bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantitative susceptibility source separation improves the reader agreement in the identification of MS paramagnetic rim lesions
Authors: Demmon Emily , Gauthier Susan , Kovanlikaya Ilhami , Wang Yi , Dimov Alexey , Spincemaille Pascal , Nguyen Thanh
Published: August 2024

Multiple Sclerosis (MS) is an autoimmune disorder characterized by focal inflammatory demyelination. Paramagnetic rim lesions (PRLs) form an important subset of chronic active MS lesions that show a hypocellular core and persistent glial inflammation and continuing myelin damage at the rim on histopathology. PRLs are a critical clinical target for MS therapy. Our goal in this project is to improve overall detection of PRLs through utilization of quantitative paramagnetic source maps.
Inhomogeneous Magnetization Transfer (ihMT) of Peripheral Nerve in Patients with Chronic Inflammatory Demyelinating Polyradiculoneuropathy
Authors: Kurosawa Ryuna , Yokota Hajime , Sada Takayuki , Matsumoto Koji , Yoda Takafumi , Yoneyama Masami , Namiki Takashi , Gilbert Guillaume , Masuda Yoshitada , Uno Takashi
Published: August 2024

Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is an immune-mediated demyelinating disease. The purpose of this study is to evaluate the usefulness of ihMT in the diagnosis of CIDP by measuring myelin levels using ihMT imaging. ihMTR of the sciatic nerve of CIDP patients was significantly lower than that of the normal subjects. Our finding was compatible with previously reported pathological changes. Myelin imaging by ihMT has the potential to be used as a new biomarker in the diagnosis of CIDP.
Altered cortical susceptibility heterogeneity in patients with beta-thalassemia
Authors: Bu Meiru , Deng Xi , Shi Lingling , Cui Wei , Qian Long , Zeng Zisan , Jiang Muliang
Published: August 2024

Beta-thalassemia (β-TM) is an inherited blood disorder that causes the body to make less hemoglobin. In this study, we examined altered cortical susceptibility heterogeneity in patients with β-TM vs. healthy controls using magnetic resonance imaging (MRI). For the altered regions of susceptibility heterogeneities in the β-TM group, an increase was only found in the left hippocampus, while decreased heterogeneities were observed for all other regions located in the frontal and temporal lobes. Thus, we concluded that susceptibility heterogeneities could reveal the β-TM-affecting regions.
Brain structures of a human embryo depicted by MR microscopy with different contrasts
Authors: Kunieda Kazuki , Makihara Kazuyuki , Yamada Shigehito , Terada Yasuhiko
Published: August 2024

Brain structures of human embryos are several tens of micrometers in size, and MR microscopy is essential for elucidating human embryos. However, conventional fast T1-weighted imaging could not delineate some critical structures. In this study, T1, T2, and T2* values were measured to simulate the contrast of each tissue of the human embryo brain, and MR images were acquired at the extremely high resolution of (30 μm)3 using pulse sequences that emphasized the contrast difference in the brain structures. This technique would unveil the three-dimensional microstructure and developmental process of the brain’s central nervous system in its early stages.
Quantitative evaluation of deep gray matter in striatal-cerebellar-brainstem circuits in Parkinson’s disease patients with freezing of gait
Authors: Zhang Youmin , He Naying , Jin Zhijia , Liu Yu , Wang Xinhui , Haacke E. Mark , Yan Fuhua
Published: August 2024

This study evaluated the structural changes of the deep gray matter in the cortico-basal ganglia and cerebellar motor circuit in Parkinson’s disease patients with freezing of gait. Using region-of-interest-based quantitative susceptibility mapping analysis, we found pronounced striatum atrophy combined with caudal substantia nigra abnormal iron accumulation in Parkinson’s disease patients with freezing of gait. This result offered new insight into future research investigating the pathophysiology of the freezing of gait.
Quantitative Myelin Water Imaging Using Short TR Adiabatic Inversion Recovery Prepared FSE (STAIR-FSE) and EPI (STAIR-EPI) Sequences
Authors: Moazamian Dina , Sedaghat Sam , Athertya Jiyo , Malhi Bhavsimran , Shin Soo Hyun , Lo James , Jang Hyungseok , Chang Eric , Du Jiang , Bydder Graeme , Ma Yajun
Published: August 2024

Myelin water imaging (MWI) techniques have shown great promise for the early detection of demyelination and monitoring the effectiveness of neuroprotective therapies in remyelination. The purpose of this study is to develop new clinical transitional MWI techniques, which employ a short TR adiabatic inversion recovery (STAIR) preparation in combination with clinical FSE and EPI acquisitions. Quantified apparent myelin water fractions (aMWFs) show myelin loss in lesions and normal-appearing white matter (NAWM) in patients with multiple sclerosis compared to normal white matter (NWM) in healthy volunteers, demonstrating their potential in clinical practice.
Fully Automated Hippocampus Segmentation Pipeline using Deep Convolutional Neural Networks
Authors: Sackl Maximilian , Tinauer Christian , Enzinger Christian , Schmidt Reinhold , Ropele Stefan
Published: August 2024

Segmentation of the hippocampus on T1-weighted structural MR images is required to quantify the neurodegenerative effects in Alzheimer’s disease studies. In this work, we propose an automated artificial intelligence-based pipeline for hippocampus segmentation combined with manual ground truth (GT) data that originates from high-resolution T2-weighted MR images. Results are evaluated against the manual GT-labels and compared to the segmentation results from FreeSurfer v732. Our deep learning-based segmentation outperforms FreeSurfer in terms of accuracy and speed, while reference experiments using the T2-based GT-labels yield the best results. Thus, using T2-weighted images for ground truth generation can improve automated HC segmentation.
Reliability of brain volume measurements on 3D-FLAIR is similar to 3D-T1 in multiple sclerosis
Authors: van Nederpelt David , Noteboom Samantha , Strijbis Eva , Brouwer Iman , Moraal Bastiaan , Jasperse Bas , Mutsaerts Henk-Jan , Schoonheim Menno , Barkhof Frederik , Vrenken Hugo , Kuijer Joost
Published: August 2024

