bluuebunny/crossref_metadata_2025 huggingface dataset:
Resolve fiber crossings using orientation distribution function (ODF) of decomposed sub-voxel paramagnetic and diamagnetic susceptibility
Authors: Chen Jingjia , Gkotsoulias Dimitrios , Jaffe Jennifer , Crockford Catherine , Wittig Roman , Möller Harald E. , Liu Chunlei
Published: August 2023

DECOMPOSE-QSM was applied on high angular-resolution multi-echo gradient-echo data of a chimpanzee brain to evaluate its ability in resolving orientation mixture of substructure fiber bundles. The orientation distribution function (ODF) of the separated paramagnetic and diamagnetic susceptibility provides smooth transitions of multiple fiber orientations. Additionally, the paramagnetic maps from DECOMPOSE show a potential to resolve fiber crossings in deep gray matter regions.
Microvascular Morphology Alteration Using Relaxation Rate Change with Gd-based MRI Contrast Agent in the Patient with Alzheimer’s Disease
Authors: Ryu Chang-Woo , Guo Xiao-Yi , Kwon HyeokJung , Park Soonchan , Rhee Hak Young , Cho A-Rang , Jahng Geon-Ho
Published: August 2023

To assess the cerebral microvascular alteration in the demented patients relative to a non-demented population using in vivo microvascular index maps by using Gd-based contrast agent at a 3T MRI system, we included 11 non-demented participants and 11 AD patients. Compared with the non-demented group, BVf and MvWI were significantly increased in the demented group. Both mVD and VSI were only significantly decreased in the demented group at the white matter hyperintensity (WMHI) area. BVf and MvWI were significantly positively correlated with age and VSI was significantly positively correlated with MMSE.
Identification of Subcortical White Matter Biomarkers in Multiple Sclerosis Patients according to AVLT performance using Random Forest
Authors: Montalba Cristian , Franco Pamela , Labbé Tomás , Andia Marcelo , Guevara Miguel , Mangin Jean-François , Cruz Juan Pablo , Ciampi Ethel , Cárcamo Claudia , Guevara Pamela , Uribe Sergio
Published: August 2023

Radiological biomarkers of cognitive impairment in Multiple Sclerosis (MS) is still scarce. This study aimed to identify subcortical white matter biomarkers of cognitive impairment related to verbal episodic memory in MS patients and healthy controls, by using a random forest approach.
Comparing the SPIJN algorithm for myelin water fraction mapping with conventional NNLS evaluation in healthy and multiple sclerosis brains
Authors: Berg Ronja , Amthor Thomas , Vavasour Irene , Doneva Mariya , Preibisch Christine
Published: August 2023

Myelin water fraction (MWF) mapping provides information on myelin concentration, which can be affected by neurological diseases. Most commonly, a non-negative least squares (NNLS) algorithm is used to obtain MWF. A faster alternative is the Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm. Here, we compared both methods in several brain regions from healthy participants and normal-appearing and lesion tissue from MS patients (EDSS 0-1.5). We found that NNLS-based lesion-average MWF was rather comparable to white matter while SPIJN-based MWF was lower. Thus, SPIJN could be more sensitive to demyelination in lesions but comparisons to gold standard techniques are clearly needed.
Identification of Subtle Alterations for Demarcation of Disease Transition in Murine Aortic Valve Stenosis by Multiparametric MRI
Authors: Quast Christine , Jacoby Christoph , Kelm Malte , Flögel Ulrich
Published: August 2023

Aortic valve stenosis (AS) is one of the most frequent valve diseases in the elderly with relevant prognostic impact. Becausesufficient experimental models were lacking, we recently refined a murine model of gradable experimental AS closely mimicking disease progression in humans. Here, we aimed at developing a comprehensive MRI approach for simultaneous assessment of changes in valvular, myocardial as well as aortic function in mice. We demonstrate that in this murine model high resolution MRI is capable to reliably display transvalvular aortic flow profiles with concomitant quantification of structural and functional changes inaortic valve, left ventricle, and ascending aorta.
Clinical impact of automatic failure mode evaluation using self-calibrated phase contrast correction in phase contrast cardiac MRI
Authors: Solana Ana Beatriz , Minderhoud Savine , Wielopolski Piotr , Hernandez-Tamames Juan , Budde Ricardo , Helbing Willem , Janich Martin , Hirsch Alexander
Published: August 2023

Phase contrast (PC) cardiac MRI is clinically used to quantify flow. The quantification accuracy is diminished by background phase errors. Stationary tissue-based background phase correction algorithms are commercially available, but their accuracy is still under evaluation. Here, we investigate if a self-calibrated phase contrast (SCPC) algorithm which includes automatic failure mode classification, can improve accuracy in a large single-vendor multi-scanner study including 346 PC scans. Our results show that SCPC improves flow quantification accuracy and can identify most PC scans which are unreliable regardless of stationary tissue correction or not.
Estimating perfusion and permeability using neural network with training data generated from vessel construction and transport simulation
Authors: Zhang Qihao , Romano Dominick , Nguyen Thanh , Spincemaille Pascal , Wang Yi
Published: August 2023

We propose to estimate perfusion parameters (perfusion $$$F$$$, permeability $$$K^{trans}$$$, vascular space volume $$$V_p$$$ and extravascular extracellular volume $$$V_e$$$) from contrast enhanced MRI using Quantitative Transport and Exchange network (QTEnet), a deep learning method that does not require an arterial input function. Training data were generated by solving the transport equation in simulated high-resolution vasculature and computing the corresponding 4D tracer propagation. A 3D U-net was trained to reconstruct perfusion parameters from the tracer propagation images. Tracer propagation simulated in experimentally obtained tumor vasculature was used for valiation, and the method was then applied to glioma DCE MRI data.
Placental MRI: The effect of maternal breath hold on T2* quantified by multi-echo gradient echo EPI
Authors: Stout Jeffrey , Turk Esra Abaci , Gagoski Borjan , Manhard Mary , Barth William , Adalsteinsson Elfar , Grant P.
Published: August 2023

