High-resolution Magnetic Resonance Imaging Research Articles

Hyperenhancement of LA Wall by Three-Dimensional High-Resolution Late Gadolinium-Enhanced MRI and Recurrence of AF After Catheter Ablation

Background/Objectives: This study investigated the relationship between LA (LA) enhancement on three-dimensional (3D) late gadolinium enhancement (LGE) MRI and recurrence after catheter ablation in patients with AF (AF). Methods: A total of one hundred patients with AF (mean age: 68 ± 9 years, 50% with paroxysmal AF) were included in this study. Each patient underwent a high-resolution 3D LGE MRI prior to catheter ablation, allowing for detailed imaging of the LA wall. Quantitative analysis of the enhancement was performed using dedicated software designed for volumetric measurements of LA LGE. Recurrence of AF was monitored over a 90-day period following the ablation procedure. The primary outcome was the correlation between the volume of LGE in the LA and the recurrence of AF. Results: Multivariate analysis confirmed that the volume of LA LGE, defined as the volume exceeding 1SD above the mean signal intensity of the LA, was an independent predictor of recurrence [hazard ratio: 1.16 (95%CI: 1.04–1.29, p = 0.0057)]. The area under the curve for recurrence prediction using 3D LGE MRI was 0.74 (95%CI: 0.63–0.86), with an optimal threshold of 11.72 mL, providing a sensitivity of 55% (95%CI: 32–77%) and a specificity of 86% (95%CI: 77–93%). Conclusions: LA enhancement assessed by high-resolution LGE MRI may serve as a valuable imaging marker for predicting the recurrence in patients with AF following catheter ablation.

Fast interactive simulations of cardiac electrical activity in anatomically accurate heart structures by compressing sparse uniform cartesian grids

Background and Objective:Numerical simulations are valuable tools for studying cardiac arrhythmias. Not only do they complement experimental studies, but there is also an increasing expectation for their use in clinical applications to guide patient-specific procedures. However, numerical studies that solve the reaction–diffusion equations describing cardiac electrical activity remain challenging to set up, are time-consuming, and in many cases, are prohibitively computationally expensive for long studies. The computational cost of cardiac simulations of complex models on anatomically accurate structures necessitates parallel computing. Graphics processing units (GPUs), which have thousands of cores, have been introduced as a viable technology for carrying out fast cardiac simulations, sometimes including real-time interactivity. Our main objective is to increase the performance and accuracy of such GPU implementations while conserving computational resources. Methods:In this work, we present a compression algorithm that can be used to conserve GPU memory and improve efficiency by managing the sparsity that is inherent in using Cartesian grids to represent cardiac structures directly obtained from high-resolution MRI and mCT scans. Furthermore, we present a discretization scheme that includes the cross-diagonal terms in the computational cell to increase numerical accuracy, which is especially important for simulating thin tissue sections without the need for costly mesh refinement. Results:Interactive WebGL simulations of atrial/ventricular structures (on PCs, laptops, tablets, and phones) demonstrate the algorithm’s ability to reduce memory demand by an order of magnitude and achieve calculations up to 20x faster. We further showcase its superiority in slender tissues and validate results against experiments performed in live explanted human hearts. Conclusions:In this work, we present a compression algorithm that accelerates electrical activity simulations on realistic anatomies by an order of magnitude (up to 20x), thereby allowing the use of finer grid resolutions while conserving GPU memory. Additionally, improved accuracy is achieved through cross-diagonal terms, which are essential for thin tissues, often found in heart structures such as pectinate muscles and trabeculae, as well as Purkinje fibers. Our method enables interactive simulations with even interactive domain boundary manipulation (unlike finite element/volume methods). Finally, agreement with experiments and ease of mesh import into WebGL paves the way for virtual cohorts and digital twins, aiding arrhythmia analysis and personalized therapies.

Accelerated High-Resolution Deep Learning Reconstruction Turbo Spin Echo MRI of the Knee at 7 T.