New methods have enabled segmentation on sequences other than T1 for brain volume measurements in multiple sclerosis (MS), such as those more readily available in clinic as FLAIR and PD. However, reliability studies have not been performed yet in MS, limiting their use. Here, we assessed within-scanner and between-scanner reliability of FLAIR segmentations in 30 people with MS on three different MR scanners. We found similar reliability compared to T1w scans, with high intra-scanner reliability but systematic differences between scanners. This suggests that within-scanner volume measurements of FLAIR are possible, but standardization is needed for between-scanner single patient measurements.
Tract-specific Evaluation of White Matter Hyperintensity Segmentation
Authors: Sinclair Aaron , Callaghan Ross , Zhang Hui
Published: August 2024

We propose a tract-specific white matter hyperintensity (WMH) segmentation evaluation as a new way to assess WMH segmentation techniques. Currently, WMH segmentation is assessed globally or between periventricular and deep white matter (WM) regions, which has no obvious functional relevance. WM tracts have known functional relevance and associations to neurological conditions. We demonstrate that this new approach allows for functionally-relevant assessment of techniques. Two WMH segmentation techniques are compared to highlight the performance differences across a key tract associated with processing speed. We also found significant performance differences across this tract, which would be missed by standard evaluation methods.
Hybrid-space reconstruction with add-on distortion correction for simultaneous multi-slab DWI
Authors: Zhang Jieying , Liu Simin , Wang Yishi , Guo Hua
Published: August 2024

3D simultaneous multi-slab imaging (SMSlab) can achieve high-resolution DWI with high SNR efficiency. Recently, we integrated SMSlab DWI with blipped-CAIPI gradients (blipped-SMSlab) and proposed a hybrid-space reconstruction algorithm, REACH. In this study, REACH is extended for distortion correction, which is called DC-REACH. It can correct the image distortions and the phase interferences introduced by the blipped-CAIPI gradients simultaneously. It also distinctly reduces the g-factor penalty via the joint reconstruction of the blip-up/down data.
Unsupervised Susceptibility Artifact Correction in DTI Using a Deep Learning Forward-Distortion Model
Authors: Alkilani Abdallah Zaid , Çukur Tolga , Saritas Emine Ulku
Published: August 2024

Diffusion weighted imaging (DWI) requires correction of susceptibility artifacts before conducting quantitative analyses. Correction is typically performed by acquiring DWI images in reversed phase-encode directions, which are used to estimate and correct for the effects of susceptibility-induced field. In this work, we propose a Forward-Distortion Network (FD-Net) for correcting susceptibility artifacts at multiple b-values. We evaluate the quality of the corrected DWI images and Diffusion Tensor Imaging (DTI) metrics, using FSL’s TOPUP as a reference classical method. In addition to rapid execution times, FD-Net exhibits high-fidelity performance for both DWI images and DTI metrics.
Renal Cell Carcinoma: Predicting Venous Tumor Thrombus Consistency via IVIM-Diffusion-weighted MR Imaging and Apparent Diffusion Coefficient
Authors: Zhao Jian , Wang Hai-Yi , Wang Mei-Feng , Kang Huan-Huan , Guo Hui-Ping , Zhou Shao-Peng , Ye Hui-Yi
Published: August 2024

Problem: Evaluation of VTT consistency through preoperative images has not been reported yet. Methods: Intravoxel incoherent motion (IVIM)-derived parameters and apparent diffusion coefficient (ADC) were employed to predict VTT consistency of RCC. Results: Dt of the primary tumor and VTT generated the area under the ROC curve (AUC) values of 0.758 (95%CI: 0.671, 0.832) and 0.712 (95%CI: 0.622, 0.792) for differentiating friable and solid VTT. The AUC value of the model combining Dp and Dt of VTT and Dt of the primary tumor reached 0.886 (95%CI: 0.814, 0.937). Conclusions: IVIM parameters can effectively predict the VTT consistency of RCC.
TKE-Net: Deep Learning for Estimation of Super-Resolved Turbulent Kinetic Energy Maps from 4D-Flow MRI Data
Authors: Kazemi Amirkhosro , Stoddard Marcus , Amini Amir
Published: August 2024

Variations in velocity derivative fluctuations have been correlated with changes in pressure gradient. Image denoising and super-resolution techniques are required to accurately quantify velocity fluctuations. We propose a novel network, which we call TKE-Net to estimate Turbulent Kinetic Energy (TKE) which utilizes a ResNet convolutional neural network backbone. The network is trained and tested with low-resolution simulated CFD data, as could be derived from low resolution 4D flow in a phantom model of arterial stenosis. The results indicate good accuracy in estimating TKE. The method was also applied to in-vitro 4D flow MRI data in identical geometry.
Supervised automation of “whole-chest” 4D flow MRI analysis from original DICOM files to quantification of aortic pulse wave velocity
Authors: Jarvis Kelly , Johnson Ethan , Berhane Haben , Richter Adam , Weiss Elizabeth , Markl Michael
Published: August 2024

Analysis of pulse wave velocity by 4D flow MRI usually involves a manual processing pipeline with multiple steps of active use. We set out to automate the entire pipeline from original DICOMs to parameter quantification for evaluation of “whole-chest” 4D flow MRI. A deep learning algorithm trained on aortic acquisitions was used to facilitate segmentation. The supervised automation pipeline allowed for shorter analysis times and less user interaction, enabling the user to focus on refining aortic segmentations generated by deep learning. Results were comparable, but additional work including adjustment of preprocessing settings and retraining of CNN is warranted for optimization.
Accelerated phase-contrast for diastolic function evaluation using k-t PCA methods
Authors: Xiang Jie , Lamy Jerome , Galiana Gigi , Peters Dana
Published: August 2024

