been developed to predict the grading and genomics from imaging, automate the diagnosis from histopathology, and provide insight into prognosis. Conclusion: Novel AI approaches offer acceptable performance in gliomas. Further investigation is necessary to improve the methodology and determine the full clinical utility of these novel approaches. [ABSTRACT FROM AUTHOR]

Objective: Unusual clinical course. Background: Rapunzel syndrome is a rare condition involving the extension of bezoars from the stomach to the distal gastrointestinal tract. Laparotomy remains the gold standard treatment for this condition because of the size of the bezoars. Although bacterial peritonitis is a known complication of laparotomy in Rapunzel syndrome, very few cases of post-surgical fungal peritonitis have been reported in these patients. Case Report: In this case report, we present a case of Rapunzel syndrome complicated by post-surgical fungal peritonitis and formation of fungus balls. To our knowledge, fungal peritonitis with fungus balls has never been reported in the English literature as a Rapunzel syndrome complication. Conclusions: It is important to cover Candida and other fungi with an antifungal regimen in pediatric patients with Rapunzel syndrome pre- and post-surgery. In addition, prolonged fever and septic symptoms post-surgery warrant a search for peritoneal fungus balls that are not simply responsive to anti-fungal therapy and may necessitate repeat laparotomy. [ABSTRACT FROM AUTHOR]

CT perfusion (CTP) is an evolving protocol for stroke evaluation in many hospitals, but there are several pitfalls in CT perfusion. Herein I present a patient suspicious of brain infarction under "stroke code". CT perfusion was initially visually interpreted and because of obvious asymmetry between the right and left cerebral hemispheres the interpretation was consistent with right cerebral ischemia. CT angiogram (CTA) did not demonstrate significant vascular stenosis. Subsequent electroencephalography (EEG) was consistent with status epilepticus from the left cerebral hemisphere. Since more and more CTPs are nowperformed in acute setting of code stroke more patients are being imaged with ongoing seizure with increased perfusion in epileptogenic brain parenchyma. This is different from the conventional concept of hypo perfusion of the involved brain in CTP performed in the "post-ictal" phase. The interpreting radiologist should be informed about the patient symptoms and should avoid solo visual assessment of CT perfusion in patients under the "stroke code". [ABSTRACT FROM AUTHOR]

Hybrid imaging with integrated positron emission tomography (PET) and magnetic resonance imaging (MRI) combines the advantages of the high-resolution anatomic data from MRI and functional imaging data from PET, and has the potential to improve the diagnostic evaluation of various types of cancers. The clinical oncologic applications of this newest hybrid imaging technology are evolving and substantial efforts are underway to define the role of PET/MRI in routine clinical use. The current published literature suggests that PET/MRI may play an important role in the evaluation of patients with certain types of malignancies, involving anatomic locations such as the pelvis and the liver. The purpose of this article is to review the current published PET/MRI literature in specific body oncologic applications. In addition, PET/MRI protocols and some of the technical issues of this hybrid imaging will be briefly discussed. J. Magn. Reson. Imaging 2016;44:265-276. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s12311-021-01355-3 B Correction to: The Cerebellum b https://doi.org/10.1007/s12311-021-01355-3 In the original manuscript, the authors missed to include Dr Mohammad Hadi Aarabi as one of the authors. It has been agreed by authors to add Dr. Mohammad Hadi Aarabi as the eighth author and he is affiliated to Department of Neuroscience (DNS), Padova Neuroscience Center-PNC, University of Padova, Padua, Italy. [Extracted from the article]

Antidepressant effects of magnetic resonance imaging (MRI) based stimulation have been reported in animal studies, but no human studies are available on subjects with major depressive disorder. Here, the efficacy of two diagnostic MRI protocols (echo-planar diffusion-weighted imaging (DWI) and T1-weighted imaging) was assessed in patients with major depressive disorder. In this double-blind randomized clinical trial, 51 patients with clinically proven major depressive disorder were randomly enrolled into three equal groups. All patients were receiving a selective serotonin reuptake inhibitor as the only antidepressant treatment. The first group received echo-planar DW stimulation (DWI group), the second group received T1-weighted stimulation (T1 group), and the third group experienced a similar condition without receiving any magnetic stimulation (sham group). The Hamilton rating scale for depression (HAMD24) and Beck depression inventory (BDI) were used to assess the effect of MR stimulation on depressive symptoms. In comparison to baseline, mean HAMD24 and BDI scores significantly ( p < 0.001) decreased in the DWI (by 35% and 39%) and T1 (by 38% and 39%) groups 2 weeks after MR stimulation. In the sham group, reduction in HAMD24 (19%, p = 0.04) and BDI score (15%, p = 0.07) were lower than the MR stimulation groups. Two weeks after the MR experiments, changes in mean HAMD24 score and BDI score were significantly ( p < 0.05) higher in subjects treated with MR stimulation (DWI or T1) vs. sham group. In conclusion, this study demonstrated the antidepressant effects of DWI and T1 MRI protocols. Our results may point to usefulness of MR stimulation for clinical use in patients with major depressive disorder. [ABSTRACT FROM AUTHOR]

The cover image is based on the Case Report I Cauda Equina Syndrome in an Ovarian Malignant-Mixed Müllerian Tumor with Leptomeningeal Spread i by Joshua Bernstock, Gustavo Chagoya, Andrew Janssen et al., https://doi.org/10.1002/ccr3.2472 GLO:H4ZE/01dec19:ccr32659-toc-0001.jpg PHOTO (COLOR): . gl. [Extracted from the article]

Protein SUMOylation is a dynamic post-translational modification which is involved in a diverse set of physiologic processes throughout the cell. Of note, SUMOylation also plays a role in the pathobiology of a myriad of cancers, one of which is glioblastoma (GBM). Accordingly, herein, we review core aspects of SUMOylation as it relates to GBM and in so doing highlight putative methods/modalities capable of therapeutically engaging the pathway for treatment of this deadly neoplasm. [ABSTRACT FROM AUTHOR]