bluuebunny/crossref_metadata_2025 huggingface dataset:
Simple Method for Bloch-Siegert B1 Map Data Processing
Authors: Wheaton Andrew , Dannels Wayne
Published: August 2024

A simple data processing method for calculating B1 map data using the Bloch-Siegert shift method is described. The proposed method uses a phase conjugate approach instead of conventional phase subtraction. The proposed method has the dual advantages of 1) not requiring phase unwrapping and 2) enabling simple and SNR-efficient complex data combination for multi-channel phased array coils. One consequence of using a phase conjugate approach is a reduced range of resolvable B1 due to phase aliasing. A practical solution is offered to resolve this problem by making an assumption of the realistic range of expected B1.
Reliable Low-Field B0-Maps by Deep Learning with Physical Constraints
Authors: Schote David , Winter Lukas , Kolbitsch Christoph , Kofler Andreas
Published: August 2024

Heavy B0-field inhomogeneities in low-field MRI can lead to geometric distortions in the reconstruction, if not compensated. We simulated low-field data to evaluate different approaches for estimating the field map from phase difference maps. By using spherical harmonic basis functions as physical constraints in our neural network approach we could improve the estimation of B0-field maps compared to other network architectures and methods not involving neural networks.
The Effect of Breathing on Pulmonary Blood Flow using Pseudocontinuous Arterial Spin Labeling (PCASL) in a Test-Retest Design
Authors: Kolb Manuel , Seith Ferdinand , Mack Isabella , Küstner Thomas , Pohmann Rolf , Martirosian Petros
Published: August 2024

PCASL can quantitively measure pulmonary blood flow and detect pulmonary embolism. However, patients suffering from lung embolisms are usually unable to follow breathing commands required for optimal imaging. In this study, the influence of respiratory states on pulmonary perfusion measured with PCASL was investigated. Nineteen healthy volunteers were studied with an ECG-triggered PCASL sequence in a test-retest design. It was found that mean perfusion was highest during expiration, followed by free breathing and lowest in inspiration. A significant difference was observed between the maximal inspiration and expiration breath-hold conditions. Perfusion values acquired by PCASL in the lung parenchyma showed high reproducibility.
MRI-based radiomics nomogram for preoperatively differentiating intrahepatic cholangiocarcinoma from colorectal liver metastases Abstract
Authors: Xu Ying , Li Lu , Yang Yi , Ye Feng , Wang Sicong , Xie Lizhi , Wang Yanan , Zhao Xinming
Published: August 2024

A total of 133 patients in training cohort (64 IMCC and 69 CRLM) and 57 patients in validation cohort (29 IMCC and 28 CRLM) were included. Radiomics features were extracted from the DCE-MR images and selected by the least absolute shrinkage and selection operator algorithm to establish the radiomics model. The radiomics nomogram was constructed combining the radiomics model and clinical model. The radiomics nomogram combining radiomics signatures based on DCE-MRI with clinical factors (serum CEA level and tumor diameter) may provide a reliable and noninvasive tool to discriminate IMCC from CRLM, which could help guide treatment strategies and prognosis prediction preoperatively.
The PRISM clinical trial: Quantitative imaging for personalized liver radiation therapy
Authors: Tadimalla Sirisha , Wang Tim , Gebski Val , Foster Sheryl , Lam Vincent , Sykes Jonathan , Finnegan Robert , George Jacob , Ahern Verity , Sourbron Steven , Haworth Annette
Published: August 2024

Quantitative imaging biomarkers of liver function offer a potential opportunity to optimize radiation dose distributions for personalized treatment of patients with liver cancers using radiation therapy. The PRISM clinical study aims to determine if radiation treatment plans guided by liver function maps from MRI can increase the therapeutic dose to tumours. We have developed a dedicated multi-parametric MRI protocol for the quantitative assessment of liver composition, structure and function. Details of the protocol and pilot data are presented here.
Toward Assessment of Renal Tubule Volume Fraction in Rat Kidney Using Decomposition of Parametric T2 Mapping
Authors: Tasbihi Ehsan , Gladytz Thomas , Starke Ludger , Millward Jason , Seeliger Erdmann , Niendorf Thoralf
Published: August 2024

Increased incidence of kidney diseases is a concern, for which rapid biomarkers are lacking. Changes in tubule volume fraction (TVF) is a potential biomarker for kidney disease. T2-mapping may be useful to asses TVF in noninvasive manner. To study this, we developed a protocol tailored for T2-mapping of the rat kidney, and determined a suitable numerical solution for multi-exponential decomposition of the T2-decay. Evaluation and validation of these algorithms using synthetic data and phantom showed an accuracy of 98%. This demonstrates that our approach is promising for research into quantitative assessment of renal TVF in in vivo applications.
Feasible study of multimodal apparent diffusion (MAD) in kidney
Authors: Wang Shuang , Ji Tuo , Zhang Jingdong , YU Dan , Dai Yongming , Liu Lin
Published: August 2024

The multimodal apparent diffusion (MAD) is a new approach with a predefined number of components associated with microstructure. In this work, the performance of quad-modal apparent diffusion in the kidney was assessed with simulation for different conditions. In-vivo demonstration and comparison with other models showed an explicable parametrization and improved fitting performance.
High resolution diffusion weighted imaging on pancreas through reduced FOV and compressed SENSE: a feasibility study
Authors: Zhang Yajing , Wu Zhigang , Su Wengu , Wang Jiazheng , Zhao Yan , Van Cauteren Marc
Published: August 2024