The aim of this study was to compare the image quality of 7 T turbo spin echo (TSE) knee images acquired with varying factors of parallel-imaging acceleration reconstructed with deep learning (DL)-based and conventional algorithms. This was a prospective single-center study. Twenty-three healthy volunteers underwent 7 T knee magnetic resonance imaging. Two-, 3-, and 4-fold accelerated high-resolution fat-signal-suppressing proton density (PD-fs) and T1-weighted coronal 2D TSE acquisitions with an encoded voxel volume of 0.31 × 0.31 × 1.5 mm 3 were acquired. Each set of raw data was reconstructed with a DL-based and a conventional Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) algorithm. Three readers rated image contrast, sharpness, artifacts, noise, and overall quality. Friedman analysis of variance and the Wilcoxon signed rank test were used for comparison of image quality criteria. The mean age of the participants was 32.0 ± 8.1 years (15 male, 8 female). Acquisition times at 4-fold acceleration were 4 minutes 15 seconds (PD-fs, Supplemental Video is available at http://links.lww.com/RLI/A938 ) and 3 minutes 9 seconds (T1, Supplemental Video available at http://links.lww.com/RLI/A939 ). At 4-fold acceleration, image contrast, sharpness, noise, and overall quality of images reconstructed with the DL-based algorithm were significantly better rated than the corresponding GRAPPA reconstructions ( P < 0.001). Four-fold accelerated DL-reconstructed images scored significantly better than 2- to 3-fold GRAPPA-reconstructed images with regards to image contrast, sharpness, noise, and overall quality ( P ≤ 0.031). Image contrast of PD-fs images at 2-fold acceleration ( P = 0.087), image noise of T1-weighted images at 2-fold acceleration ( P = 0.180), and image artifacts for both sequences at 2- and 3-fold acceleration ( P ≥ 0.102) of GRAPPA reconstructions were not rated differently than those of 4-fold accelerated DL-reconstructed images. Furthermore, no significant difference was observed for all image quality measures among 2-fold, 3-fold, and 4-fold accelerated DL reconstructions ( P ≥ 0.082). This study explored the technical potential of DL-based image reconstruction in accelerated 2D TSE acquisitions of the knee at 7 T. DL reconstruction significantly improved a variety of image quality measures of high-resolution TSE images acquired with a 4-fold parallel-imaging acceleration compared with a conventional reconstruction algorithm.

Intracranial aneurysm instability prediction model based on 4D-Flow MRI and HR-MRI

This study aims to develop a reliable predictive model for assessing intracranial aneurysm (IA) instability by utilizing four-dimensional flow magnetic resonance imaging (4D-Flow MRI) and high-resolution MRI (HR-MRI). Initially, we curated a prospective dataset, dubbed the primary cohort, by aggregating patient data that was consecutively enrolled across two centers from November 2018 to November 2021. Unstable aneurysms were defined as those with symptoms, morphological change or ruptured during follow-up periods. We introduce a specialized ensemble learning framework, termed the Hybrid Model, which synergistically combines two heterogeneous base learning algorithms: 4D-Flow logistic regression (4D-Flow-LR) and Multi-crop Attention Branch Network (MicroAB-Net). The ability of the hybrid model to predict aneurysm instability was compared with baseline models: PHASES (population, hypertension, age, size, earlier rupture, and site) LR, ELAPSS (earlier subarachnoid hemorrhage, location, age, population, size, and shape) LR, aneurysm wall enhancement (AWE) LR, and Radiomics using the area under the curve (AUC) with Delong's test. Finally, the Hybrid Model was further validated in the validation cohort (patients enrolled between December 2021 to May 2022). In the primary cohort, 189 patients (144 women [76.2 ​%]; aged 58.90 years ​± ​10.32) with 213 IAs were included. In the validation cohort, 48 patients (35 women [72.9 ​%]; aged 55.0 years ​± ​10.77) with 53 IAs were included. The Hybrid Model achieved the highest performance both in the primary cohort (AUC ​= ​0.854) and the validation cohort (AUC ​= ​0.876). The Hybrid model provided a promising prediction of aneurysm instability.

The value of hippocampal sub-region imaging features for the diagnosis and severity grading of ASD in children