T2* imaging has been the focus of research into the non-invasive MRI assessment of placental function, yet the fundamental physiology that determines placental T2* is under active investigation. We explored the effect of maternal breath holding on placental T2* quantified with multi-echo GRE EPI. We quantified T2* in free-breathing and breath hold periods by identifying voxels that responded to the breath hold stimulus through fitting with a GLM, and found a consistent positive increase in T2* during breath hold. This increase may be evidence that fetal SO2 rises during mild maternal hypercapnia, as has been observed previously in instrumented animals.
Multi-modal MRI reveals changes in placental function following preterm premature rupture of membranes
Authors: Melbourne Andrew , Zampieri Carla Avena , Flouri Dimitra , Hajnal Joseph , David Anna , Rutherford Mary , Hutter Jana , Story Lisa
Published: August 2023

Preterm premature rupture of membranes (PPROM) complicates up to 40% of deliveries less than 37 completed weeks gestation. Absence of clinical symptoms means that fetal infection can be missed and later complications are significantly higher. There is thus a real need for non-invasive antenatal assessment of the early signs of placental inflammation. This study combines an efficient multimodal Diffusion-Relaxation acquisition with dedicated analysis to study the placental phenotype associated with PPROM. Initial results indicate that multi-modal MRI measurement of placental function is linked to eventual gestational age at delivery.
Role of puborectalis thickness measurement in the assessment of pelvic floor dysfunction and its correlation with HMO classification.
Authors: Jawahar Anugayathri , Subbaiah Perla , Sheth Vipul
Published: August 2023

Pelvic floor dysfunction is a common problem affecting women over 50 years of life causing significant morbidity. Traditionally, H-line and M-line measurements have been used to assess pelvic organ prolapse. However, puborectalis muscle which plays a crucial role in pelvic floor intactness can be measured to reflect the weakening of the pelvic floor. We evaluated and found puborecatalis measurement can be used as a supplement to H-line and M-line measurements in assessing pelvic organ prolapse.
MCR-ALS application for prostate cancer localization
Authors: Stamatelatou Angeliki , Bertinetto Carlo , Jansen Jeroen , Postma Geert , Heerschap Arend , Scheenen Tom
Published: August 2023

Three-dimensional MRSI data of the prostate was analyzed with a Multivariate Curve Resolution-Alternating (MCR) approach for rapid automated localization and classification of cancer and healthy tissue. This data-driven method was used to extract common spectroscopic components without a need of prior knowledge, and compared to fitting a linear combination of prior knowledge models (LCModel). The MCR method identified components with known prostate metabolites and residual lipid and water signals Altogether, our approach can be considered as a step towards the development of an automated tool for classification of prostate MRSI spectra, avoiding subjective human intervention.
Usage of Dissolution DNP Magnetic Resonance Spectroscopy Depicts Efficacy of Chemotherapeutic and Radiotherapeutic Anticancer Interferences
Authors: Elhelaly Abdelazim Elsayed , Hyodo Fuminori , Koyasu Norikazu , Tomita Hiroyuki , Murata Masaharu , Noda Yoshifumi , Kato Hiroki , Matsuo Masayuki
Published: August 2023

DNP highly improves the sensitivity of magnetic resonance spectroscopy allowing for greater insight into in vivo metabolic activity. We used our dissolution 13C DNP system to monitor the Warburg effect in MIA PaCa human pancreatic carcinoma model mice subjected to radiotherapy or chemotherapy. In vivo production of 13C lactate in tumors showed a significant reduction after radiation therapy. Mice subjected to anticancer drugs also showed a significant reduction in the relative production of 13C lactate at an early stage of the treatment course before any anatomical changes in the structure or size of the tumors were detectable by MRI images.
IVIM MRI and PET in Locally Advanced Cervical Carcinoma undergoing Concurrent Chemoradiation Therapy
Authors: Capaldi Dante , Wang Jen-Yeu , Sheth Vipul , Kidd Elizabeth , Hristov Dimitre
Published: August 2023

IVIM MRI provides measurements of diffusion and perfusion, which has been shown to be predictive of prognosis, responsive to chemoradiotherapy, and correlated with DCE MRI in cervical cancer. We hypothesized that IVIM in cervical cancer patients would be sensitive to CCRT, and hence our objective was to first investigate changes in IVIM in cervical cancer patients undergoing adjuvant CCRT and evaluate the relationship between these metrics with changes in tumor volume and PET. Preliminary results show that IVIM measurements are related to both PET and changes in overall tumor volume and may reflect changes in the tumor microenvironment during treatment.
Parallel Greedy Learning for Accelerating Cardiac Cine MRI
Authors: Ozturkler Batu , Sahiner Arda , Ergen Tolga , Desai Arjun , Sandino Christopher , Vasanawala Shreyas , Pauly John , Mardani Morteza , Pilanci Mert
Published: August 2023

Deep unrolled models have recently shown state-of-the-art performance for reconstruction of dynamic MR images. However, training these networks via backpropagation is limited by intensive memory and compute requirements to calculate gradients and store intermediate activations per layer. Motivated by these challenges, we propose an alternative training method by greedily relaxing the training objective. Our approach splits the end-to-end network into decoupled network modules, and optimizes each module separately, avoiding the need to compute end-to-end gradients. We demonstrate that our method outperforms end-to-end backpropagation by 3.3 dB in PSNR and 0.025 in SSIM with the same memory footprint.
Deep Learning Reconstruction for FRONSAC
Authors: Zhang Zhehong , Galiana Gigi
Published: August 2023