Pancreas imaging remains challenging because of its small size and motion, and conventional diffusion weighted imaging (DWI) suffers from poor image quality due to low signal-to-noise (SNR) and image blurring. This study performs several schemes to achieve high resolution high image quality pancreas DWI with reduced FOV using Compressed SENSE.
Oxygen-enhanced high-resolution 3D ultrashort echo time MRI for patients with connective tissue diseases: a preliminary study
Authors: Zhang Feng , Yang Yu Xin , Jiang Lei , Zhao Liang , Dai Yongming , Zhu Jiong
Published: August 2024

This preliminary study investigates the utility of high-resolution 3D-UTE to assess patients with CTD-ILD and their pulmonary function, including both pulmonary parenchyma and lesions, using OE-UTE-MRI. Our results suggest that high-resolution 3D UTE and OE-UTE MRI could potentially be as useful as thin-section CT for lesion detection of CTD patients with ILD and provide additional pulmonary functional loss assessment.
APT histogram parameters for Response Prediction of Neoadjuvant Chemotherapy in Rectal Cancer: A Prospective Study
Authors: Gong Xiaoling , Shen Yu , Wen Daguang , Zhang Xiaoxiao , Zhang Xiaoyong , Wang Ziqiang , Wu Bing
Published: August 2024

Early imaging prediction of neoadjuvant chemotherapy (NACT) response would enable a personalized treatment approach to improve therapeutic response and avoid treatment morbidity in rectal cancer. Morphological changes base on T2 weighted MRI and free dispersion limitation of water molecules in tumor have limited value in evaluating efficacy after NACT. Amide proton transfer (APT)–weighted MRI, indirectly detecting the concentration of tissue macromolecular proteins, could help to inform us of the proliferation and biological status of tumor cells. The aim of this study is to determine if APT MRI is useful in early assessment of treatment response in persons with rectal cancer.
Framework for Characterizing in vivo Passive Myocardial Stiffness using in vivo MRI
Authors: Kolawole Fikunwa , Cork Tyler , Loecher Michael , Wang Vicky , Kuhl Ellen , Ennis Daniel
Published: August 2024

As increased passive myocardial stiffness is implicated in the etiology of many cardiac diseases, its in vivo estimation can improve management of heart disease. MRI-driven computational constitutive modeling can be used to obtain subject-specific passive myocardial stiffness. We present a method for building an in silico model to estimate subject-specific passive myocardial stiffness by combining LV geometric data derived from cine bSSFP, regional kinematics extracted from tagged MRI, and myocardial microstructure measured using in vivo cDTI. This project aims to develop a clinically translatable in vivo passive myocardial stiffness evaluation framework by integrating cardiac MRI and computational modeling.
No separate acquisition timing scheme is necessary for the MOLLI technique when used for the post contrast cardiac T1 mapping
Authors: Yee Seonghwan
Published: August 2024

The modified Look-Locker imaging (MOLLI) technique, widely used in cardiac T1 mapping, requires specification of an acquisition timing scheme. For better quantification of wide range of T1 values, different acquisition schemes have been used for the prior- and post-contrast conditions. However, the strategy of having two different acquisition schemes might add complexity to the consistent management of clinical protocols, especially in a clinical environment with multiple MRI systems. Hence, a phantom experiment was performed to examine the necessity of this strategy. The results here suggest that having a separate acquisition scheme for the post-contrast condition would not be necessary.
Deep Learning Algorithm Based on LTSM for Automated Bi-Ventricle Segmentation of CMR Images
Authors: Lin Lu , Jiang Difei , Xiao Yueting , Wang Yining
Published: August 2024

Cardiac Magnetic Resonance(CMR) imaging is an advanced cardiovascular imaging modality to evaluate cardiac structure and function. Therefore, the accuracy of segmentation directly affects the clinical evaluation and diagnosis. In this study, we used Long Short-Term Memory(LSTM) network, proposing a novel deep learning-based model for accurate automated bi-ventricle segmentation of CMR images.
Myocardial changes evaluation based on CMR imaging in patients with obstructive hypertrophic cardiomyopathy after Liwen procedure
Authors: Zheng Minwen , li shuangxin
Published: August 2024

This study evaluated the structural, functional and tissue characteristic changes of myocardium in patients with hypertrophic obstructive cardiomyopathy after treated with the Liwen procedure using cardiac magnetic resonance (CMR) techniques. Compared with pre-operation, one year after treated with Liwen procedure (a new effective procedure), patients’ septal and left ventricular free wall thickness and left ventricular mass (LVM) were significantly reduced. There was no significant change in left ventricular ejection fraction (LVEF) (P>0.05).
Early detection of left ventricular involvement in arrhythmogenic right ventricular cardiomyopathy by Feature Tracking
Authors: Li Xuan , Wu Jiang
Published: August 2024

This retrospective study aimed to detect left ventricular myocardial strain by CMR-FT in ARVC patients. The 25 ARVC patients were divided into 2 subgroups: the preserved LVEF group (LVEF ≥50%, n=15) and the reduced LVEF group (LVEF <50%, n=10). The biventricular global and regional myocardial strain parameters in the radial, circumferential, and longitudinal directions were compared between ARVC and control group. ROC curve analysis showed the left ventricular basal longitudinal strain exhibited good performance in differential diagnosis between the LVEF ≥50% ARVC and the control group. In conclusion, CMR-FT can early detect left ventricular myocardial motion changes in ARVC patients.
Evaluating High-Resolution High-b-value OGSE Time-dependent Diffusion in Human Brain at Ultra-high-gradient 3.0T
Authors: Zhu Ante , Abad Nastaren , Shih Robert , Huang Raymond , Bhushan Chitresh , Sprenger Tim , McNab Jennifer , DeMarco J Kevin , Ho Vincent , Foo Thomas
Published: August 2024

