bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of tomoelastography for the differentiation between solid pseudopapillary neoplasms and pancreatic neuroendocrine neoplasms
Authors: Yuan Jiaxin , Shi Siya , Wang Liqin , Hu Xuefang , Yu Jinhui , Wen Tingting , Feng Shiting , Peng Zhenpeng , Luo Yanji
Published: August 2024

This prospective study enrolled patients with pathologically confirmed solid pseudopapillary tumors (SPNs) and pancreatic neuroendocrine tumors (pNENs) who underwent preoperative tomoelastography examinations at our hospital. Sixty-four patients were included (18 patients with SPNs; 46 patients with pNENs). SPNs showed significantly lower stiffness (P<0.001) and fluidity (P=0.001) than pNENs. Both stiffness and fluidity allowed distinguishing SPNs from pNENs. AUCs were 0.899 for stiffness, 0.760 for fluidity. Tomoelastography is a novel multi-frequency MRE technique that can facilitate the differentiation between SPNs and pNENs.
The value of amide proton weighted imaging in predicting perineural invasion of prostate cancer
Authors: Li Xiwei , Chen Lihua , Wang Nan , Wang Jiazheng , Liu Ailian
Published: August 2024

Perinerval infiltration (PNI) is closely related to the degree of radical operation and postoperative recurrence. Pathological examination is the gold standard for PNI diagnosis, but it is an invasive examination. The APTw imaging can be used for disease diagnosis and therapeutic evaluation by detecting the content of protein and polypeptide in tissues and cells. In this study, APTw was used to evaluate the PNI in prostate cancer. The results showed that the APT values of PNI (+) group was higher than other one group. Therefore, APTw is of great value in differentiation of perinerval invasion from prostate cancer.
Preliminary Study of CMR to Evaluate Structural and Functional Alterations of the Left Ventricle in Patients with Parkinson's Disease
Authors: Yue Xun , Peng Pengfei , Sun Jiayu
Published: August 2024

Parkinson's disease (PD) is the second most frequent neurodegenerative disease. Likewise, heart failure (HF) is one of the most common causes of mortality and morbidity in the world. The prevalence of HF has been found to be twice among PD patients compared with overall population regardless any other heart diseases and cardiovascular disease risk factors. Cardiac MRI is the clinically recognised gold standard for the assessment of ventricular functional parameters and myocardial histology. We have designed a study to assess the cardiac function and structure in patients with PD compared with a control group by means of cardiac magnetic resonance.
Utility of single breath-hold compressed sensing cine imaging in optimizing clinical cardiac magnetic resonance scanning procedure
Authors: Wang Fuyan , Pu Cailing , Hu Hongjie
Published: August 2024

The main goal of this study is to evaluate the practicability of a single breath-hold whole-heart coverage compressed sensing cine sequence in daily CMR examination, moreover, to optimize the scanning procedure for patients with different kinds of cardiac dysfunction. For patients, especially those are diagnosed with chronic heart failure, the single breath-hold CS cine can substantially shorten scanning time and provide reliable cardiac function parameters comparing with routine bSSFP cine. This single breath-hold CS cine sequences is recommended to be used before contrast injection because of gadolinium agent induced reduction of end-systolic/diastolic volume and image contrast.
A priliminary evaluation of myocardialgadolinium deposition in apical hypertrophic cardiomyopathy with T1mapping
Authors: Yang Hongzhi , wang shaoyu , Yang Ruwu
Published: August 2024

In this study, we used the CMR T1mapping technique was to evaluate the correlation between T1R and gadolinium deposition in the myocardium of patients with apical hypertrophic cardiomyopathy after gadolinium enhancement.
Optimization method for estimating tissue microstructure size-distributions with diffusion weighted imaging
Authors: Jimenez Pablo , Zwick Analia , Alvarez Gonzalo
Published: August 2024

Characterization of microstructures in living-tissues by non-invasive imaging is one of the key and outstanding challenges for diagnosing early stages of pathologies and understanding disease mechanisms. Here we implement an optimal control strategy for obtaining microstructure details by Diffusion-Weighted Imaging sequences. We estimate microstructure parameters of size-distribution models for axon bundles, attaining the ultimate precision limits predicted by quantum-information tools. We performed proof-of-principle experiments of the optimization protocol with an ex-vivo mouse-brain contrasted with simulations. These results might drastically reduce the total acquisition time compared to the present state-of-the-art, opening alternative avenues towards unraveling diagnostic information by quantitative MRI.
Inter-subject variability in fiber orientation density function increases with aging
Authors: Moss Hunter , Benitez Andreana , Jensen Jens
Published: August 2024

The fiber orientation density function (fODF) estimated from diffusion MRI is typically used as an input for fiber tractography or microstructural modeling. However, since it encodes the fine details of the intra-voxel distribution of axon orientations, it can also be regarded as a quantity of physical interest that is potentially sensitive to subtle white matter changes. Here we demonstrate a method for quantifying inter-subject fODF differences in individual voxels within a white matter skeleton for a cohort of healthy older adults. We find that inter-subject fODF variability increases with age suggesting that diverse processes affect axons in healthy aging.
The Value of Neurite Orientation Dispersion and Density MR Imaging in Diagnosing Temporal Lobe Epilepsy with Hippocampal Sclerosis
Authors: Zhang Xiaonan , Zhao Guohua , Zhang Huiting , Gao Eryuan , Cheng Jingliang
Published: August 2024