BackgroundHippocampal structural changes in Autism Spectrum Disorder (ASD) are inconsistent. This study investigates hippocampal subregion changes in ASD patients to reveal intrinsic hippocampal anomalies. MethodsA retrospective study from Hainan Children’s Hospital database (2020–2023) included ASD patients and matched controls. We classified ASD participants based on severity, dividing all subjects into four groups: normal, mild, moderate, and severe. High-resolution T1-weighted MRI images were analyzed for hippocampal subregion segmentation and volume calculations using Freesurfer. Texture features were extracted via the Gray-Level Co-occurrence Matrix. The Receiver Operating Characteristic curve was used to evaluate seven random forest predictive models constructed from volume, subregion, and texture features, as well as their combinations following feature selection. ResultsThe study included 114 ASD patients (98 boys, 2–8 years; 16 girls, 2–6 years; 17 mild, 57 moderate, 40 severe) and 111 healthy controls (HCs). No significant differences in volumes were found between ASD patients and HCs (adjusted P-value >0.05). The seven random forest models showed that single volume and texture features performed poorly for ASD classification; however, integrating various feature types improved AUC values. Further selection of texture, subregion, and volume features enhanced AUC performance across normal and varying severity categories, demonstrating the potential value of specific subregions and integrated features in ASD diagnosis. ConclusionRandom forest models revealed that hippocampal volume, texture features, and subregion characteristics are crucial for diagnosing and assessing the severity of ASD. Integrating selected texture and subregion features optimized diagnostic efficacy, while combining texture, subregion, and volume features further improved severity grading effectiveness.

Nonlinear parameter estimation with physics-constrained spectral–spatial priors for highly accelerated chemical exchange saturation transfer MRI

Objective.To develop a nonlinear, model-based parameter estimation method directly from incomplete measurements ink - wspace for robust spectral analysis in highly accelerated chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI).Approach. A CEST-specific, separable nonlinear model, which describes spectral decomposition using multi-pool Lorentzian functions (conventional magnetization transfer (MT), direct saturation of water signals (DS), amide, amine, and nuclear Overhauser effect) derived from the steady-state Bloch McConnel equation, is incorporated into a measurement model in CEST MRI. Furthermore, signal drop in saturation transfer experiments is formulated by an additional, separable nonlinear spectral prior indicating that the symmetric z-spectra synthesized using conventional MT and DS always remain higher or equal to the whole z-spectra with all pools. Given the above considerations, linear and nonlinear parameters in the proposed method are estimated in an alternating fashion directly from highly incomplete measurements ink - wspace by solving a constrained optimization problem with the physics-constrained spectral priors while imposing additional sparsity priors on spatial parameter maps.Main results.Compared with conventional methods, the proposed method yields clearer delineation of tumor-specific CEST maps without apparent artifact and noise.Significance.We successfully demonstrated the feasibility of the proposed method for CEST MRI with highly incomplete measurements thus enabling high-resolution whole brain CEST MRI in clinically reasonable imaging time.

Spectra of intracranial diseases in Chinese military pilots (cadets) unqualified for transfer to pilot modified high performance aircraft.

With very high mortality and disability rates, cerebrovascular diseases and intracranial tumors severely threaten the health and fighting strength of flying personnel, requiring great concern and intensive screening in clinic, early warning in an early and accurate manner and early intervention of diseases possibly resulting in inflight incapacitation are key emphases of aeromedical support in clinic. To probe into the spectra of intracranial diseases, flight factors and medical imaging characteristics of military pilots (cadets) in the physical examination for transfer to pilot modified high performance aircraft, thus rendering theoretical references for clinical aeromedical support of pilots. A total of 554 military pilots (cadets) undergoing physical examination for transfer to pilot modified high performance aircraft from December 2020 to April 2024 in a military medical center were enrolled in this study. Then, a retrospective study was carried out on intracranial disease spectra and head magnetic resonance imaging (MRI) data of 36 pilots (cadets) who were unqualified for transfer to pilot modified high performance aircraft. Besides, a descriptive statistical analysis was conducted on the clinical data, age, fighter type and head MRI data of such pilots (cadets). Abnormal head images were found in 36 out of 554 pilots (cadets) participating in the physical examination for transfer to pilot modified high performance aircraft, including arachnoid cyst in 17 (3.1%) military pilots (cadets), suspected very small aneurysm in 11 (2.0%), cavernous hemangioma in 4 (0.7%), vascular malformation in 2 (0.4%), and pituitary tumor in 3 (0.5%, one of which developed cavernous hemangioma simultaneously). Among the 17 pilots (cadets) with arachnoid cyst, 4 were identified as unqualified for transfer to pilot modified high performance aircraft because the marginal brain tissues were compressed by the cyst > 6 cm in length and diameter. The 11 pilots (cadets) with suspected very small aneurysms identified by 3.0T MRI consisted of 6 diagnosed with conus arteriosus by digital subtraction angiography and qualified for transfer to pilot modified high performance aircraft, and 5 identified as very small intracranial aneurysms with diameter < 3 mm and unqualified for transfer to pilot modified high performance aircraft. No symptoms and signs were observed in the 4 military pilots (cadets) with cavernous hemangioma, and the results of MRI revealed bleeding. The 1 of the 4 had the lesion located in pons and developed Rathke cyst in pituitary gland at the same time, and unqualified for transfer to pilot modified high performance aircraft. The 2 of the 4 were unqualified for flying, and 2 transferred to air combat service division. The 2 pilots (cadets) with vascular malformation were identified as unqualified for transfer to pilot modified high performance aircraft. Among the 3 pilots (cadets) with pituitary tumor, one pilot cadet was identified as unqualified for flying since the tumor compressed the optic chiasma, one had cavernous hemangioma in pons in the meantime and transferred to air combat service division, and one was diagnosed with nonfunctional microadenoma and qualified for transfer to pilot modified high performance aircraft. High-resolution head MRI examination is of great significance for screening and detecting cerebrovascular diseases and intracranial tumors in military flying personnel, and attention should be paid to its clinical application to physical examination for transfer to pilot modified high performance aircraft.