Oscillating gradient spin echo (OGSE) time-dependent diffusion MRI has been shown to improve assessment of intra-cranial disease progression including glioma and multiple sclerosis. In human brain studies, however, high-resolution and high-b-value OGSE diffusion measurements suffer from low signal-to-noise ratio and Rician noise bias. In our preliminary studies with ultra-high-performance gradient 3.0T system, apparent diffusivity coefficient (ADC) of white matter at OGSE 35 Hz showed lower values when ADC was estimated from high b-values ≥1000 s/mm2 with 1.5-mm isotropic resolution, due to Rician noise bias. The effect of Rician noise bias on OGSE ADC measurement was reduced by using real-valued signals.
Estimating brain tissue stiffness from cardiac-induced 7T MRI displacement measurements
Authors: Ingeberg Marius Burman , van Houten Elijah , Zwanenburg Jaco
Published: August 2024

Mechanical properties of the human brain can be altered by a variety of pathologies. These properties can be estimated from in vivo MRI measurements of brain tissue displacements as induced by the heartbeat. Previously obtained 7T MRI displacements measurements were used to reconstruct stiffness parameters using a subzone-based non-linear inversion scheme. Various structures of the brain can be observed in the reconstructed parameter distributions, and the results show good test-retest reliability. The preliminary results show promise of this approach to yield non-invasive assessment of brain tissue microstructure as a tool to investigate brain disease.
Modelling transverse relaxometry using myelin-induced off-resonance fields and magnetisation transfer
Authors: Cottaar Michiel , Jbabdi Saad
Published: August 2024

We present a new Monte Carlo MR simulator, which in addition to simulating the random diffusion of water restricted by any obstacles also simulates (1) the off-resonance field due to myelin and (2) signal loss due to magnetisation transfer. We use this simulator to study the interaction of diffusion, relaxation, and magnetisation transfer. We simulate gradient and spin echo measurements in white matter. The myelin off-resonance field is found to greatly reduce T2* due to dephasing of the signal between compartments, but barely affects T2. Magnetisation transfer at tissue boundaries explains T2 differences between intra-, extra-axonal, and myelin water.
Improving Xenon-129 Lung Ventilation Image Quality with a Commercial Deep-Learning Based Image Reconstruction
Authors: Stewart Neil , de Arcos Jose , Biancardi Alberto , Pilgrim-Morris Jemima , Rodgers Oliver , Munro Ryan , Collier Guilhem , Norquay Graham , Marshall Helen , Brau Anja , Lebel Marc , Wild Jim
Published: August 2024

The utility of a deep learning based reconstruction tool for improving the quality of hyperpolarized 129Xe lung ventilation images was assessed. DL-reconstructed 129Xe ventilation image quality and SNR was improved compared with conventionally reconstructed images. In a cohort of patients with asthma and/or COPD, a small bias towards increased ventilation defect percentage, and a bias towards decreased coefficient of variation, in DL-reconstructed vs. conventionally-reconstructed images, was observed. Initial feasibility of utilising this tool for reduced-cost 129Xe ventilation imaging using natural-abundance xenon, and improved spatial resolution imaging with 129-enriched xenon, is demonstrated.
Q-Dixon and T2 Mapping for assessment of intervertebral disc degeneration in lower back pain
Authors: Feng Futing , Wang Wei , Chen Meining , Liu Lusi , Sun Mixue , Luo Min
Published: August 2024

The diagnostic performance of MR T2w-based Pfirrmann classification decreases in early and severe stages in patients with lower back pain(LBP). The MR mapping technique, including q-Dixon and T2 mapping, allows for visualization and quantification of the discs and vertebrae in patients with LBP. The changes of bone marrow fat (BMF), T2 and T2* values can be seen in different pain levels and Pfirrmann classification, with great potential in quantifying biochemical degeneration of the lumbar spine.
Ultrashort Echo Time, MRI porosity index, and suppression ratio correlate with the cortical bone microstructural and mechanical properties
Authors: Jerban Saeed , Ma Yajun , Alenezi Salem , Moazamian Dina , Athertya Jiyo , Jang Hyungseok , Dorthe Erik , Dlima Darryl , Woods Gina , Chung Christine , Chang Eric , Du Jiang
Published: August 2024

The cortical bone porous microstructure can be evaluated using ultrashort echo time (UTE) MRI. UTE-MRI-based evaluation of bone has been underutilized partly due to the high cost and time demands of MRI in general. The porosity index (PI) and the suppression ratio (SR) are two rapid UTE-based bone evaluation techniques (~ 5 mins scan time each), which can potentially reduce the time demand and cost in future clinical studies. We have investigated the relationship of PI and SR measures with human cortical bone microstructural and mechanical properties. PI and SR showed significant correlations with microstructural and mechanical properties.
A multiscale approach based on the combination of DTI, XRD and histology to study the myeloarchitecture in a rat model of mTBI
Authors: Fratini Michela , Molina Isabel San Martín , Burghammer Manfred , Grünewald Tilman , Salo Raimo , Narvaez Omar , Guidi Maria , Giove Federico , Aggarwal Manisha , Tohka Jussi , Sierra Alejandra , Campi Gaetano
Published: August 2024

We have combined high-resolution structural imaging techniques, such as scanning micro-X-ray diffraction (SμXRD), DTI and histology to study the myeloarchitecture in both healthy and pathological rat brains. For the latter, we focused on an animal model of mild traumatic brain injury (mTBI) that is the most common form of acquired brain injury caused by an external force into the brain. We have performed a quantitative morphometrical analysis of myelin, mapping its relevant morphological and topological parameters (period, orientation, and integrated intensity fluctuation) to assess tissue microstructural damage 35 days after mTBI and sham-operation
Postmortem Imaging with Reusable 3D Printed Ex Vivo Brain Enclosures/Cutting Guide for MRI Registration with Gross Anatomy Photographs at 7T
Authors: Berardinelli Jacob , Kofler Julia , Li Jinghang , Flaugh Owen , Farhat Nadim , Santini Tales , Sajewski Andrea , Schweitzer Noah , Mettenburg Joseph , Ikonomovic Milos , Aizenstein Howard , Ibrahim Tamer
Published: August 2024