Diastolic function evaluation requires estimates of early and late diastolic mitral valve flow velocities (E and A), normally evaluated by echocardiography, using phase contrast (PC). Our goal was to investigate k-t principal component analysis (PCA), constrained by either global and local principal components, for E and A measurements. Importantly, we found that retaining the central k-space used in estimating the principal components improved the final velocity maps. We compared local PCA with global PCA. Retrospectively undersampled images showed strong agreement with standard PC acquisitions. Higher E and A were observed using higher temporal resolution in prospective k-t PCA PC acquisitions.
Mapping stimulus-driven hemodynamic changes in white matter using 7T high-resolution fMRI
Authors: Fan Jiawen , Gonzalez-Castillo Javier , Bandettini Peter , Polimeni Jonathan , Chen Jingyuan
Published: August 2024

In this study, by integrating 7T high-resolution imaging and massive data averaging, we show that white matter fMRI activations can be detected at a single-voxel level. Hemodynamic changes evoked by the flickering checkerboard stimuli were not homogenous within the optic radiation, and the averaged pattern exhibited a delayed time to peak longer than V1, consistent with previous literature. The current datasets also revealed stimulus-locked changes in certain white-matter tracts beyond the visual pathway.
Entrainment between musical stimuli and cortical depth-dependent fMRI signals
Authors: Lee Hsin-Ju , Lee Hankyeol , Uludag Kamil , Lin Fa-Hsuan
Published: August 2024

We use cortical-depth dependent fMRI to study the correlation between neural oscillations and fMRI signals across cortical depths in the auditory cortex during music listening. The correlation between fMRI signals and acoustic stimuli was the strongest at the primary auditory cortex in the intermediate cortical depths during the first listening, matching the hypothesis of feedforward signal supported by the connectivity. The correlation was suppressed in the repeated listening, superficial as well as deep depths, and at the secondary auditory cortex.
Test-retest reliability of PRESS- and sLASER-localized multi-metabolite spectral editing
Authors: Mikkelsen Mark , Noeske Ralph , Shungu Dikoma
Published: August 2024

Multi-metabolite spectral-edited MRS enables the efficient detection of multiple low-concentration metabolites. Two such approaches, HERMES and HERCULES, directly edit two or more metabolites in a single scan. However, the reproducibility of these techniques has yet to be fully established. This study investigated PRESS- and sLASER-localized HERMES and HERCULES test-retest reliability, with the additional aim of demonstrating that sLASER localization is the better of the two sequences for obtaining reproducible measurements. Overall, the test-retest reliability of sLASER was found to be higher than that of PRESS.
Short-TE semi-LASER 1H MRS of the primary motor cortex in ALS and controls at 7 Tesla
Authors: Eftekhari Zeinab , Shaw Thomas B , Jin Jin , O'Brien Kieran , Cowin Gary , Deelchand Dinesh , Henderson Robert , Steyn Frederik , Tu Sicong , Bogner Wolfgang , Barth Markus
Published: August 2024

Magnetic Resonance Spectroscopy (MRS) can offer a unique, non-invasive tool for measuring the neurochemicals in the brain in vivo. This technique may be useful for studying the ratio of metabolites in both health and disease, including in Amyotrophic Lateral Sclerosis (ALS), where differing neuronal populations of the motor cortex are impacted. This study aimed to develop a 7T MRS protocol for ALS patients and measured metabolite ratios in the upper and lower limb regions of the motor cortex at 7T in controls and in ALS. This has the potential to improve progression monitoring and diagnostic certainty in early-stage disease.
Optimizing MRSI semi-LASER for mouse brain tumor studies: evaluation of increased spatial resolution and k-space sampling strategies
Authors: Javed Zoona , Martinez Gary V , Mulero-Acevedo Marta , Candiota Ana , Arús Carles , Egaña Miquel Cabañas , Lope-Piedrafita Silvia
Published: August 2024

MRSI-based nosological images have been previously applied to monitor therapy response in a murine model of GL261 glioblastoma using a commercially available MRSI-PRESS sequence. Due to the heterogeneous nature of glioblastomas, increasing spatial resolution could provide additional insight into changes related to therapy response. The in-house implementation of the MRSI-semi-LASER sequence, using weighted acquisition, has allowed us a 20% slice thickness reduction without losing relevant spectral quality. Moreover, different k-space sampling strategies have been evaluated showing significant SNR increase with elliptical sampling, which may allow further increase in the spatial resolution or reduction in the total experimental time.
Removal of lipid signals and other short T2 components in GRE-MRI and FID-MRSI using quadratic radio frequency phase increments
Authors: Hingerl Lukas , Strasser Bernhard , Hangel Gilbert , Motyka Stanislav , Niess Fabian , Niess Eva , Lipka Alexandra , Goranovic Dario , Lazen Philipp , Gruber Stephan , Trattnig Siegfried , Bogner Wolfgang
Published: August 2024

We present an elegant and easy to implement method for MRI and CSI steady-state sequences to remove or suppress lipids or other components with short transverse relaxation times by neither introducing additional pulses nor hardware and by just altering the excitation pulse phase.
Tailoring a convolutional neural network towards spectral quantification and reconstruction of simulated 7T brain FID-MRSI data
Authors: Goranovic Dario , Motyka Stanislav , Strasser Bernhard , Weiser Paul , Langs Georg , Bogner Wolfgang
Published: August 2024