This work is the first to apply deep learning to the reconstruction of images encoded with nonlinear gradients. We apply a model-based deep learning network (MoDL) to simulated FRONSAC images and compare these to a PSF-based matrix inversion as well as cg-SENSE. The MoDL based reconstruction did not significantly change the behavior of signal noise. However, results demonstrate that the model-based deep learning network can outperform traditional reconstruction methods at high undersampling factors. Simulations also suggests that the regularizing network has potential to correct for miscalibration in the nonlinear gradient trajectory.
A deep learning based direct mapping method for EPI image reconstruction
Authors: Oh Changheun , Oh Sung Suk , Chung Jun-Young , Han Yeji
Published: August 2023

Echo planar imaging (EPI) is one of the fastest MRI pulse sequences that can acquire whole k-space data during a single excitation. In EPI, partial acquisition can be used for reducing the TR and the effective TE can be further reduced as the portion of the acquired k-space is reduced. However, the quality of the image decreases drastically as the acquired k-space portion is reduced. In this study, we proposed a solution for image reconstruction from partially acquired EPI based on a deep-learning based direct mapping method, where the images are directly reconstructed from input k-space data.
Explaining variation in DTI parameters with meningioma microscopy: A comparison between a neural network and an image-feature-based approach
Authors: Brabec Jan , Friedjungová Magda , Vašata Daniel , Englund Elisabet , Knutsson Linda , Szczepankiewicz Filip , Sundgren Pia C , Nilsson Markus
Published: August 2023

Diffusion MRI reflects tissue microstructure and mean diffusivity (MD) and fractional anisotropy (FA) are often readily interpreted in terms of cellularity and cell anisotropy, respectively. Here, we investigated to which degree histological features accounts for their variations in fixed sections of meningioma tumors. Histological slices were quantified in terms of cellularity and cell anisotropy, or by a neural network. Results show that in some cases the majority of the variation can be attributed to cellularity whereas in others none. Similarly, in some samples only a minority of the variability is attributable to the variability in FA explained by neural network.
Comparison of two retrospective tracking techniques in presence of fast and slow motion.
Authors: Marchetto Elisa , Murphy Kevin , Gallichan Daniel
Published: August 2023

We investigated the artifacts arising from different types of head motion during brain structural MR imaging and how well these artifacts can be compensated for using retrospective correction based on two different motion-tracking techniques: FatNavs and Tracoline systems. High image quality could be recovered in our slow-motion scenarios using both motion estimation techniques. Masking the non-rigid part of the neck during FatNav volumes registration led to higher image quality when large pitch-motion was present. The fast continuous motion scenario led to more severe image artifacts that could not be fully compensated by the retrospective motion correction techniques used.
Unsupervised Deep Learning using modified Cycle Generative Adversarial Network for rigid motion correction in pediatric brain MRI
Authors: Kim Sewook , Lee Seul , Yi Jaeuk , Al-Masni Mohammed , Gho Sung-Min , Choi Young Hun , Kim Dong-Hyun
Published: August 2023

Motion artifact that appears due to patient movement in MRI scans is a major obstacle in pediatric imaging. Since acquiring paired motion-clean and motion-corrupted dataset is difficult, unsupervised deep learning such as Cycle Generative Adversarial Network (Cycle-GAN) has been used in motion correction tasks these days. In this study, we propose a rigid motion artifact reducing strategy with modified Cycle-GAN by replacing generator that converts motion-free to motion-corrupted domain with a motion simulator. Our proposed model outperforms in contrast preservation and reducing artifacts compared to the original Cycle-GAN as well as reduces training parameters.
On the anisotropy of IVIM-derived microvascular cerebral pseudo-diffusion: a physics-informed neural network approach
Authors: Voorter Paulien H.M. , Jansen Jacobus F.A. , van der Thiel Merel M. , Staals Julie , van Oostenbrugge Robert-Jan , van Dinther Maud , Backes Walter H. , Drenthen Gerhard S.
Published: August 2023

Acquisition of intravoxel incoherent motion (IVIM) images with diffusion sensitization in at least six directions (IVIM tensor imaging) provides the unique opportunity to non-invasively measure the anisotropy of both the parenchymal and microvascular diffusivity (D and D*). We demonstrate the feasibility of whole-brain IVIM tensor analysis by utilizing a physics-informed neural network fitting approach to achieve more accurate assessment of D, D*, and the corresponding tensors. The fractional anisotropy of D* (FA(D*)) was explored for different brain tissue regions, which revealed lower FA(D*) in cortical gray matter and higher FA(D*) in deep gray matter compared to white matter.
Joint estimation of T2 and diffusion tensor from DW-SSFP using EPG
Authors: Lamy Julien , Santin Mathieu , de Sousa Paulo Loureiro
Published: August 2023

The DW-SSFP sequence is useful to attain strong diffusion-weighting on clinical systems while keeping a short repetition time. However, its analytical model does not account for the echo time. Using a 3D EPG model, we show that the echo time plays an important role, and that it cannot be neglected. We then provide a new method to jointly estimate T2 and the diffusion tensor on an ex-vivo fetal brain at 3 T.
MR measurement of the mean-position distribution
Authors: Ordinola Alfredo , Özarslan Evren
Published: August 2023

