Mohammadreza Alizadeh

Purpose In this study, we will compare the diagnostic values of head CT decision rules in predicting the findings of CT scans in a prospective multicenter study in university emergency departments in Iran. Methods The primary outcome was any traumatic lesion findings in brain CT scans, and the secondary outcomes were death, the need for mechanical ventilation, and neurosurgical intervention. Decision rules including the Canadian CT Head Rule (CCHR), New Orleans Criteria (NOC), National Institute for Health and Clinical Excellence (NICE), National Emergency X-Radiography Utilization Study (NEXUS), and Neurotraumatology Committee of the World Federation of Neurosurgical Societies (NCWFNS) were compared for the main outcomes. Results In total, 434 mild TBI patients were enrolled in the study. The NCWFNS had the highest sensitivity (91.14%) and the lowest specificity (39.42%) for predicting abnormal finding in CT scan compared to other models. While the NICE obtained the lowest sensitivity (79.75%), it was associated with the highest specificity (66.67%). All model performances were improved when administered to predict neurosurgical intervention among patients with GCS 13–15. NEXUS (AUC 0.862, 95% CI 0.799–0.924) and NCWFNS (AUC 0.813, 95% CI 0.723–0.903) had the best performance among all evaluated models. Conclusion The NCWFNS and the NEXUS decision rules performed better than the CCHR and NICE guidelines for predicting any lesion in the CT imaging and neurosurgical intervention among patients with mTBI with GCS 13–15. For a subset of mTBI patients with GCS 15, the NOC criteria have higher sensitivity for abnormal CT imaging, but lower specificity and more requested CTs.

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.

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.

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.