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This study systematically compared the performance of ss-EPI-DWI, rs-EPI-DWI (RESOLVE), and TGSE-BLADE-DWI for detecting small ischemic lesions (10 –2 mm) using a DWI phantom to gain insights for optimization of microstructural orbital MRI for retinal ischemia diagnosis. A DWI phantom simulating ischemic lesions embedded in healthy neuronal tissue was used to quantitatively and qualitatively assess the sequences at 3T. Signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), relative contrast (ReCon), geometric distortion rate (GDR) and apparent diffusion coefficient (ADC) accuracy were measured, with correlation analysis examining the effect of lesion size. Qualitative analysis was performed by two neuroradiologists evaluating the images in different criteria using a 5-point Likert scale. Among all sequences rs-EPI-DWI showed the most precise ADC ( p  < 0.001), highest CNR ( p  < 0.001) and relative contrast ( p  < 0.001) and non-inferiority to ss-EPI-DWI in SNR ( p  = 0.06). Both TGSE-BLADE-DWI and rs-EPI-DWI showed less GDR and susceptibility artifacts than ss-EPI-DWI qualitatively. All sequences depicted even the 2 mm lesion qualitatively; however, lesion size most strongly affected TGSE-BLADE-DWI quantitatively. Therefore, rs-EPI-DWI and TGSE-BLADE-DWI are promising alternatives to conventional ss-EPI-DWI for microstructural orbital MRI and may prove useful for clinical diagnosis of acute retinal ischemia due to high spatial resolution with reliable ADC acquisition, low geometric distortion and reduced susceptibility artifacts.

Cerebral viscoelastic constants can be measured in a noninvasive, image-based way by magnetic resonance elastography (MRE) for the detection of neurological disorders. However, MRE brain maps of viscoelastic constants are still limited by low spatial resolution. Here we introduce three-dimensional multifrequency MRE of the brain combined with a novel reconstruction algorithm based on a model-free multifrequency inversion for calculating spatially resolved viscoelastic parameter maps of the human brain corresponding to the dynamic range of shear oscillations between 30 and 60 Hz. Maps of two viscoelastic parameters, the magnitude and the phase angle of the complex shear modulus, |G*| and φ, were obtained and normalized to group templates of 23 healthy volunteers in the age range of 22 to 72 years. This atlas of the anatomy of brain mechanics reveals a significant contrast in the stiffness parameter |G*| between different anatomical regions such as white matter (WM; 1.252±0.260 kPa), the corpus callosum genu (CCG; 1.104±0.280 kPa), the thalamus (TH; 1.058±0.208 kPa) and the head of the caudate nucleus (HCN; 0.649±0.101 kPa). φ, which is sensitive to the lossy behavior of the tissue, was in the order of CCG (1.011±0.172), TH (1.037±0.173), CN (0.906±0.257) and WM (0.854±0.169). The proposed method provides the first normalized maps of brain viscoelasticity with anatomical details in subcortical regions and provides useful background data for clinical applications of cerebral MRE.

Objectives To evaluate the effects of anatomical phantom structure on task-based image quality assessment compared with a uniform phantom background. Methods Two neck phantom types of identical shape were investigated: a uniform type containing 10-mm lesions with 4, 9, 18, 30, and 38 HU contrast to the surrounding area and an anatomically realistic type containing lesions of the same size and location with 10, 18, 30, and 38 HU contrast. Phantom images were acquired at two dose levels (CTDIvol of 1.4 and 5.6 mGy) and reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Detection accuracy was evaluated by seven radiologists in a 4-alternative forced choice experiment. Results Anatomical phantom structure impaired lesion detection at all lesion contrasts ( p  < 0.01). Detectability in the anatomical phantom at 30 HU contrast was similar to 9 HU contrast in uniform images (91.1% vs. 89.5%). Detection accuracy decreased from 83.6% at 5.6 mGy to 55.4% at 1.4 mGy in uniform FBP images ( p  < 0.001), whereas AIDR 3D preserved detectability at 1.4 mGy (80.7% vs. 85% at 5.6 mGy, p  = 0.375) and was superior to FBP ( p  < 0.001). In the assessment of anatomical images, superiority of AIDR 3D was not confirmed and dose reduction moderately affected detectability (74.6% vs. 68.2%, p  = 0.027 for FBP and 81.1% vs. 73%, p  = 0.018 for AIDR 3D). Conclusions A lesion contrast increase from 9 to 30 HU is necessary for similar detectability in anatomical and uniform neck phantom images. Anatomical phantom structure influences task-based assessment of iterative reconstruction and dose effects. Key Points • A lesion contrast increase from 9 to 30 HU is necessary for similar low-contrast detectability in anatomical and uniform neck phantom images. • Phantom background structure influences task-based assessment of iterative reconstruction and dose effects. • Transferability of CT assessment to clinical imaging can be expected to improve as the realism of the test environment increases.