The hippocampal microstructural alterations by using routine magnetic resonance imaging presents a challenge. This study aimed to evaluate the performance of the NODDI models in temporal lobe epilepsy (TLE) patients with hippocampal sclerosis (HS) by comparison with the routine Flair sequence. Our results found that all NODDI parameters had significant differences between ipsilateral HS and contralateral HS/HC, and had better diagnostic performance than Flair sequence. In addition, combined NODDI model had significant better diagnostic performance than all the single parameters. In conclusion, NODDI is superior to Flair image in diagnosing TLE with HS.
Direct detection of polarization transfer from hyperpolarized 129Xe to thermally polarized 1H at 2 mT
Authors: Kelley Michele , Bryden Nicholas , Atalla Sebastian , Branca Rosa
Published: August 2024

We present a simple protocol for polarizing 1H at ultra-low field. By simply bubbling hyperpolarized Xe gas in a solution containing thermally polarized 1H spins, the proton thermal polarization can be enhanced by more than 100-fold. This enhancement is clearly observed, even in absence of saturation pulses, at ultra-low field where thermal polarization is close to background noise levels. Simultaneous detection of 1H and 129Xe magnetizations shows that the transfer of polarization from 129Xe to 1H spins is a continuous process that lasts until the dissolved-phase 129Xe polarization is relaxed back to thermal equilibrium.
Efficient Fetal Brain Segmentation according to the Point Spread Function of MRI
Authors: Xu Yunzhi , Li Jiaxin , Feng Xue , Qing Kun , Wu Dan , Zhao Li
Published: August 2024

High apparent resolution of fetal MRIs is provided by slice-to-volume reconstruction pipelines widely. However, the physical resolution of the fetal brain is lower than that. Therefore, we hypothesize that fetal brain segmentation can be performed based on downsampled fetal brain MRI according to its point spread function. In this work, 150 adult brain and 80 fetal brain MRIs were used to validate hypothesize. Using downsampled fetal data with factor of 4, a highly efficient segmentation model achieved similar segmentation accuracies compared to original data, which demonstrated that segmentation models can be developed based on PSF.
Improved Robustness for Deep Learning-based Segmentation of Perfusion CMR Using Data Adaptive Uncertainty-guided Spatiotemporal Analysis
Authors: Yalcinkaya Dilek Mirgun , Youssef Khalid , Heydari Bobak , Raman Subha , Dharmakumar Rohan , Sharif Behzad
Published: August 2024

We proposed and validated Data Adaptive Uncertainty-Guided Spatiotemporal (DAUGS) analysis that leverages the data-driven uncertainty map of the segmentation contours among a pool of trained deep neural networks (DNNs) and automatically selects the segmentation result with the highest level of certainty. Our results suggest that proposed DAUGS and standard DNN-based analysis demonstrated on-par performance on the internal test set which is from the same institution as training set and acquired with FLASH sequence. In contrast, DAUGS analysis considerably outperformed DNN-based analysis on the external test set which was acquired with a bSSFP pulse sequence at a different institution, demonstrating the improved robustness of the proposed method despite limited training data.
MRI One-stop-shop for Diagnosis of Shoulder Disease
Authors: Wang Jienan , Chen ShuQing , Ma LiFei , Zhang Rui , Wu XiaoMeng
Published: August 2024

In this study, shoulder imaging was achieved by MRI one-stop imaging, which contained different sequences. After the post-processing, a variety of fusion images could be formed to comprehensively evaluate the soft tissue, nerve, cartilage and bone of the shoulder, and then gave us a comprehensive view of the shoulder.
Investigation of the fat-bone-muscle connection in osteoporosis and osteoarthritis by 1H MRS
Authors: Maiuro Alessandra , Mattioli Daniele , Manenti Guglielmo , Gasbarra Elena , Tarantino Umberto , Capuani Silvia
Published: August 2024

The metabolic pathways involved in the development of osteoporosis and osteoarthritis, was investigated by SVS1H MRS. Metabolites and fatty acids of the bone marrow and the adjacent muscle of healthy, osteoporotic and osteoarthritic woman were quantified using LCModel. The increase of E23 resonance in muscles is a potential marker of sarcopenia correlated to osteoporosis. The decrease of the L53 resonance in bone marrow highlights the presence of osteoporosis (together with total lipids increase) or osteoarthritis (together with bone marrow water increase).
The MR-Bioreactor : Micro-MRI of thick living tissues to characterize 4-days old ex-ovo chick embryo morphology.
Authors: Gnanago Jean-Lynce , Calvet Sophie , Gerges Tony , Gilmus Valernst , Sousa Camila Pereira , Cabrera Michel , Falk Julien , Lambert Simon
Published: August 2024

Thanks to their accessibility for experimental manipulations, their availability and their low cost, chick embryos have been used as animal models for developmental biology for long. In these applications, non-invasive 3D imaging of the embryos is needed to monitor the embryos development. Morphological characterization of ex-ovo chick embryo generally require tissue fixing which can alter MR characterizations. In this work, we use our MR-Bioreactor to perform a high resolution morphological characterization of a chick embryo maintained in living conditions.
Simultaneous Saturation and Excitation (SatEx) pulse
Authors: Hodono Shota , Wu Chia-yin , Dixon Carl , Maillet Donald , Jin Jin , Polimeni Jonathan , Cloos Martijn
Published: August 2024

We propose a new slice-selective excitation pulse that simultaneously saturates magnetization adjacent to it. The Saturation and Excitation (SatEx) pulse is a summation of two asymmetric sinc pulses whose leading lobes have been cut combined with an asymmetric excitation pulse with its final lobes truncated. The saturation and excitation slice profile were validated in simulations and a flow-phantom scan. The flow-phantom scan showed strong saturation of inflow effects. Since the SatEx pulse is as short as a conventional sinc excitation pulse, it can be implemented in a wide range of fast imaging sequences to suppress inflow effects without lengthening TR.
Denoising Effect of Double-Loop Spiral Coil with ultra-High Dielectric Constant Materials for MRI Applications
Authors: poshtgol Parisa Lotfi , Gandji Navid P. , Lanagan Michael , Soon Soo-Han , Chen Wei , Yang Qing X
Published: August 2024