The distribution of net displacements, commonly referred to as the ensemble average propagator, has been measured using Stejskal-Tanner experiments. Here, a recently introduced diffusion sensitization method is employed in a similar manner to obtain the distribution of mean positions. By utilizing the two schemes synergistically, low b-value measurements are employed to decouple dynamic second moments from static ones. We illustrate our findings on an excised mouse spinal cord imaged using a benchtop MRI scanner.
Effect of wall elasticity on flow MRI in 3D printed models
Authors: Unal Isil , Dengiz Duygu , Peschke Eva , Quandt Echard , Ravesh Mona Salehi , Pravdivtseva Mariya , Hövener Jan-Bernd , Jansen Olav
Published: August 2023

2D phase-contrast (PC) MRI or 4D flow MRI allows to quantify the blood flow in vivo. However, the accuracy of these methods is influenced by many parameters. To optimize and validate these methods, patient-derived vascular models are key. Here, 3D printing is revolutionizing the manufacturing process, but realistic wall properties are essential for meaningful results. In this study, commercial elastic printing materials were used to fabricate vascular models. A tensile test was applied to all samples. Then the effect of wall elasticity on flow was investigated with 2D PC and 4D flow MRI. Wall motion was quantified using CINE MRI.
Optimization and evaluation of inversion pulses for background suppressed pseudo-Continuous Arterial Spin Labeling at 7T
Authors: Zhao Chenyang , Wang Kai , Graf Christina , Stollberger Rudolf , Wang Danny
Published: August 2023

Background suppression (BS) of pseudo-Continuous Arterial Spin Labeling (pCASL) needs to be optimized at 7T to ameliorate the ASL signal loss caused by the low inversion efficiency (IE) of BS due to B1 inhomogeneity. In this study, the original HS pulse used as BS at 3T was assessed at 7T, and four non-selective inversion pulses, including HS, WURST, OPTIM, and pTx adiabatic, were optimized and evaluated in phantom and in-vivo studies. Less than 80% IE achieved by the original HS pulse was improved to 85% by optimized pulses. Markedly higher tSNR was reported in pCASL with the optimized pulses.
Open Science Initiative for Perfusion Imaging (OSIPI): Arterial Spin Labeling Imaging and Analysis Lexicon and Reporting Recommendations
Authors: Suzuki Yuriko , Clement Patricia , Dai Weiying , Dolui Sudipto , Fernández-Seara Maria , Lindner Thomas , Mutsaerts Henk , Petr Jan , Shao Xingfeng , Taso Manuel , Thomas David
Published: August 2023

As part of the Open Science Initiative for Perfusion Imaging (OSIPI), the aim of this work is to develop a Lexicon and Reporting Recommendations for arterial spin labeling (ASL) perfusion MR imaging and analysis. The lexicon describes standardized nomenclature and terminology for ASL acquisition techniques, parameters and physiological constants that are required for quantitative analysis. Additionally, a community-endorsed recommendation for reporting acquisition parameters in publications is provided. Overall, this project aims to improve the clarity and consistency of ASL terminology, which in turn will facilitate comparisons between different studies.
SAR-reduced Asymmetric tr-FOCI for PICORE-ASL
Authors: Chi Didi , Blunck Yasmin , Glarin Rebecca , Davey Catherine , Pfeuffer Josef , Staeb Daniel , Jin Jin , Johnston Leigh
Published: August 2023

PICORE-ASL using tr-FOCI pulses during labelling typically generates high power deposition at 7T. The current study introduces an asymmetric tr-FOCI pulse for PICORE-ASL to achieve SAR reduction. Results from simulations, phantom and in vivo experiments demonstrate the SAR reduction that can be achieved by using the asymmetric pulses without sacrificing inversion efficiency, slice profiles or CBF measurement.
The value of APTw combined with DKI for prediction of pelvic lymph node metastasis of cervical cancer
Authors: Meng Xing , Liu Ailian , Tian Shifeng , Ma Changjun , LIN Liangjie , Song Qingwei , Hu Geli , Wang Jiazheng
Published: August 2023

Cervical cancer is one of the most common malignant cancers in pelvic cavity, and trends in young adults. This study aims to investigate the value of amide proton transfer weighted (APTw) combined with diffusion kurtosis imaging (DKI) for prediction of pelvic lymph node metastasis of cervical cancer, the accurate diagnosis of which is significant for the treatment and prognosis of cervical cancer.
Automatic Prostate Tumor Segmentation: Does the Convolutional Neural Network Learn How the Tumor Looks, or What the Radiologist Sees?
Authors: Gunashekar Deepa Darshini , Bielak Lars , Oerther Benedict , Benndorf Matthias , Grosu Anca , Zamboglou Constantinos , Bock Michael
Published: August 2023

A convolutional neural network was implemented to automatically segment tumors in multi-parametric MRI data. The influence of the variability in the ground truth data was evaluated for automated prostate tumor segmentation. Therefore, the agreement between the predictions of the CNN was measured with co-registered whole mount histopathology images and the tumor contours drawn by an expert radio-oncologist. The results indicate that the network can discriminate tumor from healthy tissue rather than mimicking the radiologist.
Hyperpolarized 13C Pyruvate MR-Assisted Longitudinal Risk Stratification in Prostate Cancer Patient – From Surveillance to Surgery
Authors: Chen Hsin-Yu , Nguyen Hao , Wang Zhen , Ohliger Michael , Simko Jeffry , Cooperberg Matthew , Gebrezgiabhier Daniel , Carvajal Lucas , Gordon Jeremy , Kurhanewicz John , Aggarwal Rahul , Vigneron Daniel , Bok Robert
Published: August 2023