Brain morphometry derived from clinical imaging has an underexplored potential for the multimodal prediction of postoperative delirium (POD), an acute encephalopathy that can lead to long-term adverse outcomes or death. This study conducted a comprehensive analysis of patient trajectories, integrating magnetic resonance imaging (MRI) data and electronic health records (EHRs) across two general surgical cohorts. We applied univariate test methods and linear mixed-effects models correcting for confounding. Non-linear multi-layer perceptrons (MLPs), boosted decision trees, and logistic regressions were trained on EHR data, brain morphometry measures, and their multimodal fusion to predict POD. Age-adjusted correlations identified cortical thickness of temporal gyri, as well as thalamic and brainstem volumes to be POD-relevant neuroanatomical features. MLP models demonstrated robust predictive capability, achieving notably high performances up to 86% AUROC (area under the receiver operating characteristic). Multimodal fusion yielded pronounced benefits in less critically ill patients. MLP model weights showed high predictive potential for cerebral atrophy in higher-order cortical regions, including the temporal pole, superior frontal gyrus, and the insula. These findings reveal the previously unrecognized potential of clinically derived brain morphometry in enhancing early multimodal predictions of POD. A better understanding of brain vulnerability in POD may translate into improved clinical decision making based on multimodal health care data.

Recent reviews and meta‐analyses reported structural gray matter changes in patients suffering from adult‐onset posttraumatic stress disorder (PTSD) and in subjects with and without PTSD who experienced childhood trauma. However, it remains unclear if such structural changes are also affecting the white matter. The aim of this systematic review is to provide a comprehensive overview of all empirical investigations measuring white matter integrity in populations affected by PTSD and/or childhood trauma. To this end, results from different methodological approaches were included. Twenty‐five articles are reviewed of which 10 pertained to pediatric PTSD and the effects of childhood trauma measured during childhood, seven to the effects of childhood trauma measured during adulthood, and eight to adult‐onset PTSD. Overall, reductions in white matter volume were reported more often than increases in these populations. However, the heterogeneity of the exact locations indicates only a weak overlap across published studies. In addition, a meta‐analysis was carried out on seven whole‐brain diffusion tensor imaging (DTI) studies in adults. Significant clusters of both increases and decreases were identified in various structures, most notably the cingulum and the superior longitudinal fasciculus. Future research directions are discussed.

Scanner-related changes in data quality are common in medical imaging, yet monitoring their impact on diagnostic AI performance remains challenging. In this study, we performed standardized consistency testing of an FDA-cleared and CE-marked AI for triage and notification of intracranial aneurysms across changes in image data quality caused by dose and image reconstruction. Our assessment was based on repeated examinations of a head CT phantom designed for AI evaluation, replicating a patient with three intracranial aneurysms in the anterior, middle and posterior circulation. We show that the AI maintains stable performance within the medium dose range but produces inconsistent results at reduced dose and, unexpectedly, at higher dose when filtered back projection is used. Data quality standards required for AI are stricter than those for neuroradiologists, who report higher aneurysm visibility rates and experience performance degradation only at substantially lower doses, with no decline at higher doses.