We investigated the denoising effect of employing double-loop spiral coil (DLSC) versus the conventional single loop surface coil in the presence of ultrahigh dielectric constant materials (uHDCM). The DLSC confines the conservative E-field distribution between the loops which as a result reduces the E-field in the sample, therefore reduces the noise level. Reduction of conservative E-Field makes the non-conservative E-field more dominant in the sample, which synergistically with the noise reduction allows increasing transmit efficiency and receive sensitivity for MRI application.
Reproducibility and variability of tailored and universal nonselective excitation pulses at 7T for human body imaging: Re-scans after one year
Authors: Aigner Christoph , Bassenge Jean Pierre , Dietrich Sebastian , Lutz Max , Krüger Felix , Schmitter Sebastian
Published: August 2024

3D ultrahigh field (UHF) imaging of the body, particularly the heart, is highly challenging due to the inhomogeneous transmit field (B1+) leading to spatially varying flip-angle (FA) patterns. This study demonstrates that pre-computed universal pulses (UPs) allow for calibration-free 3D cardiac FA homogenization at 7T, despite inter-subject variations because of sex, age, BMI, and coil-placement differences. Furthermore, the performance is robust across multiple MRI operators or re-scans after one year. UPs are, therefore, suited to significantly simplify UHF cardiac imaging by removing the need for lengthy calibration prescans.
Impact of a High-Permittivity Helmet on Transmit Efficiency Across a Wide Range of Field Strengths and Relative Permittivities
Authors: Carluccio Giuseppe , Collins Christopher
Published: August 2024

High-Permittivity Materials are used in MRI to manipulate the B1 field distribution for example to provide a stronger transmit efficiency. For a given coil, the transmit efficiency depends on the frequency. Here we examine the effects of a high-permittivity helmet on the transmit efficiency in exciting the brain with a birdcage coil over a range of frequencies. The optimal frequency providing the maximum transmit efficiency is not significantly impacted by the presence of the helmet, while the maximum efficiency can increase by about 100% compared to when no helmet is used.
Multi-Continent Analysis of Geometric Distortion in Low-Field MRI
Authors: Ogier Stephen , Sorby-Adams Annabel , Jordanova Kalina , Dienstfrey Andrew , Gimbutas Zydrunas , Guo Jennifer , Kirsch John , Schiff Steven , Mulondo Ronald , Obungoloch Johnes , Poorman Megan , Pitts John , Kimberly W. Taylor , Keenan Kathryn
Published: August 2024

The assessment of brain morphology requires geometric accuracy, and the monitoring of pathologies like dementia requires geometric stability over time and between systems. We aim to assess the geometric accuracy and stability of a head-only 64 mT system by imaging the cylindrical phantom provided by the manufacturer, positioned with a 3D-printed holder for stability, and analyzing the geometric fidelity of the images produced by a variety of product sequences. The initial assessment examines the perimeter of the phantom and how it varies along the S-I direction.
Calibration of R2' relaxation rate and hepatic iron concentration by Monte Carlo simulations
Authors: Li Xiaoben , Ma Mengyuan , Wang Jinyang , Cheng Junying , Yao Wenjun , Wang Changqing
Published: August 2024

The R2' relaxation rate is expected to become a more specific biomarker in hepatic iron overload because it is not affected by pathological factors. However, calibrating the relationship between R2' relaxation rate and hepatic iron concentration (HIC) at different field strengths is time-consuming. In this work, we develop Monte Carlo simulations to investigate relationship between R2' relaxation rate and HIC in hepatic iron overload at both 1.5T and 3.0T. Results show strong linear relationships between R2' predictions and HIC. The Monte Carlo simulations may greatly shorten the clinical calibration time of MRI relaxation rates and HIC.
Estimate the Linear Effect of Inter-Scanner Variability: Insight from Paired Cross-Scanner T1-weighted Images
Authors: Chen Chang-Le , Torbati Mahbaneh Eshaghzadeh , Luo Weiquan , Minhas Davneet , Laymon Charles , Hwang Seong Jae , Crainiceanu Ciprian , Maillard Pauline , Fletcher Evan , DeCarli Charles , Aizenstein Howard , Tudorascu Dana
Published: August 2024

To broaden our knowledge of inter-scanner variability, we established a pipeline to linearly estimate the site effect by incorporating ComBat modeling and superpixel parcellation. We found that the variation prominently manifested in tissue contrast, noise level, and field inhomogeneity with respect to cross-site data. We further used the estimated parameters to harmonize images. The image quality and structural similarity of cross-scanner data can be improved after the harmonization procedure, and the variation in volumetric measures can also be reduced. This study provides further insight for the research focusing on the development of image harmonization methods.
The effect of AIF and tissue time-course temporal alignment on pharmacokinetic model trans-cytolemmal water exchange sensitivity
Authors: Li Xin , Huang Wei , Rooney William , Springer Charles
Published: August 2024

Using DCE modeling to quantify prostate transcytolemmal water exchange effect faces the challenges of often insufficient interstitial contrast agent concentration as well as suboptimal temporal resolution. Using ultra-high temporal resolution prostate DCE data, the goal of this work is to investigate the impact of DCE-MRI temporal alignment between the arterial input function (AIF) and the tissue time-courses on water exchange quantification. Results here show that when perfect alignment is not achievable in practice, an earlier AIF bolus arrival bias will generally reduce the capability for water-exchange quantification using DCE-MRI.
Time-Resolved MRI Kinesiology: Reconstructing force and velocity during active loading
Authors: van Riel Max , van den Berg Cornelis , Sbrizzi Alessandro
Published: August 2024

