bluuebunny/crossref_metadata_2025 huggingface dataset:
Imaging Nigrosome-1 using Wave-CAIPI Susceptibility Weighted Imaging at 3T
Authors: Liu Peng , He Naying , Zhang Youmin , FU Caixia , Li Qing , Haacke E. Mark , Liu Yu , Liu Wei , Wang Xinhui , Polak Daniel , Yan Fuhua
Published: August 2024

In this work, the ability of Wave-CAIPI accelerated 3D SWI for imaging the Nigrosome-1(N1) sign was evaluated. Short-TE, long-TE and conventional SWI protocols were compared for the detection of the N1 sign. Qualitative and quantitative analyses were used to evaluate the presence or absence of the N1 sign and the contrast-to-noise (CNR) of the N1 sign relative to adjacent tissues. The results showed that Wave-CAIPI SWI had no significant differences with conventional SWI for recognizing the N1 sign. Wave-CAIPI SWI can be a replacement of conventional SWI (4 min 52s) with shorter scan times of 2min 26s covering the whole brain.
Multimodal assessment of nigrostriatal degeneration in de novo Parkinson’s disease
Authors: López-Aguirre Miguel , Matarazzo Michele , Blesa Javier , Sánchez-Ferro Álvaro , Monje Mariana H.G. , Obeso José , Pineda-Pardo José A.
Published: August 2024

FDOPA uptake rate, fractional volume of free-water and R2* relaxometry are imaging biomarkers sensitive to dopaminergic decline, microstructural degeneration, and iron disruption respectively, three pathological processes developed within the nigrostriatal system in Parkinson’s disease (PD). A multimodal comprehensive characterization of these biomarkers in early PD was performed, assessing them within striatum and substantia nigra pars compacta in a de novo PD cohort. While iron disruption was not observed, PD subjects revealed dopaminergic and microstructural alterations within the nigrostriatal system, following both similar spatial patterns. These results serve to improve our understanding of nigrostriatal vulnerability and degeneration in early PD.
Detection of hormone-producing pituitary microadenoma by Contrast-Enhanced Submillimeter level 3D T1w SPACE: Comparison with 2D T1w Images
Authors: Cheng Cheng , Ji Shengzhang , Zhao Rui , Zhang Chen , Huo Guang hui
Published: August 2024

By compared the images quality and diagnostic efficacy of enhanced 3D T1w SPACE and 2D T1w TSE, this study aims to investigate the value of Contrast-Enhanced submillimeter slice 3D T1w SPACE sequence in hormone-producing pituitary microadenoma.
Clinical application of direct signal control and other B1 shimming methods for infratentorial region T2 weighted imaging at 7T
Authors: Wang Xiaoyu , Qu Jianxun , Raphael Tomi-Tricot , Malik Shaihan J , Wang Song , Bian Xiangbing , Lou Xin
Published: August 2024

This was a clinical application study of direct signal control (DSC) technology on 7T MRI. The result suggests that DSC-T2w provides good-quality for whole-brain imaging. When imaging region is restricted, we can also use static B1 shimming with a dedicated shimming region. This study demonstrated that DSC technology can improve the image quality in 7T brain scan.
Spatial habitats features derived from multiparametric MR imaging predict long versus short-term survival in gliomas: Preliminary findings
Authors: Ma Hui , Ma Zuliwei , Zeng Shanmei , Wang Mengzhu , Song Yang , Zhang Chengxiu , Yang Zhiyun , Zhao Jing
Published: August 2024

We developed spatial habitats based on multiparametric MRI and evaluated associations between features in these habitats and survival time in patients with high-grade gliomas. The voxels in MR images were grouped into 2 clusters using the K-means clustering algorithm of in-house software nnFAE (V.0.0.10). Structural MRI habitats were defined on CE-T1WI and T2-Flair images, and physiologic MRI habitats were defined on MK derived from DKI and Ktrans derived from DCE imaging. Results showed physiologic habitats weighed more than structural ones, and suggested low vascular-permeability-and-tissue-complexity habitats may play an important role in distinguishing long- and short-term survival of high-grade gliomas patients.
Brain MRI phenotypes of glioblastomas are suggestive of overall patient survival
Authors: Schmitz-Abecassis Bárbara , Dirven Linda , Jiang Janey , Keller Jasmin , Croese Robert , van Dorth Daniëlle , Kant Ilse , Taphoorn Martin , van Osch Matthias , Koekkoek Johan , de Bresser Jeroen
Published: August 2024