The abstract investigates the possibilities of using convolutional neural networks for enhanced and robust spectral quantification of simulated 7T FID-MRSI brain spectra. The proposed network architecture predicts wavelet parameters for baseline correction, as well as spectral parameters and metabolite amplitudes for spectral reconstruction. The potential reduction in quantification times could thus mitigate some disadvantages of current MRSI processing techniques.
Compressed Sensing for MRSI with Concentric Ring Trajectories at 7 T
Authors: Strasser Bernhard , Andronesi Ovidiu , Hingerl Lukas , Motyka Stanislav , Trattnig Siegfried , Bogner Wolfgang , Klauser Antoine
Published: August 2024

We show the feasibility of compressed sensing for MRSI using concentric ring trajectories. Four volunteers (three for 2D- and one for 3D-MRSI) were measured in about 9 minutes (2D-MRSI), and 14 minutes (3D-MRSI) using an FID-based MRSI sequence at 7 T. An iterative compressed sensing reconstruction including coil sensitivities and a total general variation spatial regularization was performed with retrospective undersampling factors of 1.5, 2.0 and 2.9. RMSE values were below 22 % and SSIM values above 0.8 for medium accelerations below 2.9 in the 2D case. The metabolic maps and spectra are similar to the gold standard without acceleration.
Effects of denoising on diffusion-weighted MRS data
Authors: Genovese Guglielmo , Marjańska Małgorzata
Published: August 2024

Diffusion-weighted (DW) MRS is a useful tool for detecting microstructural changes linked to neurological diseases. However, DW-MRS suffers from low signal-to-noise ratio, which makes human application extremely difficult. To overcome this issue, a denoising algorithm based on low-rank approximation was recently utilized. Here, effects of the application of low-rank based denoising algorithm to DW-MRS data are described based on synthetic data. Severely artifactually low group SDs for the apparent diffusion coefficients (ADCs) of all metabolites and biased mean ADC values were observed after denoising. These findings suggest that low-rank approximations are detrimental to a reliable quantification of ADCs of metabolites.
Ex-vivo MR spectroscopy in paraformaldehyde-fixed mouse brain
Authors: Abaei Alireza , Deelchand Dinesh K , Antonucci Stefano , Scekic-Zahirovic Jelena , Heuvel Florian olde , Roselli Francesco , Rasche Volker
Published: August 2024

The goal of this study is to demonstrate the feasibility and reliability of metabolite characterization by MR spectroscopy ex vivo in order to maximize the information obtained from a single brain specimen, without the limitations such as scanning time, degraded MRI quality due to intervening tissue and motion artifacts. We demonstrate that ex-vivo spectroscopy obtained after rapid PBS/PFA perfusion is strongly correlated with the MR spectrum previously acquired in the same animal but in vivo but distinct abnormalities due to hypoxia and incomplete fixation do appear; the quality of the spectrum quickly degrades upon longer fixation times.
A noise robust image reconstruction deep neural network with cycle interpolation
Authors: Kim Jeewon , Lee Wonil , Kang Beomgu , So Seohee , Park HyunWook
Published: August 2024

We propose a new Parallel Imaging scheme using a deep neural network which performs well with fewer ACS line in noisy environments. The proposed scheme includes ACS loss which is used in RAKI and cycle interpolation loss that we newly propose in our work. RAKI generalized GRAPPA in noisy environments by applying non-linear k-space interpolation with a deep neural network. However, it requires additional ACS lines to output satisfactory performance. Here, we suggest a new scheme to overcome the reconstruction performance in a noisy environment with fewer ACS lines.
15-Channel Head Cap Array using Twisted-Pair Elements for MRI
Authors: Maravilla Julian , Knizek Colin , Khairallah Nazem , Arias Ana , Lustig Michael
Published: August 2024

A tight fitting and wearable 15-Channel Head Cap Array using Twisted-Pair Elements was designed and characterized for potential use in a multimodal imaging system. The RF Array was characterized in terms of safety and SNR. The elements in the array (Twisted-Pair coil) show >40dB isolation for active detuning with no significant component heating under harsh RF conditions (ΔT<4°C). SNR evaluations revealed a 3x increase in peripheral SNR and retainment of SNR under parallel imaging conditions when compared to a commercial head array. An array of this caliber can be used for fMRI sleep studies and simultaneous TMS/EEG/fMRI.
RF FRONT-END RECEIVER USED IN 1.5T MRI
Authors: Inamdar Anvesh , Gothankar Sanket , Niak Bhaskar , Harsh Rajesh
Published: August 2024

In an MRI, the receiver coil produces moderately low signals that are difficult to detect in a noisy environment. As a result, there was a requirement for a customised RF front end that could tolerate high power leakage from coils, provide adequate isolation, low noise figure, and have a good gain factor. The developed RF front end complies with the requirements and produces images with low noise
Rat angiography from far away: design and performance of a small bath cryostat with NMR capability for transport of hyperpolarized samples.
Authors: Capozzi Andrea , Zhao Yupeng , Karlsson Magnus , Hansen Esben , Bertelsen Lotte , Laustsen Christoffer , Lerche Mathilde , Ardenkjær-Larsen Jan Henrik
Published: August 2024

Hyperpolarization via dissolution Dynamic Nuclear Polarization has the potential to revolutionize diagnostic radiology. Nevertheless, the methodology struggles to enter everyday clinical practice. One of the reasons why broad consensus among clinicians is still missing lies in the technical complexity that characterize hyperpolarization via dDNP. Differently from PET, hyperpolarized MR contrast agent cannot be transported and have to be prepared on-site. We developed a robust methodology to change this paradigm. We herein present our latest updates on transportable hyperpolarization technology.
Can dynamic gadoxetic acid-enhanced MRI combined with water specific T1 mapping predict the early-stage of Nonalcoholic Steatohepatitis in rat?
Authors: Wan Qian , Peng Hao , Liu Feng , Cheng Chuanli , Liu Xiaoyi , Tie Changjun , Liu Xin , Wang Yi , Zou Chao
Published: August 2024

