Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty.

BACKGROUND: International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages. OBJECTIVES: To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine-learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism. MATERIALS: Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2-year follow-up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 ("Clin1"); (2) MRI visual reading blinded to the clinical diagnosis ("MRI"); (3) both MRI visual reading and clinical criteria at V1 ("MRI and Clin1"), and (4) a machine-learning algorithm ("Algorithm"). The gold standard diagnosis was established by expert consensus after a 2-year follow-up. RESULTS: We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit ("Clin1": balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% ("MRI": 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit ("MRI and Clin1": 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% ("Algorithm": 76.1%; P = 0.08). CONCLUSION: Our study shows the use of MRI analysis, whether by visual reading or machine-learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Neuromelanin-Sensitive Magnetic Resonance Imaging Changes in the Locus Coeruleus/Subcoeruleus Complex in Patients with Typical and Atypical Parkinsonism.

BACKGROUND: The locus coeruleus/subcoeruleus complex (LC/LsC) is a structure comprising melanized noradrenergic neurons. OBJECTIVE: To study the LC/LsC damage across Parkinson's disease (PD) and atypical parkinsonism in a large group of subjects. METHODS: We studied 98 healthy control subjects, 47 patients with isolated rapid eye movement sleep behavior disorder (RBD), 75 patients with PD plus RBD, 142 patients with PD without RBD, 19 patients with progressive supranuclear palsy (PSP), and 19 patients with multiple system atrophy (MSA). Twelve patients with MSA had proven RBD. LC/LsC signal intensity was derived from neuromelanin magnetic resonance imaging using automated software. RESULTS: The signal intensity was reduced in all parkinsonian syndromes compared with healthy control subjects, except in PD without RBD. The signal intensity decreased as age increased. Moreover, the signal intensity was lower in MSA than in isolated RBD and PD without RBD groups. In PD, the signal intensity correlated negatively with the percentage of REM sleep without atonia. There were no differences in signal intensity between PD plus RBD, PSP, and MSA. CONCLUSIONS: Neuromelanin signal intensity was reduced in all parkinsonian disorders, except in PD without RBD. The presence of RBD in parkinsonian disorders appears to be associated with lower neuromelanin signal intensity. Furthermore, lower LC/LsC signal changes in PSP could be partly caused by the effect of age. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Regional Selectivity of Neuromelanin Changes in the Substantia Nigra in Atypical Parkinsonism.

BACKGROUND: Neurodegeneration in the substantia nigra pars compacta (SNc) in parkinsonian syndromes may affect the nigral territories differently. OBJECTIVE: The objective of this study was to investigate the regional selectivity of neurodegenerative changes in the SNc in patients with Parkinson's disease (PD) and atypical parkinsonism using neuromelanin-sensitive magnetic resonance imaging (MRI). METHODS: A total of 22 healthy controls (HC), 38 patients with PD, 22 patients with progressive supranuclear palsy (PSP), 20 patients with multiple system atrophy (MSA, 13 with the parkinsonian variant, 7 with the cerebellar variant), 7 patients with dementia with Lewy body (DLB), and 4 patients with corticobasal syndrome were analyzed. volume and signal-to-noise ratio (SNR) values of the SNc were derived from neuromelanin-sensitive MRI in the whole SNc. Analysis of signal changes was performed in the sensorimotor, associative, and limbic territories of the SNc. RESULTS: SNc volume and corrected volume were significantly reduced in PD, PSP, and MSA versus HC. Patients with PSP had lower volume, corrected volume, SNR, and contrast-to-noise ratio than HC and patients with PD and MSA. Patients with PSP had greater SNR reduction in the associative region than HC and patients with PD and MSA. Patients with PD had reduced SNR in the sensorimotor territory, unlike patients with PSP. Patients with MSA did not differ from patients with PD. CONCLUSIONS: This study provides the first MRI comparison of the topography of neuromelanin changes in parkinsonism. The spatial pattern of changes differed between PSP and synucleinopathies. These nigral topographical differences are consistent with the topography of the extranigral involvement in parkinsonian syndromes. © 2022 International Parkinson and Movement Disorder Society.

Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism.

PURPOSE OF REVIEW: Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA). RECENT FINDINGS: Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools. SUMMARY: These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.

Automated Categorization of Parkinsonian Syndromes Using Magnetic Resonance Imaging in a Clinical Setting.

BACKGROUND: Machine learning algorithms using magnetic resonance imaging (MRI) data can accurately discriminate parkinsonian syndromes. Validation in patients recruited in routine clinical practice is missing. OBJECTIVE: The aim of this study was to assess the accuracy of a machine learning algorithm trained on a research cohort and tested on an independent clinical replication cohort for the categorization of parkinsonian syndromes. METHODS: Three hundred twenty-two subjects, including 94 healthy control subjects, 119 patients with Parkinson's disease (PD), 51 patients with progressive supranuclear palsy (PSP) with Richardson's syndrome, 35 with multiple system atrophy (MSA) of the parkinsonian variant (MSA-P), and 23 with MSA of the cerebellar variant (MSA-C), were recruited. They were divided into a training cohort (n = 179) scanned in a research environment and a replication cohort (n = 143) examined in clinical practice on different MRI systems. Volumes and diffusion tensor imaging (DTI) metrics in 13 brain regions were used as input for a supervised machine learning algorithm. To harmonize data across scanners and reduce scanner-dependent effects, we tested two types of normalizations using patient data or healthy control data. RESULTS: In the replication cohort, high accuracies were achieved using volumetry in the classification of PD-PSP, PD-MSA-C, PSP-MSA-C, and PD-atypical parkinsonism (balanced accuracies: 0.840-0.983, area under the receiver operating characteristic curves: 0.907-0.995). Performances were lower for the classification of PD-MSA-P, MSA-C-MSA-P (balanced accuracies: 0.765-0.784, area under the receiver operating characteristic curve: 0.839-0.871) and PD-PSP-MSA (balanced accuracies: 0.773). Performance using DTI was improved when normalizing by controls, but remained lower than that using volumetry alone or combined with DTI. CONCLUSIONS: A machine learning approach based on volumetry enabled accurate classification of subjects with early-stage parkinsonism, examined on different MRI systems, as part of their clinical assessment. © 2020 International Parkinson and Movement Disorder Society.

Teaching brain imaging through a drawing method may improve learning in medical students.

OBJECTIVES: Brain imaging is particularly difficult to learn and to teach. This study aimed to evaluate the performance of teaching brain imaging through drawing method in medical faculty students. METHODS: We conducted a prospective, interventional, randomized, single-blind study in third-year voluntary medical students between December 2016 and June 2019. Eighty medical students received a theoretical training on brain imaging interpretation and were subsequently randomized into two groups ("teaching through drawing" and "standard teaching"). An initial evaluation was carried out to assess the students' basic level. Three teaching and training sessions were spread over 2 months in each group. One month after the third teaching session, students were evaluated by an examiner who was blind to the student's group. The same comprehensive evaluation grid has been used for the initial and final students' evaluations to give an objective score out of 20 points. Students' scores were compared between groups using the t test and effect sizes were measured using Cohen's d. RESULTS: Students' mean age was 21.1 years old. In total, 61.3% were female. Regarding initial evaluation, scores did not differ significantly between both groups (10.1 ± 2.0 versus 9.9 ± 1.9, p = 0.65), thus confirming the homogeneity of the students' basic level. The scores obtained from the final evaluation were significantly higher for the "teaching through drawing" students than for the "standard teaching" students (14.7 ± 2.7 vs 13.2 ± 2.0, p = 0.009, Cohen's d = 0.62). CONCLUSIONS: This study provides class II evidence that the method of drawing alone can improve brain imaging comprehension and analysis in medical faculty students. KEY POINTS: • The method of drawing can improve brain imaging analysis in medical faculty students. • A large majority of students were satisfied by the method of brain imaging teaching through drawing.

Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability.

Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P < 0.0001). Voxel-wise analyses confirmed that lesion frequency was higher in progressive compared to relapsing-remitting patients, with significant bilateral clusters in the spinal cord corticospinal tracts (P < 0.01). The baseline Expanded Disability Status Scale score was associated with lesion volume fraction within the brain (r = 0.31, P < 0.0001), brainstem (r = 0.45, P < 0.0001) and spinal cord (r = 0.57, P < 0.0001) corticospinal tracts. The spinal cord corticospinal tracts lesion volume fraction remained the strongest factor in the multiple linear regression model, independently from cord atrophy. Baseline spinal cord corticospinal tracts lesion volume fraction was also associated with disability progression at 2-year follow-up (P = 0.003). Our results suggest a cumulative effect of lesions within the corticospinal tracts along the brain, brainstem and spinal cord portions to explain physical disability in multiple sclerosis patients, with a predominant impact of intramedullary lesions.

Retrospective Observational Study of Brain MRI Findings in Patients with Acute SARS-CoV-2 Infection and Neurologic Manifestations.

Background This study provides a detailed imaging assessment in a large series of patients infected with coronavirus disease 2019 (COVID-19) and presenting with neurologic manifestations. Purpose To review the MRI findings associated with acute neurologic manifestations in patients with COVID-19. Materials and Methods This was a cross-sectional study conducted between March 23 and May 7, 2020, at the Pitié-Salpêtrière Hospital, a reference center for COVID-19 in the Paris area. Adult patients were included if they had a diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with acute neurologic manifestations and referral for brain MRI. Patients with a prior history of neurologic disease were excluded. The characteristics and frequency of different MRI features were investigated. The findings were analyzed separately in patients in intensive care units (ICUs) and other departments (non-ICU). Results During the inclusion period, 1176 patients suspected of having COVID-19 were hospitalized. Of 308 patients with acute neurologic symptoms, 73 met the inclusion criteria and were included (23.7%): thirty-five patients were in the ICU (47.9%) and 38 were not (52.1%). The mean age was 58.5 years ± 15.6 [standard deviation], with a male predominance (65.8% vs 34.2%). Forty-three patients had abnormal MRI findings 2-4 weeks after symptom onset (58.9%), including 17 with acute ischemic infarct (23.3%), one with a deep venous thrombosis (1.4%), eight with multiple microhemorrhages (11.3%), 22 with perfusion abnormalities (47.7%), and three with restricted diffusion foci within the corpus callosum consistent with cytotoxic lesions of the corpus callosum (4.1%). Multifocal white matter-enhancing lesions were seen in four patients in the ICU (5%). Basal ganglia abnormalities were seen in four other patients (5%). Cerebrospinal fluid analyses were negative for SARS-CoV-2 in all patients tested (n = 39). Conclusion In addition to cerebrovascular lesions, perfusion abnormalities, cytotoxic lesions of the corpus callosum, and intensive care unit-related complications, we identified two patterns including white matter-enhancing lesions and basal ganglia abnormalities that could be related to severe acute respiratory syndrome coronavirus 2 infection. © RSNA, 2020 Online supplemental material is available for this article.

Spatial distribution of multiple sclerosis lesions in the cervical spinal cord.

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework - robust to variability in both image parameters and clinical condition - for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n = 30). Data spanned three contrasts (T1-, T2-, and T2∗-weighted) for a total of 1943 vol and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p ≤ 0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.

Variability of T1-weighted signal intensity of pericallosal lipomas in the fetus.

