External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease.

A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for automated volumetry and to compare the results with the manual measurement methods used in clinical practice as well as volume calculations of the caudate nuclei based on manual segmentations. Twenty-two patients were included retrospectively, consisting of eleven patients with Huntington's disease and caudate nucleus atrophy and an age- and sex-matched control group. To quantify caudate head atrophy, the frontal horn width to intercaudate distance ratio and the intercaudate distance to inner table width ratio were obtained. The software mdbrain was used for automated volumetry. Manually measured ratios and automatically measured volumes of the groups were compared using two-sample t-tests. Pearson correlation analyses were performed. The relative difference between automatically and manually determined volumes of the caudate nuclei was calculated. Both ratios were significantly different between the groups. The automatically and manually determined volumes of the caudate nuclei showed a high level of agreement with a mean relative discrepancy of - 2.3 ± 5.5%. The Huntington's disease group showed significantly lower volumes in a variety of supratentorial brain structures. The highest degree of atrophy was shown for the caudate nucleus, putamen, and pallidum (all p < .0001). The caudate nucleus volume and the ratios were found to be strongly correlated in both groups. In conclusion, in patients with progressed Huntington's disease, it was shown that the automatically determined caudate nucleus volume correlates strongly with measured ratios commonly used in clinical practice. Both methods allowed clear differentiation between groups in this collective. The software additionally allows radiologists to more objectively assess the involvement of a variety of brain structures that are less accessible to standard semiquantitative methods.

Data Extraction from Free-Text Reports on Mechanical Thrombectomy in Acute Ischemic Stroke Using ChatGPT: A Retrospective Analysis.

Background Procedural details of mechanical thrombectomy in patients with ischemic stroke are important predictors of clinical outcome and are collected for prospective studies or national stroke registries. To date, these data are collected manually by human readers, a labor-intensive task that is prone to errors. Purpose To evaluate the use of the large language models (LLMs) GPT-4 and GPT-3.5 to extract data from neuroradiology reports on mechanical thrombectomy in patients with ischemic stroke. Materials and Methods This retrospective study included consecutive reports from patients with ischemic stroke who underwent mechanical thrombectomy between November 2022 and September 2023 at institution 1 and between September 2016 and December 2019 at institution 2. A set of 20 reports was used to optimize the prompt, and the ability of the LLMs to extract procedural data from the reports was compared using the McNemar test. Data manually extracted by an interventional neuroradiologist served as the reference standard. Results A total of 100 internal reports from 100 patients (mean age, 74.7 years ± 13.2 [SD]; 53 female) and 30 external reports from 30 patients (mean age, 72.7 years ± 13.5; 18 male) were included. All reports were successfully processed by GPT-4 and GPT-3.5. Of 2800 data entries, 2631 (94.0% [95% CI: 93.0, 94.8]; range per category, 61%-100%) data points were correctly extracted by GPT-4 without the need for further postprocessing. With 1788 of 2800 correct data entries, GPT-3.5 produced fewer correct data entries than did GPT-4 (63.9% [95% CI: 62.0, 65.6]; range per category, 14%-99%; P < .001). For the external reports, GPT-4 extracted 760 of 840 (90.5% [95% CI: 88.3, 92.4]) correct data entries, while GPT-3.5 extracted 539 of 840 (64.2% [95% CI: 60.8, 67.4]; P < .001). Conclusion Compared with GPT-3.5, GPT-4 more frequently extracted correct procedural data from free-text reports on mechanical thrombectomy performed in patients with ischemic stroke. © RSNA, 2024 Supplemental material is available for this article.

Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.

OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD. MATERIALS AND METHODS: A convolutional neural network was trained using manually corrected, filter-based segmentations (n = 1000) to automatically segment the PVS in the centrum semiovale from interpolated, coronal T2-weighted magnetic resonance imaging scans (n = 894). These scans were sourced from the national German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study. Convolutional neural network-based segmentations and those performed by a human rater were compared in terms of segmentation volume, identified PVS clusters, as well as Dice score. The comparison revealed good segmentation quality (Pearson correlation coefficient r = 0.70 with P < 0.0001 for PVS volume, detection rate in cluster analysis = 84.3%, and Dice score = 59.0%). Subsequent multivariate linear regression analysis, adjusted for participants' age, was performed to correlate PVS volume with clinical diagnoses, disease progression, cerebrospinal fluid biomarkers, lifestyle factors, and cognitive function. Cognitive function was assessed using the Mini-Mental State Examination, the Comprehensive Neuropsychological Test Battery, and the Cognitive Subscale of the 13-Item Alzheimer's Disease Assessment Scale. RESULTS: Multivariate analysis, adjusted for age, revealed that participants with AD and MCI, but not those with SCD, had significantly higher PVS volumes compared with CU participants without SCD (P = 0.001 for each group). Furthermore, CU participants who developed incident MCI within 4.5 years after the baseline assessment showed significantly higher PVS volumes at baseline compared with those who did not progress to MCI (P = 0.03). Cognitive function was negatively correlated with PVS volume across all participant groups (P ≤ 0.005 for each). No significant correlation was found between PVS volume and any of the following parameters: cerebrospinal fluid biomarkers, sleep quality, body mass index, nicotine consumption, or alcohol abuse. CONCLUSIONS: The very early changes of PVS volume may suggest that alterations in PVS function are involved in the pathophysiology of AD. Overall, the volumetric assessment of centrum semiovale PVS represents a very early imaging biomarker for AD.

Impact of an AI software on the diagnostic performance and reading time for the detection of cerebral aneurysms on time of flight MR-angiography.

PURPOSE: To evaluate the impact of an AI-based software trained to detect cerebral aneurysms on TOF-MRA on the diagnostic performance and reading times across readers with varying experience levels. METHODS: One hundred eighty-six MRI studies were reviewed by six readers to detect cerebral aneurysms. Initially, readings were assisted by the CNN-based software mdbrain. After 6 weeks, a second reading was conducted without software assistance. The results were compared to the consensus reading of two neuroradiological specialists and sensitivity (lesion and patient level), specificity (patient level), and false positives per case were calculated for the group of all readers, for the subgroup of physicians, and for each individual reader. Also, reading times for each reader were measured. RESULTS: The dataset contained 54 aneurysms. The readers had no experience (three medical students), 2 years experience (resident in neuroradiology), 6 years experience (radiologist), and 12 years (neuroradiologist). Significant improvements of overall specificity and the overall number of false positives per case were observed in the reading with AI support. For the physicians, we found significant improvements of sensitivity on lesion and patient level and false positives per case. Four readers experienced reduced reading times with the software, while two encountered increased times. CONCLUSION: In the reading with the AI-based software, we observed significant improvements in terms of specificity and false positives per case for the group of all readers and significant improvements of sensitivity and false positives per case for the physicians. Further studies are needed to investigate the effects of the AI-based software in a prospective setting.

Synchronous versus metachronous spinal metastasis: a comparative study of survival outcomes following neurosurgical treatment.

PURPOSE: Patients with spinal metastases (SM) from solid neoplasms typically exhibit progression to an advanced cancer stage. Such metastases can either develop concurrently with an existing cancer diagnosis (termed metachronous SM) or emerge as the initial indication of an undiagnosed malignancy (referred to as synchronous SM). The present study investigates the prognostic implications of synchronous compared to metachronous SM following surgical resection. METHODS: From 2015 to 2020, a total of 211 individuals underwent surgical intervention for SM at our neuro-oncology facility. We conducted a survival analysis starting from the date of the neurosurgical procedure, comparing those diagnosed with synchronous SM against those with metachronous SM. RESULTS: The predominant primary tumor types included lung cancer (23%), prostate cancer (21%), and breast cancer (11.3%). Of the participants, 97 (46%) had synchronous SM, while 114 (54%) had metachronous SM. The median overall survival post-surgery for those with synchronous SM was 13.5 months (95% confidence interval (CI) 6.1-15.8) compared to 13 months (95% CI 7.7-14.2) for those with metachronous SM (p = 0.74). CONCLUSIONS: Our findings suggest that the timing of SM diagnosis (synchronous versus metachronous) does not significantly affect survival outcomes following neurosurgical treatment for SM. These results support the consideration of neurosurgical procedures regardless of the temporal pattern of SM manifestation.

Association between occlusion location, net water uptake and ischemic lesion growth in large vessel anterior circulation strokes.