Serial hyperpolarized 13C+mpMRI and paired metabolic image-guided biopsy were employed in a new integrative active surveillance (AS) paradigm, exemplified by a patient who initially enrolled in AS for 5 years, but later underwent radical prostatectomy upon progression. Metabolic biomarker kPL images detected early progression preceding radiologic and clinical parameters. Final whole-gland histopathology also linked kPL and PI-RADS targets to multifocal tumors, where kPL spatially reflected intratumoral heterogeneity, and high kPL regions correlated with adverse pathologic features such as G4 cribriform pattern, extracapsular extension, and lymphovascular invasion. Results indicated HP 13C may help optimize AS by improving clinical risk calculation.
Elevated magnetic resonance imaging measures of adipose tissue deposition in women with breast cancer treatment-related lymphedema
Authors: Crescenzi Rachelle , Donahue Paula , Garza Maria , Lee Chelsea , Patel Niral , Gonzalez Victoria , Jones Sky , Donahue Manus
Published: August 2023

The overall goal of this work is to apply Dixon fat-water MRI to test fundamental hypotheses regarding the role of elevated adiposity in breast cancer treatment-related lymphedema (BCRL) condition severity. BCRL is a common co-morbidity of breast cancer therapies, yet factors that contribute to BCRL progression remain incompletely characterized. We observed that adiposity quantified by MRI is elevated in the affected upper extremity and torso of women with BCRL and increases with condition severity. As such, Dixon MRI may provide a surrogate marker of BCRL onset and may help to inform the varied course of lymphedema progression.
Short- and long-term changes of ADC and rF% in patients with bone metastases from breast cancer
Authors: Colombo Alberto , Giardini Eleonora , Summers Paul , Pricolo Paola , Zugni Fabio , Belmonte Maddalena , Petralia Giuseppe
Published: August 2023

Evaluating short and long-term apparent diffusion coefficient (ADC) and relative fat fraction (rF%) changes could provide a better understanding of therapy response of bone metastases from breast cancer. Baseline ADC and rF% values computed from whole-body MRI, were compared with those measured at 12 and 36 week evaluations after treatment start. ADC and rF% significantly increased in responders at 12-weeks. At 36-weeks, ADC values range broadened, while rF% further increased. Short-term ADC and rF% changes are consistent with previous reports. Long-term changes highlight two patterns of response in which either high diffusion or fat repopulation prevail.
A Cartilage-Specific Loss Function Improves Image Reconstruction Performance in Multiple Tissues of Clinical Interest
Authors: Tolpadi Aniket , Calivà Francesco , Han Misung , Bahroos Emma , Larson Peder , Majumdar Sharmila , Pedoia Valentina
Published: August 2023

Most MRI image reconstruction algorithms are optimized for full-volume performance rather than specific tissues. Using a KIKI-Net style architecture and multi-component loss function in image space and k-space as baseline, we find a cartilage-specific loss function improves reconstruction performance at R=4 and R=8 in both cartilage and menisci. Thus, it may be possible to improve clinical utility of reconstruction pipelines across tissues of heightened clinical interest using a simple loss function weighting. Furthermore, full-volume standard reconstruction metrics worsened at R=4 and R=8 while tissue-specific metrics improved, calling into question whether these metrics are best for assessing reconstruction pipeline clinical utility.
Improved Neural Network-Based Coil Compression
Authors: Cole Elizabeth , Meng Qingxi , Raina Anishka , Pauly John , Vasanawala Shreyas
Published: August 2023

Coil compression is performed in magnetic resonance imaging (MRI) to enable smaller datasets and faster computation time. However, the traditional coil compression process is lengthy and lossy. In this work, we proposed a novel neural network-based coil compression method to achieve higher reconstruction accuracy and faster coil compression. Our method consistently achieved up to 1.5x lower NRMSE compared to SVD and GCC on the fastMRI knee dataset. The computational requirements of our method are practical, and inference runs 10 times faster than the traditional methods.
VERDICT MRI for estimation of intracellular volume fraction and cell radius: comparison with histology in a mouse model of neuroendocrine tumor
Authors: Lundholm Lukas , Montelius Mikael , Jalnefjord Oscar , Forssell-Aronsson Eva , Ljungberg Maria
Published: August 2023

VERDICT MRI provides estimates of intracellular volume fraction and cell radius non-invasively which may facilitate e.g., tumor grade classification and longitudinal studies without the need for biopsy. Tumors of a human SI-NET animal model were irradiated and measured with diffusion MRI. Colormaps of cell radius index and intracellular fraction were derived from both VERDICT analysis of the MR data and histological analysis of stained tumor slices. VERDICT maps of intracellular fraction corresponded well with histology in necrotic tissue, however the cell radius index was poorly estimated in these regions. Further work is needed to optimize VERDICT for different tissue types.
Analysis of resting state functional connectivity of white matter tracts in spinal cord of squirrel monkey using Graph Theory
Authors: Sengupta Anirban , Mishra Arabinda , Wang Feng , Chen Li Min , Gore John
Published: August 2023

The goal of this study was to investigate the nature of spontaneous BOLD fluctuations in white-matter (WM) of spinal-cord and to use these to identify the intrinsic functional architecture of WM tracts and their correlations with the gray-matter (GM) hubs. Connectivity measures were obtained using resting state BOLD signals between WM-WM and WM-GM regions, followed by network analysis using graph-theory. We found WM and GM hubs on the dorsal side exhibit greater temporal correlation as exhibited by their stronger node strength in resting state. Also, within segment WM-WM and WM-GM correlations were found to be stronger than those between segments.
A New MRI acquisition method for quantitative myocardial oxygen extraction imaging
Authors: Zheng Jie , Li Ran , Eldeniz Cihat , Schindler Thomas , Peterson Linda , Woodard Pamela
Published: August 2023

