Novel Imaging Approaches for Glioma Classification in the Era of the World Health Organization 2021 Update: A Scoping Review.

The 2021 WHO classification of CNS tumors is a challenge for neuroradiologists due to the central role of the molecular profile of tumors. The potential of novel data analysis tools in neuroimaging must be harnessed to maintain its role in predicting tumor subgroups. We performed a scoping review to determine current evidence and research gaps. A comprehensive literature search was conducted regarding glioma subgroups according to the 2021 WHO classification and the use of MRI, radiomics, machine learning, and deep learning algorithms. Sixty-two original articles were included and analyzed by extracting data on the study design and results. Only 8% of the studies included pediatric patients. Low-grade gliomas and diffuse midline gliomas were represented in one-third of the research papers. Public datasets were utilized in 22% of the studies. Conventional imaging sequences prevailed; data on functional MRI (DWI, PWI, CEST, etc.) are underrepresented. Multiparametric MRI yielded the best prediction results. IDH mutation and 1p/19q codeletion status prediction remain in focus with limited data on other molecular subgroups. Reported AUC values range from 0.6 to 0.98. Studies designed to assess generalizability are scarce. Performance is worse for smaller subgroups (e.g., 1p/19q codeleted or IDH1/2 mutated gliomas). More high-quality study designs with diversity in the analyzed population and techniques are needed.

Speeding Up and Improving Image Quality in Glioblastoma MRI Protocol by Deep Learning Image Reconstruction.

A fully diagnostic MRI glioma protocol is key to monitoring therapy assessment but is time-consuming and especially challenging in critically ill and uncooperative patients. Artificial intelligence demonstrated promise in reducing scan time and improving image quality simultaneously. The purpose of this study was to investigate the diagnostic performance, the impact on acquisition acceleration, and the image quality of a deep learning optimized glioma protocol of the brain. Thirty-three patients with histologically confirmed glioblastoma underwent standardized brain tumor imaging according to the glioma consensus recommendations on a 3-Tesla MRI scanner. Conventional and deep learning-reconstructed (DLR) fluid-attenuated inversion recovery, and T2- and T1-weighted contrast-enhanced Turbo spin echo images with an improved in-plane resolution, i.e., super-resolution, were acquired. Two experienced neuroradiologists independently evaluated the image datasets for subjective image quality, diagnostic confidence, tumor conspicuity, noise levels, artifacts, and sharpness. In addition, the tumor volume was measured in the image datasets according to Response Assessment in Neuro-Oncology (RANO) 2.0, as well as compared between both imaging techniques, and various clinical-pathological parameters were determined. The average time saving of DLR sequences was 30% per MRI sequence. Simultaneously, DLR sequences showed superior overall image quality (all p < 0.001), improved tumor conspicuity and image sharpness (all p < 0.001, respectively), and less image noise (all p < 0.001), while maintaining diagnostic confidence (all p > 0.05), compared to conventional images. Regarding RANO 2.0, the volume of non-enhancing non-target lesions (p = 0.963), enhancing target lesions (p = 0.993), and enhancing non-target lesions (p = 0.951) did not differ between reconstruction types. The feasibility of the deep learning-optimized glioma protocol was demonstrated with a 30% reduction in acquisition time on average and an increased in-plane resolution. The evaluated DLR sequences improved subjective image quality and maintained diagnostic accuracy in tumor detection and tumor classification according to RANO 2.0.

Intensity Score of Vessel Wall Contrast Enhancement in MRI Allows Prediction of Disease Progression in Moyamoya Angiopathy.

