Three-dimensional T1-weighted Images Research Articles

Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning.

To assess glymphatic function and white matter integrity in children with autism spectrum disorder (ASD) using multi-parametric MRI, combined with machine learning to evaluate ASD detection performance. This retrospective study collected data from 110 children with ASD (80 exploratory, 43 validation) and 68 typically developing children (50 exploratory, 18 validation) from two centers. The automated diffusion tensor imaging along the perivascular space (aDTI-ALPS), fractional anisotropy (FA), cerebrospinal fluid volume, and perivascular space (PVS) volume indices were extracted from DTI, three-dimensional T1-weighted, and T2-weighted images. Intergroup comparisons were conducted using t-tests, Mann-Whitney U-test, and tract-based spatial statistics. Correlation analysis assessed the relationship between glymphatic function, white matter integrity, and clinical scales. Machine learning models based on MRI indices were developed using the AutoGluon framework. The PVS volume (p < 0.001) was larger, and aDTI-ALPS index (p < 0.001) was lower in children with ASD compared to typically developing children. FA values were reduced in the ASD group and positively correlated with aDTI-ALPS index. The aDTI-ALPS index correlated with ASD severity (r = -0.27, p = 0.02) and developmental delays (r = 0.63, p < 0.001). Mediation analysis indicated the aDTI-ALPS index partially mediated the relationship between white matter integrity and developmental delay. The MRI-based model achieved an area under the curve of 0.84 for ASD diagnosis. Analyzing glymphatic function and white matter integrity enhances understanding of ASD's neurobiological underpinnings. The multi-parametric MRI, combined with machine learning, can facilitate the early detection of ASD. Question How can multi-parametric MRI based on the glymphatic system improve early diagnosis of autism spectrum disorder (ASD) beyond the limitations of current behavioral assessments? Findings Glymphatic dysfunction and disruptions in white matter integrity were associated with clinical symptoms of ASD. Multi-parametric MRI with machine learning can improve early ASD detection. Clinical relevance Multi-parametric MRI, focusing on glymphatic function and white matter integrity, enhances the diagnostic accuracy of ASD by serving as an objective complement to clinical scales.

High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique.

The purpose of this study was to investigate whether the high-precision magnetic resonance (MR) sequence using modified Fast 3D mode wheel and Precise IQ Engine (PIQE), that was collected in a wheel shape with sequential data filling in the k-space in the phase encode-slice encode plane, is feasible for breath-hold (BH) three-dimensional (3D) T1-weighted imaging of the hepatobiliary phase (HBP) of gadoxetic acid-enhanced MRI in comparison to the compressed sensing (CS) sequence using Advanced Intelligent Clear-IQ Engine (AiCE). This retrospective study included 54 patients with focal hepatic lesions who underwent dynamic contrast-enhanced MRI. Both standard HBP images using CS with AiCE and high-precision HBP images using modified Fast 3D mode wheel and PIQE were obtained. Image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were evaluated using the Wilcoxon signed-rank test. p values of < 0.05 were considered to be statistically significant. Scores for image noise, conspicuity of liver contours and intrahepatic structures, and overall image quality in high-precision HBP imaging using modified Fast 3D mode wheel and PIQE were significantly higher than those in HBP imaging using CS and AiCE (all p < 0.001). There was no significant difference in the presence of artifact and motion-related blurring. There were no significant differences between the sequences in SNR (p = 0.341) or CNR (p = 0.077). The detection rate of focal hepatic lesions was 71.4-85.3% in CS with AiCE, and 82.2-95.8% in modified Fast 3D mode wheel and PIQE. A high-precision MR sequence using a modified Fast 3D mode wheel and PIQE is applicable for the HBP of BH 3D T1-weighted imaging.