Force and velocity are two important quantities for studying muscles, but retrieving these quantities using MRI is challenging. Spectro-Dynamic MRI allows the characterization of dynamical systems at a high spatial and temporal resolution directly from k-space data. Using an iterative reconstruction algorithm, we can reconstruct time-resolved MR images, time-resolved motion fields, mechanical parameters, and an activation force, at a temporal resolution of 11 ms. As a proof-of-principle, MR data was acquired with a motion phantom moving like an actively driven linear elastic system. All dynamic variables could be reconstructed accurately. This method could become useful for studying muscles under dynamic loads.
Accelerated 3D Multi-Echo Spin-Echo sequence for T2 mapping of mouse brain metastases using a subspace-based reconstruction
Authors: TROTIER Aurélien , Corbin Nadège , Miraux Sylvain , Ribot Emeline
Published: August 2024

T2 mapping is an important biomarker for pre-clinical imaging to characterize the grows of metastasis but suffers from long acquisition time when performed in 3D. Undersampling of the k-space combined to advanced iterative reconstruction using the temporal redondancy of the data along the echo train could be beneficial to reach a reasonable scan time. This works demonstrates that a subspace-based reconstruction for T2 mapping can be used to accelerate a 3D Multi-Echo Spin-Echo acquisition for in-vivo mouse brain metastasis quantification with an acceleration factor up to 10 while keeping an isotropic spatial resolution of 156µm.
Improving Spiral Deblurring with Square Kernels and Low-Pass Preconditioning
Authors: Wang Dinghui , Chao Tzu Cheng , Pipe James
Published: August 2024

Advantages of spiral imaging include fast scan speed and high SNR efficiency. Success implementation of spiral imaging relies on utilization of efficient deblurring methods. The goal of this work is to improve the performance of a previous deblurring method, using square kernels and low-pass preconditioning. Data from phantom and volunteers demonstrate that artifacts can be reduced while computational demand is also reduced by the proposed kernels.
Fast SMWI via denoising for nigral hyperintensity detection in Parkinson’s disease
Authors: Youn Jonghyo , Park Juhyung , Ji Sooyeon , An Hongjun , Heo Hwan , Lee MyeongOh , Song Soohwa , Kim Eung Yeop , Lee Jongho
Published: August 2024

Nigral hyperintensity detection in substantia nigra is a potential biomarker for PD. An advanced SWI method, SMWI, has demonstrated reliable detection of the hyperintensity at 3T but it requires a 4 m 15 s scan protocol which is too long for PD patients, suffering from motion artifacts. In this study, we developed a new 2 m 56 s protocol by reducing phase FOV and applying deep learning-powered denoising to compensate for SNR loss from the shorter scan. The new protocol was validated using both simulated and real data via an automated tool and an expert radiologist.
Longitudinal 129Xe MRI assessment of lung gas transfer and microstructure over 1 year in patients with asthma and/or COPD
Authors: Marshall Helen , Collier Guilhem , Chan Ho-Fung , Smith Laurie , Hughes Paul , Capener Dave , Bray Jody , Joseph Sinoy , Munro Ryan , Rodgers Olly , Ball James , Stewart Neil , Norquay Graham , Brook Martin , Armstrong Leanne , Hardaker Latife , Fihn-Wikander Titti , Hughes Rod , Wild Jim
Published: August 2024

Longitudinal changes of 129Xe MRI metrics in patients with asthma and/or COPD have not yet been reported. 140 patients with asthma and/or COPD were scanned at 2 visits, 1 year apart, using 129Xe gas transfer and diffusion MRI. From visit 1 to visit 2 red blood cell (RBC) / membrane (M) and RBC/gas decreased and the amplitude of red blood cell oscillations (ARBCO) increased when all patients were considered. RBC/M and RBC/gas decreased in asthma+COPD, and RBC/M decreased and ARBCO increased in asthma from visit 1 to visit 2. M/gas and acinar microstructure metrics did not change significantly between visits.
129Xe MRI Assessment of Disease Progression in Patients with COPD treated with Azithromycin: Multi-Site Repeatability and Preliminary Results
Authors: Mata Jaime , Mugler John , Driehuys Bastiaan , Mummy David , Bell Laura , Coimbra Alexandre , Belloni Paula , Niedbalski Peter , Shim Yun Michael
Published: August 2024

Harmonization of imaging methodology among three sites was successfully achieved. Preliminary results for longitudinal treatment with azithromycin demonstrated the sensitivity of 129Xe MRI in detecting ventilation changes, presumably caused by Sars-Cov2 infection or termination of azithromycin treatment at week 24 due to hearing loss. This preliminary data supports that 129Xe MRI is a sensitive tool for detecting subtle changes in COPD early and may potentially reduce the length of clinical trials that aim to visualize therapeutic responses.
Detection of Emphysema using Phase-Resolved functional Lung Imaging Parametric Response Mapping (PREFULPRM)
Authors: Voskrebenzev Andreas , Kaireit Till Frederik , Gutberlet Marcel , Klimeš Filip , Behrendt Lea , Shin Hoen-oh , Kauczor Hans-Ulrich , Welte Tobias , Wacker Frank , Vogel-Claussen Jens
Published: August 2024