BACKGROUND: Pericallosal lipomas are often associated with corpus callosum dysgenesis. The diagnosis of lipoma, suggested on ultrasonography, relies on the classic T1 hyperintensity on magnetic resonance imaging (MRI). However, this feature may be absent prenatally. OBJECTIVE: Our objective was to study the changes of T1 intensity in fetal lipomas with comparison to postnatal/postmortem data and to assess the factors influencing the signal variations of pericallosal lipomas on prenatal MRI. MATERIALS AND METHODS: Patients with callosum dysgenesis and interhemispheric hyperechogenicity suggestive of a pericallosal lipoma with available postnatal or postmortem data were included. Gestational age, lipoma size and pattern, corpus callosum size and changes in fetal fat T1 intensity were recorded. Comparison with postmortem neuropathology was available for one fetus. RESULTS: Eleven patients with callosum dysgenesis and pericallosal lipomas (seven curvilinear and four tubulonodular) were included. All MRI scans were performed in the third trimester. Curvilinear lipomas were thinner and six cases were associated with prenatal T1 iso-intensity. Typical T1 hyperintensity appeared on postnatal MRI only. All tubulonodular lipomas were much larger and showed prenatal T1 hyperintensity. In two patients, the lipoma increased in size on postnatal MRI. CONCLUSION: The type and size of a lipoma influence T1 prenatal intensity. Absence of T1 intensity was observed in curvilinear lipomas only. Curvilinear lipomas are much thinner. Changes in T1 intensity may also be related to fat maturation within the lipoma and, subsequently, to gestational age. In the case of callosum dysgenesis, absence of prenatal T1 pericallosal hyperintensity should not exclude the diagnosis of pericallosal lipoma.

Developmental patterns of fetal fat and corresponding signal on T1-weighted magnetic resonance imaging.

BACKGROUND: Evaluation of subcutaneous fetal fat layer thickness on T1-weighted sequences can be used to predict birth weight. Little is known about normal MR signal patterns of subcutaneous tissue throughout pregnancy. OBJECTIVE: To establish developmental patterns of subcutaneous fetal fat signal on T1-weighted sequences during the 2nd and 3rd trimesters. MATERIALS AND METHODS: We retrospectively examined T1-weighted images of 110 fetal MRI scans. We measured signal intensity of subcutaneous fat on thighs, buttocks, trunk, nuchal region, chin and scalp. We then calculated the ratios of the obtained values with fetal muscle, amnios and maternal fat signal, and compared the results with those of immunohistochemical examination of adipose tissue extracted from the abdominal wall of fetuses as part of standard autopsy protocol. RESULTS: We included 60 MRI scans in fetuses without intra-uterine growth restriction or macrosomia of non-diabetic mothers (range 23-37 weeks of gestation). Fat T1 intensity of all anatomical regions was low in all fetuses before 26 weeks of gestation. It became more hyperintense with increasing gestational age, in the following order: chin and nuchal region, then buttocks, thighs and trunk, and eventually the scalp at 33 weeks of gestation. After 33 weeks of gestation, all fetal subcutaneous tissues demonstrated overall hyperintense signal. This progression followed the conversion at immunohistochemistry of fetal adipose tissue composition from predominant brown to white adipose cells in 19 fetuses (19-41 weeks of gestation). CONCLUSION: Between 26 weeks and 33 weeks of gestation, subcutaneous fetal fat signal changed in an orderly pattern from chin to buttocks and scalp. This may reflect the conversion from predominant brown to white adipose tissues in subcutaneous fetal fat.

Spinal cord ischemia revealed by a Brown-Sequard syndrome and caused by a calcified thoracic disc extrusion with spontaneous regression: a case report and review of the literature.

BACKGROUND: Thoracic disc herniation is relatively uncommon, accounting for less than 1% of all spinal herniations. Although most often asymptomatic, they may represent a rare cause of spinal cord ischemia. CASE REPORT: We report the case of a healthy 43-year-old North African male who presented with a Brown-Sequard syndrome revealing a spinal cord ischemia caused by a thoracic disc extrusion. The initial MRI revealed a calcified disc extrusion at the level of T5-T6 without significant spinal cord compression or signal abnormality. A pattern consistent with a medullary ischemia only appeared 48 h later. The patient was treated conservatively with Aspirin and Heparin, which were discontinued later because of a negative cardiovascular work-up. The calcified disc extrusion, which was later recognized as the cause of the ischemia, decreased spontaneously over time and the patient recovered within a few months. CONCLUSIONS: Our case highlights the challenge in diagnosing and managing this uncommon condition. We propose a literature review showing the different therapeutic strategies and their corresponding clinical outcomes.