BACKGROUND AND OBJECTIVES: The underlying pathophysiological cause of moyamoya angiopathy (MMA) is still unclear. High-resolution vessel wall imaging has become a useful tool. The aim was to study vessel wall contrast-enhancement (VW-CE) as an imaging marker to predict disease progression in MMA. METHODS: Patients with MMA, who had undergone serial contrast-enhanced high-resolution MRI with concomitant and follow-up digital subtraction angiography, were analyzed retrospectively. VW-CE was semiquantified by measurement of the signal intensity of the vessel wall in in contrast-enhanced high-resolution MRI. A comparative quotient with the contrast-intensity of the pituitary stalk was calculated and graded accordingly from grade 1 to 5. VW-CE status was correlated with disease status, stroke, cerebrovascular reactivity in CO2-triggered blood-oxygen level-dependent MRI, angiographic disease progression, revascularization surgery, and follow-up imaging. RESULTS: Forty eight patients met the inclusion criteria. N = 56 MRI and digital subtraction angiography time-intervals were evaluated for 12 vessel sections per hemisphere each (N = 1344). N = 38 (79%) patients showed VW-CE and N = 10 (21%) did not. VW-CE was only observed in the terminal internal carotid artery and the proximal circle of Willis (N = 96/1344). Notably, patients with VW-CE significantly more often presented with acute infarction in the concomitant MRI. The incidence of angiographically proven disease progression was significantly associated with the incidence of VW-CE, and time to disease progression was earlier in higher grades of VW-CE compared with lower grades. CONCLUSION: VW-CE is a semiquantifiable marker for disease activity in patients with MMA and associated with disease progression and increased risk of stroke. VW-CE analysis can be routinely performed in patients with MMA to estimate the risk for disease progression and stroke.

Evaluation of the contribution of individual arteries to the cerebral blood supply in patients with Moyamoya angiopathy: comparison of vessel-encoded arterial spin labeling and digital subtraction angiography.

PURPOSE: Vessel-encoded arterial spin labeling (VE-ASL) is able to provide noninvasive information about the contribution of individual arteries to the cerebral perfusion. The aim of this study was to compare VE-ASL to the diagnostic standard digital subtraction angiography (DSA) with respect to its ability to visualize vascular territories. METHODS: In total, 20 VE-ASL and DSA data sets of 17 patients with Moyamoya angiopathy with and without revascularization surgery were retrospectively analyzed. Two neuroradiologists independently assessed the agreement between VE-ASL and DSA using a 4-point Likert scale (no- very high agreement). Additionally, grading of the vascular supply of subterritories (A1-A2, M1-M6) on the VE-ASL images and angiograms was performed. The intermodal agreement was calculated for all subterritories in total and for the subdivision into without and after revascularization (direct or indirect bypass). RESULTS: There was a very high agreement between the VE-ASL and the DSA data sets (median = 1, modus = 1) with a substantial inter-rater agreement (kw = 0.762 (95% CI 0.561-0.963)). The inter-modality agreement between VE-ASL and DSA in vascular subterritories was almost perfect for all subterritories (k = 0.899 (0.865-0.945)), in the subgroup of direct revascularized subterritories (k = 0.827 (0.738-0.915)), in the subgroup of indirect revascularized subterritories (k = 0.843 (0.683-1.003)), and in the subgroup of never revascularized subterritories (k = 0.958 (0.899-1.017)). CONCLUSION: Vessel-encoded ASL seems to be a promising non-invasive method to depict the contributions of individual arteries to the cerebral perfusion before and after revascularization surgery.

Deep learning-accelerated image reconstruction in back pain-MRI imaging: reduction of acquisition time and improvement of image quality.

INTRODUCTION: Low back pain is a global health issue causing disability and missed work days. Commonly used MRI scans including T1-weighted and T2-weighted images provide detailed information of the spine and surrounding tissues. Artificial intelligence showed promise in improving image quality and simultaneously reducing scan time. This study evaluates the performance of deep learning (DL)-based T2 turbo spin-echo (TSE, T2DLR) and T1 TSE (T1DLR) in lumbar spine imaging regarding acquisition time, image quality, artifact resistance, and diagnostic confidence. MATERIAL AND METHODS: This retrospective monocentric study included 60 patients with lower back pain who underwent lumbar spinal MRI between February and April 2023. MRI parameters and DL reconstruction (DLR) techniques were utilized to acquire images. Two neuroradiologists independently evaluated image datasets based on various parameters using a 4-point Likert scale. RESULTS: Accelerated imaging showed significantly less image noise and artifacts, as well as better image sharpness, compared to standard imaging. Overall image quality and diagnostic confidence were higher in accelerated imaging. Relevant disk herniations and spinal fractures were detected in both DLR and conventional images. Both readers favored accelerated imaging in the majority of examinations. The lumbar spine examination time was cut by 61% in accelerated imaging compared to standard imaging. CONCLUSION: In conclusion, the utilization of deep learning-based image reconstruction techniques in lumbar spinal imaging resulted in significant time savings of up to 61% compared to standard imaging, while also improving image quality and diagnostic confidence. These findings highlight the potential of these techniques to enhance efficiency and accuracy in clinical practice for patients with lower back pain.