Despite multimodal anti-tumor treatment, glioblastomas typically progress, yet identifying true tumor progression on MRI-scans is challenging. We aimed to establish brain MRI phenotypes of glioblastomas by combined analysis of radiological scoring of structural and perfusion tumor characteristics 3-months post-radiotherapy. Hierarchical clustering analysis method was applied to group patients by similar tumor characteristics and it was analyzed whether these groups showed differences in tumor progression and overall survival outcome. Four distinct MRI phenotypes of glioblastoma were established and showed between-group differences in median overall survival time.
Comparison Between Postcontrast T1-Weighted Thin-slice 2D Spin Echo and 3D SPACE Sequences in Detection of Brain Metastases at 1.5T and 3T
Authors: Rulseh Aaron , Ryznarova Zuzana , Vymazal Josef
Published: August 2024

We compared standard T1-weighted thin-slice SE and T1-weighted SPACE sequences in the detection of metastatic brain lesions at 1.5 and 3 Tesla in 56 patients. Three raters evaluated the presence of lesions in 2 sessions minimally 6 weeks apart. Our results show that T1-weighted SPACE is not inferior to standard thin-slice SE sequences in the detection of brain metastases. All three experienced raters reached excellent consistency between SE and SPACE and agreement with ground truth.
The Effect of RF Pulse Duration Settings in Basis Sets on Sensitivity and Specificity of 2HG Spectroscopy
Authors: Kim Sanghoon , Choi Changho , Najam Natasha , Lin Alexander
Published: August 2024

2HG is the specific biomarker for the IDH mutation in tumors. In this study, we utilized two different 2HG basis sets, one using a 4.8ms refocusing pulse duration and another with 5.8ms. Using the two different basis sets, we analyzed the same data and found large differences in the sensitivity and specificity results.
IMPROVED EX-VIVO IMAGING USING BRAIN & CONTAINER-SPECIFIC 3D-PRINTED HOLDERS
Authors: Jegathambal Sethu Boopathy , Leppert Ilana , Rudko David , Shmuel Amir
Published: August 2024

Depending on the medium, it might be difficult to maintain the brain stable during ex-vivo imaging. In addition, the SNR might not be homogeneous. We propose using brain and container-specific 3D-printed models for holding the brain. The method requires preliminary imaging of the container and the brain. Then, a 3D-printed model is created, with profiles that match the surface of the brain on one side and the inner surface of the container on the other. The holder is designed to maintain the brain stable in space, where the SNR is high and homogeneous, while allowing contact with the immersion fluid.
MAVRIC SL can reduce inter-rater variability of the measurements for the cervical spine segment height in ACDF patients on 3T MRI
Authors: Yang Renjie , Liu Changsheng , Liu Weiyin , Li Liang , Zha Yunfei
Published: August 2024

Subsidence assessment is an important indicator for postoperative follow-ups for ACDF patients and normally performed on radiographs. It is still challenging to image ACDF patients using conventional MRI for the measure of segment height is influenced by the metal artifacts. In this study, MAVRIC SL showed better inter-rater agreement on measurements of segment height compared to FSE T1WI. 20 cases on MAVRIC SL and 6 cases on FSE T1W1 among 22 patients showed the measurements of segment height was less than the maximum allowed difference (2mm). This study demonstrated that MAVRIC SL has a strong potential in the subsidence assessment.
Quantitative MRI of DCE andIVIM for differentiating low-risk from non-low-risk early-stage endometrial carcinoma
Authors: Wang Hongxia , Yan Ruifang , Wang Beiran , Li Zhong , Jin Xingxing , Guo Zhenfang , Liu Wangyi , Wang Kaiyu , Guo Jinxia , Han Dongming
Published: August 2024