The ability to continuously prototype and 3D print new containers as well as using an improved transmit coil has led to major improvements in ex-vivo image quality. This has also allowed for a more automated registration process of the MR images to the gross anatomy
An in-bore PIN diode driver based on a single chip with nanoseconds rise/fall time
Authors: Schildknecht Christoph , Lagore Russell , Waks Matt , Adriany Gregor , Pruessmann Klaas
Published: August 2024

An in-bore PIN diode driver with eight output channels is presented here. The driver is based on a single-chip solution making the implementation simple and of high performance. The rise and fall times of the driver's output are in the single-digit nanosecond range with a peak output current of up to 5.7A per channel. Triggering the driver can be done either with an optical or electrical signal. The driver was tested on the bench and in-bore of a 10.5T MR scanner.
Ultra-thin metasurface pads for spine MRI
Authors: Dubois Marc , Trabelsi Amira , Gomez Tania Vergara , Jomin Pierre , Berrahou Djamel , Bendahan David , Kober Frank , Callot Virginie , Enoch Stefan , Abdeddaim Redha
Published: August 2024

Spine imaging is usually conducted at 3T given the need of high spatial resolution. Unfortunately, the lumbar and thoracic spine regions of interest will lie in areas of weak transmit efficiency. Recent studies showed that high permittivity ceramic blocks can improve image quality. Here we present a new approach based on ultra-thin, lightweight, flexible metasurface pads yielding improved efficiency and homogeneity of the B1+ field along the spine in clinical 3T MRI settings. Our design offers seamless integration to regular equipment leading to more efficient and safer spine imaging protocols.
A Design of 10-100 MHz Broadband NMR Transmission-line Probe
Authors: Yao Shouquan , Xu Juncheng , Song Yiqiao , Shen Ming , Hu Bingwen , Jiang Yu
Published: August 2024

This work demonstrated a broadband NMR probe with a bandwidth of 10-100 MHz. Based on transmission-line structure, broadband transmission was achieved. As for broadband reception, high-speed active T/R switches and low-noise differential amplifiers were used for high-sensitivity RF reception. The SNR of FID signal detected by broadband probe was 74% of that of conventional resonance probe, which means the feasibility of the broadband NMR transmission-line probe was verified.
MRI Simulations for Complex 3D Flow using the Lattice Boltzmann Method
Authors: Adler Ansgar , Scholand Nick , Kollmeier Jost , Wang Yong , Uecker Martin
Published: August 2024

The lattice Boltzmann method (LBM) is a versatile technique to simulate fluid dynamics in complex environments. We extended the LBM to flows with a spin 1/2 degree of freedom in external magnetic fields. We performed 3D simulations for FLASH MRI of a laminar flow in a pipe and the complex flow of the Karman vortex street.
Thermal Model in Feedforward Control of the Gradient Array System in MRI
Authors: Aydın Ege , Babaloo Reza , Atalar Ergin
Published: August 2024

Resistive elements in a gradient system, namely the gradient coil and the amplifier, causes heating and the total system resistance to increase. With feedforward controllers, such changes cause inaccurate gradient fields to occur, which in turn causes image artifacts. To mitigate self-heating caused resistance change issues, modeling the gradient system's thermal behavior is necessary. Such a model introduces additional parameters to the overall feedforward model, and identifying these parameters correctly is essential for accurate current waveforms. For this purpose, we propose a method to extract these parameters along with a more complete thermal model.
A Novel Method to Estimate and Control the Eddy Power Loss within the Cryostat: A Co-Simulation Approach to Tune Z-Gradient Array Coil
Authors: Takrimi Manouchehr , Atalar Ergin
Published: August 2024

We propose a fast computational method based on a series of electromagnetic simulations to calculate a proper set of feeding currents for a z-gradient array coil that dynamically provides the best shield for its primary array coil. The net magnetic field generated by each array element is calculated, and the total average eddy power (energy) loss resulting from fast-switching stray fields inside the cryostat assembly is estimated and controlled. Two design scenarios with comparable performance criteria are offered for a 48-element z-gradient array coil. The accuracy of the estimated eddy power losses is compared with that of commercial software.
Metasurface for passive RF shimming to improve brain imaging at 7T
Authors: Koloskov Vladislav , Shchelokova Alena , Webb Andrew
Published: August 2024

We propose a new passive radiofrequency (RF) shimming approach using a flexible, compact, low-cost, and long-term stability metasurface to improve brain imaging at 7T. The metasurface can be manufactured as a periodic structure based on a set of metal crosses connected by the capacitors, thus having a thickness of less than 1 mm. Numerical studies with the human voxel model showed up to 6% homogeneity improvement at the regions of interest (ROI) in the presence of the metasurface in comparison with the conventional case, which also outperforms the effect of the dielectric pad’s placement.
PINN with Divergence-Free Vector Potential for Velocity Fields Denoising in 4D flow MRI
Authors: Bisbal Javier , Mura Joaquin , Sotelo Julio , Mella Hernán , Arrieta Cristóbal , Irarrazaval Pablo , Uribe Sergio
Published: August 2024