Deep learning-accelerated image reconstruction in MRI of the orbit to shorten acquisition time and enhance image quality.

BACKGROUND AND PURPOSE: This study explores the use of deep learning (DL) techniques in MRI of the orbit to enhance imaging. Standard protocols, although detailed, have lengthy acquisition times. We investigate DL-based methods for T2-weighted and T1-weighted, fat-saturated, contrast-enhanced turbo spin echo (TSE) sequences, aiming to improve image quality, reduce acquisition time, minimize artifacts, and enhance diagnostic confidence in orbital imaging. METHODS: In a 3-Tesla MRI study of 50 patients evaluating orbital diseases from March to July 2023, conventional (TSES ) and DL TSE sequences (TSEDL ) were used. Two neuroradiologists independently assessed the image datasets for image quality, diagnostic confidence, noise levels, artifacts, and image sharpness using a randomized and blinded 4-point Likert scale. RESULTS: TSEDL significantly reduced image noise and artifacts, enhanced image sharpness, and decreased scan time, outperforming TSES (p < .05). TSEDL showed superior overall image quality and diagnostic confidence, with relevant findings effectively detected in both DL-based and conventional images. In 94% of cases, readers preferred accelerated imaging. CONCLUSION: The study proved that using DL for MRI image reconstruction in orbital scans significantly cut acquisition time by 69%. This approach also enhanced image quality, reduced image noise, sharpened images, and boosted diagnostic confidence.

Improved diagnostic confidence and tumor type prediction in adult-type diffuse glioma by multimodal imaging including DCE perfusion and diffusion kurtosis mapping - A standardized multicenter study.

BACKGROUND AND PURPOSE: To evaluate the feasibility of a multimodal approach involving dynamic contrast-enhanced (DCE) perfusion imaging and diffusion kurtosis imaging (DKI) in the preoperative imaging of brain tumors in a multicenter setting, and to evaluate the effect on diagnostic confidence and accuracy for tumor grade and type prediction. MATERIALS AND METHODS: One hundred and thirty-three patients with brain tumors were imaged in six hospitals with a standardized multimodal protocol. Standard imaging and six parameter maps derived from DCE and DKI sequences were reviewed off-site by two independent readers. Image quality and diagnostic confidence were evaluated in qualitative analyses. Quantitative analyses were performed to assess diagnostic accuracy and the performance of DKI and DCE parameters for tumor grade differentiation and molecular tumor type determination. RESULTS: Standardized acquisition of DCE and DKI maps was feasible with excellent image quality. Diagnostic confidence was significantly improved from 85 % to 96 % (p = 0.0005) by additional review of the DCE and DKI maps. The combination of mean kurtosis and CBV was particularly advantageous for differentiating low-grade and high-grade glioma, oligodendroglial vs. astrocytic, and IDH1/2 wild type vs. mutated tumors. CONCLUSION: A multimodal imaging approach with DCE and DKI improves diagnostic confidence and yields higher diagnostic accuracy for predicting tumor grade and type in adult-type glioma.

Penumbral Rescue by normobaric O = O administration in patients with ischemic stroke and target mismatch proFile (PROOF): Study protocol of a phase IIb trial.