Comparison of image quality and lesion conspicuity between conventional and deep learning reconstruction in gadoxetic acid-enhanced liver MRI

ObjectiveTo compare the image quality and lesion conspicuity of conventional vs deep learning (DL)-based reconstructed three-dimensional T1-weighted images in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI).MethodsThis prospective study (NCT05182099) enrolled participants scheduled for gadoxetic acid-enhanced liver MRI due to suspected focal liver lesions (FLLs) who provided signed informed consent. A liver MRI was conducted using a 3-T scanner. T1-weighted images were reconstructed using both conventional and DL-based (AIRTM Recon DL 3D) reconstruction algorithms. Three radiologists independently reviewed the image quality and lesion conspicuity on a 5-point scale.ResultsFifty participants (male = 36, mean age 62 ± 11 years) were included for image analysis. The DL-based reconstruction showed significantly higher image quality than conventional images in all phases (3.71–4.40 vs 3.37–3.99, p < 0.001 for all), as well as significantly less noise and ringing artifacts than conventional images (p < 0.05 for all), while also showing significantly altered image texture (p < 0.001 for all). Lesion conspicuity was significantly higher in DL-reconstructed images than in conventional images in the arterial phase (2.15 [95% confidence interval: 1.78, 2.52] vs 2.03 [1.65, 2.40], p = 0.036), but no significant difference was observed in the portal venous phase and hepatobiliary phase (p > 0.05 for all). There was no significant difference in the figure-of-merit (0.728 in DL vs 0.709 in conventional image, p = 0.474).ConclusionDL reconstruction provided higher-quality three-dimensional T1-weighted imaging than conventional reconstruction in gadoxetic acid-enhanced liver MRI.Critical relevance statementDL reconstruction of 3D T1-weighted images improves image quality and arterial phase lesion conspicuity in gadoxetic acid-enhanced liver MRI compared to conventional reconstruction.Key PointsDL reconstruction is feasible for 3D T1-weighted images across different spatial resolutions and phases.DL reconstruction showed superior image quality with reduced noise and ringing artifacts.Hepatic anatomic structures were more conspicuous on DL-reconstructed images.Graphical

Trajectories and sex differences of brain structure, oxygenation and perfusion functions in normal aging

Background: Brain structure, oxygenation and perfusion are important factors in aging. Coupling between regional cerebral oxygen consumption and perfusion also reflects functions of neurovascular unit (NVU). Their trajectories and sex differences during normal aging important for clinical interpretation are still not well defined. In this study, we aim to investigate the relationship between brain structure, functions and age, and exam the sex disparities.Method: A total of 137 healthy subjects between 20∼69 years old were enrolled with conventional MRI, structural three-dimensional T1-weighted imaging (3D-T1WI), 3D multi-echo gradient echo sequence (3D-mGRE), and 3D pseudo-continuous arterial spin labeling (3D-pCASL). Oxygen extraction fraction (OEF) and cerebral blood flow (CBF) were respectively reconstructed from 3D-mGRE and 3D-pCASL images. Cerebral metabolic rate of oxygen (CMRO2) were calculated as follows: CMRO2=CBF·OEF·[H]a, [H]a=7.377 μmol/mL. Brains were segmented into global gray matter (GM), global white matter (WM), and 148 cortical subregions. OEF, CBF, CMRO2, and volumes of GM/WM relative to intracranial volumes (rel_GM/rel_WM) were compared between males and females. Generalized additive models were used to evaluate the aging trajectories of brain structure and functions. The coupling between OEF and CBF was analyzed by correlation analysis. P or PFDR < 0.05 was considered statistically significant.Results: Females had larger rel_GM, higher CMRO2 and CBF of GM/WM than males (P < 0.05). With control of sex, CBF of GM significantly declined between 20 and 32 years, CMRO2 of GM declined subsequently from 33 to 41 years and rel_GM decreased significantly at all ages (R2 = 0.27, P < 0.001; R2 = 0.17, P < 0.001; R2 = 0.52, P < 0.001). In subregion analysis, CBF declined dispersedly while CMRO2 declined widely across most subregions of the cortex during aging. Robust negative coupling between OEF and CBF was found in most of the subregions (r range = -0.12∼-0.48, PFDR < 0.05).Conclusion: The sex disparities, age trajectories of brain structure and functions as well as the coupling of NVU in healthy individuals provide insights into normal aging which are potential targets for study of pathological conditions.