Value of MRI-visible perivascular spaces in predicting levodopa responsiveness of patients with Parkinson’s disease

PurposeInter-individual difference in levodopa responsiveness is a challenge for physicians to administer personalized treatment for patients with Parkinson’s disease (PD). Previous studies demonstrated that magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) might lead to an incomplete response to levodopa. This study aimed to investigate the association between MRI-visible PVS and levodopa responsiveness in patients with PD. MethodsThis cross-sectional study enrolled a total of 327 patients with PD (median age 64.0[57.0–68.0] years, 180 male) who had undergone high-resolution T2-weighted structural MRI at our hospital between 2019 and 2023. An acute levodopa challenge test was performed to evaluate levodopa responsiveness. The patients were divided into two groups: levodopa responsive (MDS-UPDRS-III reduction ≥ 33 %, n = 274) and irresponsive groups (MDS-UPDRS-III reduction < 33 %, n = 53). We employed quantitative and semi-quantitative methods to evaluate MRI-visible PVS in patients with PD, including PVS number, volume fraction, and visual score. Additionally, the imaging features of the levodopa-responsive and irresponsive groups were compared. ResultsThere were no significant differences in PVS number, volume fraction, and visual score between the levodopa-responsive and −irresponsive groups. The indicators from quantitative and semi-quantitative analyses of PVS were not found to be independent predictors of levodopa responsiveness. None of the indicators from the quantitative or semi-quantitative analyses of PVS were significantly associated with poor responsiveness to levodopa treatment. ConclusionsMRI-visible PVS are not independently associated with levodopa responsiveness, and their value in predicting levodopa responsiveness in patients with PD is limited.

Dynamic contrast‑enhanced MRI combined with intravoxel incoherent motion in quantitative evaluation for preoperative risk stratification of resectable rectal adenocarcinoma.

Rectal adenocarcinoma is a common malignant tumor of the digestive tract. However, it is difficult to obtain tumor microstructural information using conventional magnetic resonance imaging (MRI). Dynamic contrast-enhanced (DCE)-MRI and intravoxel incoherent motion (IVIM) have been used in tumor research. The present study aimed to explore the application of DCE-MRI and IVIM in the risk stratification of resectable rectal adenocarcinoma. To achieve this, 75 patients with rectal adenocarcinoma confirmed via postoperative pathological examination who underwent high-resolution MRI, IVIM and DCE-diffusion-weighted imaging before surgery were retrospectively enrolled and divided into very low-risk (19 cases), low-risk (29 cases) and medium-risk (27 cases) groups. The quantitative parameters of DCE-MRI and IVIM were obtained using the GenIQ and Medical Imaging Interaction Toolkit software, respectively. One-way analysis of variance or the Kruskal-Wallis H test were used to analyze the differences in the measured parameters between the different risk groups. Receiver operating characteristic curves were used to analyze the diagnostic efficacy of each parameter. The differences in rate constant (Kep), perfusion fraction (f) and false diffusion coefficient (D*) between the different risk stratification groups were statistically significant (P<0.05). When the very low- and low-risk groups were compared, f + D* had the highest diagnostic efficiency [area under the curve (AUC)=0.719], with a sensitivity and specificity of 100 and 51.70%, respectively. When the low- and medium-risk groups were compared, Kep had the highest diagnostic efficiency (AUC=0.602), with a sensitivity and specificity of 72.41 and 55.56%, respectively. When the very low-risk and medium-risk groups were compared, Kep + f + D* had the highest diagnostic efficiency (AUC=0.887), with a sensitivity and specificity of 100 and 70.4%, respectively. Thus, DCE-MRI and IVIM can aid the prognostic risk stratification of resectable rectal adenocarcinoma, and Kep, f and D* are potential quantitative imaging parameters for the risk stratification of rectal adenocarcinoma.