Ischemic lesion net water uptake (NWU) represents a quantitative imaging biomarker for cerebral edema in acute ischemic stroke. Data on NWU for distinct occlusion locations remain scarce, but might help to improve the prognostic value of NWU. In this retrospective multicenter cohort study, we compared NWU between patients with proximal large vessel occlusion (pLVO; ICA or proximal M1) and distal large vessel occlusion (dLVO; distal M1 or M2). NWU was quantified by densitometric measurements of the early ischemic region. Arterial collateral status was assessed using the Maas scale. Regression analysis was used to investigate the relationship between occlusion location, NWU and ischemic lesion growth. A total of 685 patients met inclusion criteria. Early ischemic lesion NWU was higher in patients with pLVO compared with dLVO (7.7% vs 3.9%, P < .001). The relationship between occlusion location and NWU was partially mediated by arterial collateral status. NWU was associated with absolute ischemic lesion growth between admission and follow-up imaging (ß estimate, 5.50, 95% CI, 3.81-7.19, P < .001). This study establishes a framework for the relationship between occlusion location, arterial collateral status, early ischemic lesion NWU and ischemic lesion growth. Future prognostic thresholds for NWU might be optimized by adjusting for the occlusion location.

A versatile look-up algorithm for mapping pH values and magnesium ion content using 31 P MRSI.

31 P MRSI allows for the non-invasive mapping of pH and magnesium ion content (Mg) in vivo, by translating the chemical shifts of inorganic phosphate and adenosine-5'-triphosphate (ATP) to pH and Mg via suitable calibration equations, such as the modified Henderson-Hasselbalch equation. However, the required constants in these calibration equations are typically only determined for physiological conditions, posing a particular challenge for their application to diseased tissue, where the biochemical conditions might change manyfold. In this article, we propose a multi-parametric look-up algorithm aiming at the condition-independent determination of pH and Mg by employing multiple quantifiable 31 P spectral properties simultaneously. To generate entries for an initial look-up table, measurements from 114 model solutions prepared with varying chemical properties were made at 9.4 T. The number of look-up table entries was increased by inter- and extrapolation using a multi-dimensional function developed based on the Hill equation. The assignment of biochemical parameters, that is, pH and Mg, is realized using probability distributions incorporating specific measurement uncertainties on the quantified spectral parameters, allowing for an estimation of most plausible output values. As proof of concept, we applied a version of the look-up algorithm employing only the chemical shifts of γ- and ß-ATP for the determination of pH and Mg to in vivo 3D 31 P MRSI data acquired at 7 T from (i) the lower leg muscles of healthy volunteers and (ii) the brains of patients with glioblastoma. The resulting volumetric maps showed plausible values for pH and Mg, partly revealing differences from maps generated using the conventional calibration equations.

First implementation of dynamic oxygen-17 (17O) magnetic resonance imaging at 7 Tesla during neuronal stimulation in the human brain.

OBJECTIVE: First implementation of dynamic oxygen-17 (17O) MRI at 7 Tesla (T) during neuronal stimulation in the human brain. METHODS: Five healthy volunteers underwent a three-phase 17O gas (17O2) inhalation experiment. Combined right-side visual stimulus and right-hand finger tapping were used to achieve neuronal stimulation in the left cerebral hemisphere. Data analysis included the evaluation of the relative partial volume (PV)-corrected time evolution of absolute 17O water (H217O) concentration and of the relative signal evolution without PV correction. Statistical analysis was performed using a one-tailed paired t test. Blood oxygen level-dependent (BOLD) experiments were performed to validate the stimulation paradigm. RESULTS: The BOLD maps showed significant activity in the stimulated left visual and sensorimotor cortex compared to the non-stimulated right side. PV correction of 17O MR data resulted in high signal fluctuations with a noise level of 10% due to small regions of interest (ROI), impeding further quantitative analysis. Statistical evaluation of the relative H217O signal with PV correction (p = 0.168) and without (p = 0.382) did not show significant difference between the stimulated left and non-stimulated right sensorimotor ROI. DISCUSSION: The change of cerebral oxygen metabolism induced by sensorimotor and visual stimulation is not large enough to be reliably detected with the current setup and methodology of dynamic 17O MRI at 7 T.

Early neurological deterioration in patients with acute ischemic stroke is linked to unfavorable cerebral venous outflow.