The early detection of the inflammation and fibrosis grade are important to Nonalcoholic steatohepatitis (NASH) patients. Gadoxetic acid with MRI T1 quantitation is one of promising noninvasive method. However, intracellular hepatocyte lipid is a confounding factor for the accurate T1 quantitation in NASH case. Here, we used a water specific T1 (wT1) mapping with dynamic gadoxetic acid enhanced MRI in a rat NASH model induced by MCD diet. The results demonstrated that gadoxetic acid was not helpful to differentiate the inflammation and fibrosis severity in the early stage of NASH in rats.
1H-MRS reveals changes of metabolites in the olfactory bulb of PM2.5-exposed mice
Authors: Li Ren , Zhang Yong , Zhang Xiao-Yong
Published: August 2024

PM2.5 has been shown to be harmful to the central nervous system of mammals. Long term exposure to PM2.5 may cause changes in brain neural metabolites. However, there were few magnetic resonance spectroscopy (MRS) studies in rodents under PM2.5 exposure. In this work, we developed an air enrichment system to concentrate PM2.5. Using 1H-MRS, we successfully observed the brain metabolic profile of olfactory bulb in PM2.5-exposed mice, and found the concentration changes of some key metabolites in the brain, indicating that PM2.5 has a non-negligible impact on brain metabolism.
Automated Segmentation of Knee Cartilage from Ultra-High Resolution 7 Tesla 3D bSSFP MRI Using Transfer Learning
Authors: Guo Luxuan , Kukran Simran , Balaji Krithika , Bangerter Neal
Published: August 2024

7T 3D knee MRI shows great promise for the quantification of cartilage volume and thickness to assess osteoarthritis, but manual segmentation is time consuming. Segmented 7T 3D knee datasets to train machine learning techniques are limited. Here, we trained a network on a larger dataset of segmented 3T 3D knee MRI scans and used transfer learning to create an automatic segmentation network of 7T MRI knee cartilage using a small number of segmented 7T images. The resulting network constructed demonstrated vastly improved automatic segmentation of the knee cartilage at 7T compared to the network trained with limited 7T data only.
The effectiveness of the volume transfer constant (Ktrans) as an aid to regional segmentation of nasopharyngeal tumors
Authors: Huang Junhui , Liu Zhou , Zou Liyan , Chen Yingying , Hu Zhanli , Liang Dong , Liu Xin , Zheng Hairong , Zhang Na
Published: August 2024

Accurate segmentation of nasopharyngeal tumor lesions from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) facilitates subsequent diagnosis and treatment. However, current segmentation methods do not incorporate the pathological properties of the tumor. Therefore, this paper proposes a multimodal DCE-MRI segmentation method that uses the pharmacokinetic features of NPC, Ktrans, as modal information to assist nasopharyngeal tumor segmentation. We validated our method in several classical deep learning segmentation networks, and DCE-MRI with fused Ktrans eigenmodes had higher Dice coefficients than DCE-MRI with a single modality. The best segmentation results were obtained by this method on the ResUNet model (dice=74.39).
An Adaptive Weighted Active Contour Segmentation Model for 3T/5T MRI from the Same Person
Authors: Huang Zhenxing , Geng Mengxiao , Zheng Liyun , Dai Yongming , Zhang Na , Liang Dong , Zheng Hairong , Hu Zhanli
Published: August 2024

Image segmentation is a complex and core technique in the medical image domain. However, low-quality images, such as images with weak edges, may bring considerable challenges for radiologists. In this paper, we propose an adaptive weighted curvature-based active contour model by coupling heat kernel convolution and adaptively weighted high-order total variation to improve diagnosis effectiveness. The numerical experimental results on 3T/5T MRI datasets demonstrate that the proposed model is quite efficient and robust compared with several traditional segmentation methods, which would exert great value in quantitative image evaluation of MRI diagnosis for the same person.
Deep Learning Based 3D Whole Liver and Spleen Segmentation for Quantitatively Reproducible Liver Fat and Iron Deposition Grading
Authors: Gouda Ahmed , Basar Saqib , Chodakiewitz Yosef , Attariwala Rajpaul , London Sean , Hashemi Sam
Published: August 2024

Over the years, Magnetic Resonance Imaging (MRI) has become the optimal noninvasive method to quantify liver steatosis and to detect hepatic iron deposition. The conventional manual sampling technique of liver fat quantification at multiple regions is complex, inefficient and a time-consuming process. In addition, it may produce varying results for the heterogeneous fat deposition, which is prone to radiologist’s subjectivity. In this research, we propose a fully automated artificial intelligence (AI) based method for hepatic steatosis quantification and hepatic iron deposition detection using whole liver and spleen volume segmentation.
Q-space trajectory imaging with positivity constraints: a machine learning approach
Authors: Boito Deneb , Özarslan Evren
Published: August 2024

Q-space trajectory imaging (QTI) is a diffusion MRI framework which access features of the microstructure through the statistical moments of the diffusion tensor distribution. To overcome unreliable estimates obtained with standard fitting methods, a constrained estimation framework named QTI+ was recently proposed. Constrained optimization however typically requires sophisticated fitting routines which introduce a heavy computational burden. In this work we thus explore the possibility of speeding up the QTI parameter estimation, while retaining strict positivity constraints, using artificial intelligence. Results are shown on synthetic datasets as well as for healthy subjects and data from brain tumor patients.
Fast mean kurtosis measurements using navigator-free 3D multi-slab DWI
Authors: Lee Chu-Yu , Mani Merry
Published: August 2024

The fast mean kurtosis measurements using 2D DWI has reduced the scan time substantially but remains subject to low SNR, particularly at b-value = 2500 s/mm2. A larger voxel (≥ 2 mm3) is normally used to increase SNR. This study presents the navigator-free 3D multi-slab DWI for fast mean kurtosis measurements with a resolution of 1.5 mm3. By using a short TR of 2.5 sec, the work demonstrates the promise of using the navigator-free 3D multi-slab DWI for whole-brain fast mean kurtosis measurements with an improved SNR efficiency.
Altered resting state networks associated with REM sleep behavioral disorder in Parkinson’s disease
Authors: Mekbib Destaw , Cai Miao , Dai Weiying , Liu Xiaoli , Zhao Li
Published: August 2024

