TAFRO syndrome with a fatal clinical course following BNT162b2 mRNA (Pfizer-BioNTech) COVID-19 vaccination: A case report.

TAFRO syndrome is a rare disorder that manifests as thrombocytopenia, anasarca, fever, reticulin myelofibrosis, renal dysfunction, and organomegaly. Although this disease often follows a severe clinical course, the cause remains unknown. The coronavirus disease 2019 (COVID-19) pandemic is a major global problem. Vaccination against COVID-19 has been successful; however, there are concerns about severe adverse events. Herein, we report a rare presentation of TAFRO syndrome triggered by the COVID-19 vaccine with a fatal clinical course. A 42-year-old Japanese man presented to our hospital complaining of fever lasting for 2 weeks that occurred a day after receiving the BNT162b2 mRNA (Pfizer-BioNTech) COVID-19 vaccine. The patient had a low platelet count, ascites, reticulin myelofibrosis, renal failure, and lymphadenopathy and was diagnosed with TAFRO syndrome. Despite administering several immunosuppressive drugs, the condition did not improve. The patient repetitively developed and eventually died of bacteremia caused by multidrug-resistant Klebsiella pneumoniae. We highlight the first reported case of TAFRO syndrome after COVID-19 vaccination.

Chronic Cortical Cerebral Microinfarcts Slow Down Cognitive Recovery After Acute Ischemic Stroke.

Background and Purpose- Cortical cerebral microinfarcts (CMIs) have been associated with vascular dementia and Alzheimer disease. The aim of the present study was to evaluate the role of cortical CMI detected on 3T magnetic resonance imaging, on the evolution of cognition during the year following an acute ischemic stroke. Methods- We conducted a prospective and monocentric study, including patients diagnosed for a supratentorial ischemic stroke with a National Institutes of Health Stroke Scale score ≥1, without prestroke dementia or neurological disability. Cortical CMIs were assessed on a brain 3T magnetic resonance imaging realized at baseline, as well as markers of small vessel disease, stroke characteristics, and hippocampal atrophy. Cognitive assessment was performed at 3 time points (baseline, 3 months, and 1 year) using the Montreal Cognitive Assessment, the Isaacs set test, and the Zazzo's cancellation task. Generalized linear mixed models were performed to evaluate the relationships between the number of cortical CMI and changes in cognitive scores over 1 year. Results- Among 199 patients (65±13 years old, 68% men), 88 (44%) had at least one cortical CMI. Hypertension was the main predictor of a higher cortical CMI load (B=0.58, P=0.005). The number of cortical CMI was associated with an increase time at the Zazzo's cancellation task over 1 year (B=3.84, P=0.01), regardless of the other magnetic resonance imaging markers, stroke severity, and demographic factors. Conclusions- Cortical CMIs are additional magnetic resonance imaging markers of poorer processing speed after ischemic stroke. These results indicate that a high load of cortical CMI in patients with stroke can be considered as a cerebral frailty condition which counteracts to the recovery process, suggesting a reduced brain plasticity among these patients.

Neurodegeneration of the Substantia Nigra after Ipsilateral Infarct: MRI R2* Mapping and Relationship to Clinical Outcome.

Background The substantia nigra (SN) is suspected to be affected after remote infarction, in view of its large array of connections with the supratentorial brain. Whether secondary involvement of SN worsens overall clinical outcome after a supratentorial stroke has not previously been studied. Purpose To assess longitudinal changes in SN R2* by using MRI in the setting of ipsilesional supratentorial infarct and the relationship of SN signal change to clinical outcome. Materials and Methods Participants prospectively included from 2012 to 2015 were evaluated at 24-72 hours (baseline visit) and at 1 year with MRI to quantify R2*. The SN was segmented bilaterally to calculate an R2* asymmetry index (SN-AI); greater SN-AI indicated greater relative R2* in the ipsilateral compared with contralateral SN. The 95th percentile of R2* (hereafter, SN-AI95) was compared according to infarct location with mixed linear regression models. We also conducted voxel-based comparisons of R2* and identified individual infarcted voxels associated with high SN-AI95 through voxel-based lesion-symptom mapping. Multivariable regression models tested the association between SN-AI95 and clinical scores. Results A total of 181 participants were evaluated (127 men, 54 women; mean age ± standard deviation, 64.2 years ± 13.1; 75 striatum infarcts, 106 other locations). Visual inspection, SN-AI95, and average maps consistently showed higher SN R2* at 1 year if ipsilateral striatum was infarcted than if it was not (SN-AI95, 4.25 vs -0.88; P < .001), but this was not observed at baseline. The striatal location of the infarct was associated with higher SN-AI95 at 1 year independently from infarct volume, SN-AI95 at baseline, microbleeds, age, and sex (ß = 4.99; P < .001). Voxel-based lesion-symptom mapping confirmed that striatum but also insula, internal capsule, and external capsule were associated with higher SN-AI95 at 1 year. SN-AI95 was an independent contributor of poor motor outcome (Box and Block Test, ß = -.62 points; P = .01). Conclusion In patients with stroke, greater substantia nigra R2*, likely reflective of greater iron content, can be observed at 1 year ipsilateral from remote infarcts of specific location, which is associated with worse motor function. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Vernooij in this issue.