Ventilation measurements using signal differences between expiratory and inspiratory respiration states gained popularity as a biomarker for ventilation abnormalities. One method, which incorpartes such measurements is Phase-resolved functional lung imaging (PREFUL). A further classification of abnormalities such as emphysema and air-trapping beyond the current gas-exchange measurement is desirable. Therefore a MR adaption of CT’s parametric-response mapping (CTPRM) method is proposed as an additional post-processing method for PREFUL. The analysis of 34 patients with chronic obstructive pulmonary disease (COPD), shows that there is a high regional (Overlap normal 91%) and total lung concordance (r>0.86) for the proposed method PREFULPRM and CTPRM.
Using Dynamic Mode Decomposition for Functional Lung Imaging
Authors: Ilicak Efe , Ozdemir Safa , Zapp Jascha , Schad Lothar , Zöllner Frank
Published: August 2024

Fourier Decomposition and related techniques have demonstrated the viability of obtaining regional pulmonary functions. To this end, novel post-processing techniques have been previously proposed to obtain ventilation and perfusion related information from dynamic acquisitions. To improve upon these methods, here we propose the use of an advanced data processing framework based on dynamic mode decomposition (DMD) for functional lung MRI. Phantom and in vivo results indicate that DMD achieves similar performance compared to established techniques and improves robustness in cases with fewer number of measurements.
Pulmonary Hypertension Detection by Cardiac Magnetic Resonance Feature Tracking in Patients with Left Heart Failure
Authors: Li Yunling , Yang Kai , Chen Xiuyu , Lian Jianxiu , Sun Yong , Zhao Shihua
Published: August 2024

To investigate the relationship correlation of cardiac magnetic resonance (CMR) feature tracking (FT)-derived right ventricular (RV) global longitudinal strain (RV-GLS) and RV global circumferential strain (RV-GCS) with mean pulmonary artery pressure (mPAP) and pulmonary vascular resistance (PVR) to explore the diagnostic value of RV strain parameters in advanced left heart failure patients with pulmonary hypertension (PH). Study findings included as following: (a) CMR-FT RV-GLS and RV-GCS were independent risk factors for PH in patients with end-stage left heart disease, among all CMR imaging parameters; (b) Both RV-GCS (AUC = 0.868) and RV-GLS (AUC = 0.873) were valuable in predicting PH.
Impact of malignant ventricular arrhythmia on left ventricular function in dilated cardiomyopathy patients assessed by CMR feature tracking
Authors: Kan Ao , Dai JianKun , Li Shuhao , Hu MengYao , Gong Lianggeng
Published: August 2024

This study aiming at assessing the impact of malignant ventricular arrhythmia (VA+) on left ventricular (LV) function in dilated cardiomyopathy (DCM) patients using cardiovascular magnetic resonance (CMR) feature tracking (FT). 34 VA+ and 39 VA- (benign) DCM patients were measured with CMR cine imaging. Although the left ventricular ejection fraction was similar between these two groups, FT results showed the global longitudinal peak strain (GLS) was significantly lower in VA+ than in VA-. GLS had certain diagnostic value for differentiate VA+ and VA- in DCM patients. Glycosylated hemoglobin (HBA1c) was an independent determinant parameter for GLS in DCM patients.
Cardiac Power to Mass Assessment by MRI in Patients with Hypertrophic Cardiomyopathy and Normal Ejection Fraction
Authors: Qing Li , Zhen Zhou , Yifeng Gao , Jiang Ke , Xu Lei
Published: August 2024

Cardiac power (CP) output in patients with heart failure has been studied, while its importance in hypertrophic cardiomyopathy (HCM) patients is yet unclear. 99 HCM patients and 65 gender- and age-matched controls with cardiac MR were included in the study. HCM patients showed significantly higher CP (p=0.031) but lowered NCP (p<0.001) than the controls. The correlation analysis of NCP and functional parameters revealed that NCP was inversely correlated with LV mass (R=-0.395, p<0.001) in HCM patients. NCP decreased significantly in HCM patients and may continue to deteriorate with increasing LV mass.
CMR-based Personalizing Risk Stratification for Outcomes in Dilated Cardiomyopathy: A Single-center Prospective Study.
Authors: Zhou Di , Chow Kelvin , An Jing , Lu Minjie
Published: August 2024

In this study, we explored individual weight of CMR metrics for predicting short-term outcomes in DCM. ECV fraction performed excellent potential of clinical translation for prognosis in patients with DCM. LGE has better prognostic value than other CMR metrics for SCD and aborted SCD. LV strain may contribute to predict advanced heart failure, which not aid to the risk stratification of SCD. In this way, we developed a risk stratification model based on cardiac MR imaging including NYHA functional class, left ventricular ejection fraction, late gadolinium enhancement, and mean extracellular volume. It may improve clinical assessment and individual decision making.
Right ventricular strain for the diagnosis and prognosis of arrhythmogenic right ventricular cardiomyopathy
Authors: Dong Zhixiang , Zhao Shihua
Published: August 2024

To find out the values of strain parameters in the diagnosis and prognosis of arrhythmogenic right ventricular cardiomyopathy (ARVC), 247 patients with initial diagnosis of suspected ARVC were included in this study. Results showed that right ventricular global longitudinal strain (RV GLS) had moderate to high discriminatory power to identify patients with different likelihood of ARVC. Besides, patients with reduced RV GLS had a higher estimated cumulative incidence of combined cardiovascular events. These findings indicate that cardiac magnetic resonance feature tracking could potentially be used as a preferred imaging method in the first visit and follow-up of ARVC.
CASSAVA: a Compressed Adaptive SenSing Algorithm with Variable k‑space Averaging for high‑resolution volumetric 31P MRSI at 7T
Authors: Rincon Gino , Boyd Philip , Franke Vanessa , Bauer Cornelius , Ladd Mark , Bachert Peter , Korzowski Andreas
Published: August 2024