Resting-state functional MRI has played a fundamental role in the study of Parkinson’s disease (PD) with rapid eye movement sleep behavior disorder (RBD). In this work, we investigated changes in functional connectivity within and between resting-state networks and their relationship to global fluctuations in 13 PD with RBD, 28 PD without RBD, 6 RBD without PD, and 20 healthy controls. Based on an in-house reliable data selection strategy, unique effects on the lateral visual network in RBD patients and on the sensorimotor network in PD patients were found. These may provide novel clues to understanding the pathology and improve diagnosis.
Efficient Myocardial Spectroscopy combining Metabolite-Cycling with Respiratory Bellows at 3T
Authors: Bschorr Fabian , Speidel Tobias , Zoelch Niklaus , Hock Andreas , Abaei Alireza , Rasche Volker
Published: August 2024

Despite its diagnostic values1-4, the application of cardiac spectroscopy (CMRS) in clinical routine is generally limited by technical challenges and long scan times. A protocol for CMRS is proposed using metabolite-cycling, local, ECG-triggered shimming, ECG-triggering and a respiratory bellows. The protocol is evaluated in a volunteer cohort and provides myocardial triglyceride content (MTGC) quantification results that correlate well intrasession- (r=0.98, p<0.001) and intersession-wise (r=0.95, p<0.001). Thus, a good repeatibility and technical stability for the quantification of MTGC could be achieved with an average scan time of 440s at 3T.
Time-resolved deuterium metabolic imaging of the human brain at 7T
Authors: Zhang* Minghao , Karkouri* Jabrane , Atkinson Daniel , Rodgers Christopher
Published: August 2024

Deuterium metabolic imaging (DMI) is a new way to track brain metabolism. We present initial results from 3 volunteers scanned with a new 18-element 2H + 2-element 1H array coil on a Siemens 7T Terra scanner. We utilised our array’s high SNR to track metabolism by whole-brain 3D DMI after drinking 6,6’-[2H2]-glucose (Glc). Signals from HDO, Glc, Glx and Lac were visible over 2hrs at 5min temporal and 6.9mL spatial resolution. We also ran 2.9mL 3D DMI. We achieved HDO SNR of 43 in 13min, which compares favourably published SNR=13 in 10min at 9.4T1 and ~50 in 28min at 7T.2
Comparison the metabolism of [2H2]glucose,[2H7]glucose and [2H5]glucose in rat C6 glioma cells
Authors: Yuan Jiawen , Fang Yi , Wan Qian , Zou Chao , Zhang Xiaoliang , Liu Xin , Zheng Hairong , Li Ye
Published: August 2024

Deuterium MRS(I) has emerged as a novel metabolic imaging method, which can effectively reflect the increased aerobic glycolysis of tumors. Recently, [2,3,4,6,6-2H5] glucose has been shown to be a cost-effective deuterium-labeled substrate for studying glycolysis in tumors. However, the effects of different deuterium-labeled substrates on metabolism require further comparison. In this study, we compared the differences between [6,6-2H2] glucose, [1,2,3,4,5,6,6’-2H7] glucose, and [2,3,4,6,6-2H5] glucose in rat C6 glioma cells.
Low field Breast and Chest Wall Imaging for MR guided Proton Therapy
Authors: Koonjoo Neha , Hornung Torben , Yan Susu , Rosen Matthew , Bortfeld Thomas
Published: August 2024

The use of low field MRI guidance in proton therapy is a new area of research especially during treatment of breast cancer. In this study, we optimized and constructed five different breast/chest RF coils at low field as proof of concept for a future MR guided proton therapy system design. Different coil shapes and sizes were tested. Organs-at-Risk (OAR) and different anatomical regions were optimized for imaging. Using the five coils, phantom images were acquired at 6.5 mT and MR signal across slices were compared to the calculated optimized B1 field homogeneity. Human breast imaging was also carried out.
High permittivity ceramics for improving detection of fMRI activation at 1.5T
Authors: Koloskov Vladislav , Zubkov Mikhail , Solomakha Georgiy , Puchnin Viktor , Levchuk Anatoliy , Efimtcev Alexander , Melchakova Irina , Shchelokova Alena
Published: August 2024

We show that high permittivity materials (HPMs) can improve functional magnetic resonance imaging (fMRI) at 1.5T, increasing the receive sensitivity of a commercial multi-channel head coil. Both numerical simulations and experiment showed ~25% improvement in the signal-to-noise ratio (SNR) of a commercial head coil in the areas of interest when HPM blocks were placed in proximity. This led to an increase in the detected motor cortex fMRI activation volume by an average of 56%, thus resulting in more accurate functional imaging at 1.5T.
Improving signal-to-noise ratio and contrast in Wrist Magnetic Resonance Imaging at 1.5T with Wireless Metasurface Resonantor
Authors: Wang Yakui , Chi Zhonghai , Yi Yi , Wu Maopeng , Wang Lixue , Jiang Deqing , He Li , Zhao Xihai , Meng Yonggang , Zhou Ji , Zhao Qian , Zheng Zhuozhao
Published: August 2024

We designed a wireless metasurface resonator(WMR) for wrist magnetic resonance imaging(MRI) at 1.5T and tested the imaging effect. Phantoms and 14 wrist jionts(7 healthy volunteers) were examed with T1W SE and fat-suppressed PDW FSE sequences at a 1.5T MRI system. Commercial 12-channel wrist array coil(12CH-WR) and WMR(coupling with integrated spine coil) were used to receive MR signal respectively. We found that WMR could improve the image SNR by 1.5~2 times, and significantly improve the image contrast compared with the traditional 12CH-WR.
The Metaslab: A combined Metamaterial and Metasurface for Improved Transmit Performance and Use as a Receive Array.
Authors: Smart Lauren , Maunder Adam , Iyer Ashwin , De Zanche Nicola
Published: August 2024