High-resolution volumetric dynamic magnetic resonance imaging of the wrist using an 8-channel flexible receive coil.

Real-time imaging is useful for the evaluation of wrist instability. However, currently available real-time magnetic resonance imaging (MRI) methods are limited due to their 2D nature or provide insufficient temporal resolution and image quality for quantitative kinematic analysis. This work introduces a novel approach for volumetric dynamic MRI of the wrist joint during active motion and demonstrates the feasibility of tracking carpal bone motion. A flexible 8-element 3T wrist receive coil and 3D-printed support platform for guiding motion were designed for dynamic wrist imaging. 2D real-time images were acquired using a fat-saturated FLASH sequence with radial sampling and reconstructed with the GRASP algorithm. Corresponding volumetric dynamic wrist images were obtained by assembling 2D real-time images into 3D snapshots using autodetected MRI-visible markers for slice alignment. The proposed method was demonstrated for radial-ulnar deviation on five healthy volunteers. The flexible wrist coil provided high SNR while allowing a wide range of wrist movements. 2D real-time wrist images were acquired with a temporal resolution of 48ms/frame with negligible streaking artifacts. Carpal bones and metacarpal bones were properly aligned in the assembled dynamic volumes for all five subjects. The excellent bone-to-tissue contrast enabled accurate segmentation of the individual carpal bones on the assembled dynamic volumes. This work introduces a novel wrist coil and demonstrates that real-time volumetric dynamic examination of the moving wrist is feasible. The achieved image quality and high temporal resolution could enable automatic segmentation of carpal bones and quantitative kinematic assessment for evaluating wrist instability.

Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction

Purpose: BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of more complex reconstruction that is computationally prohibitive. In this work we develop rapid reconstruction pipeline for BUDA-cEPI to pave the way for its deployment in routine clinical and neuroscientific applications. The proposed reconstruction includes the development of ML-based unrolled reconstruction as well as rapid ML-based B0 and eddy current estimations that are needed. The architecture of the unroll network was designed so that it can mimic S-LORAKS regularization well, with the addition of virtual coil channels.Methods: BUDA-cEPI RUN-UP – a model-based framework that incorporates off-resonance and eddy current effects was unrolled through an artificial neural network with only six gradient updates. The unrolled network alternates between data consistency (i.e., forward BUDA-cEPI and its adjoint) and regularization steps where U-Net plays a role as the regularizer. To handle the partial Fourier effect, the virtual coil concept was also introduced into the reconstruction to effectively take advantage of the smooth phase prior and trained to predict the ground-truth images obtained by BUDA-cEPI with S-LORAKS.Results: The introduction of the Virtual Coil concept into the unrolled network was shown to be key to achieving high-quality reconstruction for BUDA-cEPI. With the inclusion of an additional non-diffusion image (b-value = 0 s/mm2), a slight improvement was observed, with the normalized root mean square error further reduced by approximately 5 %. The reconstruction times for S-LORAKS and the proposed unrolled networks were approximately 225 and 3 s per slice, respectively.Conclusion: BUDA-cEPI RUN-UP was shown to reduce the reconstruction time by ∼88× when compared to the state-of-the-art technique, while preserving imaging details as demonstrated through DTI application.

Plasma p-tau181 and GFAP reflect 7T MR-derived changes in Alzheimer's disease: A longitudinal study of structural and functional MRI and MRS.

