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Standard DSC-PWI analyses are based on concrete parameters and values, but an approach that contemplates all points in the time-intensity curves and all voxels in the region-of-interest may provide improved information, and more generalizable models. Therefore, a method of DSC-PWI analysis by means of normalized time-intensity curves point-by-point and voxel-by-voxel is constructed, and its feasibility and performance are tested in presurgical discrimination of glioblastoma and metastasis.In this retrospective study, patients with histologically confirmed glioblastoma or solitary-brain-metastases and presurgical-MR with DSC-PWI (August 2007-March 2020) were retrieved. The enhancing tumor and immediate peritumoral region were segmented on CE-T1wi and coregistered to DSC-PWI. Time-intensity curves of the segmentations were normalized to normal-appearing white matter. For each participant, average and all-voxel-matrix of normalized-curves were obtained. The 10 best discriminatory time-points between each type of tumor were selected. Then, an intensity-histogram analysis on each of these 10 time-points allowed the selection of the best discriminatory voxel-percentile for each. Separate classifier models were trained for enhancing tumor and peritumoral region using binary logistic regressions.A total of 428 patients (321 glioblastomas, 107 metastases) fulfilled the inclusion criteria (256 men; mean age, 60 years; range, 20-86 years). Satisfactory results were obtained to segregate glioblastoma and metastases in training and test sets with AUCs 0.71-0.83, independent accuracies 65-79%, and combined accuracies up to 81-88%.This proof-of-concept study presents a different perspective on brain MR DSC-PWI evaluation by the inclusion of all time-points of the curves and all voxels of segmentations to generate robust diagnostic models of special interest in heterogeneous diseases and populations. The method allows satisfactory presurgical segregation of glioblastoma and metastases.• An original approach to brain MR DSC-PWI analysis, based on a point-by-point and voxel-by-voxel assessment of normalized time-intensity curves, is presented. • The method intends to extract optimized information from MR DSC-PWI sequences by impeding the potential loss of information that may represent the standard evaluation of single concrete perfusion parameters (cerebral blood volume, percentage of signal recovery, or peak height) and values (mean, maximum, or minimum). • The presented approach may be of special interest in technically heterogeneous samples, and intrinsically heterogeneous diseases. Its application enables satisfactory presurgical differentiation of GB and metastases, a usual but difficult diagnostic challenge for neuroradiologist with vital implications in patient management.

Non-invasive differential diagnosis of brain tumours is currently based on the assessment of tumour vascularity through magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, given its limited accuracy, reaching a definitive diagnosis often requires complex neurosurgical interventions that compromise the patients’ quality of life. We applied deep learning on DSC images from histology-confirmed patients with glioblastoma, metastasis or lymphoma, the three most common brain malignancies. The convolutional neural network trained on ~ 50,000 voxels from 40 patients provided intra-tumour probability maps that yielded clinical-grade diagnosis. Performance was tested in 400 additional cases and an external validation cohort (n = 128). The tool reached a three-way accuracy of 0.78, superior to standard diagnosis with cerebral blood volume (0.55) and percentage of signal recovery (0.59) perfusion metrics. Our open-access software, Brain Enhancing Region Radiological analysis (BERRY), demonstrates the potential of voxel-wise probability maps for differential diagnosis of brain tumours using standard-of-care MRI.

Background and purpose SARS-CoV-2 causes multiorgan disease due to altered coagulability and microangiopathy. Patients may have an increased risk of cerebrovascular accidents (CVA). Our objective was to analyze clinical and neuroimaging characteristics of patients with ischemic CVA during the pandemic peak in our region, in order to identify atypical presentations. Methods We performed a cross-sectional analysis of patients admitted under code-stroke protocol to our center with a final diagnosis of ischemic brain infarction. We analyzed the main imaging and demographic characteristics and reviewed neuroimaging for atypical presentations. Results One-hundred patients with confirmed ischemic CVA were included. Nineteen had positive polymerase chain reaction testing for SARS-CoV-2 on admission. These patients had a lower prevalence of proximal arterial occlusion on imaging, higher in-hospital mortality, and worse baseline disability. No differences were identified in affected vascular territory, volume of infarction, initial CT stroke score, prevalence of hemorrhagic transformation, gender, age, cardiovascular risk factors, time to admission, symptom severity on entry, or decision to treat with thrombolysis or mechanical thrombectomy. Prevalence of COVID-19 in our code-stroke sample was higher than that for our province during this time period. Conclusion The COVID-19 group had more in-hospital mortality, less proximal arterial occlusion on CT or MR angiography, and lower baseline modified Rankin Scale score. We suggest a possibly higher proportion of microangiopathic involvement or undetected distal large-vessel occlusion in the COVID-19 stroke group. Excess mortality was explained by severe respiratory failure. Otherwise, stroke patients with COVID-19 did not differ demographically or clinically from those without the illness.