Long-Term Middle Meningeal Artery Caliber Reduction Following Trisacryl Gelatine Microsphere Embolization for the Treatment of Chronic Subdural Hematoma.

PURPOSE: Middle meningeal artery (MMA) particle embolization is a promising treatment of chronic subdural hematomas (CSDH). The main purpose of this study is to measure MMA proximal caliber and assess the visibility of the two main MMA branches as a surrogate for long-term distal arterial patency following MMA CSDH embolization with trisacryl gelatine microspheres (TAGM). METHODS: This is a single-center retrospective study. All patients having undergone MMA TAGM only embolization for CSDH treatment between 15 March 2018 and 6 June 2020 with an interpretable follow-up magnetic resonance imaging (MRI) examination and no confounding factors were included. Patients were compared with controls matched for age, sex and MRI machine. Two independent readers analyzed the MRI images. RESULTS: In this study, 30 patients having undergone embolization procedures using TAGM of 36 MMAs were included. The follow-up MRI scans were performed after a mean delay of 14.8 ± 7.1 months (range 4.9-29.4 months). The mean diameter of TAGM embolized MMAs (1 mm; 95% confidence interval, CI 0.9-1.1) was significantly smaller than the mean diameter of paired control MMAs (1.3 mm; 95% CI 1.3-1.4) (p < 0.001). The mean proximal diameter of the embolized MMAs (0.9 mm; 95% CI 0.7-1.1) was significantly smaller than the mean diameter of the contralateral MMAs in the same patients (1.4 mm; 95% CI 1.3-1.6)(p < 0.001). CONCLUSION: Long-term follow-up MRI demonstrated a significant impact of TAGM embolization on MMA proximal caliber as well as on the visibility of the two main MMA branches. All comparisons indicated that there was a probable lasting impact of embolization on the patency of distal branches.

Comparison of mean diffusivity, R2* relaxation rate and morphometric biomarkers for the clinical differentiation of parkinsonism.

INTRODUCTION: Quantitative biomarkers for clinical differentiation of parkinsonian syndromes are still lacking. Our aim was to evaluate the value of combining clinically feasible manual measurements of R2* relaxation rates and mean diffusivity (MD) in subcortical regions and brainstem morphometric measurements to improve the discrimination of parkinsonian syndromes. METHODS: Twenty-two healthy controls (HC), 25 patients with Parkinson's disease (PD), 19 with progressive supranuclear palsy (PSP) and 27 with multiple system atrophy (MSA, 21 with the parkinsonian variant -MSAp, 6 with the cerebellar variant -MSAc) were recruited. R2*, MD measurements and morphometric biomarkers including the midbrain to pons area ratio and the Magnetic Resonance Parkinsonism Index (MRPI) were compared between groups and their diagnostic performances were assessed. RESULTS: Morphometric biomarkers discriminated better patients with PSP (ratio: AUC 0.89, MRPI: AUC 0.89) and MSAc (ratio: AUC 0.82, MRPI: AUC 0.75) from other groups. R2* and MD measurements in the posterior putamen performed better in separating patients with MSAp from PD (R2*: AUC 0.89; MD: AUC 0.89). For the three-class classification "MSA vs PD vs PSP", the combination of MD and R2* measurements in the posterior putamen with morphometric biomarkers (AUC: 0.841) outperformed each marker separately. At the individual-level, there were seven discordances between imaging-based prediction and clinical diagnosis involving MSA. Using the new Movement Disorder Society criteria for the diagnosis of MSA, three of these seven patients were clinically reclassified as predicted by quantitative imaging. CONCLUSION: Combining R2* and MD measurements in the posterior putamen with morphometric biomarkers improves the discrimination of parkinsonism.