Compressed sensing (CS) techniques suggest the feasibility of reducing the measurement duration of high‑resolution 31P‑MRSI at 7T to a clinically reasonable time (20 minutes) while preserving data quality. The proposed Compressed Adaptive SenSing Algorithm with Variable k‑space Averaging (CASSAVA) reconstructs 31P‑MRSI data with an undersampling factor of $$$R=3.8$$$ while simultaneously maintaining spectral peak accuracy and a high spatial resolution. This was demonstrated in the conducted simulation, retrospective, and prospective studies by evaluating the reconstructed spectra and intracellular pH maps of healthy and tumor tissues as a benchmark test. As a result, clinical research on larger patient cohorts becomes feasible.
Dual responsive MR probe based on oxidation-triggered chemical shift
Authors: Ziolkowska Natalia , Sulkova Katerina , Kracikova Lucie , Vit Martin , Laga Richard , Jirak Daniel
Published: August 2024

Presented novel phosphorus- and fluorine-containing polymer possess high sensitivity at 31P/19F-MR and a large chemical shift from biological phosphorus signal (∆δ=60 ppm) due to phosphorothioate P=S group in its structure. The probe represents a conceptually new approach for phosphorus MR, as it undergoes oxidation-induced structural changes in the presence of ROS, represented in greater amounts in cancer tissue. The additional 19F-MR signal serve as an on-site information on the polymer distribution in the organism.
Accelerated in-vivo 23Na Multi-Quantum Coherences MRI by utilizing Low-Rank Matrix Completion
Authors: Licht Christian , Rapacchi Stanislas , Schad Lothar
Published: August 2024

Sodium (23Na) MRI has received increased attention as a potential biomarker for disease states thanks to the advent of ultra-high field MRI. One interesting asset from 23Na MRI is the distinction between single and triple quantum signal to further characterize tissues. However, 3D 23Na multi-quantum coherences (MQC) imaging requires multiple radiofrequency phase-cycling, which is inherently time-consuming and therefore difficult to include in protocols. In this work, we propose to accelerate 23Na MQC MRI by leveraging multi-dimensional under-sampling coupled with a dedicated Low-Rank matrix completion image reconstruction.
17O-MRI of the cerebral metabolic rate of oxygen during electrical stimulation of the paws in the rat at 11.7 T
Authors: Tourais Amelie , Hery Cameron , Guillermier Martine , Valette Julien , Baligand Celine
Published: August 2024

CMRO2 is an important metric for the evaluation of neurovascular and neurometabolic coupling. However, the degree of coupling between brain activity and CMRO2 remains a matter of debate. In this work, we used 17O-ZTE-MRI at 11.7 T to measure CMRO2 during neuronal activation in the rat primary somatosensory cortex. To improve measurements sensitivity, we acquired data over two consecutive cycles of 17O2 inhalation-washout. We show that a significant functional increase in CMRO2 (+7±5%, p=0.016), and in the rates of metabolized water gain and loss KG (+19±11%, p=0.18) and KL (10±6%, p=0.014) can be detected with good spatial resolution after summation.
Comparison of short and long TR Gradient Recalled Echo (GRE) measures for total sodium concentration mapping in the calf
Authors: Prestwich Ben , Francis Susan
Published: August 2024

Sodium (23Na) MRI measures of tissue are SNR limited. Here, we compare a 3D gradient recalled echo (GRE) 23Na scans with a short TR and fully recovered TR for estimation of tissue sodium concentration (TSC) in the calf. We validate measures by collecting 23Na T1 measures of the calf and reference bottles. A short TR scan is shown to provide increased image SNR, resulting in higher measures of TSC, along with improved depiction of the skin. Using the short TR GRE scan, older subjects and haemodialysis patients are shown to have higher calf TSC than younger subjects.
Reproducibility of 7T human cardiac 3D 31P-MRSI using concentric ring k-space trajectories (CRT).
Authors: Mózes Ferenc , Clarke William , Valkovič Ladislav
Published: August 2024

Cardiac 31P-MRS provides insight into metabolism of the failing heart. The commonly employed 3D-MRSI acquisitions are rather slow, even at 7T. Fast readout trajectories, such as concentric ring (CRT) have been recently suggested to substitute the slow Cartesian sampling (CSI), however their repeatability is yet unknown. Our preliminary data suggest comparable intra-session repeatability, but somewhat lower inter-session repeatability for mid septal voxels using 2.5 min CRT in comparison to 6.5 min CSI. Similar trends were observed for higher resolution CRT.
Quantitative Analysis and Scan Time Impact of DL Recon Applied to Single-Shot Diffusion of the Prostate
Authors: Milshteyn Eugene , Guidon Arnaud , Harisinghani Mukesh
Published: August 2024

Increasing the speed of multiparametric prostate MRI (mpMRI) is highly desirable. However, usual tradeoffs between signal-to-noise (SNR) and scan time must be considered and impact on quantitative metrics must be analyzed. One recently proposed approach applied a commercialized deep learning reconstruction (DL Recon) to prostate T2-weighted imaging, leveraging the capabilities of the DL algorithm to achieve a robust, high-quality T2-weighted acquisition in half the time. As such, this work focuses on evaluating the DL Recon on diffusion weighted imaging, which shows promise to cut acquisition time by ~70% and therefore benefit mpMRI.
Motion artifact assessment for magnetic resonance imaging using a learned combination of deep learning model predictions.
Authors: Saksena Vanya , Arroyo-Camejo Silvia , Hossbach Julian , Schneider Rainer , Maier Andreas
Published: August 2024