BACKGROUND AND PURPOSE: DSC-PWI has demonstrated promising results in the presurgical diagnosis of brain tumors. While most studies analyze specific parameters derived from time-intensity curves, very few have directly analyzed the whole curves. The aims of this study were the following: 1) to design a new method of postprocessing time-intensity curves, which renders normalized curves, and 2) to test its feasibility and performance on the diagnosis of primary central nervous system lymphoma. MATERIALS AND METHODS: Diagnostic MR imaging of patients with histologically confirmed primary central nervous system lymphoma were retrospectively reviewed. Correlative cases of glioblastoma, anaplastic astrocytoma, metastasis, and meningioma, matched by date and number, were retrieved for comparison. Time-intensity curves of enhancing tumor and normal-appearing white matter were obtained for each case. Enhancing tumor curves were normalized relative to normal-appearing white matter. We performed pair-wise comparisons for primary central nervous system lymphoma against the other tumor type. The best discriminatory time points of the curves were obtained through a stepwise selection. Logistic binary regression was applied to obtain prediction models. The generated algorithms were applied in a test subset. RESULTS: A total of 233 patients were included in the study: 47 primary central nervous system lymphomas, 48 glioblastomas, 39 anaplastic astrocytomas, 49 metastases, and 50 meningiomas. The classifiers satisfactorily performed all bilateral comparisons in the test subset (primary central nervous system lymphoma versus glioblastoma, area under the curve = 0.96 and accuracy = 93%; versus anaplastic astrocytoma, 0.83 and 71%; versus metastases, 0.95 and 93%; versus meningioma, 0.93 and 96%). CONCLUSIONS: The proposed method for DSC-PWI time-intensity curve normalization renders comparable curves beyond technical and patient variability. Normalized time-intensity curves performed satisfactorily for the presurgical identification of primary central nervous system lymphoma.

BackgroundAlexander disease, an autosomal dominant leukodystrophy, is caused by missense mutations in GFAP. Although mostly diagnosed in children, associated with severe leukoencephalopathy, milder adult forms also exist.MethodsA family affected by adult-onset spastic paraplegia underwent neurological examination and cerebral MRI. Two patients were sequenced by whole exome sequencing (WES). A candidate variant was functionally tested in an astrocytoma cell line.ResultsThe novel variant in GFAP (Glial Fibrillary Acidic Protein) N-terminal head domain (p.Gly18Val) cosegregated in multiple relatives (LOD score: 2.7). All patients, even those with the mildest forms, showed characteristic signal changes or atrophy in the brainstem and spinal cord MRIs, and abnormal MRS. In vitro, this variant did not cause significant protein aggregation, in contrast to most Alexander disease mutations characterised so far. However, cell area analysis showed larger size, a feature previously described in patients and mouse models.ConclusionWe suggest that this variant causes variable expressivity and an attenuated phenotype of Alexander disease type II, probably associated with alternative pathogenic mechanisms, that is, astrocyte enlargement. GFAP analysis should be considered in adult-onset neurological presentations with pyramidal and bulbar symptoms, in particular when characteristic findings, such as the tadpole sign, are present in MRI. WES is a powerful tool to diagnose atypical cases.

Matemàtiques i informàtica; Neurologia; Oncologia Matemáticas e informática; Neurología; Oncología Mathematics and computing; Neurology; Oncology Glioblastoma is the most common primary brain tumor. Standard therapy consists of maximum safe resection combined with adjuvant radiochemotherapy followed by chemotherapy with temozolomide, however prognosis is extremely poor. Assessment of the residual tumor after surgery and patient stratification into prognostic groups (i.e., by tumor volume) is currently hindered by the subjective evaluation of residual enhancement in medical images (magnetic resonance imaging [MRI]). Furthermore, objective evidence defining the optimal time to acquire the images is lacking. We analyzed 144 patients with glioblastoma, objectively quantified the enhancing residual tumor through computational image analysis and assessed the correlation with survival. Pathological enhancement thickness on post-surgical MRI correlated with survival (hazard ratio: 1.98, p