4D flow MRI suffers from different sources of noise and aliasing artifacts. Recent denoising techniques are time-consuming or dependent of parameter estimation. We developed a physics informed neural network with divergence-free vector potential as a non-parametric denoising technique for 4D flow MRI. Results from simulated pulsatile flow and CFD vascular model shows significant noise reduction and aliasing correction. Future work includes comparison with other techniques on different types of data and uncertainty quantification.
Exploiting diffusion MRI data redundancy on a denoising framework - application on MR images (OGSE, μFA protocols) of the Marmoset Brain (in-vivo)
Authors: Campos Vinicius , Santini Tales , Baron Corey , Vieira Marcelo
Published: August 2024

Oscillating gradients spin-echo (OGSE) and microscopic fractional anisotropy (μFA) are diffusion MRI advanced techniques able to provide additional information of the microstructures of the brain1-5, when compared to traditional diffusion MRI. However, high-resolution DWI images present low signal to noise ratio (SNR). In this work, we presented a different framework, named VST_dMRI_BM4D, for denoising dMRI data by exploiting data redundancy and using the variance stabilization transformation (VST) concept7-9. Results show the proposed method is comparable to, and in some cases superior than, MPPCA6, potentially making it a useful tool to be used in the dMRI field.
Accelerating myelin water fraction imaging using compressed sensing and BMC-mcDESPOT
Authors: Alsameen Maryam , Gong Zhaoyuan , Laporte John , Faulkner Mary , Akhonda Mohammad , Bouhrara Mustapha
Published: August 2024

We demonstrated the feasibility of compressed sensing (CS) to accelerate myelin water fraction (MWF) imaging using the BMC-mcDESPOT method. Our results showed that derived MWF maps using CS were similar to those derived without CS. Findings from this study indicate that whole brain, high resolution, MWF map can be derived within a few minutes.
SOC-GRAPPA: An MPSoC based Accelerator for GRAPPA
Authors: Basit Abdul , Inam Omair , Omer Hammad
Published: August 2024

GRAPPA is a cartesian pMRI method widely adopted for high-speed image reconstruction in many clinical applications e.g. real-time cardiac MRI. However, general-purpose computers have limited processing capabilities to address the computational complexity of GRAPPA in real-time MRI. Recently, multi-processor system-on-chip (MPSoC) has emerged as a potential candidate to meet the rising computational demands of GRAPPA for real-time image reconstruction. In this paper, design and implementation details of a novel MPSoC based GRAPPA accelerator i.e. SOC-GRAPPA are presented. The experimental results of 18-coil cardiac dataset show that the proposed accelerator is capable of reconstructing 30 frames/second in real-time cardiac MRI.
Accelerated Four-Dimensional Rosette J-resolved Spectroscopic Imaging (4D ROSE-JRESI) with semi-LASER Localization: A pilot study
Authors: Joy Ajin , Emir Uzay , Macey Paul M. , Thomas M. Albert
Published: August 2024

Undersampling spatial and spectral dimensions is essential to achieve clinically feasible scan times in multi-dimensional spectroscopic imaging. Sampling pattern of rosette trajectory has higher incoherence than that of the other non-Cartesian trajectories like spiral and radial, and can achieve higher compressed-sensing reconstruction performance. While rosette spectroscopic imaging has been attempted for 2D (2 spatial+1 spectral) and 3D (3 spatial+1 spectral) spectroscopic imaging, it has thus far not been shown for J-resolved spectroscopic imaging. In this pilot study, we implemented a rosette echo-planar J-resolved spectroscopic imaging (ROSE-JRESI) sequence and studied the feasibility of high acceleration factors for clinically feasible runtimes.
129Xe MRS Gas-Exchange Abnormalities in Poorly-controlled Asthma
Authors: Matheson Alexander , McIntosh Marrissa , Paul Narinder , Bhalla Anurag , Yamashita Cory , Parraga Grace
Published: August 2024

Large and small airway-wall and lumen abnormalities and occlusion are hallmark findings in asthma, but pathologic abnormalities have also been reported in the pulmonary vasculature. 129Xe MR-spectroscopy provides a way to quantify 129Xe gas in the airways and as it diffuses through the alveolar tissue-membrane and binds to red-blood-cells in the pulmonary capillaries. Static and dynamic 129Xe MR-spectroscopy were undertaken in participants with poorly controlled asthma in whom there was significantly different 129Xe MR RBC:membrane ratio compared to healthy-volunteers. Cardiopulmonary oscillations were observed in all 129Xe compartments; the oscillation amplitude in the gas-compartment was related to oscillometry airways impedance measurements.
Local correlation of echo-time dependent observed lung T1 and quantitative perfusion in patients with chronic obstructive pulmonary disease
Authors: Triphan Simon , Konietzke Marilisa , Biederer Jürgen , Kauczor Hans-Ulrich , Heußel Claus , Wielpütz Mark
Published: August 2024

Observed TE-dependent T1 has been shown to correlate with MRI perfusion scores. Here, 22 patients with COPD were examined using DCE MRI and 2D UTE. Perfusion and T1(TE) was quantified based on these, respectively. Correlations of T1(TE) with perfusion measures were examined, with the strongest inter-patient correlation at TE2=500μs but stronger local correlations at TE1=70μs and TE3=1200μs than at TE2. The average T1 in defect areas according to DCE was shorter than in normal areas, with the smallest difference at TE2. This implies that the local TE-dependence in defect voxels is further away from previously published behaviour in healthy volunteers.
Comparison of ventilation defects quantified by Technegas V-SPECT and hyperpolarized 129Xe MRI
Authors: Radadia Nisarg , Friedlander Yonni , Konyer Norman , Jamal Mobin , Huang Chynna , Farncombe Troy , Marriott Christopher , Finley Christian , Agzarian John , Dolovich Myrna , Noseworthy Michael , Nair Parameswaran , Shargall Yaron , Svenningsen Sarah
Published: August 2024