Assessing changes in brain structure in new-onset children with acute lymphoblastic leukemia.

Brain structure injury was presented in acute lymphoblastic leukemia (ALL) after treatment; however, its alterations in new-onset stage are still unclear. We aim to explore white matter (WM) and grey matter (GM) alterations using surface-based morphometry (SBM) and tract-based spatial statistics (TBSS) in new-onset pediatric ALL. Thirty-five ALL and 33 typically developing (TD) children were prospectively recruited and underwent three-dimensional T1-weighted and diffusion tensor (DTI) imaging. DTI metrics, cortical GM features, anddeep GM nuclei volume were compared between groups differences. In ALL, the only increased FA in the body of corpus callosum (PFWE-corrected = 0.023) and left superior corona radiata (PFWE-corrected = 0.045) were presented. Relative to TDs, pediatric ALL presented a significant decrease in cortical surface area (CSA), thickness (CT), and volume in orbital gyri, supramarginal gyrus, middle temporal gyrus, and superior temporal gyrus (all CWP = 0.01). Additionally, increased CT and CSA were found in lingual gyrus and left sulcus intermedius primus, respectively (all CWP = 0.01). Smaller volumes in pediatric ALL were observed in bilateral thalamus, caudate, hippocampus, and right putamen (PFDR-corrected < 0.05). Widespread brain structural abnormalities were found in new-onset pediatric ALL, which suggest disease itself can cause brain structural injury. This study revealed the altered white matter integrity and gray matter morphology characteristics in childhood acute lymphoblastic leukemia on new-onset stage. It is suggested that there may be structural impairment before chemotherapy. MRI is a sensitive way for early detection on brain structural damage in childhood acute lymphoblastic leukemia.

Choroid plexus volumes in patients with transient global amnesia: A retrospective study.

Increased choroid plexus (ChP) volume is well known to be associated with glymphatic system dysfunction. This study aimed to investigate glymphatic system function in patients with transient global amnesia (TGA) compared to healthy controls through ChP volumes measurements. We retrospectively enrolled patients with TGA from our hospital, as well as healthy controls. This was retrospectively observational study followed STROBE guideline. All participants underwent brain magnetic resonance imaging, including three-dimensional T1-weighted imaging. We analyzed and compared ChP volumes between patients with TGA and healthy controls and investigated the relationship between ChP volumes and clinical characteristics in patients with TGA. We enrolled 44 patients with TGA and 47 healthy controls. Among the 44 patients with TGA, 38 experienced a single TGA event, while 6 had recurrent TGA events. ChP volumes did not significantly differ between patients with TGA and healthy controls (2.140% vs 2.089%, P = .568). However, ChP volumes were higher in patients with a single TGA event compared to those with recurrent events (2.204% vs 1.740%, P < .013). We observed a significant positive correlation between ChP volumes and age in patients with TGA (R = 0.282, P = .007). ChP volumes were not associated with the duration of amnesia in patients with TGA (R = 0.187, P = .274). We find no differences in the glymphatic system function, as demonstrated by ChP volume for the first time. This study also found a significant correlation between ChP volume and age in patients with TGA, indicating that aging influences glymphatic system function.