Relationship between aging and T1 relaxation time in deep gray matter: A voxel-based analysis.

PURPOSE: To investigate age-related changes in T1 relaxation time in deep gray matter structures in healthy volunteers using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE). MATERIALS AND METHODS: In all, 70 healthy volunteers (aged 20-76, mean age 42.6 years) were scanned at 3T magnetic resonance imaging (MRI). A MP2RAGE sequence was employed to quantify T1 relaxation times. After the spatial normalization of T1 maps with the diffeomorphic anatomical registration using the exponentiated Lie algebra algorithm, voxel-based regression analysis was conducted. In addition, linear and quadratic regression analyses of regions of interest (ROIs) were also performed. RESULTS: With aging, voxel-based analysis (VBA) revealed significant T1 value decreases in the ventral-inferior putamen, nucleus accumbens, and amygdala, whereas T1 values significantly increased in the thalamus and white matter as well (P < 0.05 at cluster level, false discovery rate). ROI analysis revealed that T1 values in the nucleus accumbens linearly decreased with aging (P = 0.0016), supporting the VBA result. T1 values in the thalamus (P < 0.0001), substantia nigra (P = 0.0003), and globus pallidus (P < 0.0001) had a best fit to quadratic curves, with the minimum T1 values observed between 30 and 50 years of age. CONCLUSION: Age-related changes in T1 relaxation time vary by location in deep gray matter. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:724-731.

MP2RAGE for deep gray matter measurement of the brain: A comparative study with MPRAGE.

BACKGROUND: To compare magnetization-prepared two rapid acquisition gradient echoes (MP2RAGE) imaging with conventional MPRAGE imaging for deep gray matter (GM) segmentation, reproducibility, contrast ratio (CR) and contrast-to-noise ratio (CNR), and to evaluate reproducibility of T1 maps derived from MP2RAGE. METHODS: MP2RAGE and MPRAGE imaging were conducted twice for each of 20 volunteers on a 3 Tesla MRI scanner. Images were normalized and segmented using SPM12 with the DARTEL algorithm. Reproducibility of segmentation was evaluated using coefficients of variation (COVs) of deep GM probability maps between first and second scans, which was compared between MP2RAGE and MPRAGE. Differences in deep GM probability were compared voxel-wise. CR and CNR analyses were conducted using regions of interest. COVs of T1 maps were also evaluated. RESULTS: Comparison of GM probability maps demonstrated that putamen, caudate nucleus and thalamus were segmented significantly larger in MP2RAGE than in MPRAGE, and MP2RAGE was inferior only at some areas of globus pallidus and lateral thalamus (P < 0.05; false discovery rate, FDR). CRs of deep GM structures were significantly better in MP2RAGE (P < 0.0001). COVs of deep GM probability maps were significantly higher at large areas of the deep GM in MPRAGE (P < 0.05, FDR). COVs ranged from 0.50 to 3.31% in MP2RAGE and from 0.62 to 4.12% in MPRAGE. COVs of the T1 map were around 2%. CONCLUSION: MP2RAGE yields greater reproducibility and better tissue contrast than MPRAGE in deep GM. T1 maps derived from MP2RAGE were highly reliable. MP2RAGE is useful for measurement and analysis of deep GM.

Quiet Diffusion-weighted MR Imaging of the Brain for Pediatric Patients with Moyamoya Disease.

PURPOSE: Diffusion-weighted MRI (DWI) is an essential sequence for evaluating pediatric patients with moyamoya disease (MMD); however, acoustic noise associated with DWI may lead to motion artifact. Compared with conventional DWI (cDWI), quiet DWI (qDWI) is considered less noisy and able to keep children more relaxed and stable. This study aimed to evaluate the suitability of qDWI compared with cDWI for pediatric patients with MMD. METHODS: In this observational study, MR examinations of the brain were performed either with or without sedation in pediatric patients with MMD between September 2017 and August 2018. Three neuroradiologists independently evaluated the images for artifacts and restricted diffusion in the brain. The differences between qDWI and cDWI were compared statistically using a chi-square test. RESULTS: One-hundred and six MR scans of 56 patients with MMD (38 scans of 15 sedated patients: 6 boys and 9 girls; mean age, 5.2 years; range, 1-9 years; and 68 scans of 42 unsedated patients: 19 boys and 23 girls; mean age, 10.7 years; range, 7-16 years) were evaluated. MR examinations were performed either with or without sedation (except in one patient). In sedated patients, no artifact other than susceptibility was observed on qDWI, whereas four artifacts were observed on cDWI (P = .04). One patient awoke from sedation during cDWI scanning, while no patient awoke from sedation during qDWI acquisition. For unsedated patients, three scans showed artifacts on qDWI, whereas two scans showed artifacts on cDWI (P = .65). Regarding restricted diffusion, qDWI revealed three cases, while two cases were found on cDWI (P = .66). CONCLUSION: qDWI induced fewer artifacts compared with cDWI in sedated patients, and similar frequencies of artifacts were induced by qDWI and by cDWI in unsedated patients. qDWI showed restricted diffusion comparable to cDWI.