The aim of this work is to review the spectrum of sinonasal lesions that extend to the endocranium and to present key points that may narrow the differential diagnosis. The most frequent sinonasal lesions that extend into the endocranium are malignant; however, benign entities are not unusual. Imaging diagnosis is difficult because malignant lesions and benign entities share similar clinical, epidemiologic, and imaging features. Tumor features in relation to bone, intratumor homogeneity and structure, magnetic resonance imaging signal, along with clinical and epidemiologic aspects may allow an appropriate diagnostic focus with important management implications.

The skull vault, formed by the flat bones of the skull, has a limited spectrum of disease that lies between the fields of neuro- and musculoskeletal radiology. Its unique abnormalities, as well as other ubiquitous ones, present particular features in this location. Moreover, some benign entities in this region may mimic malignancy if analyzed using classical bone-tumor criteria, and proper patient management requires being familiar with these presentations. This article is structured as a practical review offering a systematic diagnostic approach to focal calvarial lesions, broadly organized into four categories: (1) pseudolesions: arachnoid granulations, meningo-/encephaloceles, vascular canals, frontal hyperostosis, parietal thinning, parietal foramina, and sinus pericrani; (2) lytic: fibrous dysplasia, epidermal inclusion and dermoid cysts, eosinophilic granuloma, hemangioma, aneurysmal bone cyst, giant cell tumor, metastasis, and myeloma; (3) sclerotic: osteomas, osteosarcoma, and metastasis; (4) transdiploic: meningioma, hemangiopericytoma, lymphoma, and metastasis, along with other less common entities. Tips on the potential usefulness of functional imaging techniques such as MR dynamic susceptibility (T2*) perfusion, MR spectroscopy, diffusion-weighted imaging, and PET imaging are provided.

Despite a large cohort of 103 patients with COVID-19, the authors found a large number of symptomatic patients with negative neuroimaging findings, and no conclusions can be drawn concerning concrete associations between neuroimaging and COVID-19. The rapid spread of the coronavirus disease 2019 (COVID-19) pandemic has shaken hospitals worldwide. Some authors suggest that neurologic involvement could further complicate the disease. This descriptive study is a cross-sectional review of 103 patients diagnosed with COVID-19 who underwent neuroimaging (of a total of 2249 patients with COVID-19 in our center). Analyzed variables were neurologic symptoms and acute imaging findings. The most frequent symptoms that motivated neuroimaging examinations were mild nonfocal neurologic symptoms, code stroke (refers to patients presenting with signs and symptoms of stroke whose hyperacute assessment and care is prioritized), focal neurologic symptoms, postsedation encephalopathy, and seizures. No cases of encephalitis or direct central nervous system involvement were detected. Thirteen patients presented with acute ischemic events, and 7, with hemorrhagic events; however, most reported multiple vascular risk factors. Despite the large cohort of patients with COVID-19, we found a large number of symptomatic patients with negative neuroimaging findings, and no conclusions can be drawn concerning concrete associations between neuroimaging and COVID-19.

Alexander disease, an autosomal dominant leukodystrophy, is caused by missense mutations inA family affected by adult-onset spastic paraplegia underwent neurological examination and cerebral MRI. Two patients were sequenced by whole exome sequencing (WES). A candidate variant was functionally tested in an astrocytoma cell line.The novel variant inWe suggest that this variant causes variable expressivity and an attenuated phenotype of Alexander disease type II, probably associated with alternative pathogenic mechanisms, that is, astrocyte enlargement.

We report the case of a 52-year-old man with a history of acute myeloid leukemia who presented to the emergency room with fatigue, dyspnea and chest pain. Initial routine examination showed signs of right heart failure. A CT was requested to rule out pulmonary embolism. The imaging revealed the presence of a cardiac infiltrative mass involving the heart’s right free wall that proved to be a chloroma.

A patient in his 80s was brought to our emergency department with severe abdominal pain, hypotension and bradycardia. Initial laboratory findings revealed lactic acidosis. An abdominal CT was requested to rule out intestinal ischaemia or visceral perforation. The CT showed blood-contrast levels in the superior vena cava and right auricle (figure 1, arrows in A) with minimal contrast flow …