The interplay of genetic and environmental factors on the morphology of the limbic cortex and hippocampal subfields: Insights from an MRI twin study

IntroductionThe limbic system and the hippocampus are complex brain structures with key roles in memory, emotions, sexual stimulation and learning, with subregion abnormalities associated with a range of disorders and psychopathologies. Our study aimed to explore the heritability of specific subfield structures within the limbic system and hippocampus first in a Caucasian twin sample with volBrain pipeline. Materials and Methods59 healthy adult Caucasian twin pairs from the Hungarian Twin Registry without any history of previous neurodegenerative or cerebrovascular diseases underwent brain MRI on a 3.0 T scanner (43 monozygotic, MZ and 16 dizygotic, DZ pairs, with a median age of 50±+27 years). The volBrain automated volumetry pipeline was used to calculate the subcortical and general brain volumes from three-dimensional T1-weighted images. Based on age- and sex-adjusted MZ and DZ intra-pair correlations, the univariate ACE model was applied to calculate additive genetic, shared and unshared environmental influences. ResultsAdjusting for age and sex, moderate to strong heritability (A: 59.7 to 73.1 %) was found for most limbic cortex volumes, except for the volumes of entorhinal area and posterior cingulate gyrus where common environmental contribution was detected (C: 56.6 % and 65.0 %, respectively). A substantial heritability (A: 67.0 to 79.4 %) was estimated for the overall hippocampus and most subfield volumes, except for the CA2-CA3 region which was determinated by common environmental factors (C: 45.7 %). Unique environmental variance was a minor to moderate contributor across all variables (E: 20.6 to 54.3 %). ConclusionsAlbeit most limbic cortex, overall hippocampus and most subfield volumes are under substantial genetic influence in healthy adult twins, the volumes of entorhinal area, posterior cingulate gyrus and the CA2-CA3 region of the hippocampus are influenced common environmental factors. The findings underline the importance of unique environmental factors which may play a role in the prevention of disorders related to limbic cortex and hippocampus.

Association between subcortical nuclei volume changes and cognition in preschool-aged children with tetralogy of Fallot after corrective surgery: a cross-sectional study

BackgroundNeurocognitive disorders frequently occur in patients with cyanotic congenital heart disease (CCHD) because of the hemodynamic abnormalities induced by preoperative cardiac structural changes. We aimed to evaluate subcortical nuclei volume changes and cognition in postoperative tetralogy of Fallot (TOF) children, and analyze their relationship with preoperative cardiac structural changes.MethodsThis case-control study involved thirty-six children with repaired TOF and twenty-nine healthy controls (HCs). We utilized three-dimensional (3D) T1-weighted high-resolution structural images alongside the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV) to evaluate the cognitive differences between the TOF and HC group.ResultsWe observed notable differences in subcortical nuclei volume between the TOF and HC group, specifically in the left amygdala nucleus (LAM, TOF: 1292.60 ± 155.57; HC: 1436.27 ± 140.62, p < 0.001), left thalamus proper nucleus (LTHA, TOF: 6771.54 ± 666.03; HC: 7435.36 ± 532.84, p < 0.001), and right thalamus proper nucleus (RTHA, TOF: 6514.61 ± 715.23; HC: 7162.94 ± 554.60, p < 0.001). Furthermore, a diminished integrity of LAM ( β:-19.828, 95% CI: -36.462, -3.193), which showed an inverse relationship with the size of the preoperative ventricular septal defect (VSD), correlated with lower working memory indices in children with TOF.ConclusionsOur findings indicate that subcortical nuclei structural injuries possibly potentially stemming from cardiac anatomical abnormalities, are associated with impaired working memory in preschool-aged children with TOF. The LAM in particular may serve as a potential biomarker for neurocognitive deficits in TOF, offering predictive value for future neurodevelopmental outcomes, and shedding light on the neurophysiological mechanisms of these cognitive impairments.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Radiomics based on diffusion tensor imaging and 3D T1-weighted MRI for essential tremor diagnosis.