A previously developed MRI method for quantitative myocardial oxygen extraction mapping showed promising results, but image quality suffered from distortion and low in-plane resolution. Therefore we developed a new image acquisition method which both doubled the in-plane spatial resolution and corrected image distortion and tested it in healthy subjects. Reproducibility studies showed comparable results between the two methods. Rigorous animal and/or human validation studies are warranted to study its translational potential in the assessment of patients with myocardial metabolic dysfunction.
MultI-Compartment Model based Parametric Mapping of the Heart with a Single MOLLI Acquisition (MIC-MOLLI)
Authors: Liu Jing , Ordovas Karen , Wang Yan , Lupo Janine , Xu Duan , Lee Yoojin , Abraham Roselle , Saloner David
Published: August 2023

In this study, we developed a multi-compartment model based method for deriving multi-parametric mapping of the heart from the MOLLI T1 mapping acquisition. The preliminary results on patients with hypertrophic cardiomyopathy demonstrated the feasibility of deriving 9 quantitative parametric maps from a single scan and showed its potential of providing a comprehensive assessment of the myocardial tissue composition.
Ultrashort Echo Time Magnetization Transfer Ratio (UTE-MTR) Measurements of Paraspinal Muscles Correlate Well with Lumbar Disc Herniation
Authors: Feng Jia-Xin , Liu Jin , Liao Jian-Wei , Li Wei , Chen Xiao-Jun , Yao Lin , Huang Pan-Hui , Qian Long , Ma Ya-Jun , Li Shao-Lin
Published: August 2023

Ultrashort echo time magnetization transfer (UTE-MT) is suggested to a non-invasive technique to assess collagenous matrix indirectly. In this study, we utilized UTE-MT sequence to investigate the relationship between UTE-MT ratio (UTE-MTR) measurements of paraspinal muscles and disc herniation in patients with disc degeneration. We found that the UTE-MTR showed a good performance in differentiation of patients with and without disc herniation, thus potentially valuable in predicting disc termination.
Assessment of skeletal muscle energy metabolism by 31P MRS in COVID19 and Multiple Sclerosis patients: technical and clinical insights
Authors: Naëgel Antoine , Karkouri Jabrane , Ratiney Hélène , Kennouche Djahid , Royer Nicolas , Millet Guillaume , Slide Jill , Morel Jérôme , Croisille Pierre , Viallon Magalie
Published: August 2023

Dynamic 31P MRS was performed during a standardized exercise of the lower leg, in patients with chronic fatigue enrolled in 2 clinical studies: multiple sclerosis patients and COVID19 patients that were hospitalized in intensive care unit and requiring respiratory assistance. In this work, we also revisit certain assumptions on the metabolite T1 and question shortcuts often made to shorten 31P protocol for a better patient’s compliance.
A Diffusion Tensor Imaging approach to investigate the effects of exercise on quadricep muscle fiber lengths
Authors: Dunne Reese , Gold Garry , Mazzoli Valentina
Published: August 2023

There is currently no established method to monitor muscle architecture throughout exercise intervention. This work investigates the value of DTI and fiber tractography to detect changes in fiber length in the quadriceps caused by resistance training. Five human subjects participated in a three-month training regimen, and DTI scans of their quadriceps were acquired. Through DTI tractography, fiber lengths were measured and compared between quadricep muscle components. There were no statistically significant changes in fiber length after three months of exercise, showing further optimization is needed to utilize DTI tractography for monitoring fiber length changes due to exercise.
Assessment of skeletal muscle extracellular volume fraction in Becker Muscular Dystrophy using MR fingerprinting with water and fat separation
Authors: Marty Benjamin , Baudin Pierre-Yves , Fromes Yves , Wahbi Karim , Reyngoudt Harmen
Published: August 2023

Becker muscular dystrophy (BMD) is a genetic neuromuscular disorder leading to muscle weakness and degeneration. Quantitative MRI has been widely proposed to characterize skeletal muscle tissue structure of BMD and revealed increased intramuscular fat fraction associated with functional decline. In this study, we measured the extracellular volume fraction (ECV) of skeletal muscle tissues using MR fingerprinting with water and fat separation. We evaluated this variable as an early imaging biomarker of skeletal muscle tissue alterations. Compared to healthy controls, we showed that the muscles of BMD subjects present elevated ECV before fatty replacement occurs.
Spontaneous motor unit activity in a healthy ageing population measured using motor unit MRI (MUMRI)
Authors: Birkbeck Matthew , Heskamp Linda , Hall Julie , Schofield Ian , Sayer Avan , Dodds Richard , Whittaker Roger , Blamire Andrew
Published: August 2023

Sarcopenia is commonly associated with ageing, whereby individuals lose muscle mass and strength. One potential contributor to sarcopenia is the degeneration of motor units (MU), defined as a single motor neuron and the muscle fibres it innervates. We used motor unit MRI (MUMRI) to investigate changes to spontaneous MU activity and morphology in a cohort of healthy ageing adults. We found that MU activity and morphology did not appear to change with healthy ageing. We next aim to apply the MUMRI technique in patients with sarcopenia to look for evidence of accelerated MU loss compared to these healthy controls.
Assessing Semi-Automatic processing of Muscle Mass and Fat Fractions from mDIXON whole body MRI
Authors: Nicholas Rosemary , Greenhaff Paul , Francis Susan
Published: August 2023