Golgi localization of SARS-CoV-2 spike protein and interaction with furin in cerebral COVID-19 microangiopathy: a clue to the central nervous system involvement?

In a neuropathological series of 20 COVID-19 cases, we analyzed six cases (three biopsies and three autopsies) with multiple foci predominantly affecting the white matter as shown by MRI. The cases presented with microhemorrhages evocative of small artery diseases. This COVID-19 associated cerebral microangiopathy (CCM) was characterized by perivascular changes: arterioles were surrounded by vacuolized tissue, clustered macrophages, large axonal swellings and a crown arrangement of aquaporin-4 immunoreactivity. There was evidence of blood-brain-barrier leakage. Fibrinoid necrosis, vascular occlusion, perivascular cuffing and demyelination were absent. While no viral particle or viral RNA was found in the brain, the SARS-CoV-2 spike protein was detected in the Golgi apparatus of brain endothelial cells where it closely associated with furin, a host protease known to play a key role in virus replication. Endothelial cells in culture were not permissive to SARS-CoV-2 replication. The distribution of the spike protein in brain endothelial cells differed from that observed in pneumocytes. In the latter, the diffuse cytoplasmic labeling suggested a complete replication cycle with viral release, notably through the lysosomal pathway. In contrast, in cerebral endothelial cells the excretion cycle was blocked in the Golgi apparatus. Interruption of the excretion cycle could explain the difficulty of SARS-CoV-2 to infect endothelial cells in vitro and to produce viral RNA in the brain. Specific metabolism of the virus in brain endothelial cells could weaken the cell walls and eventually lead to the characteristic lesions of COVID-19 associated cerebral microangiopathy. Furin as a modulator of vascular permeability could provide some clues for the control of late effects of microangiopathy.

Temporo-basal sulcal connections: a manual annotation protocol and an investigation of sexual dimorphism and heritability.

The temporo-basal region of the human brain is composed of the collateral, the occipito-temporal, and the rhinal sulci. We manually rated (using a novel protocol) the connections between rhinal/collateral (RS-CS), collateral/occipito-temporal (CS-OTS) and rhinal/occipito-temporal (RS-OTS) sulci, using the MRI of nearly 3400 individuals including around 1000 twins. We reported both the associations between sulcal polymorphisms as well with a wide range of demographics (e.g. age, sex, handedness). Finally, we also estimated the heritability, and the genetic correlation between sulcal connections. We reported the frequency of the sulcal connections in the general population, which were hemisphere dependent. We found a sexual dimorphism of the connections, especially marked in the right hemisphere, with a CS-OTS connection more frequent in females (approximately 35-40% versus 20-25% in males) and an RS-CS connection more common in males (approximately 40-45% versus 25-30% in females). We confirmed associations between sulcal connections and characteristics of incomplete hippocampal inversion (IHI). We estimated the broad sense heritability to be 0.28-0.45 for RS-CS and CS-OTS connections, with hints of dominant contribution for the RS-CS connection. The connections appeared to share some of their genetic causing factors as indicated by strong genetic correlations. Heritability appeared much smaller for the (rarer) RS-OTS connection.

Severity, timeline, and management of complications after stereotactic brain biopsy.