INTRODUCTION: Early neurological deterioration (END) is associated with poor outcomes in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). Causes of END after mechanical thrombectomy (MT) include unsuccessful recanalization and reperfusion hemorrhages. However, little is known about END excluding the aforementioned causes. We aimed to investigate factors associated with unexplained END (ENDunexplained) with regard to the cerebral collateral status. PATIENTS AND METHODS: Multicenter retrospective study of AIS-LVO patients with successful MT (mTICI 2b-3). On admission CT angiography (CTA), pial arterial collaterals and venous outflow (VO) were assessed using the modified Tan-Scale and the Cortical Vein Opacification Score (COVES), respectively. ENDunexplained was defined as an increase in NIHSS score of ⩾ 4 within the first 24 hours after MT without parenchymal hemorrhage on follow-up imaging. Multivariable regression analyses were performed to examine factors of ENDunexplained and unfavorable functional outcome (modified Rankin Scale score 3-6). RESULTS: A total of 620 patients met the inclusion criteria. ENDunexplained occurred in 10% of patients. While there was no significant difference in pial arterial collaterals, patients with ENDunexplained exhibited more often unfavorable VO (81% vs. 53%; P < 0.001). Unfavorable VO (aOR [95% CI]; 2.56 [1.02-6.40]; P = 0.045) was an independent predictor of ENDunexplained. ENDunexplained was independently associated with unfavorable functional outcomes at 90 days (aOR [95% CI]; 6.25 [2.06-18.94]; P = 0.001). DISCUSSION AND CONCLUSION: Unfavorable VO on admission CTA was associated with ENDunexplained. ENDunexplained was independently linked to unfavorable functional outcomes at 90 days. Identifying AIS-LVO patients at risk of ENDunexplained may help to select patients for intensified monitoring and guide to optimal treatment regimes.

Whole-Brain Intracellular pH Mapping of Gliomas Using High-Resolution 31P MR Spectroscopic Imaging at 7.0 T.

Malignant tumors commonly exhibit a reversed pH gradient compared with normal tissue, with a more acidic extracellular pH and an alkaline intracellular pH (pHi). In this prospective study, pHi values in gliomas were quantified using high-resolution phosphorous 31 (31P) spectroscopic MRI at 7.0 T and were used to correlate pHi alterations with histopathologic findings. A total of 12 participants (mean age, 58 years ± 18 [SD]; seven male, five female) with histopathologically proven, newly diagnosed glioma were included between September 2018 and November 2019. The 31P spectroscopic MRI scans were acquired using a double-resonant 31P/1H phased-array head coil together with a three-dimensional (3D) 31P chemical shift imaging sequence (5.7-mL voxel volume) performed with a 7.0-T whole-body system. The 3D volumetric segmentations were performed for the whole-tumor volumes (WTVs); tumor subcompartments of necrosis, gadolinium enhancement, and nonenhancing T2 (NCE T2) hyperintensity; and normal-appearing white matter (NAWM), and pHi values were compared. Spearman correlation was used to assess association between pHi and the proliferation index Ki-67. For all study participants, mean pHi values were higher in the WTV (7.057 ± 0.024) compared with NAWM (7.006 ± 0.012; P < .001). In eight participants with high-grade gliomas, pHi was increased in all tumor subcompartments (necrosis, 7.075 ± 0.033; gadolinium enhancement, 7.075 ± 0.024; NCE T2 hyperintensity, 7.043 ± 0.015) compared with NAWM (7.004 ± 0.014; all P < .01). The pHi values of WTV positively correlated with Ki-67 (R2 = 0.74, r = 0.78, P = .001). In conclusion, 31P spectroscopic MRI at 7.0 T enabled high-resolution quantification of pHi in gliomas, with pHi alteration associated with the Ki-67 proliferation index, and may aid in diagnosis and treatment monitoring. Keywords: 31P MRSI, pH, Glioma, Glioblastoma, Ultra-High-Field MRI, Imaging Biomarker, 7 Tesla Supplemental material is available for this article. © RSNA, 2023.

Undetected pseudoprogressions in the CeTeG/NOA-09 trial: hints from postprogression survival and MRI analyses.