Previous studies have demonstrated the comparability of ventilation assessed by SPECT and hyperpolarized gas MRI methods; however, these comparisons were qualitative and limited to visual scoring methods based on radiologist reporting. Thus, we quantified the relationship between ventilation-defect-percent (VDP) assessed from same-day Technegas ventilation-SPECT and hyperpolarized 129Xe MRI, in patients with early-stage lung cancer. We observed that ventilation defects quantified by Technegas V-SPECT and 129Xe MRI VDP were correlated and increased in patients with COPD. A bias towards higher Technegas V-SPECT VDP was detected and may be explained by differences in contrast agent properties, image acquisition conditions, and/or quantification pipelines.
Differences in Myocardial Strain at End-Inspiration versus End-Expiration with Remote Exposure to Secondhand Tobacco Smoke
Authors: Dong Huiming , Zhou Ang , Au Natalie , Arjomandi Mehrdad , Mitsouras Dimitrios
Published: August 2024

Prolonged exposure to secondhand tobacco smoke (SHS) is associated with abnormal pulmonary function and cardiovascular response. In this study, we examined cardiac function in SHS-exposed participants using cardiac MR (CMR) and displacement encoding with stimulated echoes (DENSE) to determine whether the cardiac function is affected by air trapping-a hallmark of heavy past SHS exposure. We found that SHS-exposed participants had lower myocardial radial strain than unexposed participants at both end-inspiration and end-expiration imaging. Neither stroke volume nor cardiac output exhibited the decrease seen in unexposed participants at end-inspiration, but radial strain was significantly lower compared to end-expiration in SHS-exposed participants.
Performance of compressed-sensing cardiac MR in evaluating left ventricular function: a systematic review and meta-analysis
Authors: Wang Zhaozhao , Yang Anqi , Zhou Zien , Wang Chi , An Jing , He Yi
Published: August 2024

SSFP-cine CMR imaging has been recommended to evaluate LV function and structure. However, a long scan time limited its widely application. A novel fast CS-cine CMR imaging might be an option, but its accuracy is inconclusive. Therefore, we conducted a systematic review and meta-analysis for it. We included 23 observational studies for pooling. There was no difference in LVEF, LVEDV, LVESV and LVmass, along with no heterogeneity across different subgroups by MR field intensity, breath-holding, children, and arrhythmia (all P for inter-subgroup heterogeneity <0.05). The quality of CS-cine images was acceptable and was superior to SSFP-cine images in arrhythmia patients.
Feasibility of Strain Encoded (SENC) MRI to Assess Cardiac Contractility on a Commercial 0.55T System
Authors: LIU YINGMIN , Tani Donel , Joseph Matthew , Osman Nael , Khan Mahmood , Varghese Juliet , Simonetti Orlando
Published: August 2024

In phantom, human volunteers, and an animal model, this study shows the feasibility of strain encoding (SENC) on a commercially available 0.55T low field scanner with limited gradient performance. Measured through-slice strain in a deformation phantom agrees with steady-state free precession (SSFP) cine; global strains in healthy humans fall into the normal expected range; infarcted myocardial segments in a porcine model demonstrated reduced strain.
Heart Failure with Normal Natriuretic Peptide Levels and Preserved Ejection Fraction: A Prospective Clinical and CMR study
Authors: He Jian , Yang Wenjing , Chow Kelvin , An Jing , Lu Minjie
Published: August 2024

The predisposed HFpEF has relatively unique clinical and CMR features, which indicates it may be an important subtype or precursor of HFpEF. However, the specific clinical significance of these features requires further prognostic studies.
Fractal Analysis: Left Ventricular Trabecular Complexity Cardiac MRI Adds Independent Risks for HFpEF in Participants with ESRD
Authors: Zhang Tian-yi , Wu Peng , Wu Lian-Ming , Mou Shan
Published: August 2024

The aim of this study was to measure left ventricular (LV) trabecular complexity by fractal dimension (FD) in patients with end-stage renal disease (ESRD), and assess whether FD is an independent risk predictor for heart failure with preserved ejection fraction (HFpEF) in this population. We found that LV mean basal FD was an independent predictor for HFpEF in the multivariate analysis. Adding LV mean basal FD to the baseline model resulted in a higher C-index and significant NRI, indicating better discriminatory ability to HFpEF en ESRD patients.
Spatially resolved assessment of 31P metabolite levels in liver metastases with 31P MRSI at 7T
Authors: van den Wildenberg Lieke , Runderkamp Bobby , Seelen Leonard , van Laarhoven Hanneke , Gosselink Mark , van der Kemp Wybe , Mohammad Nadia Haj , Klomp Dennis , Prompers Jeanine
Published: August 2024

Methods for early treatment response evaluation to systemic therapy of liver metastases are lacking. Tumor tissue is characterized by an increased PME/PDE ratio. However, with commonly used 31P surface coils for liver 31P MRS, the liver is not fully covered. Using an integrated 31P whole-body transmit coil in combination with a 16-channel body receive array at 7T, we were able to spatially map 31P metabolite levels throughout the whole liver in a patient with liver metastases. We found highly elevated levels of both PE/ATP and PC/ATP in liver metastases in comparison with healthy liver tissue.
Combining Extreme Narrowing and Slow Motion Regime in a Simple Motional Model for Sodium NMR Environment.
Authors: Reichert Simon , Schepkin Victor , Kleimaier Dennis , Schad Lothar
Published: August 2024