Due to the absence of biomarkers, the misdiagnosis of essential tremor (ET) with other tremor diseases and enhanced physiologic tremor is very common in practice. Combined radiomics based on diffusion tensor imaging (DTI) and three-dimensional T1-weighted imaging (3D-T1) with machine learning (ML) give a most promising way to identify essential tremor (ET) at the individual level and further reveal the potential imaging biomarkers. Radiomics features were extracted from 3D-T1 and DTI in 103 ET patients and 103 age-and sex-matched healthy controls (HCs). After data dimensionality reduction and feature selection, five classifiers, including the support vector machine (SVM), random forest (RF), logistic regression (LR), extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP), were adopted to discriminate ET from HCs. The mean values of the area under the curve (mAUC) and accuracy were used to assess the model's performance. Furthermore, a correlation analysis was conducted between the most discriminative features and clinical tremor characteristics. All classifiers achieved good classification performance (with mAUC at 0.987, 0.984, 0.984, 0.988 and 0.981 in the test set, respectively). The most powerful discriminative features mainly located in the cerebella-thalamo-cortical (CTC) and visual pathway. Furthermore, correlation analysis revealed that some radiomics features were significantly related to the clinical tremor characteristics in ET patients. These results demonstrated that combining radiomics with ML algorithms could not only achieve high classification accuracy for identifying ET but also help us to reveal the potential brain microstructure pathogenesis in ET patients.

Collet-Sicard syndrome due to cervical artery dissection disclosed by high-resolution magnetic resonance imaging.

Cervical artery dissection (CAD) represents a leading cause of unilateral lower cranial nerve IX-XII palsy, known as Collet-Sicard syndrome (CSS). High-resolution magnetic resonance imaging (HR-MRI) is widely used in the evaluation of patients with CAD, providing information regarding vessel wall abnormalities and intraluminal thrombus. We present a patient with palsy of multiple lower cranial nerves in the context of CSS, attributed to unilateral spontaneous internal carotid artery dissection. We describe a 68-year-old man with unremarkable previous history, who presented with subacute, gradually worsening dysphagia and hoarse voice. Clinical examination revealed right-sided palsy of cranial nerves IX-XII. Three-dimensional fat-saturated black-blood T1-weighted high-resolution vessel wall imaging disclosed spontaneous dissection with intramural hematoma along the distal right internal carotid artery. Neck MRI showed inward displacement of right aryepiglottic fold, right pyriform sinus dilatation, and right true vocal cord in middle position, indicative of right vagus nerve palsy, atrophy of right trapezius and sternocleidomastoid muscles, due to right spinal accessory nerve palsy, and unilateral tongue atrophy with fatty infiltration, characteristic for right hypoglossal nerve palsy. This case highlights the utility of high-resolution vessel wall imaging and especially fat-saturated T1-weighted black-blood SPACE (sampling perfection with application-optimized contrast using different flip-angle evolutions) sequences in the accurate diagnosis of CAD, revealing the characteristic mural hematoma and intimal flap. HR-MRI is also valuable in the recognition of indirect signs of lower cranial nerve compression.

Association between patients with migraine and sarcopenia: A retrospective study.

Recently, interest in sarcopenia has been increasing in patients with various neurological diseases. Thus, we investigated the presence of sarcopenia in patients with episodic migraine (EM) based on temporal muscle thickness (TMT). This was a retrospectively observational study following STROBE guidelines. We enrolled patients with EM and healthy controls. Both groups underwent brain magnetic resonance imaging, including three-dimensional T1-weighted imaging. We calculated the TMT using T1-weighted imaging, which is a marker for sarcopenia. We compared TMT between patients with EM and healthy controls, and analyzed it according to presence of migraine aura. We retrospectively enrolled 82 patients with EM and 53 healthy controls. TMT was not different between patients with EM and healthy controls (10.804 ± 2.045 mm in patients with EM vs 10.721 ± 1.547 mm in healthy controls, P = .801). Furthermore, TMT was not different according to presence of migraine aura in patients with EM (10.994 ± 2.016 mm in patients with migraine aura vs 10.716 ± 2.071 mm in those without, P = .569). There were no correlations between TMT and clinical characteristics in patients with EM, including age, age of onset, duration of migraine, headache intensity, and headache frequency. This study found no statistical difference in TMT between patients with EM and healthy controls or between patients with EM with and without aura. These findings suggest that there is no evidence of sarcopenia in patients with EM.