RATIONALE: Oxygen is essential for cellular energy metabolism. Neurons are particularly vulnerable to hypoxia. Increasing oxygen supply shortly after stroke onset could preserve the ischemic penumbra until revascularization occurs. AIMS: PROOF investigates the use of normobaric oxygen (NBO) therapy within 6 h of symptom onset/notice for brain-protective bridging until endovascular revascularization of acute intracranial anterior-circulation occlusion. METHODS AND DESIGN: Randomized (1:1), standard treatment-controlled, open-label, blinded endpoint, multicenter adaptive phase IIb trial. STUDY OUTCOMES: Primary outcome is ischemic core growth (mL) from baseline to 24 h (intention-to-treat analysis). Secondary efficacy outcomes include change in NIHSS from baseline to 24 h, mRS at 90 days, cognitive and emotional function, and quality of life. Safety outcomes include mortality, intracranial hemorrhage, and respiratory failure. Exploratory analyses of imaging and blood biomarkers will be conducted. SAMPLE SIZE: Using an adaptive design with interim analysis at 80 patients per arm, up to 456 participants (228 per arm) would be needed for 80% power (one-sided alpha 0.05) to detect a mean reduction of ischemic core growth by 6.68 mL, assuming 21.4 mL standard deviation. DISCUSSION: By enrolling endovascular thrombectomy candidates in an early time window, the trial replicates insights from preclinical studies in which NBO showed beneficial effects, namely early initiation of near 100% inspired oxygen during short temporary ischemia. Primary outcome assessment at 24 h on follow-up imaging reduces variability due to withdrawal of care and early clinical confounders such as delayed extubation and aspiration pneumonia. TRIAL REGISTRATIONS: ClinicalTrials.gov: NCT03500939; EudraCT: 2017-001355-31.

Deep Learning Accelerated Image Reconstruction of Fluid-Attenuated Inversion Recovery Sequence in Brain Imaging: Reduction of Acquisition Time and Improvement of Image Quality.

RATIONALE AND OBJECTIVES: Fluid-attenuated inversion recovery (FLAIR) imaging is playing an increasingly significant role in the detection of brain metastases with a concomitant increase in the number of magnetic resonance imaging (MRI) examinations. Therefore, the purpose of this study was to investigate the impact on image quality and diagnostic confidence of an innovative deep learning-based accelerated FLAIR (FLAIRDLR) sequence of the brain compared to conventional (standard) FLAIR (FLAIRS) imaging. MATERIALS AND METHODS: Seventy consecutive patients with staging cerebral MRIs were retrospectively enrolled in this single-center study. The FLAIRDLR was conducted using the same MRI acquisition parameters as the FLAIRS sequence, except for a higher acceleration factor for parallel imaging (from 2 to 4), which resulted in a shorter acquisition time of 1:39 minute instead of 2:40 minutes (-38%). Two specialized neuroradiologists evaluated the imaging datasets using a Likert scale that ranged from 1 to 4, with 4 indicating the best score for the following parameters: sharpness, lesion demarcation, artifacts, overall image quality, and diagnostic confidence. Additionally, the image preference of the readers and the interreader agreement were assessed. RESULTS: The average age of the patients was 63 ± 11years. FLAIRDLR exhibited significantly less image noise than FLAIRS, with P-values of< .001 and< .05, respectively. The sharpness of the images and the ability to detect lesions were rated higher in FLAIRDLR, with a median score of 4 compared to a median score of 3 in FLAIRS (P-values of<.001 for both readers). In terms of overall image quality, FLAIRDLR was rated superior to FLAIRS, with a median score of 4 vs 3 (P-values of<.001 for both readers). Both readers preferred FLAIRDLR in 68/70 cases. CONCLUSION: The feasibility of deep learning FLAIR brain imaging was shown with additional 38% reduction in examination time compared to standard FLAIR imaging. Furthermore, this technique has shown improvement in image quality, noise reduction, and lesion demarcation.

A novel fully automated method for measuring ASPECTS to improve stroke diagnosis: Comparison to traditional ASPECTS.