This study investigates a model of ion motion that is compatible with 23Na T1­ and T2 mechanism of relaxation and even works with quasi mono-exponential T1. We compare this model with the commonly used Debye model using agar as a tissue model system at 9.4T and 21.1T.
Deep learning-based image quality and spatial resolution improvement in Turbo Spin Echo Diffusion Weighted Imaging for prostate
Authors: Kwon Jihun , Yuda Kohei , Yoneyama Masami , Katsumata Yasutomo , Cauteren Marc
Published: August 2024

Diffusion-weighted imaging (DWI) plays an important role in assessing the significance of prostate cancer. DWI with Turbo Spin Echo readout (TSE-DWI) is robust to image distortion but suffers from low signal to noise ratio. In this study, we investigated the use of prototype AI-based reconstruction technique (SmartSpeed Precise Image) to improve the image quality of TSE-DWI images. The image quality was compared between conventional Compressed-SENSE (C-SENSE), SmartSpeed AI, and SmartSpeed Precise Image. Volunteer data demonstrated a significant improvement of sharpness in both b=0 and 1000 s/mm2 images as well as ADC map, compared with C-SENSE and SmartSpeed AI reconstructions.
Deep learning-based high-resolution T2-weighted imaging elevated clarity of prostatic calcification and diagnostic efficacy
Authors: Ke Zan , Li Liang , Wen Zhi , Liu Weiyin , Zha Yunfei
Published: August 2024

Prostatic calcification is common in benign prostatic hyperplasia (BPH) and usually asymptomatic. Our study showed the prostate T2WIDL images have higher subjective rating scores, clearer lesion contrast and improved detection rate of prostatic calcification, higher SNR and CNR. In addition, T2WIDL more clearly and sharply displayed prostate capsule, lesion contrast, prostate calcification and anatomical details Therefore, AIR™ Recon DL based T2WI (T2WIDL) quality in prostate MRI offer higher overall image quality and elevated a younger radiologist’s diagnostic performance on prostate calcification.
Can machine learning resolve model degeneracy in tissue microstructure estimation?
Authors: Guerreri Michele , Epstein Sean , Azadbakht Hojjat , Zhang Hui
Published: August 2024

This work investigates the impact of model degeneracy on machine learning-based tissue microstructure estimation. While there have been several empirical reports suggesting machine learning can not resolve model degeneracy, the impact of model degeneracy is poorly understood. Here we show how model degeneracy can be categorised into three types with varying degrees of impact on machine learning-based microstructure estimation. Our finding is important for designing optimal training data distribution.
Improving Across-Dataset Schizophrenia Classification with Structural Brain MRI Using Multi-scale Transformer
Authors: Tian Ye , Zhang Junhao , Rao Vish , Guo Jia
Published: August 2024

Schizophrenia is a neurological disorder that requires accurate and rapid detection for earlier intervention. Previous explorations in artificial intelligence showed overwhelming performance using deep learning in schizophrenia classification, though the generalization remained a challenge. We propose our 3D Multi-scale Transformer (MST) using T1W structural MRI data to detect schizophrenia. By synthesizing reconstructed images at different scales, the transformer-based architecture improves robustness to generalize in unseen data. The proposed method reaches the same-level performance of AUROC to the benchmark mark model in schizophrenia identification, and performs better in all leave-one-site-out generality tests.
Microstructural Alterations in Schizophrenia evaluated by Multidimensional Diffusion MRI and Inhomogeneous Magnetization Transfer Imaging
Authors: Tha Khin , Kitagawa Maho , Lasic Samo , Bryskhe Karin , Kwon Jihun , Versluis Marteen , Hashimoto Naoki
Published: August 2024

This prospective study aimed to identify the role of multidimensional diffusion (MDD) MRI and inhomogeneous magnetization transfer (ihMT) imaging, the former reported as capable of quantifying various microstructural diffusion properties and differentiating tissue-specific subparts and the latter as selective to changes in myelin, in underpinning the microstructural brain changes in schizophrenia. Alterations in MDD MRI indices were observed, associated with negative symptoms of schizophrenia. Altered size and shape of cells other than myelin (probably glia or neurons) are thought as coined in the pathophysiological mechanisms.
Deep learning-based Lorentzian fitting of WASSR Z-spectra
Authors: Ali Sajad Mohammed , Yadav Nirbhay , Wirestam Ronnie , Singh Munendra , Heo Hye-Young , van Zijl Peter , Knutsson Linda
Published: August 2024

Water saturation shift referencing (WASSR) Z-spectra can be used to correct shifts due to B0-field inhomogeneities, for magnetic susceptibility mapping and analysis of relaxation effects. The spectra follow a Lorentzian shape with discrete values. Hence, a Lorentzian fit to retrieve the shape parameters (amplitude A, line width LW and frequency shift ΔfH2O ) simplifies analysis. Conventionally, the least-squares (LS) method is used for such fitting despite being time consuming and sensitive to the unavoidable noise in vivo. We propose a deep learning-based Lorentzian-fitting neural network (LoFNet) that demonstrated improved robustness against noise and sampling density in combination with reduced time consumption.
Deep Image Prior with Structured Sparsity (DISCUS) for Dynamic MRI Reconstruction
Authors: Sultan Muhammad Ahmad , Chen Chong , Han Yuchi , Ahmad Rizwan
Published: August 2024

We propose an unsupervised learning method for dynamic MRI reconstruction. Our method, Deep Image prior with StruCtUred Sparsity (DISCUS), is an extension of Deep Image Prior (DIP) and employs joint optimization of network parameters and latent code vectors to recover image series. We enforce group sparsity on code vectors to reveal the underlying low-dimensional manifold of the image series. Using two sets of in vivo measurements and digital phantom simulation, we show that our approach significantly improves the reconstruction quality in terms of Normalized Mean Square Error (NMSE) and Structure Similarity Index Measure (SSIM) compared to compressed sensing and DIP.
MONAI Recon: An Open Source Tool for Deep Learning Based Accelerated MRI Reconstruction
Authors: Darestani Mohammad Zalbagi , Nath Vishwesh , Li Wenqi , He Yufan , Roth Holger , Xu Ziyue , Xu Daguang , Heckel Reinhard , Zhao Can
Published: August 2024