Associations between longitudinal changes of plasma biomarkers and cerebral magnetic resonance (MR)-derived measurements in Alzheimer's disease (AD) remain unclear. In a study population (n=127) of healthy older adults and patients within the AD continuum, we examined associations between longitudinal plasma amyloid beta 42/40 ratio, tau phosphorylated at threonine 181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and 7T structural and functional MR imaging and spectroscopy using linear mixed models. Increases in both p-tau181 and GFAP showed the strongest associations to 7T MR-derived measurements, particularly with decreasing parietal cortical thickness, decreasing connectivity of the salience network, and increasing neuroinflammation as determined by MR spectroscopy (MRS) myo-inositol. Both plasma p-tau181 and GFAP appear to reflect disease progression, as indicated by 7T MR-derived brain changes which are not limited to areas known to be affected by tau pathology and neuroinflammation measured by MRS myo-inositol, respectively. This study leverages high-resolution 7T magnetic resonance (MR) imaging and MR spectroscopy (MRS) for Alzheimer's disease (AD) plasma biomarker insights. Tau phosphorylated at threonine 181 (p-tau181) and glial fibrillary acidic protein (GFAP) showed the largest changes over time, particularly in the AD group. p-tau181 and GFAP are robust in reflecting 7T MR-based changes in AD. The strongest associations were for frontal/parietal MR changes and MRS neuroinflammation.

Aberrant hippocampal intrinsic morphological connectivity patterns in Neuromyelitis optica spectrum disorder with cognitive impairment: Insights from an individual-based morphological brain network

BackgroundAlthough several clinical studies have demonstrated that hippocampus volume loss in neuromyelitis optica spectrum disorder (NMOSD) may be a significant predictor of cognition, no consensus has been reached. To investigate the alterations of the intrinsic ,hippocampal morphological networks in cognitively impaired NMOSD patients and their correlations with cognitive performance. Methods38 NMOSD patients and 39 healthy controls (HC) were enrolled. NMOSD patients were categorized into two groups based on neuropsychological assessment, including the cognitively impaired (CI) group (n = 21) and the cognitively preserved (CP) group (n = 17). Brain high-resolution 3D-T1WI MR images were evaluated, and individual-based intrinsic hippocampus morphological networks were constructed. The between-group differences in global and nodal network topology profiles were estimated, and correlations between the nodal network metrics and cognitive scores were further analyzed. ResultsCompared to the HC and CP groups, the CI group shows significant differences in nodal network metrics of the left hippocampal tail and left hippocampal cornu ammonis (CA) 1-body. Nodal network metrics of the left hippocampal tail were significantly correlated with neurocognitive scores across the entire NMOSD group. ConclusionsNMOSD patients with cognitive impairment exhibit abnormal intrinsic hippocampal morphological networks. Nodal network property measurements can help identify those with cognitive impairment.

Morphology of the human inner ear and vestibulocochlear nerve assessed using 7T MRI.

To optimize high-resolution 7T MRI of the cochlea and measure normal cochlea and the cochlear nerve morphometry in vivo. Eight volunteers with normal hearing were scanned at 7T using an optimized protocol. Two neuroradiologists independently scored image quality. The basal turn lumen diameter (BTLD), height, width, length and volume of the cochlear, long (LD) and short (SD) diameter the calculated cross-sectional area (CSA) of the cochlear nerve were measured. Intra and inter-observer reliability was assessed using intraclass correlation (ICC). 3D T2W DRIVE combined with dielectric pads, allowed acquisition of high-resolution images showing detailed structures, such as the crista ampullaris in the semicircular canals. The overall grading scores from neuroradiologists were excellent. In the left ear, averaging over all subjects gave BTLD of 2.6 ± 0.05mm, height of 4.9 ± 0.1mm, width of 4.4 ± 0.2mm, length of 36.5 ± 0.4mm, volume of 0.16 ± 0.02ml, LD of 1.31 ± 0.1mm, SD of 1.06 ± 0.1mm, and CSA of 1.1 ± 0.1 mm2. The right ear gave BTLD of 2.6 ± 0.04mm, height of 4.9 ± 0.1mm, width of 4.4 ± 0.3mm, length of 35.5 ± 0.4mm, volume of 0.16 ± 0.02ml, LD of 1.29 ± 0.1mm, SD of 1.07 ± 0.1mm, and CSA of 1.10 ± 0.2 mm2. No statistically significant difference was found between the sides of the head (p-value > 0.05). The intra-observer reliability was high (0.77-0.94), while the inter-observer reliability varied from moderate to high (0.55-0.81). 7T MRI can provide excellent visualization of the internal structure of the cochlear and of the vestibulocochlear nerve in vivo.

MRI-guided neurolysis for the treatment of chronic refractory knee pain: a case report.