Abdominal and thoracic imaging at 3T suffers from inhomogeneous transmit fields and hot-spots in specific absorption rate (SAR) that limit image quality and imaging efficiency, respectively. We combine a lightweight metamaterial and metasurface (the ‘metaslab’) to enhance transmit efficiency and homogeneity, as well as to reduce SAR. The metaslab is further able to operate as a receive array with four distinct sensitivity patterns and sensitivity comparable to that of a conventional 4-element loop receive array. The metaslab is much lighter than comparable dielectric pads and achieves all these benefits in a similar package as a conventional coil array.
Remote detection MRI using a flexible non-selective metamaterial at 7 T
Authors: Solis-Najera Sergio , Lazovic Jelena , Vazquez Fabian , Rodriguez Alfredo
Published: August 2024

We propose a method to remotely acquire MR images at 7 T with a preclinical imager using a bio-inspired surface coil, a parallel-plate waveguide and a non-selective metamaterial. Phantom images were acquired with and without a flexible metasurface inserted in cylindrical phantom filled with saline solution and a birdcage coil. Uniformity profiles were computed for all cases showing that the birdcage coil and metasurface profiles have a very good correspondance. An improvement was observed for the images obtained with the metasurface. This approach offers a convenient alternative to obtained high quality images.
Design of a Highly Decoupled Compact Dual-tuned Transceiver RF Coil Arrays for 1H MRI and 31P MRSI at 7T
Authors: PAYNE KOMLAN , Bhosale Aditya , Ying Leslie , Zhang Xiaoliang
Published: August 2024

In this work, we developed a decoupled multichannel double-tuned RF coil array for 1H/31P MR imaging and spectroscopy at the ultrahigh field of 7T. One of the difficulties in designing such high-frequency double-tuned coil arrays is to electromagnetically decouple the two frequency channels simultaneously. To address this issue, we designed a double-crossed magnetic wall (or ICE) decoupling which can independently and simultaneously decouple the 1H channels and 31P channels. With the improved performance, this developed 1H/31P transceiver array is expected to offer improved detection quality and imaging speed in 1H/31P metabolic imaging applications at 7T.
In vivo measurement of rat brain water content at 9.4T using super-resolution reconstruction
Authors: Thomas Dennis , Oros-Peusquens* Ana-Maria , Schöneck Michael , Willuweit Antje , Abbas Zaheer , Zimmermann Markus , Felder Jörg , Celik Avdo , Shah N. Jon
Published: August 2024

Animal models have an indisputable role in the investigation of brain pathology. Investigating water content in vivo could lead to a better understanding of pathogenesis and hence, a robust technique to measure water content using MRI would be very beneficial. Here, we adapt a super-resolution-based technique, previously developed for humans, to the rat brain and report in vivo high-resolution (200μm isotropic) water content maps, obtained using a 9.4T MRI scanner. High resolution, isotropic water content maps of the rat brain are demonstrated. The water content values obtained using the proposed MR technique are compared with ex vivo wet/dry methods.
Metabolic Activity Diffusion Imaging [MADI] of Rat Brain Glioma
Authors: Schlegel Joshua , Baker Eric , Holland Samantha , Stoller Jared , Packwood William , Li Xin , Barajas Ramon , Springer Charles , Pike Martin
Published: August 2024

We compared the novel DWI MRI-based metabolic activity [MA] imaging approach [MADI] to 18FDG-PET, employing an in vivo rat glioma model. The MADI-derived parameter, kio*V product, is proportional to Na+/K+ ATPase [NKA] activity, the primary cellular energy consumer. The kioV decreased within the tumor vs. contralateral while 18FDG uptake increased. This is consistent with the Warburg effect in glioma, which activates glucose uptake but also switches energy production from mitochondrial oxidative phosphorylation to glycolysis, thus reducing overall ATP production and NKA activity. MADI expands DWI MRI utility, providing a novel, noninvasive MA imaging method, with greater resolution than PET.
Improved glutamine detection using diffusion-weighted SPECIAL at 14.1T
Authors: Mosso Jessie , Simicic Dunja , Lanz Bernard , Gruetter Rolf , Cudalbu Cristina
Published: August 2024

Brain glutamine (Gln) is a key biomarker of hepatic encephalopathy (HE). The estimation of its diffusion properties with diffusion-weighted MRS is of high interest in the field but remains challenging due to its low concentration. We propose a new diffusion-weighted MRS sequence, DW-SPECIAL, which enables to reach shorter echo times and is thus beneficial for strongly J-coupled metabolites such as Gln. DW-SPECIAL reduces the uncertainty in Gln diffusion decays and the standard deviation across animals for Gln diffusivity in a homogenous control population and paves the way for an in-depth study of Gln diffusion properties in HE.
Imaging the transmembrane pH gradient in gliomas
Authors: Mishra Sandeep , Mihailović Jelena , Hyder Fahmeed , Coman Daniel
Published: August 2024

Extracellular acidosis in relation to intracellular milieu is a unique feature of the tumor microenvironment. The difference between intracellular pH (pHi) and extracellular pH (pHe) is much larger in tumors than normal tissue. Measuring the transmembrane pH gradient (ΔpH=pHi–pHe) could provide a tool for assessing tumor aggressiveness, monitoring treatment efficacy, guiding localized drug delivery, and understanding tumor responsiveness. This work establishes transmembrane pH gradient imaging in brain tumors. We observed a significantly higher transmembrane pH gradient in RG2 tumors compared to normal brain. Decreasing transmembrane pH gradient may serve as a functional biomarker for positive therapeutic outcome.
Zero filling does not inherently improve precision of real relative to complex-domain fitting in 1H-MR spectra with physiological baselines
Authors: Campos Leonardo , Swanberg Kelley , Juchem Christoph
Published: August 2024