PURPOSE: In the randomized CeTeG/NOA-09 trial, lomustine/temozolomide (CCNU/TMZ) was superior to TMZ therapy regarding overall survival (OS) in MGMT promotor-methylated glioblastoma. Progression-free survival (PFS) and pseudoprogression rates (about 10%) were similar in both arms. Further evaluating this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at first progression according to modified RANO criteria (mRANO). METHODS: We classified the patients of the CeTeG/NOA-09 trial according to long vs. short PPS employing a cut-off of 18 months and compared baseline characteristics and survival times. In patients with available MRIs and confirmed progression, the increase in T1-enhancing, FLAIR hyperintense lesion volume and the change in ADC mean value of contrast-enhancing tumor upon progression were determined. RESULTS: Patients with long PPS in the CCNU/TMZ arm had a particularly short PFS (5.6 months). PFS in this subgroup was shorter than in the long PPS subgroup of the TMZ arm (11.1 months, p = 0.01). At mRANO-defined progression, patients of the CCNU/TMZ long PPS subgroup had a significantly higher increase of mean ADC values (p = 0.015) and a tendency to a stronger volumetric increase in T1-enhancement (p = 0.22) as compared to long PPS patients of the TMZ arm. CONCLUSION: The combination of survival and MRI analyses identified a subgroup of CCNU/TMZ-treated patients with features that sets them apart from other patients in the trial: short first PFS despite long PPS and significant increase in mean ADC values upon mRANO-defined progression. The observed pattern is compatible with the features commonly observed in pseudoprogression suggesting mRANO-undetected pseudoprogressions in the CCNU/TMZ arm of CeTeG/NOA-09.

Post-Surgical Depositions of Blood Products Are No Major Confounder for the Diagnostic and Prognostic Performance of CEST MRI in Patients with Glioma.

Amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) imaging can predict clinical outcomes in patients with glioma. However, the treatment of brain tumors is accompanied by the deposition of blood products within the tumor area in most cases. For this reason, the objective was to assess whether the diagnostic interpretation of the APT and ssMT is affected by methemoglobin (mHb) and hemosiderin (Hs) depositions at the first follow-up MRI 4 to 6 weeks after the completion of radiotherapy. A total of 34 participants underwent APT and ssMT imaging by applying reconstruction methods described by Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT and MTRRexMT) and Mehrabian et al. (MTconst). Contrast-enhancing tumor (CE), whole tumor (WT), mHb and Hs were segmented on contrast-enhanced T1wCE, T2w-FLAIR, T1w and T2*w images. ROC-analysis, Kaplan-Meier analysis and the log rank test were used to test for the association of mean contrast values with therapy response and overall survival (OS) before (WT and CE) and after correcting tumor volumes for mHb and Hs (CEC and WTC). CEC showed higher associations of the MTRRexMT with therapy response (CE: AUC = 0.677, p = 0.081; CEC: AUC = 0.705, p = 0.044) and of the APTwasym with OS (CE: HR = 2.634, p = 0.040; CEC: HR = 2.240, p = 0.095). In contrast, WTC showed a lower association of the APTwasym with survival (WT: HR = 2.304, p = 0.0849; WTC: HR = 2.990, p = 0.020). Overall, a sophisticated correction for blood products did not substantially influence the clinical performance of APT and ssMT imaging in patients with glioma early after radiotherapy.

Clinical significance and prevalence of subarachnoid hyperdensities on flat detector CT after mechanical thrombectomy: does it really matter?

BACKGROUND: Subarachnoid hyperdensities after mechanical thrombectomy (MT) are a common finding. However, it is often regarded as clinically insignificant. OBJECTIVE: With this single-center investigation, to identify the prevalence of subarachnoid hyperdensities following MT, associated predictors, and the impact on the clinical outcome of the patients. METHODS: 383 patients from the stroke registry were analyzed for the presence of subarachnoid hyperdensities on flat detector CT (FDCT) directly after the completion of MT, and on follow-up dual-energy CT, then classified according to a visual grading scale. 178 patients were included with anterior circulation occlusions. Regression analysis was performed to identify significant predictors, and Kruskal-Wallis analysis and Χ2 test were performed to test the variables among the different groups. The primary outcome was the modified Rankin Scale (mRS) score at 90 days and was analyzed with the Wilcoxon-Mann-Whitney rank-sum test. RESULTS: The prevalence of subarachnoid hyperdensities on FDCT was (66/178, 37.1%) with patients experiencing a significant unfavorable outcome (P=0.035). Significantly fewer patients with subarachnoid hyperdensities achieved a mRS score of ≤3 at 90 days 25/66 (37.9%) vs 60/112 (53.6%), P=0.043). In addition, mortality was significantly higher in the subarachnoid hyperdensities group (34.8% vs 19.6%, P=0.024). Distal occlusions and a higher number of device passes were significantly associated with subarachnoid hyperdensities (P=0.026) and (P=0.001), respectively. Patients who received intravenous tissue plasminogen activator had significantly fewer subarachnoid hyperdensities (P=0.029). CONCLUSIONS: Postinterventional subarachnoid hyperdensities are a frequent finding after MT and are associated with neurological decline and worse functional outcome. They are more common with distal occlusions and multiple device passes.