Muscle volume and fat fraction can be quantified from mDIXON scans either manually or using automated processes. Here we compare manual volumes of thigh and calf muscle ROIs with an automated pipeline created using FSL’s FAST segmentation, to compare muscle volume and fat fraction across subject groups and with their DXA values. Automatic volume segmentations correlated highly with manually drawn measures (r=.975) as well as DXA (r=0.840). Group comparisons show COPD and post-COVID patients had significantly lower muscle mass and higher fat fraction. Automatic segmentation performs well compared to manually derived volumes and is more time efficient.
Prospective correction of multi-shot diffusion imaging using motion compensation and dual-speed EPI
Authors: Moulin Kevin , Cork Tyler , Troalen Thomas , Ennis Daniel , Croisille Pierre , Viallon Magalie
Published: August 2023

Multi-shot (MS) reduces image distortion in EPI caused by B0 field inhomogeneity and enables higher resolution diffusion imaging. However, interaction between physiologic motion and diffusion encoding gradients leads to strong image aliasing artifacts in MS-EPI due to phase discrepancies. We propose prospective strategies to reduce shot-to-shot phase variation for interleaved phase-segmented diffusion MS-EPI. First and second order motion compensated diffusion gradient waveforms and dual-speed EPI with oversampled k-space center were evaluated as a shot-to-shot phase mitigation strategy. Validations were performed in silico, in vitro, and in vivo in the brain, liver, and heart.
Investigating Spiral Arterial Spin Labeling with Pulseq and Field Monitoring at 7T
Authors: Ma Ruoyun Emily , Ivanov Dimo , Huber Renzo , Kurban Denizhan , Poser Benedikt
Published: August 2023

We developed several ASL sequences at 7T with a FAIR-QUIPSS II labeling scheme and various spiral readout strategies using Pulseq. Iterative algebraic image reconstruction was performed with CG-SENSE, using the field evolution data measured with external NMR probes. Robust performance in detecting brain’s perfusion signal was observed in 2D single- and multi-band spiral acquisitions especially at relatively high spatial resolution, without the requirement for a longer scan time. 3D spiral acquisition showed reduced contrast level in perfusion maps and requires further investigation and optimization.
Optimization of a breast EPI-DWI protocol with high b-values and anterior-posterior phase-encoding direction: initial results
Authors: Rodríguez-Soto Ana , Batasin Summer , Fang Lauren , Carl Michael , Ojeda-Fournier Haydee , Keenan Kathryn , Rakow-Penner Rebecca
Published: August 2023

Diffusion-weighted imaging (DWI) acquired with echo-planar imaging (EPI) is utilized in breast MRI protocols to evaluate cancer lesions. While clinical implementation is limited by the distortion artifacts which affect EPI, methods such as reverse polarity gradient (RPG) and data collection with reduced field-of-view (FOV) have been used to reduce distortion. Evaluating these methods in minimizing distortion for images acquired with parallel imaging (PI) is a promising approach to improve EPI-DWI breast imaging. Here, we evaluated the distortion magnitude of EPI-DWI data collected with and without PI on a breast phantom and tested the feasibility of this protocol in vivo.
Machine Enhanced Reconstruction Learning and Interpretation Networks (MERLIN)
Authors: Hammernik Kerstin , Küstner Thomas
Published: August 2023

Machine Learning (ML) methods have evolved tremendously during the last decade. A number of frameworks support the development of new ML methods. However, support for high-dimensional and complex-valued data processing is often limited. Therefore, we propose a Machine Enhanced Reconstruction Learning and Interpretation Networks (MERLIN) framework that seamlessly integrates with existing ML solutions such as Tensorflow/Keras and Pytorch and complements them by high-dimensional, complex-valued and MR-specific operators and layers. Furthermore, standard data processing pipelines in Python are provided in the context of MRI reconstruction.
A data-driven method for automatic regularization selection in a hybrid DL-SENSE reconstruction
Authors: Hosseini Zahra , Feiweier Thorsten , Conklin John , Kannengiesser Stephan , Nickel Marcel , Lang Min , Tabari Azadeh , Filho Augusto , Lo Wei-Ching , Longo Maria , Lev Michael , Schaefer Pamela , Rapalino Otto , Huang Susie , Cauley Stephen , Clifford Bryan
Published: August 2023

The integration of deep learning priors into regularized CG-SENSE reconstructions enables high quality MR images to be generated from noisy, undersampled data. The regularization parameter in these methods can be tuned to control the level of denoising, allowing a network to generalize to novel SNR conditions without retraining. However, manual tuning of the regularization parameter can be time consuming. This work presents a data-driven method for automatic regularization selection using commonly acquired noise calibration data. Results indicate the method generalizes across clinically relevant imaging scenarios and provides diagnostically equivalent image quality to that obtained by manual parameter tuning.
Accelerating MR Elastography using Deep Learning-Reconstruction of Undersampled Data
Authors: Bugge Robin , Ottesen Jon Andre , Fuster Elies , Bjørnerud Atle , Emblem Kyrre
Published: August 2023

Problem summary: Brain MR elastography is associated with extended acquisition times, which is alleviated by reduced coverage or resolution. The aim of this project is to utilize deep learning to accelerate MRE. Methods: We employ an MRE for fully sampled acquisition. Undersampled data is simulated by masking phase-encoding steps. A cascaded reconstruction network is used to reconstruct the phase image from undersampled k-space. Results: There are subtle differences between the reconstructed and fully sampled phase images. We observe a non-significant difference for stiffness values in our preliminary results. Conclusions: The method shows promise for accelerating MR elastography data.
Evidence of Lactate Shuttling in the Human Brain with Hyperpolarized 13C-MRI
Authors: Uthayakumar Biranavan , Bragagnolo Nadia , Soliman Hany , Chen Albert , Endre Ruby , Perks William , Ma Nathan , Heyn Chris , Black Sandra , Cunningham Charles
Published: August 2023