BACKGROUND AND PURPOSE: To compare the accuracy of subjective Alberta Stroke Program Early CT Score (sASPECTS) evaluation and that of an automated prototype software (aASPECTS) on nonenhanced CT (NECT) in patients with early anterior territory stroke and controls using side-to-side quantification of hypoattenuated brain areas. METHODS: We retrospectively analyzed the NECT scans of 42 consecutive patients with ischemic stroke before reperfusion and 42 controls using first sASPECTS and subsequently aASPECTS. We assessed the differences in Alberta Stroke Program Early CT Score (ASPECTS) and calculated the sensitivity and specificity of NECT with CT perfusion, whereas cerebral blood volume (CBV) served as the reference standard for brain infarction. RESULTS: The clot was located in the middle cerebral artery (MCA) in 47.6% of cases and the internal carotid artery (ICA) in 28.6% of cases. Ten cases presented combined ICA and MCA occlusions. The stroke was right sided in 52.4% of cases and left sided in 47.6%. Reader-based NECT analysis yielded a median sASPECTS of 10. The median CBV-based ASPECTS was 7. Compared to the area of decreased CBV, sASPECTS yielded a sensitivity of 12.5% and specificity of 86.8%. The software prototype (aASPECTS) yielded an overall sensitivity of 65.5% and a specificity of 92.2%. The interreader agreement for ASPECTS evaluation of admission NECT and follow-up CT was almost perfect (κ = .93). The interreader agreement of the CBV color map evaluation was substantial (κ = .77). CONCLUSIONS: aASPECTS of NECT can outperform sASPECTS for stroke detection.

Computed tomography perfusion imaging-guided intravenous thrombolysis in acute minor ischemic stroke.

Background: Over 50% of acute ischemic stroke (AIS) patients present with minor neurological deficits, and optimal treatment is still debated. The randomized PRISMS trial did not show beneficial effects of intravenous thrombolysis (IVT) in unselected patients with minor stroke and non-disabling neurological deficits. Purpose: The study aimed to evaluate if AIS patients with minor stroke may benefit from computed-tomography-perfusion (CTP)-guided IVT. The primary endpoint was good functional outcomes, defined as a modified Rankin Scale score of 0-2 at 90 days. Methods: AIS patients with a NIHSS of ≤5 presenting within 4.5 h underwent multimodal CT-imaging including CTP. CTP mismatch was defined as hypoperfusion on CTP with time-to-peak delay >6 s without corresponding hypoperfusion in cerebral blood volume. IVT decision was left to the attending stroke physicians. Patients with large vessel occlusion (LVO) and absolute contraindications to IVT were excluded. Results: In total, 267 consecutive patients were included [mean age: 72 ± 14 years, 45.3% female patients, 75.3% received IVT, median NIHSS on admission: 3 (IQR 2, 4)]. CTP mismatch was detected in 41.8% of IVT- treated patients (IVT+) and 28.8% of standard treatment patients (IVT-) (p = 0.06). IVT+ had favorable outcomes at 90 days compared to IVT- (p = 0.006), but no interaction with an existing CTP mismatch was detected (ORadj: 1.676; 95% CI: 0.644-4.364). No symptomatic intracranial hemorrhage according to ECASS-III criteria occurred. Conclusion: Although selected AIS patients with minor stroke may benefit from IVT, CTP mismatch does not correlate with functional outcomes. No benefit from CTP mismatch in guiding IVT was detected in patients without LVO presenting with minor neurological deficits.

Cerebral venous sinus thrombosis and thrombocytopenia due to heparin-independent anti-PF4 antibodies after adenovirus infection.

Not available.

Automated Intracranial Clot Detection: A Promising Tool for Vascular Occlusion Detection in Non-Enhanced CT.

(1) Background: to test the diagnostic performance of a fully convolutional neural network-based software prototype for clot detection in intracranial arteries using non-enhanced computed tomography (NECT) imaging data. (2) Methods: we retrospectively identified 85 patients with stroke imaging and one intracranial vessel occlusion. An automated clot detection prototype computed clot location, clot length, and clot volume in NECT scans. Clot detection rates were compared to the visual assessment of the hyperdense artery sign by two neuroradiologists. CT angiography (CTA) was used as the ground truth. Additionally, NIHSS, ASPECTS, type of therapy, and TOAST were registered to assess the relationship between clinical parameters, image results, and chosen therapy. (3) Results: the overall detection rate of the software was 66%, while the human readers had lower rates of 46% and 24%, respectively. Clot detection rates of the automated software were best in the proximal middle cerebral artery (MCA) and the intracranial carotid artery (ICA) with 88-92% followed by the more distal MCA and basilar artery with 67-69%. There was a high correlation between greater clot length and interventional thrombectomy and between smaller clot length and rather conservative treatment. (4) Conclusions: the automated clot detection prototype has the potential to detect intracranial arterial thromboembolism in NECT images, particularly in the ICA and MCA. Thus, it could support radiologists in emergency settings to speed up the diagnosis of acute ischemic stroke, especially in settings where CTA is not available.