Choroid plexus enlargement in patients with obstructive sleep apnea

ObjectivesThe function of choroid plexus is to produce cerebrospinal fluid, which is critical for the glymphatic system function. In this study, we aimed to analyze the differences in choroid plexus volume between patients with obstructive sleep apnea (OSA) and healthy controls, with the goal of discovering the glymphatic system dysfunction in patients with OSA. MethodsWe prospectively enrolled 40 patients with OSA confirmed by polysomnography and 38 age- and sex-matched healthy controls. All participants underwent three-dimensional T1-weighted brain imaging, which was suitable for volumetric analysis. We compared choroid plexus volumes between patients with OSA and healthy controls, and analyzed the association between choroid plexus volume and polysomnographic findings in patients with OSA. ResultsChoroid plexus volumes were significantly larger in patients with OSA than in healthy controls (2.311 % vs. 2.096 %, p = 0.005). However, no significant association was detected between choroid plexus volume and polysomnographic findings. ConclusionThis study demonstrated enlargement of the choroid plexus in patients with OSA compared with healthy controls. This finding could be related with glymphatic system dysfunction in patients with OSA.

Temporal Muscle Thickness and Sarcopenia Components in Healthy Adults, Validated through Allgeun Diagnostic Tool.

Sarcopenia, characterized by progressive muscle loss and functional decline, poses significant risks, including falls, impaired daily activities, and increased mortality. We developed Allgeun, a novel device that measures handgrip strength, muscle mass, and physical performance. This study aimed to investigate whether temporal muscle thickness (TMT) could be used as a sarcopenia marker and to evaluate the usability of Allgeun. This prospective study enrolled 28 participants without medical or neurological disorders. They underwent three-dimensional T1-weighted imaging using a 3 Tesla magnetic resonance imaging scanner. TMT was measured based on T1-weighted images by a board-certified neuroradiologist. Allgeun was used to measure the following three key components of sarcopenia: muscle strength (handgrip strength), muscle mass (calf and thigh circumference), and physical performance (five times the chair stand test). Correlation analysis was conducted between TMT and the results of the handgrip strength, calf and thigh circumferences, and chair stand tests. There were moderate positive correlations between TMT and calf circumference (r = 0.413, p = 0.029), thigh circumference (r = 0.486, p = 0.008), and handgrip strength (r = 0.444, p = 0.018). However, no significant correlation was observed between TMT and physical performance (r = -0.000, p = 0.998). Our findings underscore TMT's potential as an indicator of sarcopenia, particularly regarding muscle mass and strength. Additionally, we demonstrated that the new device, Allgeun, is useful for screening and diagnosing the severity of sarcopenia.

Altered cerebellar volumes and intrinsic cerebellar networks in patients with transient global amnesia.

This study aimed to investigate the differences in cerebellar volumes and intrinsic cerebellar networks between patients with transient global amnesia (TGA) and healthy controls. We retrospectively enrolled patients with TGA and age- and sex-matched healthy controls. We used three-dimensional T1-weighted imaging at the time of TGA diagnosis to obtain cerebellar volumes, and the intrinsic cerebellar network was calculated by applying graph theory based on cerebellar volumes. The nodes were defined as individual cerebellar volumes, and edges as partial correlations, controlling for the effects of age and sex. The cerebellar volumes and intrinsic cerebellar networks were compared between the two groups. We enrolled 44 patients with TGA and 47 healthy controls. The volume of the left cerebellar white matter in patients with TGA was significantly lower than that in healthy controls (1.0328 vs. 1.0753%, p = 0.0094). In addition, there were significant differences in intrinsic cerebellar networks between the two groups. The small-worldness index in patients with TGA was higher than that in the healthy controls (0.951 vs. 0.880, p = 0.038). In the correlation analysis, the volumes of the right cerebellar cortex and lobules VIIIB were significantly correlated with age in patients with TGA (r = -0.323, p = 0.033; r = -0.313, p = 0.038, respectively). Patients with TGA exhibit alterations in cerebellar volumes and intrinsic cerebellar networks compared with healthy controls. These findings may contribute to a better understanding of the pathophysiology of the TGA.

Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders

Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer’s disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aβ) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aβ-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aβ-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.

Brain Age Prediction Using Multi-Hop Graph Attention Combined with Convolutional Neural Network.

Convolutional neural networks (CNNs) have been used widely to predict biological brain age based on brain magnetic resonance (MR) images. However, CNNs focus mainly on spatially local features and their aggregates and barely on the connective information between distant regions. To overcome this issue, we propose a novel multi-hop graph attention (MGA) module that exploits both the local and global connections of image features when combined with CNNs. After insertion between convolutional layers, MGA first converts the convolution-derived feature map into graph-structured data by using patch embedding and embedding-distance-based scoring. Multi-hop connections between the graph nodes are modeled by using the Markov chain process. After performing multi-hop graph attention, MGA re-converts the graph into an updated feature map and transfers it to the next convolutional layer. We combined the MGA module with sSE (spatial squeeze and excitation)-ResNet18 for our final prediction model (MGA-sSE-ResNet18) and performed various hyperparameter evaluations to identify the optimal parameter combinations. With 2788 three-dimensional T1-weighted MR images of healthy subjects, we verified the effectiveness of MGA-sSE-ResNet18 with comparisons to four established, general-purpose CNNs and two representative brain age prediction models. The proposed model yielded an optimal performance with a mean absolute error of 2.822 years and Pearson's correlation coefficient (PCC) of 0.968, demonstrating the potential of the MGA module to improve the accuracy of brain age prediction.

Thin-slice reverse encoding distortion correction DWI facilitates visualization of non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma and surrounding normal structures

BackgroundTo evaluate the clinical usefulness of thin-slice echo-planar imaging (EPI)-based diffusion-weighted imaging (DWI) with an on-console distortion correction technique, termed reverse encoding distortion correction DWI (RDC-DWI), in patients with non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma.MethodsPatients with non-functioning PitNET/pituitary adenoma who underwent 3-T RDC-DWI between December 2021 and September 2022 were retrospectively enrolled. Image quality was compared among RDC-DWI, DWI with correction for distortion induced by B0 inhomogeneity alone (B0-corrected-DWI), and original EPI-based DWI with anterior-posterior phase-encoding direction (AP-DWI). Susceptibility artifact, anatomical visualization of cranial nerves, overall tumor visualization, and visualization of cavernous sinus invasion were assessed qualitatively. Quantitative assessment of geometric distortion was performed by evaluation of anterior and posterior displacement between each DWI and the corresponding three-dimensional T2-weighted imaging. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient values were measured.ResultsSixty-four patients (age 70.8 ± 9.9 years [mean ± standard deviation]; 33 females) with non-functioning PitNET/pituitary adenoma were evaluated. In terms of susceptibility artifacts in the frontal and temporal lobes, visualization of left trigeminal nerve, overall tumor visualization, and anterior displacement, RDC-DWI performed the best and B0-corrected-DWI performed better than AP-DWI. The right oculomotor and right trigeminal nerves were better visualized by RDC-DWI than by B0-corrected-DWI and AP-DWI. Visualization of cavernous sinus invasion and posterior displacement were better by RDC-DWI and B0-corrected-DWI than by AP-DWI. SNR and CNR were the highest for RDC-DWI.ConclusionsRDC-DWI achieved excellent image quality regarding susceptibility artifact, geometric distortion, and tumor visualization in patients with non-functioning PitNET/pituitary adenoma.Relevance statementRDC-DWI facilitates excellent visualization of the pituitary region and surrounding normal structures, and its on-console distortion correction technique is convenient. RDC-DWI can clearly depict cavernous sinus invasion of PitNET/pituitary adenoma even without contrast medium.Key points• RDC-DWI is an EPI-based DWI technique with a novel on-console distortion correction technique.• RDC-DWI corrects distortion due to B0 field inhomogeneity and eddy current.• We evaluated the usefulness of thin-slice RDC-DWI in non-functioning PitNET/pituitary adenoma.• RDC-DWI exhibited excellent visualization in the pituitary region and surrounding structures.• In addition, the on-console distortion correction of RDC-DWI is clinically convenient.Graphical

Dynamic Contrast-enhanced MRI Quantification of Altered Vascular Permeability in Autoimmune Encephalitis.