Finding a noninvasive and effective means for the risk stratification of early-stage EC is of great benefit to patients. This study aim to investigate the value of dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion (IVIM) in differentiating low-risk from non-low-risk early-stage endometrial carcinoma (EC). Results showed that both DCE-MRI and IVIM facilitate the preoperative identification of low-risk and non-low-risk early-stage EC. Compared with each single parameter, the combination of Ktrans, Ve, and f provided better predictive power and may serve as a superior imaging marker.
The Influences on Amide Proton Transfer (APT) Signal Metrics at 3T: A Simulation and In-Vitro Study
Authors: Fothergill Aisling , Higgins David , Thomas Owen , Coope David , Djoukhadar Ibrahim , Parkes Laura
Published: August 2024

Amide Proton Transfer MRI shows clinical benefit in glioma imaging. Clinically useful APTw metrics should be sensitive to changes in amide concentration, a potential marker of tumour proliferation, and insensitive to T1 changes. To investigate sensitivity, simulations and in-vitro studies were performed over a range of amide concentrations and T1 values. In-vitro data included two varied concentration series, with and without T1-maintenance, and a constant concentration T1-vaired series. In-vitro results showed APT* had poor sensitivity, MTRrex was most sensitive to concentration and T1, AREX may overcorrect for T1, and MTRasym appears least sensitive to T1 while remaining sensitive to concentration.
Whole-Brain Sub-Millimeter Resolution fMRI using 3D EPI Accelerated with Temporal Random Walk
Authors: Park Suhyung , Beckett Alexander , Hakkinen Suvi , Ma Samantha , Feinberg David
Published: August 2024

There are significant benefits to segmented 3D EPI fMRI acquisitions, which acquires high spatial and temporal resolution across the whole brain to better understand brain neuronal activity. This can be achieved through accelerated 3D EPI imaging, which provides rapid whole-brain coverage at the cost of SNR efficiency resulting from frame-by-frame reconstruction. Here, we utilize temporal information for whole-brain coverage on 8-fold accelerated 7T fMRI acquisition without altering the subsequent fMRI results.
Developmental Ramifications of the Screen Age: Uncovering Effects of Screen Time on Neural Maturation
Authors: Atalay Alexander , Newman Benjamin , Druzgal T.
Published: August 2024

Increased screen usage during adolescent development correlates with a complex response in the brain. Using a massive longitudinal human brain MRI dataset, we describe relationships between screen time and cellular microstructure across 13 cortical regions previously implicated in screen usage. Longitudinally, grey matter density had no relationship with screen time, and fractional anisotropy was significantly associated with screen time in only the ventromedial prefrontal cortex. However, microstructural 3T-CSD diffusion MRI metrics were significantly associated with increased screen time in 8 regions. The comparison between these results and typical age-associated development suggests potential negative implications of increased screen usage during adolescence.
Differential Gray Matter Volume Loss in Controlled and Uncontrolled Type 2 Diabetes Mellitus Over Time
Authors: Roy Bhaswati , Choi Sarah , Freeby Matthew , Kumar Rajesh
Published: August 2024

Patients with Type 2 diabetes mellitus (T2DM) show brain tissue changes in mood and cognitive control sites, functions that are deficient in the condition. However, the extent of brain gray matter volume loss in various sites, as well as progression of volume loss with time in controlled and uncontrolled T2DM adults are unclear. We observed higher gray matter volume loss in crucial brain areas involved in cognition and mood control in T2DM adults with uncontrolled glucose levels and accelerated progression after 6-months of follow-up. These findings indicate the need for optimal glucose management in T2DM adults.
Improved Characterization of White Matter in Multiple Sclerosis with Free Water-Corrected Diffusion MRI
Authors: By Samantha , Houde Jean-Christophe , Pachai Chahin , Maltais Loika , Torres Jorge , Grenier Gabrielle , Huang Sujuan , Bradley Daniel
Published: August 2024