First application of dynamic oxygen-17 magnetic resonance imaging at 7 Tesla in a patient with early subacute stroke.

Dynamic oxygen-17 (17O) magnetic resonance imaging (MRI) is an imaging method that enables a direct and non-invasive assessment of cerebral oxygen metabolism and thus potentially the distinction between viable and non-viable tissue employing a three-phase inhalation experiment. The purpose of this investigation was the first application of dynamic 17O MRI at 7 Tesla (T) in a patient with stroke. In this proof-of-concept experiment, dynamic 17O MRI was applied during 17O inhalation in a patient with early subacute stroke. The analysis of the relative 17O water (H217O) signal for the affected stroke region compared to the healthy contralateral side revealed no significant difference. However, the technical feasibility of 17O MRI has been demonstrated paving the way for future investigations in neurovascular diseases.

Semi-solid MT and APTw CEST-MRI predict clinical outcome of patients with glioma early after radiotherapy.

PURPOSE: The purpose of this study was to compare the potential of asymmetry-based (APTwasym ), Lorentzian-fit-based (PeakAreaAPT and MTconst ), and relaxation-compensated (MTRRex APT and MTRRex MT) CEST contrasts of the amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) for early response assessment and prediction of progression-free survival (PFS) in patients with glioma. METHODS: Seventy-two study participants underwent CEST-MRI at 3T from July 2018 to December 2021 in a prospective clinical trial four to 6 wk after the completion of radiotherapy for diffuse glioma. Tumor segmentations were performed on T2w -FLAIR and contrast-enhanced T1w images. Therapy response assessment and determination of PFS were performed according to response assessment in neuro oncology (RANO) criteria using clinical follow-up data with a median observation time of 9.2 mo (range, 1.6-40.8) and compared to CEST MRI metrics. Statistical testing included receiver operating characteristic analyses, Mann-Whitney-U-test, Kaplan-Meier analyses, and logrank-test. RESULTS: MTconst (AUC = 0.79, p < 0.01) showed a stronger association with RANO response assessment compared to PeakAreaAPT (AUC = 0.71, p = 0.02) and MTRRex MT (AUC = 0.71, p = 0.02), and enabled differentiation of participants with pseudoprogression (n = 8) from those with true progression (AUC = 0.79, p = 0.02). Furthermore, MTconst (HR = 3.04, p = 0.01), PeakAreaAPT (HR = 0.39, p = 0.03), and APTwasym (HR = 2.63, p = 0.02) were associated with PFS. MTRRex APT was not associated with any outcome. CONCLUSION: MTconst , PeakAreaAPT, and APTwasym imaging predict clinical outcome by means of progression-free survival. Furthermore, MTconst enables differentiation of radiation-induced pseudoprogression from disease progression. Therefore, the assessed metrics may have synergistic potential for supporting clinical decision making during follow-up of patients with glioma.

A novel geometry-based analysis of hippocampal morphometry in mesial temporal lobe epilepsy.

Hippocampal volumetry is an essential tool in researching and diagnosing mesial temporal lobe epilepsy (mTLE). However, it has a limited ability to detect subtle alterations in hippocampal morphometry. Here, we establish and apply a novel geometry-based tool that enables point-wise morphometric analysis based on an intrinsic coordinate system of the hippocampus. We hypothesized that this point-wise analysis uncovers structural alterations not measurable by volumetry, but associated with histological underpinnings and the neuropsychological profile of mTLE. We conducted a retrospective study in 204 individuals with mTLE and 57 age- and gender-matched healthy subjects. FreeSurfer-based segmentations of hippocampal subfields in 3T-MRI were subjected to a geometry-based analysis that resulted in a coordinate system of the hippocampal mid-surface and allowed for point-wise measurements of hippocampal thickness and other features. Using point-wise analysis, we found significantly lower thickness and higher FLAIR signal intensity in the entire affected hippocampus of individuals with hippocampal sclerosis (HS-mTLE). In the contralateral hippocampus of HS-mTLE and the affected hippocampus of MRI-negative mTLE, we observed significantly lower thickness in the presubiculum. Impaired verbal memory was associated with lower thickness in the left presubiculum. In HS-mTLE histological subtype 3, we observed higher curvature than in subtypes 1 and 2 (all p < .05). These findings could not be observed using conventional volumetry (Bonferroni-corrected p < .05). We show that point-wise measures of hippocampal morphometry can uncover structural alterations not measurable by volumetry while also reflecting histological underpinnings and verbal memory. This substantiates the prospect of their clinical application.