It is well known that glucose is the primary source of energy in the brain, but mounting evidence suggests that at least some of this glucose is first converted to lactate and shuttled between cellular compartments before being oxidized in the TCA cycle. In this study, the hypothesis that this ”lactate shuttle” contributes to the 13C-lactate and 13C-bicarbonate signal observed in the awake human brain is tested using hyperpolarized 13C MRI (HP13C-MRI).
On the experimental setup of parahydrogen-induced polarization via proton exchange.
Authors: Kuhn Jule , Them Kolja , Hövener Jan-Bernd
Published: August 2023

The PHIP-X methodology is a novel approach to hyperpolarize nuclei from specific molecules that could function as contrast agents in metabolic MRI. PHIP-X combines the strong polarization of hydrogenative PHIP with the broad applicability of proton exchange and opens up the variety of potential hyperpolarizable biomolecules. The presented experimental setup facilitates the application of pH2 pressures up to 30 bar and well-defined external magnetic fields up to 80 mT. Using this setup allowed to hyperpolarize glucose (830 mM) and achieved increasing polarization with increasing the pressure from 10 bar to 20 bar (molar polarization was more than doubled).
The effect of the glutamate response function on detection sensitivity for functional MRS: a simulation study
Authors: Schrantee Anouk , Berrington Adam , Pouwels Petra , Coolen Bram , Gurney-Champion Oliver , Najac Chloé
Published: August 2023

fMRS stimulation paradigms and analysis strategies are highly heterogeneous, partially due to lack of knowledge of the underlying metabolic response function. To better understand the potential consequences of analysis methods, this simulation study evaluates the effect of different glutamate response functions (GRFs) and binning strategies. As the GRF becomes more delayed, analyzing bins from spectra directly after ‘task’ onset results in underestimation of the true change. In moving average analyses, the fitted time-courses co-varied significantly with the input glutamate time-course. Future simulation studies will expand on other variable sources, such as habituation and hemodynamic effects, and macromolecule fitting procedures.
Improved motion compensation for water-suppressed diffusion MR Spectroscopy evaluated using synthetic data
Authors: Döring André , Jones Derek , Kreis Roland
Published: August 2023

We demonstrate that, even without having water as an internal reference, a combination of spectral registration and fitting can restore artificial signal loss promoted by incoherent averaging due to frequency/phase drifts and motion-induced dephasing for the cardinal brain metabolites (tCr, tCho, tNAA, Glx and Ins) by using a set of synthetically distorted diffusion MR spectra (including realistic phase, frequency and amplitude fluctuations).
Water-Immersed 8-Dipole Receive Array for MR-Guided Focused Ultrasound of the Brain at 3T
Authors: Maunder Adam , Pichardo Samuel , Pike G. Bruce , Mclean Melany , Robb Fraser , Iyer Ashwin , De Zanche Nicola
Published: August 2023

The piezoelectric transducer array in magnetic resonance guided focused ultrasound shields the RF body-sized birdcage (BC) fields, leading to regions of low receive sensitivity that hinder MR thermometry and structural imaging. This work presents a flexible, acoustically transparent receive array consisting of dipole sections that mimic loops and are contained within the water bath of the ultrasound transducer array helmet surrounding the head. Adjacent elements are decoupled by shared current paths and lumped inductors. In simulation, the receive sensitivity is increased by 7.8-fold compared to a BC and causes a negligible alteration of the transmit field and specific absorption rate.
A multi-directional laser ablation device for 3D conformational ablation guided by real-time volumetric MR-thermometry
Authors: Desclides Manon , Machinet Guillaume , Pierre Christophe , Ozenne Valéry , Chemouny Stéphane , Quesson Bruno
Published: August 2023

We present here a new laser device allowing us to induce local temperature increase in several directions around the inserted probe to create conformational thermal ablation. The device incorporates 6 independent emitters illuminating several angles radially to the probe. We illustrate the capabilities of the device to create various heating shapes that can be visualized by real-time 2D multi-slice MR-thermometry.
Towards motion robust MRT during Microwave Hyperthermia by integrating an 8-channel receiver coil array into the MRcollar
Authors: Sumser Kemal , Bellizzi Gennaro , Hernandez-Tamames Juan , van Rhoon Gerard , Paulides Margarethus
Published: August 2023

In the head and neck region, precise heating and temperature monitoring is a challenge. The MRcollar, an MR compatible head and neck microwave hyperthermia applicator has been developed for conformal heating and to enable MR thermometry (MRT) during the treatment. To deliver on the needs of accurate temperature monitoring, the MRcollar has been equipped with 8-channel receiver coil array. This coil array improves increased the SNR by 5 times compared to the body coil of the MRcollar. Increase in the SNR also led to improvement in the MRT precision, from 0.91 °C to 0.37 °C.
Non-Local Means Denoising of 7T Functional MR Images: Enhancing Spatial Accuracy of Fine-Grained Task-Specific Neurosignatures?
Authors: Ceja Igor Tellez , Gladytz Thomas , Starke Ludger , Tabelow Karsten , Niendorf Thoralf , Reimann Henning
Published: August 2023

Superior spatial fidelity of fMRI at ultrahigh magnetic field strengths (≥7T) in principle allows for resolving fine grained task-specific fMRI neurosignatures. Yet, spatial details of BOLD clusters are conventionally blurred by Gaussian smoothing. To preserve spatial details, spatial-adaptive non-local means (SANLM) denoising has been introduced in fMRI as an alternative to Gaussian smoothing. Here, we evaluate SANLM denoising at 7T. SANLM removes noise in homogeneous areas while maintaining edges. It prevents the spread of BOLD patterns between adjacent brain regions, but should be employed with caution, as its spatial detail is partially driven by the underlying anatomy.