Deep learning models outperform traditional methods in terms of quality and speed for numerous medical imaging applications. A critical application is the acceleration of magnetic resonance imaging (MRI) reconstruction, where a deep learning model reconstructs a high-quality MR image from a set of undersampled measurements. For this application, we present the MONAI Recon Module to facilitate fast prototyping of deep-learning-based models for MRI reconstruction. Our free and open-source software is pre-equipped with a baseline and a state-of-the-art deep-learning-based reconstruction model and contains the necessary tools to develop new models. The developed open-source software covers the entire MRI reconstruction pipeline.
Radial Magnetic Resonance Fingerprinting for quantification of T1 in metastatic breast tumor.
Authors: Dhakan Chetan B. , De La Cerda Jorge , Schuler William , MacAskill Christina J. , Flask Chris A. , Pagel Mark D , Martinez Gary V.
Published: August 2024

Quantitative Magnetic Resonance Imaging (MRI) involves pixel-wise mapping of longitudinal relaxation time T1, transverse relaxation time T2 and proton density M0 and other relevant parameters at each location in the tissue to be characterized. The goal of this study is to investigate potential benefits of Magnetic Resonance Fingerprinting in quantifying T1 relaxation times in metastatic breast tumor using radial acquisition in tumor with high temporal and spatial resolution.
Ultra-fast Radial MRI with Silent Oscillating Gradients
Authors: Ilbey Serhat , Littin Sebastian , Jia Feng , Wehkamp Niklas , Amrein Philipp , Zaitsev Maxim , Bock Michael , Özen Ali Caglar
Published: August 2024

The sampling efficiency of radial center-out MRI was increased by using additional oscillating readout gradients, which lead to an accelerated image acquisition. The idea of radial sampling along an oscillating spoke was demonstrated using a clinical MRI system with ultra-fast UTE MRI.
Single-shot 2D Radial Echo Planar Imaging using a KWIC Filter and Model-based Reconstruction Approach
Authors: Rettenmeier Christoph , Yu Zidan , Stenger V. Andrew
Published: August 2024

High quality brain images at spatial resolutions of 2x2x3 mm3 and 3.3x3.3x3 mm3 were obtained using single-shot 2D rEPI. The approach is based on an R2*, B0 and coil sensitivity informed model-based reconstruction in combination with k-space weighted image contrast (KWIC) filtering. Signal loss due to phase inconsistencies are starkly reduced by the linear phase model and R2* contrast was modifiable by adjusting the target echo time in the model of the reconstruction and KWIC filter. Bold activation maps were generated from fMRI datasets at 2x2 mm2 resolution showing activation in the visual cortex.
A Convergence Analysis for Projected Fast Iterative Soft-thresholding Algorithm under Radial Sampling MRI
Authors: Qu Biao , Zhang Zuwen , Chen Yewei , Qian Chen , Kang Taishan , Lin Jianzhong , Chen Lihua , Wu Zhigang , Wang Jiazheng , Zheng Gaofeng , Qu Xiaobo
Published: August 2024

Radial sampling is a fast magnetic resonance imaging technique. The projected fast iterative soft-thresholding algorithm (pFISTA) has shown the advantage to solved tight frame sparse reconstruction model for removing undersampling image artifacts. However, the convergence of this algorithm under radial sampling has not been clearly set up. In this work, the authors derived a theoretical convergence condition for this algorithm and an optimal step size was further suggested to allow the fastest convergence. Verifications were made in vivo data of static brain imaging and dynamic contrast-enhanced (DCE) liver imaging, demonstrating that the recommended parameter allowed fast convergence in radial MRI.
Fast Deep Learning Reconstruction of Interventional MRI Data with Radial, Undersampling k-Space Trajectories
Authors: Topalis Johanna , Schachtner Balthasar , Mittermeier Andreas , Wesp Philipp , Weber Tobias , Stüber Anna Theresa , Seidensticker Max , Ricke Jens , Parodi Katia , Ingrisch Michael , Dietrich Olaf
Published: August 2024

To reduce the data acquisition time and increase frame rates for image guidance during percutaneous needle interventions in the liver, k-space data can be acquired with a radial, undersampling acquisition scheme. The purpose of this work was to optimize a deep learning model for the fast reconstruction of k-space data in this context. The proposed deep learning model reconstructed artificial data with a better image quality compared to conventional reconstruction. Successful reconstruction of interventional phantom data suggests its potential for application during percutaneous needle interventions in the liver.
Pipeline for Robust Functional Lung Imaging with Oxygen-Enhanced MRI (OE-MRI) and Independent Component Analysis (ICA)
Authors: Needleman Sarah , Kim Mina , McClelland Jamie , Parker Geoff
Published: August 2024

Analysis of dynamic lung oxygen-enhanced MRI (OE-MRI) is challenging due to the presence of substantial artefacts and poor SNR. Understanding and minimising sources of error is critical for reliable use of the method. We have created a pipeline using independent component analysis (ICA) for the automatic extraction of functional lung information from dynamic lung OE-MRI, for which confounding factors are reduced. The pipeline demonstrated good repeatability when utilised for the analysis of a scan-rescan dynamic lung OE-MRI study at 3.0 T; the algorithmic uncertainty of ICA on the analysis pipeline was found to be minimal.