Increasing Patient Safety and Treatment Quality by Using Intraoperative MRI for Organ-Preserving Tumor Resection and High-Dose Rate Brachytherapy in Children with Bladder/Prostate and Perianal Rhabdomyosarcoma.

In children with bladder/prostate (BP) and perianal rhabdomyosarcoma (RMS), we use a hybrid treatment concept for those suitable, combining organ-preserving tumor resection and high-dose rate brachytherapy (HDR-BT). This treatment concept has been shown to improve outcomes. However, it is associated with specific challenges for the clinicians. The exact position of the tubes for BT is a prerequisite for precise radiotherapy. It can finally be determined only with an MRI or CT scan. We evaluated the use of an intraoperative MRI (iMRI) to control the position of the BT tubes and for radiotherapy planning in all patients with BP and perianal RMS who received the above-mentioned combination therapy in our department since January 2021. iMRI was used in 12 children. All tubes were clearly localized. No adverse events occurred. In all 12 children, radiotherapy could be started on time. In a historical cohort without iMRI, this was not possible in 3 out of 20 children. The use of iMRI in children with BP and perianal RMS improved patient safety and treatment quality. This technology has proven to be successful for the patient population we have defined and has become a standard procedure in our institution.

Intraoperative MRI-Guided Resection Is Not Superior to 5-Aminolevulinic Acid Guidance in Newly Diagnosed Glioblastoma: A Prospective Controlled Multicenter Clinical Trial.

PURPOSE: Prospective data suggested a superiority of intraoperative MRI (iMRI) over 5-aminolevulinic acid (5-ALA) for achieving complete resections of contrast enhancement in glioblastoma surgery. We investigated this hypothesis in a prospective clinical trial and correlated residual disease volumes with clinical outcome in newly diagnosed glioblastoma. METHODS: This is a prospective controlled multicenter parallel-group trial with two center-specific treatment arms (5-ALA and iMRI) and blinded evaluation. The primary end point was complete resection of contrast enhancement on early postoperative MRI. We assessed resectability and extent of resection by an independent blinded centralized review of preoperative and postoperative MRI with 1-mm slices. Secondary end points included progression-free survival (PFS) and overall survival (OS), patient-reported quality of life, and clinical parameters. RESULTS: We recruited 314 patients with newly diagnosed glioblastomas at 11 German centers. A total of 127 patients in the 5-ALA and 150 in the iMRI arm were analyzed in the as-treated analysis. Complete resections, defined as a residual tumor ≤0.175 cm³, were achieved in 90 patients (78%) in the 5-ALA and 115 (81%) in the iMRI arm (P = .79). Incision-suture times (P < .001) were significantly longer in the iMRI arm (316 v 215 [5-ALA] minutes). Median PFS and OS were comparable in both arms. The lack of any residual contrast enhancing tumor (0 cm³) was a significant favorable prognostic factor for PFS (P < .001) and OS (P = .048), especially in methylguanine-DNA-methyltransferase unmethylated tumors (P = .006). CONCLUSION: We could not confirm superiority of iMRI over 5-ALA for achieving complete resections. Neurosurgical interventions in newly diagnosed glioblastoma shall aim for safe complete resections with 0 cm³ contrast-enhancing residual disease, as any other residual tumor volume is a negative predictor for PFS and OS.

Clinical outcome of biomarker-guided therapies in adult patients with tumors of the nervous system.

Background: The clinical utility of molecular profiling and targeted therapies for neuro-oncology patients outside of clinical trials is not established. We aimed at investigating feasibility and clinical utility of molecular profiling and targeted therapy in adult patients with advanced tumors in the nervous system within a prospective observational study. Methods: molecular tumor board (MTB)@ZPM (NCT03503149) is a prospective observational precision medicine study for patients with advanced tumors. After inclusion of patients, we performed comprehensive molecular profiling, formulated ranked biomarker-guided therapy recommendations based on consensus by the MTB, and collected prospective clinical outcome data. Results: Here, we present initial data of 661 adult patients with tumors of the nervous system enrolled by December 31, 2021. Of these, 408 patients were presented at the MTB. Molecular-instructed therapy recommendations could be made in 380/408 (93.1%) cases and were prioritized by evidence levels. Therapies were initiated in 86/380 (22.6%) cases until data cutoff. We observed a progression-free survival ratio >1.3 in 31.3% of patients. Conclusions: Our study supports the clinical utility of biomarker-guided therapies for neuro-oncology patients and indicates clinical benefit in a subset of patients. Our data might inform future clinical trials, translational studies, and even clinical care.