Magnetic resonance imaging (MRI) is a powerful imaging modality, but susceptible to various image quality problems. Today, technicians conduct image quality assurance (IQA) during scan-time as a manual, time-consuming, and subjective process. We propose a method towards adaptable automated IQA of MR images without the need of a large, annotated image database for training. Our method implements a machine learning-based module that uses multiple predictions from an ensemble of deep learning models trained with image quality metrics. The sensitivity of this method to detect image quality problems is adaptable to clinical requirements of the end user.
Accelerating DCE-MRI Analysis for Prostate Cancer Diagnosis with Deep Neural Networks
Authors: Zhao Kai , Zheng Haoxin , Sung Kyunghyun
Published: August 2024

A deep learning based DCE-MRI analysis method was proposed with a dedicated neural network architecture and data generation framework. The proposed method does not need DCE-MRI data acquisition or annotation for training. Compared to conventional non-linear least square (NLLS) fitting methods, the proposed method significantly reduced the average processing time from hours to few minutes while preserved the estimation quality.
Multi-branch deep learning model integrated with multi-modal MRI for differential diagnosis of autism spectrum disorders
Authors: Yu Xuan , Wang Meiyun
Published: August 2024

This study proposes a multi-branch deep learning model fused with multi-modal MRI for the differential diagnosis of ASD. We solve the problem that traditional ASD classification algorithms based on static functional network connections ignore the time-varying characteristics of brain functional connections. Study the spatiotemporal characteristics of ASD brain imaging, and mine the information of functional connectivity between brain regions over time.
Surface-based morphometric abnormalities in patients with early psychosis: an MP2RAGE-based study at 7T
Authors: Wang Zirun , Gómez Yasser Alemán , Cleusix Martine , Jenni Raoul , Alameda Luis , Conus Philippe , Cuadra Merixell Bach , Hagmann Patric , Do Kim Q. , Xin Lijing
Published: August 2024

This study aims to investigate brain cortex alterations in early psychosis patients (n = 42) compared to healthy control subjects (n=35). Surface-based morphometric analysis using MP2RAGE images at 7T revealed significant clusters (corrected p<0.05) where the cortical area and cortex volume in early psychosis patients are reduced compared to healthy controls at the junction of lateral occipital, lingual and peri calcarine region at left hemisphere after permutation multiple comparison correction. Bilateral cortical areas, thickness, and volumes of the patients were reported to be changed at the surface vertex level.
Disrupted striatum-centered tracts and positive symptoms in schizophrenia patients
Authors: Zhu Yuanqiang , Wang Chen , Guo Fan , Chang Yingjuan
Published: August 2024

Stronger tract strengths of the bilateral striatum with dlPFC were detected in schizophrenia patients. Our result provided system-level insights into abnormal connectivity strength of striatal circuits in schizophrenia patients. And the strength might have potential as neuroimaging biomarkers for positive symptoms.
The selfish brain – Unaltered brain temperature in the acute state of Anorexia Nervosa
Authors: Doose Arne , Lin Alexander , Starr Tyler , Breedlove Katherine , Linn Jennifer , Ehrlich Stefan
Published: August 2024

In anorexia nervosa (AN) restrictive food intake leads to a slowed metabolism. Brain temperature, can provide information about brain metabolism. Difference between Magnetic Resonance Spectrum peaks (ΔH20-NAA) provide a proxy for brain temperature in 30 AN and 30 healthy control (HC) participants. We found no group differences in brain temperature between AN/HC. Further, we report no group differences in brain temperature between a subgroup of the AN participants with the lowest BMI/body temperature compared to a subsample with higher BMI/body temperature. The results suggest a prioritization of brain metabolism in AN in line with the selfish brain hypothesis.
Cerebral haemodynamic correlates of altered consciousness states induced by High-ventilation breathwork
Authors: Örzsik Balázs , Kartar Amy , Horinouchi Toru , Bouyagoub Samira , Anderson Brittany , Bailey Duncan , Critchley Hugo , Nagai Yoko , Asllani Iris , Colasanti Alessandro
Published: August 2024

‘Breathwork’ is pursued by a rapidly growing set of adherents, anecdotally because it evokes psychedelic experiences that positively effect mood. We measured regional cerebral blood flow (rCBF) during high-ventilation breathwork (HVB) in healthy participants. Furthermore, we assessed the relationship between rCBF changes and subjective experience, focusing on altered state of consciousness. HVB was associated with substantial global reduction in CBF. Moreover, reduction in rCBF in anterior cingulate and insular cortices scaled with intensity of subjective experiences. These brain regions are implicated in supporting interoceptive control underlying affective regulation. Understanding the neural effects of HVB can inform new clinical applications.
Investigation of nonuniform bias field in quantitative analysis of neuromelanin-sensitive MR imaging
Authors: Kang Junghwa , Lee Tea Young , Nam Yoonho
Published: August 2024

Neuromelanin-sensitive MR imaging is an indirect method for assessing dopamine function. However, quantitative and objective analysis of NM-MRI is difficult because of field inhomogeneities or motion artifacts. To investigate the effect of nonunifrom bias field on quantitative analysis in NM-MRI, synthesized random bias fields were multiplied and compared the quantitative analysis using SN ROIs and reference ROIs. The results show a weak nonuniform bias field can reduce the reliability of quantitative analysis.
Regional dynamic brain function changes in adults with autism spectrum disorder
Authors: Yue Xipeng , Shen Yu , Li Ying , Zhang Ge , Li Xiaochen , Wei Wei , Bai Yan , Xie Jiapei , Wang Xinhui , Luo Zhi , Zhang Xianchang , Wang* Meiyun
Published: August 2024

