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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.

Becoming aware of one's own states is a fundamental aspect for self-monitoring, allowing us to adjust our beliefs of the world to the changing context. Previous evidence points out to the key role of the anterior insular cortex (aIC) in evaluating the consequences of our own actions, especially whenever an error has occurred. In the present study, we propose a new multimodal protocol combining electrical stimulation mapping (ESM) and functional magnetic resonance imaging (fMRI) to explore the functional role of the aIC for self-monitoring in patients undergoing awake brain surgery. Our results using a modified version of the Stroop task tackling metacognitive abilities revealed new direct evidence of the involvement of the aIC in monitoring our performance, showing increased difficulties in detecting action-outcome mismatches when stimulating a cortical site located at the most posterior part of the aIC as well as significant BOLD activations at this region during outcome incongruences for self-made actions. Based on these preliminary results, we highlight the importance of assessing the aIC's functioning during tumor resection involving this region to evaluate metacognitive awareness of the self in patients undergoing awake brain surgery. In a similar vein, a better understanding of the aIC's role during self-monitoring may help shed light on action/outcome processing abnormalities reported in several neuropsychiatric disorders such as schizophrenia, anosognosia for hemiplegia or major depression.

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.

Contains fulltext : 248752.pdf (Publisher’s version ) (Open Access) Background and Purpose: Brain tumors can result in displacement or destruction of important white matter tracts such as the inferior fronto-occipital fascicle (IFOF). Diffusion tensor imaging (DTI) can assess the extent of this effect and potentially provide neurosurgeons with an accurate map to guide tumor resection; analyze IFOF displacement patterns in temporoinsular gliomas based on tumor grading and topography in the temporal lobe; and assess whether these patterns follow a predictable pattern, to assist in maximal tumor resection while preserving IFOF function. Methods: Thirty-four patients with temporal gliomas and available presurgical MRI were recruited. Twenty-two had insula infiltration. DTI deterministic region of interest (ROI)-based tractography was performed using commercial software. Tumor topographic imaging characteristics analyzed were as follows: location in the temporal lobe and extent of extratemporal involvement. Qualitative tractographic data obtained from directional DTI color maps included type of involvement (displaced/edematous-infiltrated/destroyed) and displacement direction. Quantitative tractographic data of ipsi- and contralateral IFOF included whole tract volume, fractional anisotropy, and fractional anisotropy of a 2-dimensional coronal ROI on the tract at the point of maximum tumor involvement. Results: The most common tract involvement pattern was edematous/infiltrative displacement. Displacement patterns depended on main tumor location in the temporal lobe and presence of insular involvement. All tumors showed superior displacement pattern. In lateral tumors, displacement tendency was medial. In medial tumors, displacement tendency was lateral. When we add insular involvement, the tendency was more medial displacement. A qualitative and quantitative assessment supported these results. Conclusions: IFOF displacement patterns are reproducible and suitable for temporoinsular gliomas presurgical planning. 9 p.

BACKGROUND: The significance of upfront systemic therapies as an alternative to whole brain radiotherapy (WBRT) for multiple brain metastases (BM) is debatable. Our purpose is to investigate if peritumoral edema could predict the intracranial response to systemic chemotherapy (chemo) in patients with advanced non-squamous non-small cell lung cancer (non-SQ-NSCLC) and synchronous multiple BM. METHODS: In this observational cohort study, we evaluated the outcome of 28 patients with multiple BM (≥3) treated with chemo based on cisplatin/carboplatin plus pemetrexed (chemo, group A, n=17) or WBRT plus subsequent chemo (group B, n=11). The intracranial response, assessed by the response assessment neuro-oncology (RANO) BM criteria, was correlated with the degree of BM-associated edema estimated by the maximum diameter ratio among fluid attenuated inversion recovery (FLAIR) and gadolinium-enhanced T1WI (T1Gd) per each BM at the baseline brain magnetic resonance imaging (MRI). RESULTS: No differences were observed in baseline characteristics between both groups, except for the number of patients under steroid treatment that was clearly superior in group B (P=0.007). Median OS was similar between groups. Regarding FLAIR/T1Gd ratio (F/Gd), patients treated with chemo alone exhibited significantly higher values (P=0.001) in those who developed intracranial progression disease (PD) (2.80±0.32 mm), compared with those who achieved partial response (PR) (1.30±0.11 mm) or stable disease (SD) (1.35±0.09 mm). In patients treated with WBRT, F/Gd ratio was not predictive of response. CONCLUSIONS: Peritumoral edema estimated by F/Gd ratio appears a promising predictive tool to identify oligosymptomatic patients with multiple BM in whom WBRT can be postponed.

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.

Graphical abstract, Highlights • Patients with late-life MDD show lower global LC connectivity in an oddball task. • Lower LC connectivity was observed with the ACC, fusiform gyrus and cerebellum. • LC-ACC connectivity correlated with two different measures of depression severity., The Locus Coeruleus (LC) is the major source of noradrenergic neurotransmission. Structural alterations in the LC have been observed in neurodegenerative disorders and at-risk individuals, although functional connectivity studies between the LC and other brain areas have not been yet performed in these populations. Patients with late-life major depressive disorder (MDD) are indeed at increased risk for neurodegenerative disorders, and here we investigated LC connectivity in late-life MDD in comparison to individuals with amnestic type mild cognitive impairment (aMCI) and healthy controls (HCs). We assessed 20 patients with late-life MDD, 16 patients with aMCI, and 26 HCs, who underwent a functional magnetic resonance scan while performing a visual oddball task. We assessed task-related modulations of LC connectivity (i.e., Psychophysiological Interactions, PPI) with other brain areas. A T1-weighted fast spin-echo sequence for LC localization was also obtained. Patients with late-life MDD showed lower global connectivity during target detection in a cluster encompassing the right caudal LC. Specifically, we observed lower LC connectivity with the left anterior cingulate cortex (ACC), the right fusiform gyrus, and different cerebellar clusters. Moreover, alterations in LC-ACC connectivity correlated negatively with depression severity (i.e., Geriatric Depression Scale and number of recurrences). Reduced connectivity of the LC during oddball performance seems to specifically characterize patients with late-life MDD, but not other populations of aged individuals with cognitive alterations. Such alteration is associated with different measures of disease severity, such as the current presence of symptoms and the burden of disease (number of recurrences).