Chronic refractory pain poses a significant challenge in knee joint pathologies, especially after exhaustion of conservative, arthroscopic, and endoprosthetic therapy options. This case report illustrates an innovative approach using MRI-assisted chemical neurolysis of a genicular nerve to manage persistent knee pain after arthroscopy. A 62-year-old male patient with chronic refractory knee pain, primarily localized at the inferomedial part of the knee, underwent high-resolution MRI to visualize the genicular nerves. This allowed for targeted ethanol-based neurolysis of the inferomedial genicular nerve. Following the procedure, the patient experienced substantial pain reduction for the follow-up duration of 4months. The successful use of MRI-assisted chemical neurolysis offers a promising alternative treatment for patients with refractory knee pain, providing long-lasting pain relief without major side effects. This technique has the potential to improve the quality of life for patients suffering from chronic knee pain While these initial results are encouraging, it is important to note that further research, including both short-term and long-term studies, as well as randomized controlled trials, is warranted to establish the efficacy and safety of this treatment method in broader populations before it can be considered for routine incorporation into pain management practices.

NIMG-33. HIGH-RESOLUTION SODIUM MRI OF HUMAN GLIOMAS AT 3T USING PHYSICS-BASED GENERATIVE AI

Abstract BACKGROUND Sodium neuroimaging is a promising technique for diagnosing and monitoring brain tumors, providing insights into microenvironment and metabolism. However, at 3T, it is limited by low signal-to-noise ratio and resolution, resulting in long acquisition times and low-quality images. To address these limitations, we developed a physics-informed generative adversarial network (GAN) approach for high-resolution sodium neuroimaging of brain tumors at 3T. METHODS 5,078 anatomical sequences from 1,330 brain tumor patients undergoing routine proton MRI were used to create a synthetic dataset with physics-based simulated artifacts, including B0 magnetic susceptibility artifacts, chemical shift artifacts, Nyquist aliasing artifacts, Gibbs artifacts, and low-resolution images, with Rician noise added during training to augment the dataset. By using multiple proton MRI contrasts, we hypothesized that the GAN model would learn to correct artifacts while preserving the inherent contrast information. We employed a transfer learning approach with a modified Pix2PixGAN architecture and an Attention-R2UNet generator. Twenty glioma patients consented to participate in this IRB-approved prospective study. Sodium and proton MRIs were acquired in the same sessions using a 3T Siemens scanner using a dual-tuned head coil, with a 3D spoiled gradient-echo sequence optimized for short TE. Sodium-proton exchanger (NHE1) expression was tested with immunohistochemistry from image-guided surgical biopsies. RESULTS High-resolution synthetic-sodium MR images were generated using the GAN model. The proposed method successfully reconstructed high-resolution synthetic-sodium MR images with improved SNR compared to traditional sodium images. Synthetic and native measurements were strongly correlated (R2=0.8539, P&amp;lt;0.0001). A significant correlation was seen between synthetic-sodium MR measurements and relative NHE1 tissue expression (ρ=0.5817, P=0.0036). CONCLUSION Results suggest that high-resolution synthetic-sodium MRI retains much of the inherent information from native sodium MR while accurately representing NHE1 expression. This approach could make high-resolution sodium neuroimaging at 3T feasible in the clinical environment, potentially improving diagnosis, monitoring, and treatment of brain tumors.

Correlation of enlarged perivascular spaces in basal ganglion and cancer-associated stroke: a case–control study in China

IntroductionThe incidence of cancer-associated ischaemic stroke (IS) is increasingly prevalent. This study aimed to assess the levels of enlarged perivascular spaces in basal ganglion (BG-EPVS) in cancer-associated patients who had...

Risk assessment for rupture of brain arteriovenous malformations using high-resolution black-blood magnetic resonance imaging: a single-center case series.