Background Blood-brain barrier (BBB) permeability change is a possible pathologic mechanism of autoimmune encephalitis. Purpose To evaluate the change in BBB permeability in patients with autoimmune encephalitis as compared with healthy controls by using dynamic contrast-enhanced (DCE) MRI and to explore its predictive value for treatment response in patients. Materials and Methods This single-center retrospective study included consecutive patients with probable or possible autoimmune encephalitis and healthy controls who underwent DCE MRI between April 2020 and May 2021. Automatic volumetric segmentation was performed on three-dimensional T1-weighted images, and volume transfer constant (Ktrans) values were calculated at encephalitis-associated brain regions. Ktrans values were compared between the patients and controls, with adjustment for age and sex with use of a nonparametric approach. The Wilcoxon rank sum test was performed to compare Ktrans values of the good (improvement in modified Rankin Scale [mRS] score of at least two points or achievement of an mRS score of ≤2) and poor (improvement in mRS score of less than two points and achievement of an mRS score >2) treatment response groups among the patients. Results Thirty-eight patients with autoimmune encephalitis (median age, 38 years [IQR, 29-59 years]; 20 [53%] female) and 17 controls (median age, 71 years [IQR, 63-77 years]; 12 [71%] female) were included. All brain regions showed higher Ktrans values in patients as compared with controls (P < .001). The median difference in Ktrans between the patients and controls was largest in the right parahippocampal gyrus (25.1 × 10-4 min-1 [95% CI: 17.6, 43.4]). Among patients, the poor treatment response group had higher baseline Ktrans values in both cerebellar cortices (P = .03), the left cerebellar cortex (P = .02), right cerebellar cortex (P = .045), left cerebral cortex (P = .045), and left postcentral gyrus (P = .03) than the good treatment response group. Conclusion DCE MRI demonstrated that BBB permeability was increased in all brain regions in patients with autoimmune encephalitis as compared with controls, and baseline Ktrans values were higher in patients with poor treatment response in the cerebellar cortex, left cerebral cortex, and left postcentral gyrus as compared with the good response group. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Filippi and Rocca in this issue.

Sarcopenia and anti-seizure medication response in juvenile myoclonic epilepsy.

This study aimed to investigate the presence of sarcopenia in patients with juvenile myoclonic epilepsy (JME) and the association between sarcopenia and response to anti-seizure medication (ASM) in patients with JME. We enrolled 42 patients with JME and 42 healthy controls who underwent brain magnetic resonance imaging with three-dimensional T1-weighted imaging. We measured the temporal muscle thickness (TMT), a radiographic marker for sarcopenia, using T1-weighted imaging. We compared the TMT between patients with JME and healthy controls and analyzed it according to the ASM response in patients with JME. We also performed a receiver operating characteristic (ROC) curve analysis to evaluate how well the TMT differentiated the groups. The TMT in patients with JME did not differ from that in healthy controls (9.630 vs. 9.956mm, p=.306); however, ASM poor responders had a lower TMT than ASM good responders (9.109 vs. 10.104mm, p=.023). ROC curve analysis revealed that the TMT exhibited a poor performance in differentiating patients with JME from healthy controls, with an area under the ROC curve of .570 (p=.270), but good performance in differentiating between ASM good and poor responders, with an area under the ROC curve of .700 (p=.015). The TMT did not differ between patients with JME and healthy controls; however, it was reduced in ASM poor responders compared to ASM good responders, suggesting a link between ASM response and sarcopenia in patients with JME. TMT can be used to investigate sarcopenia in various neurological disorders.