Most neuroimaging studies investigating autism spectrum disorder (ASD) have focused on static brain function and used children as research subjects. However, this study investigated dynamic changes of regional neural function in adult ASD patients. Significant differences in dynamic regional homogeneity (dReHo) and dynamic amplitude of low-frequency fluctuation (dALFF) were observed based on resting state fMRI in several brain areas, such as the left middle/inferior temporal gyrus and left middle occipital gyrus. A significant correlation was found between clinical scores and the dReHo/dALFF values. These results suggested that dynamic regional brain function might be helpful in understanding neural mechanisms in ASD .
Brain functional network hierarchy and neurochemical correlates in deficit and non-deficit schizophrenia
Authors: Yang Chengmin , Yao Li , Liu Jiajun , Yang Zhipeng , Lui Su
Published: August 2024

By combining the brain hierarchy changes and their likely potential molecular signatures, we found that the compression of the cortical hierarchy organization in deficit schizophrenia (NS) and non-deficit schizophrenia (NDS) with neurochemical correlates. The altered functional gradients were spatially positively correlated with the receptor of 5-HT2a in DS patients, while negatively correlated with receptor of D1/2 in NDS patients, which revealed the underlying physiological mechanisms of the heterogeneity in schizophrenia.
Parallel imaging reconstruction using iterative CNN-based denoising in image domain
Authors: Amemiya Tomoki , Suzuki Atsuro , Kaneko Yukio , Yokosawa Suguru , Shirai Toru
Published: August 2024

We propose an iterative reconstruction method of parallel imaging using convolutional neural network (CNN)-based denoising in the image domain and data-consistency processing in k-space. The proposed method reduces the noise and artifacts of a reconstructed image compared with the iterative method using sparsity of wavelet transform, suggesting that using CNN-based denoising in iterative reconstruction is effective in reducing noise in parallel imaging.
A Stochastic Approach for Joint Learning of a Neural Network Reconstruction and Sampling Pattern in Cartesian 3D Parallel MRI
Authors: Zibetti Marcelo , Regatte Ravinder
Published: August 2024

This work proposes a stochastic variation of the bias-accelerated subset selection (BASS) algorithm to learn an efficient sampling pattern (SP) for accelerated MRI. This algorithm is used in the joint learning of an SP and neural network reconstruction. We apply the proposed approach to two different 3D Cartesian parallel MRI problems. The proposed stochastic approach, when used for joint learning, improves the learning speed from 2.5X to 5X, obtaining SPs with similar properties as the non-stochastic approach with nearly the same RMSE and SSIM.
Deep Attention Unfolding CNN Architecture for Parallel MRI
Authors: Shafique Muhammad , Qazi Sohaib , Najeeb Faisal , Omer Hammad
Published: August 2024

Deep learning has made significant progress in recent years, however the local receptive field in CNN raises questions about signal synthesis and artefact compensation. This paper proposes a deep learning Spatial-Channel Attention U-Net (SCA-U-Net) to solve the folding problems arising in MR images because of undersampling. The main idea is to enhance local features in the images and restrain the irrelevant features at the spatial and channel levels. The output from SCA-U-Net is further refined by adding a small number of originally acquired low-frequency k-space data. Experimental results show a better performance of the SCA-U-Net model than classical U-Net model.
Clinical feasibility of artificial intelligence-assisted compressed sensing for accelerated MR imaging in nasopharyngeal carcinoma
Authors: Zhao Qin , Zhang Song , Zheng Liyun , Dai Yongming
Published: August 2024

To improve the scanning efficiency of magnetic resonance imaging (MRI) for nasopharyngeal carcinoma, this study investigated the value of accelerating technique, artificial intelligence-assisted compressed sensing (ACS), in comparison to conventional sequences without accelerating technique and accelerating MRI using parallel imaging (PI). Eleven patients diagnosed with nasopharyngeal carcinoma were prospectively enrolled. As a result, ACS achieved the shortest acquisition time, with similar or even better image quality and SNR than conventional sequences. ACS has the potential to provide sufficient image quality for T1- and T2-weighted imaging in nasopharyngeal carcinoma and could be an alternative to conventional sequences in clinical practice.
USING DEEP LEARNING WITH AN ACTIVE LEARNING APPROACH TO CORRECT WATER-FAT MIS-LABELING IN MR THORACIC SPINE IMAGES
Authors: Satpathi Siddhartha , Browne Jacinta , Alfayad AbdulRahman , Verdoorn Jared , Pipe James
Published: August 2024

Upon investigating a dataset of 804 studies for spinal fractures from two major vendors, the authors observed that 11% of the water-fat images in the studies are mis-labelled. This motivated the development of an automated algorithm to correct the mis-labelling. We used a 2D CNN based deep learning model to classify the images correctly with the aim of reducing error and fatigue in clinical diagnosis caused by such mis-labeling, as well as providing correct labels for further AI workflow. We also demonstrated the use of active learning in this problem by achieving the same test-error with fewer labels than using the entire training data.
Fast MR imaging with distribution convergence modeling
Authors: Cheng Jing , Cui Zhuo-Xu , Zhu Qingyong , Liang Dong
Published: August 2024

Existing deep learning-based methods for MR reconstruction mainly use MSE as loss function to train the network under the assumption that MR images follow the sub-Gaussian distribution, without considering the real distribution of the images. In this work, we propose a new DL-based method that models the image distribution with equilibrium Langevin dynamic to converge the distribution, and trains the network with Wasserstein distance to approach the real distribution. Experimental results on highly undersampled MR data demonstrate the superior performance of the proposed method.