There remains controversy surrounding the use of zero filling during spectral quantification of in vivo proton magnetic resonance spectra (1H-MRS) using linear combination model (LCM) fitting. We examine the potential mixing of real and imaginary information theorized with zero filling, and whether this is demonstrated by a comparable change in accuracy and precision provided by complex fitting. We show that application of zero filling does improve fitting precision when a baseline is not present; with an imperfectly modeled unknown in vivo baseline, however, zero filling does not necessarily reduce error in real relative to complex fits.
Simultaneous in vivo Detection of Cystathionine and 2HG at 7T and Simulation of MEGA and SLOW-editing performance
Authors: Weng Guodong , Radojewski Piotr , Slotboom Johannes
Published: August 2024

2-Hydroxyglutarate (2HG) is a biomarker for IDH-mutant glioma, and previous studies have shown that cystathionine (Cys) can be a potential biomarker for 1q/19q co-deletion of glioma. Previous studies used SVS based MEGA-editing MRS to detect 2HG and co-edited Cys, but editing efficiency of Cys is not optimal due to the narrow bandwidth of the applied MEGA editing-pulses. This work shows that SLOW-editing is able to detect both 2HG and Cys in an optimal way with whole-brain coverage.
Compressed Sensing MPRAGE accelerates automated voxel placement for 1-H MRS of the human brain
Authors: Tambalo Stefano , Hübner Sebastian , Saviola Francesca , Kober Tobias , Jovicich Jorge
Published: August 2024

The automated voxel placement (AVP) framework has been proposed to optimize accuracy and reproducibility in single-voxel brain proton spectroscopy. AVP is based on the affine transformation of brain coordinates from standard to subject-specific space defined on a 3D T1-weighted structural scan. Here we evaluate the robustness of the AVP approach by evaluating the displacement of voxel center coordinates across 3D T1w MPRAGE sequence variants, including compressed sensing (CS) accelerated protocols. We show that AVP gave small but significantly higher voxel displacements for MP2RAGE and CS-MP2RAGE. There were no significant differences between multi-echo MPRAGE (6 min) and CS-MPRAGE (1 min).
In Vivo Diffusion MRI at 7 T: High Spatial-Angular-Temporal Resolution Pursuit
Authors: Tan Frank , Liebig Patrick , Heidemann Robin , Laun Frederik , Knoll Florian
Published: August 2024

The pursuit of high-spatial-angular-temporal resolution for in vivo diffusion MRI at 7T is challenging, but also receives continuous interest. We hereby propose shift-encoded interleaved EPI and a joint reconstruction technique with LLR regularization. Preliminary results achieve up to 8.7-fold acceleration per shot in 2-shot EPI acquisition with 1.4 mm isotropic nominal resolution. Moreover, with the integrated joint reconstruction for noise reduction, high-quality diffusion-weighted images render more spatially-continuous fiber anisotropy maps and clearer fiber crossing in the fiber orientation distribution function.
Accelerated High Resolution Diffusion Imaging using 3D multi-shot EPI and Model-based Reconstruction
Authors: Lee Chu-Yu , Mani Merry
Published: August 2024

Diffusion weighted images are usually acquired using 2D EPI methods. This technique has the limitation of low spatial resolution and low SNR. 3D diffusion weighted images are attractive option for improved SNR, however the motion-induced phase inconsistencies pose a challenge for the reconstruction of such data. We present a navigator-free phase-compensated reconstruction, which can be implemented as a regular parallel imaging framework. This two-step method involves first estimating a low-resolution phase from the data itself and then integrating the phase information in the forward encoding operator. We show good phase compensation from accelerated datasets using the proposed approach.
Incorporating Tissue and Blood Relaxometry For Estimating IVIM Parameters: A Simulation Study
Authors: Mazaheri Yousef
Published: August 2024

The aim of this aim of this study is to use numerical simulation to compare the performance of the standard bi-exponential IVIM model to an extended model which incorporates tissue and blood relaxometry for the estimation of IVIM parameters.
Accelerated 3D free-breathing MRCP using Relaxation-Enhanced MAgnetization-prepared radial stack-of-STARs (REMASTAR) and Compressed SENSE
Authors: Hamano Hiroshi , Yoneyama Masami , Enzaki Masahiro , Azuma Minako , Toyonari Nobuyuki , Namiki Takashi
Published: August 2024

3D TSE RT is commonly used to MRCP imaging. But the image qualities of them are unstable especially in patients with irregular respiratory motion and tachypnea. A T2-prepared pulse is often used to emphasize long T2 component such as CSF, bile, and pancreatic duct. A 3D VANE has been applied in abdominal imaging as a useful free-breathing technique. We attempted to combine bTFE based on 3D VANE with magnetization T2prep pulses (3D REMASTAR) for MRCP instead of, otherwise in addition to 3D TSE RT. We have demonstrated the feasibility of 3D REMASTAR MRCP particularly in subject with unstable respiratory motion.
Z-spectrum Imaging of Bowel Wall Fibrosis in Crohn's Disease
Authors: Jinnah Nabeelah , Mougin Olivier , Gowland Penny , Hoad Caroline , Gascoyne Lauren , Clarke Christopher , Moran Gordon
Published: August 2024

Z-spectrum imaging was performed on bowel wall from Crohn's disease patients, to determine it's potential as a method of determining the fibrotic component of scarred bowel wall. Results show that there is a difference between the MT amplitude and linewidth of healthy compared with strictured bowel wall. Future work will involve optimising a protocol to use as a imaging biomarker of the fibrosis within bowel wall in Crohn's disease.