Chronic inflammation's role in the pathogenesis, development, and rupture of vascular malformations is undebated. Advanced magnetic resonance imaging techniques with vessel wall studies, specifically Black Blood (bbMRI), may offer insights into vascular wall instability and predict rupture. This case series aims to assess bbMRI as a predictive diagnostic tool for brain arteriovenous malformations (bAVMs) rupture, suggesting early treatment. A prospective study included demographic, clinical, and neuroimaging data from a consecutive series of patients with ruptured or unruptured bAVMs, regardless of age or gender, between October 2018 and March 2024. All patients underwent MRI brain resonance with Black Blood study. Those with impaired renal function were excluded. Statistical analyses tested sample homogeneity. Univariate and multivariate logistical regressions assessed bbMRI as a rupture predictor for bAVMs, with a p-value set at < 0.05. Ninety patients were retrieved: 64 with unruptured and 26 with ruptured bAVMs. The mean age was 31.9 years, and 55 were female. Admission symptoms were headache, neurological deficits, and seizure in 49, 21, and 19 cases, respectively. bbMRI showed wall enhancement in 56 cases, with 19 in the ruptured and 37 unruptured groups. Univariate and multivariate analyses revealed a significant correlation between bbMRI wall enhancement and bAVM rupture (p:0.033; p:0.047). bbMRI may be a useful and feasible diagnostic implement to determine vessel inflammation and the bAVMs prone to rupture. Additional studies are needed to confirm the positive bbMRI as a predictive factor for bAVMs rupture.

Performance of high-resolution diffusion-weighted magnetic resonance imaging for detecting clinically occult early breast cancers: a multi-reader study.

To compare mammography, breast ultrasound (US), high-resolution diffusion-weighted magnetic resonance imaging (DW-MRI), dynamic contrast-enhanced breast MRI (DCE-MRI), and their combinations for detecting clinically occult early breast cancers (EBCs), including ductal carcinoma in situ (DCIS). Three hundred and three consecutive women with screening imaging-detected early breast cancers (60 pure DCIS, 36 DCIS with microinvasion, and 207 invasive carcinoma less than 20mm) who underwent breast MRI at 3T including DW-MRI (b-values of 0, 800 and 1200s/mm2; in-plane resolution, 1.1 × 1.1 mm2 or 1.3 × 1.3 mm2; section thickness, 3mm) were retrospectively reviewed. Three radiologists independently reviewed each examination. Statistical analysis included Chi-square test, McNemar test for comparison of cancer detection rates, and Fleiss' Kappa for interreader agreement. Mixed-effect logistic regression analysis was employed to evaluate factors associated with cancer detection on DW-MRI. The overall cancer detection rates were 54.8% on mammography, 71.0% on breast US, 81.5% on DW-MRI, and 87.1% on DCE-MRI. On McNemar test, DW-MRI detected more cancers than mammography (adjusted p < 0.001), and its combination with mammography showed a similar cancer detection rate to DCE-MRI combined with mammography (adjusted p = 0.808). On multivariable analysis, histologic type, lesion size, ADC and CNR on DW-MRI were independent factors for cancer detection on DW-MRI. The interreader agreement for cancer detection was moderate to substantial (Fleiss' kappa: 0.52-0.65) across each modality. High-resolution DW-MRI plus mammography showed comparable cancer detection rate to DCE-MRI plus mammography for detecting clinically occult EBCs including DCIS.

British Skull Base Society Consensus on Vestibular Schwannoma Surveillance

Abstract Objective Surveillance plays a crucial role in managing patients with vestibular schwannomas (VSs). Consensus is lacking on the optimal duration, frequency, and modality of imaging. Standardizing this approach would ensure safe and effective care, reduce patient distress, and promote consistency in management decisions among clinicians. Methods In July 2022, a multi-disciplinary Delphi consensus was conducted at the British Skull Base Society Meeting. Expert United Kingdom-based skull-base surgeons and neuroradiologists were presented semi-systematic literature reviews summarizing current evidence on VS management. Anonymized opinions were collated and discussed to reach a majority vote, which was deemed the final consensus opinion. Results Recommendations for VS managed by surveillance are: (1) surveillance frequency should decrease over time; (2) surveillance may be discontinued when the remaining lifetime risk of VS growth is &lt;0.5% (∼8.5 years); (3) factors such as age, VS size, VS location, and cystic components should be considered. Surveillance after surgery or radiotherapy has limited evidence but recommendations are: (4) surveillance should be adjusted based on residual tumor size or nodular enhancement. Imaging modality and sequences are recommended to be (5) high-resolution magnetic resonance imaging with T1, T2, FIESTA/CISS multiplanar sequences, contrast is not required in untreated cases, and linear reporting of measurements is pragmatically sufficient. Conclusion This consensus and literature review provides an evidence and expert opinion–based guide to help clinicians with the surveillance of patients with VS. Further research should focus on better understanding the dynamic nature of growth risks and the growth characteristics of postintervention VS to enable personalized growth risk stratification.