Active learning strategy and hybrid training for infarct segmentation on diffusion MRI with a U-shaped network.

Automatic and reliable stroke lesion segmentation from diffusion magnetic resonance imaging (MRI) is critical for patient care. Methods using neural networks have been developed, but the rate of false positives limits their use in clinical practice. A training strategy applied to three-dimensional deconvolutional neural networks for stroke lesion segmentation on diffusion MRI was proposed. Infarcts were segmented by experts on diffusion MRI for 929 patients. We divided each database as follows: 60% for a training set, 20% for validation, and 20% for testing. Our hypothesis was a two-phase hybrid learning scheme, in which the network was first trained with whole MRI (regular phase) and then, in a second phase (hybrid phase), alternately with whole MRI and patches. Patches were actively selected from the discrepancy between expert and model segmentation at the beginning of each batch. On the test population, the performances after the regular and hybrid phases were compared. A statistically significant Dice improvement with hybrid training compared with regular training was demonstrated ( p < 0.01 ). The mean Dice reached 0.711 ± 0.199 . False positives were reduced by almost 30% with hybrid training ( p < 0.01 ). Our hybrid training strategy empowered deep neural networks for more accurate infarct segmentations on diffusion MRI.

Differential diagnosis of parkinsonian syndromes using dopamine transporter and perfusion SPECT.

OBJECTIVE: We aimed to assess whether a combined analysis of dopamine transporter (DAT)- and perfusion-SPECT images (or either) could: (1) distinguish atypical parkinsonian syndromes (APS) from Lewy body diseases (LBD; majority Parkinson disease [PD]), and (2) differentiate among APS subgroups (progressive supranuclear palsy [PSP], corticobasal syndrome [CBS], and multiple system atrophy [MSA]). METHODS: We recruited consecutive patients with neurodegenerative parkinsonian syndromes (LBD, n = 46; APS, n = 33). Individual [123I]FP-CIT- and [123I]iodoamphetamine-SPECT images were coregistered onto anatomical MRI segmented into brain regions. Striatal DAT activity and regional perfusion were extracted from each brain region for each patient and submitted to logistic regression analyses. Stepwise procedures were used to select predictors that should be included in the models to distinguish APS from LBD, and differentiate among the APS subgroups. Receiver-operating characteristic (ROC) analyses were performed to measure diagnostic power. Leave-one-out cross-validation (LOOCV) was performed to evaluate the diagnostic accuracy. RESULTS: The model to discriminate APS from LBD showed that the area under the ROC curve (AUC) was 0.923, while the total diagnostic accuracy (TDA) was 86.1% in LOOCV. In the model to distinguish PSP, CBS, and MSA from LBD, the AUC/TDA values were 0.978/94.6%, 0.978/87.0%, and 0.880/80.3%, respectively. In the model to differentiate between CBS and MSA, MSA and PSP, and PSP and CBS, the AUC/TDA values were 0.967/91.3%, 0.920/88.0%, 0.875/77.8%, respectively. CONCLUSION: An image-based automated classification using striatal DAT activity and regional perfusion patterns provided a good performance in the differential diagnosis of neurodegenerative parkinsonian syndromes without clinical information.

A case of interstitial lung disease associated with clinically amyopathic dermatomyositis: radiologic-pathologic correlation.

This case report describes a 64-year-old woman with interstitial lung disease associated with clinically amyopathic dermatomyositis. Chest computed tomography revealed consolidations along bronchovascular bundles in the periphery of the lower lungs. Interstitial lung disease developed acutely, and the patient died 3 months after the clinical diagnosis. An autopsy was performed, and a large section of the lung specimen was prepared. Various interstitial lesions including organizing pneumonia, cellular and fibrotic nonspecific interstitial pneumonia, and diffuse alveolar damage were seen in the large section. Correlating the large section and computed tomography images was useful for determining the distribution of diffuse alveolar damage.