OBJECTIVE: The literature shows discrepancies in stereotactic brain biopsy complication rates, severities, and outcomes. Little is known about the timeline of postbiopsy complications. This study aimed to analyze 1) complications following brain biopsies, using a graded severity scale, and 2) a timeline of complication occurrence. The secondary objectives were to determine factors associated with an increased risk of complications and to assess complication-related management and extra costs. METHODS: The authors retrospectively examined 1500 consecutive stereotactic brain biopsies performed in adult patients at their tertiary medical center between April 2009 and April 2019. RESULTS: Three hundred eighty-one biopsies (25.4%) were followed by a complication, including 88.2% of asymptomatic hemorrhages. Symptomatic complications involved 3.0% of the biopsies, and 0.8% of the biopsies were fatal. The severity grading scale had a 97.6% interobserver reproducibility. Twenty-three (51.1%) of the 45 symptomatic complications occurred within the 1st hour following the biopsy, while 75.6% occurred within the first 6 hours. Age ≥ 65 years, second biopsy procedures, gadolinium-enhanced lesions, glioblastomas, and lymphomas were predictors of biopsy-related complications. Brainstem biopsy-targeted lesions and cerebral toxoplasmosis were predictive of mortality. Asymptomatic hemorrhage was associated with delayed (> 6 hours) symptomatic complications. Symptomatic complications led to extended hospitalization in 86.7% of patients. The average extra cost for management of a patient with postbiopsy symptomatic complication was $35,702. CONCLUSIONS: Symptomatic complications from brain biopsies are infrequent but associated with substantial adverse effects and cost implications for the healthcare system. The use of a severity grading scale, as the authors propose in this article, helps to classify complications according to the therapeutic consequences and the patient's outcome. Because this study indicates that most complications occur within the first few hours following the biopsy, postbiopsy monitoring can be tailored accordingly. The authors therefore recommend systematic monitoring for 2 hours in the recovery unit and a CT scan 2 hours after the end of the biopsy procedure. In addition, they propose a modern algorithm for optimal postoperative management of patients undergoing stereotactic biopsy.

Association of Clinical, Biological, and Brain Magnetic Resonance Imaging Findings With Electroencephalographic Findings for Patients With COVID-19.

Importance: There is evidence of central nervous system impairments associated with coronavirus disease 2019 (COVID-19) infection, including encephalopathy. Multimodal monitoring of patients with COVID-19 may delineate the specific features of COVID-19-related encephalopathy and guide clinical management. Objectives: To investigate clinical, biological, and brain magnetic resonance imaging (MRI) findings in association with electroencephalographic (EEG) features for patients with COVID-19, and to better refine the features of COVID-19-related encephalopathy. Design, Setting, and Participants: This retrospective cohort study conducted in Pitié-Salpêtrière Hospital, Paris, France, enrolled 78 hospitalized adults who received a diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-Cov2) and underwent EEG between March 30 and June 11, 2020. Exposures: Detection of SARS-CoV-2 from a nasopharyngeal specimen using a reverse transcription-polymerase chain reaction assay or, in the case of associated pneumonia, on a computed tomography scan of the chest. Main Outcomes and Measures: Data on the clinical and paraclinical features of the 78 patients with COVID-19 were retrieved from electronic patient records. Results: Of 644 patients who were hospitalized for COVID-19, 78 (57 men [73%]; mean [SD] age, 61 [12] years) underwent EEG. The main indications for EEG were delirium, seizure-like events, and delayed awakening in the intensive care unit after stopping treatment with sedatives. Sixty-nine patients showed pathologic EEG findings, including metabolic-toxic encephalopathy features, frontal abnormalities, periodic discharges, and epileptic activities. Of 57 patients who underwent brain MRI, 41 showed abnormalities, including perfusion abnormalities, acute ischemic lesions, multiple microhemorrhages, and white matter-enhancing lesions. Fifty-five patients showed biological abnormalities, including dysnatremia, kidney failure, and liver dysfunction, the same day as the EEG. The results of cerebrospinal fluid analysis were negative for SARS-Cov-2 for all tested patients. Nine patients who had no identifiable cause of brain injury outside COVID-19 were further isolated; their brain injury was defined as COVID-19-related encephalopathy. They represented 1% (9 of 644) of patients with COVID-19 requiring hospitalization. Six of these 9 patients had movement disorders, 7 had frontal syndrome, 4 had brainstem impairment, 4 had periodic EEG discharges, and 3 had MRI white matter-enhancing lesions. Conclusions and Relevance: The results from this cohort of patients hospitalized with COVID-19 suggest there are clinical, EEG, and MRI patterns that could delineate specific COVID-19-related encephalopathy and guide treatment strategy.

The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism.

The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.