Background Women are more susceptible to multiple sclerosis (MS) than men by a ratio of approximately 3:1. However, being male is a risk factor for worse disability progression. Inflammatory genes have been linked to susceptibility, while neurodegeneration underlies disability progression. Thus, there appears to be a differential effect of sex on inflammation versus neurodegeneration. Further, gray matter (GM) atrophy is not uniform across the brain in MS, but instead shows regional variation. Here, we study sex differences in neurodegeneration by comparing regional GM atrophy in a cohort of men and women with MS versus their respective age- and sex-matched healthy controls. Methods Voxel-based morphometry (VBM), deep GM substructure volumetry, and cortical thinning were used to examine regional GM atrophy. Results VBM analysis showed deep GM atrophy in the thalamic area in both men and women with MS, whereas men had additional atrophy in the putamen as well as in localized cortical regions. Volumetry confirmed deep GM loss, while localized cortical thinning confirmed GM loss in the cerebral cortex. Further, MS males exhibited worse performance on the 9-hole peg test (9HPT) than MS females. We observed a strong correlation between thalamic volume and 9HPT performance in MS males, but not in MS females. Conclusion More regional GM atrophy was observed in men with MS than women with MS, consistent with previous observations that male sex is a risk factor for worse disease progression.

To establish a deep learning model for the detection of hypoxic-ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format. 168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images). All optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results ( AUC: 94%, ACC: 79%, AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping. Our proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome.

Drug-induced unconsciousness is an essential component of general anesthesia, commonly attributed to attenuation of higher-order processing of external stimuli and a resulting loss of information integration capabilities of the brain. In this study, we investigated how the hypnotic drug propofol at doses comparable to those in clinical practice influences the processing of somatosensory stimuli in the spinal cord and in primary and higher-order cortices. Using nociceptive reflexes, somatosensory evoked potentials and functional magnet resonance imaging (fMRI), we found that propofol abolishes the processing of innocuous and moderate noxious stimuli at low to medium concentration levels, but that intense noxious stimuli evoked spinal and cerebral responses even during deep propofol anesthesia that caused profound electroencephalogram (EEG) burst suppression. While nociceptive reflexes and somatosensory potentials were affected only in a minor way by further increasing doses of propofol after the loss of consciousness, fMRI showed that increasing propofol concentration abolished processing of intense noxious stimuli in the insula and secondary somatosensory cortex and vastly increased processing in the frontal cortex. As the fMRI functional connectivity showed congruent changes with increasing doses of propofol – namely the temporal brain areas decreasing their connectivity with the bilateral pre-/postcentral gyri and the supplementary motor area, while connectivity of the latter with frontal areas is increased – we conclude that the changes in processing of noxious stimuli during propofol anesthesia might be related to changes in functional connectivity. •Propofol significantly attenuates spinal transmission of moderate noxious stimuli.•Propofol does not alter spinal transmission of intense noxious stimuli.•Regional brain activation by noxious stimulation persists during deep anesthesia.•Propofol dose-dependently changes patterns of stimulus-evoked brain activation.•Activation pattern changes are concordant with changes in functional connectivity.

ObjectivesTo develop an anthropomorphic phantom closely mimicking patient anatomy and to evaluate the phantom for the simulation of computed tomography (CT)-guided procedures.MethodsPatient CT images were printed with aqueous potassium iodide solution (1 g/mL) on paper. The printed paper sheets were stacked in alternation with 1-mm thick polyethylene foam layers, cut to the patient shape and glued together to create an anthropomorphic abdomen phantom. Ten interventional radiologists performed periradicular infiltration on the phantom and rated the phantom procedure regarding different aspects of suitability for simulating CT-guided procedures.ResultsRadiopaque printing in combination with polyethylene foam layers achieved a phantom with detailed patient anatomy that allowed needle placement. CT-guided periradicular infiltration on the phantom was rated highly realistic for simulation of anatomy, needle navigation and overall course of the procedure. Haptics were rated as intermediately realistic. Participants strongly agreed that the phantom was suitable for training and learning purposes.ConclusionsA radiopaque 3D printed, anthropomorphic phantom provides a realistic platform for the simulation of CT-guided procedures. Future work will focus on application for training and procedure optimisation.Key Points• Radiopaque 3D printing combined with polyethylene foam achieves patient phantoms for CT-guided procedures.• Radiopaque 3D printed, anthropomorphic phantoms allow realistic simulation of CT-guided procedures.• Realistic visual guidance is a key aspect in simulation of CT-guided procedures.• Three-dimensional printed phantoms provide a platform for training and optimisation of CT-guided procedures.