CEST imaging of the APT and ssMT predict the overall survival of patients with glioma at the first follow-up after completion of radiotherapy at 3T.

BACKGROUND AND PURPOSE: Outcome prediction of patients with glioma early after the completion of radiotherapy represents a major clinical challenge. Previously, the prognostic value of chemical exchange saturation transfer (CEST) imaging has been demonstrated in patients with newly diagnosed glioma. The objective of this study was to assess the potential of amide proton transfer (APT)-, relayed nuclear Overhauser effect (rNOE)- and semi-solid magnetization transfer (ssMT)-imaging according to Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT, MTRRexNOE and MTRRexMT) and Mehrabian et al. (PeakAreaAPT, PeakAreaNOE and MTconst) for the prognostication of the overall survival (OS) of patients with glioma at the first follow-up after the completion of radiotherapy. MATERIALS AND METHODS: 49 of 72 participants with diffuse glioma, who underwent CEST MRI at 3T between July 2018 and December 2021 4 to 6 weeks after the completion of radiotherapy, were analyzed. Contrast-enhancing tumor (CE) and whole tumor (WT) volumes were segmented on T2w-FLAIR and contrast-enhanced T1w images. Kaplan-Meier analysis and logrank-test were used for statistical analyses. RESULTS: APTw imaging demonstrated the strongest association with OS (HR = 4.66, p < 0.001). The MTconst (HR = 2.54, p = 0.044) was associated with the OS of participants with residual contrast-enhancing glioma tissue, whilst the MTRRexAPT (HR = 2.44, p = 0.056) showed a trend in this sub-cohort. The MTRRexNOE, MTRRexMT and PeakAreaNOE were not associated with survival. CONCLUSION: Imaging of the APT and ssMT at the first follow-up 4 to 6 weeks after the completion of radiotherapy at 3T were associated with the overall survival of study participants with glioma.

Brain Volume Changes after COVID-19 Compared to Healthy Controls by Artificial Intelligence-Based MRI Volumetry.

Cohort studies that quantify volumetric brain data among individuals with different levels of COVID-19 severity are presently limited. It is still uncertain whether there exists a potential correlation between disease severity and the effects of COVID-19 on brain integrity. Our objective was to assess the potential impact of COVID-19 on measured brain volume in patients with asymptomatic/mild and severe disease after recovery from infection, compared with healthy controls, using artificial intelligence (AI)-based MRI volumetry. A total of 155 participants were prospectively enrolled in this IRB-approved analysis of three cohorts with a mild course of COVID-19 (n = 51, MILD), a severe hospitalised course (n = 48, SEV), and healthy controls (n = 56, CTL) all undergoing a standardised MRI protocol of the brain. Automated AI-based determination of various brain volumes in mL and calculation of normalised percentiles of brain volume was performed with mdbrain software, using a 3D T1-weighted magnetisation-prepared rapid gradient echo (MPRAGE) sequence. The automatically measured brain volumes and percentiles were analysed for differences between groups. The estimated influence of COVID-19 and demographic/clinical variables on brain volume was determined using multivariate analysis. There were statistically significant differences in measured brain volumes and percentiles of various brain regions among groups, even after the exclusion of patients undergoing intensive care, with significant volume reductions in COVID-19 patients, which increased with disease severity (SEV > MILD > CTL) and mainly affected the supratentorial grey matter, frontal and parietal lobes, and right thalamus. Severe COVID-19 infection, in addition to established demographic parameters such as age and sex, was a significant predictor of brain volume loss upon multivariate analysis. In conclusion, neocortical brain degeneration was detected in patients who had recovered from SARS-CoV-2 infection compared to healthy controls, worsening with greater initial COVID-19 severity and mainly affecting the fronto-parietal brain and right thalamus, regardless of ICU treatment. This suggests a direct link between COVID-19 infection and subsequent brain atrophy, which may have major implications for clinical management and future cognitive rehabilitation strategies.