Recurrent Acute Disseminated Encephalomyelitis (ADEM) after COVID-19-vaccination and after subsequent COVID-19-infection: A case report (part II).

Acute disseminated encephalomyelitis (ADEM) is an autoimmune disorder of the central nervous system (CNS), which is commonly associated to previous viral infection or immunization. Cases of ADEM with a potential relationship to both severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination have been reported. We recently published a rare case of a 65-year-old patient who suffered from a corticosteroid- and immunoglobulin-refractory multiple autoimmune syndrome including ADEM following Pfizer-BioNTech coronavirus disease (COVID)-19 vaccination, and whose symptoms largely resolved after repeated plasma exchange (PE). Four months later, the patient was diagnosed with SARS-CoV-2 omicron variant infection after experiencing mild upper respiratory tract symptoms. Few days later, the patient developed severe tetraparesis with magnetic resonance imaging (MRI) showing multiple new inflammatory contrast-enhancing lesions in the left middle cerebellar peduncle, cervical spinal cord, and ventral conus medullaris. Repeated cerebrospinal fluid (CSF) analyses indicated blood-brain barrier damage (increased albumin ratio) without signs of SARS-CoV-2 invasion (mild pleocytosis, no intrathecal antibody production). SARS-CoV-2 specific immunoglobulin G (IgG) were detected in serum and to a much lower degree in CSF with close correlation between both concentrations over time, reflecting antibody dynamics of vaccine- and infection-induced immune response, and blood-brain barrier patency. Daily PE therapy was initiated. Given the patient's lack of improvement after seven PE, treatment with rituximab was considered. After a first dose, however, the patient suffered epididymo-orchitis leading to sepsis, and declined rituximab continuation. At 3-months follow-up, clinical symptoms had dramatically improved. The patient regained walking ability without assistance. This case of recurrent ADEM after COVID-19-vaccination and after subsequent COVID-19-infection strongly supports the hypotheses of neuroimmunological complications in these conditions being promoted by a systemic immune response and mediated by molecular mimicry of, both, viral and vaccine SARS-CoV-2 antigens and CNS self-antigens.

Patient Reported and Clinical Outcomes after High-Dose Chemotherapy and Autologous Stem Cell Transplantation in Primary Central Nervous System Lymphoma.

Primary central nervous system lymphomas (PCNSL) are rare and associated with an adverse prognosis. High-dose chemotherapy followed by autologous stem cell transplantation (HDC/ASCT) improves progression free (PFS) and overall survival (OS) but neurocognition, performance status and quality of life (QoL) in patient-reported outcome (PRO) after HDC/ASCT remains underexplored. Especially elderly patients may insufficiently recover from this demanding therapy. Therefore, this single-center analysis investigated all PCNSL patients who received HDC/ASCT at the University Hospital Tübingen from 2006-2021 (n = 40, median age 60.5 years) in a retrospective manner. The 2-year PFS/OS was 78.7%/77.3%, respectively, without significant differences between the tested age-groups (≤60 vs. >60 years, p = 0.531/p = 0.334). Higher Thiotepa dosage was an independent predictor for better OS (p = 0.018). Additionally, a one-time prospective, cross-sectional analysis after HDC/ASCT in the same cohort was performed (n = 31; median follow-up 45 months). Here, the median ECOG improved by HDC/ASCT from 1 to 0 and mini-mental state examinations revealed unimpaired neurocognitive functioning (median 28 pts.). PRO data collected by EORTC QLQ-C30 showed a good QoL in both age groups with an average global health status (GHS) of 68.82% (≤60y: 64.72%, >60y: 74.14%). Together, our data indicate that HDC/ASCT is an effective therapy with respect to disease control, overall health status and quality of life, irrespective of patient age.