Free water (FW)-corrected metrics in diffusion MRI have shown promise in elucidating confounding pathological processes in multiple sclerosis (MS). Here, we present a retrospective analysis of FW-corrected diffusion in a cohort of 287 MS participants from a multi-center clinical trial. Our preliminary results indicate the method’s ability to distinguish different lesion types and MS subtypes.
Mapping changes in tissue 23Na concentration and cerebral blood flow during a visual task using ASL and functional Sodium Imaging (fNaI)
Authors: Asllani Iris , Örzsik Balázs , Bouyagoub Samira , Woods Joseph , Ronen Itamar , Madelin Guillaume , Cercignani Mara
Published: August 2024

Sodium MRI was combined with arterial spin labeling (ASL) perfusion MRI to detect changes in total sodium concentration (TSC) and cerebral blood flow (CBF) associated with visual tast activation on 6 healthy volunteers. There was no overlap between the areas in the visual cortex where there was a significant change in CBF (~38%) and the regions where a change (~11%) in TSC was detected. Results from partial volume correction indicate that most of the changes in TSC originated in the white matter.
MRS Quantification using Deep Learning Frameworks: an Accuracy and Efficiency Study
Authors: Turco Federico , Slotboom Johannes
Published: August 2024

We implemented a model fitting algorithm for magnetic resonance spectroscopy quantification using Pytorch. This network fit the spectra by minimizing the error between the spectrum modeled by the newtwork and the desired target. The implementation can fit multiple spectras in parallel using Pytorch GPU acceleration. We compared the results with a parallel version of TDFDFit and found it to be up to 12 time faster fitting 2048 spectras in 50 seconds.
Parametrized macromolecule models in the brain 1H MRS quantification: Effect of the baseline spline on quantification uncertainty and precision
Authors: Dell'Orco Andrea , Riemann Layla Tabea , Ellison Stephen , Ittermann Bernd , Tietze Anna , Scheel Michael , Fillmer Ariane
Published: August 2024

Parametric macromolecule (MM) models can improve the quantification of brain 1H-MRS. We quantified a publicly available repeated-acquisition dataset with LCModel and applied a parametric MM model in conjunction with four different settings for spline node distance and compared the quantification results. Coefficients of variation, average Cramér-Rao lower bound, repeatability, and reproducibility were estimated. A moderate effect of the baseline spline was shown.
Feasibility of ultrafast DCE-MRI in differentiating benign and malignant breast tumors
Authors: Huang Junhui , Qiu Lihua , Ao Yongsheng , Mu Lan , Hu Zhanli , Liang Dong , Liu Xin , Zheng Hairong , Zhang Na
Published: August 2024

The conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) technique has been shown to be very sensitive in detecting benign and malignant breast cancer lesions. However, it requires a relatively long acquisition time and hence a semiquantitative imaging technique. To reduce the acquisition time, ultrafast DCE-MRI techniques have been proposed for breast tumor imaging. Our study aims to investigate the feasibility of the ultrafast DCE-MRI technique in differentiating benign and malignant breast tumors. The results show that the semiquantitative and quantitative parameters obtained with ultrafast DCE-MRI are superior to those obtained with conventional DCE-MRI in differentiating benign and malignant breast tumors.
Improving the robustness of independent component analysis for denoising multi-echo fMRI data
Authors: Tahayori Bahman , Smith Robert , Vaughan David , Tailby Chris , Pierre Eric , Jackson Graeme , Abbott David
Published: August 2024

Multi-Echo fMRI data acquisition has multiple advantages over single-echo acquisition. Principal amongst them is that multiple echoes can distinguish neural activity from artefacts. TE Dependent ANAlysis (TEDANA) is an existing software tool designed to denoise multi-echo fMRI datasets. We evaluated the performance of TEDANA to denoise fMRI data of 120 subjects. Our results demonstrated that TEDANA improved the activation detection at a group level. However, for a subset of subjects TEDANA degraded their individual result substantially. We identified potential causes and proposed a modified framework for multi-echo data analysis that provides reasonable results at an individual subject level.
Mood repair in long-term meditators is predicted by rsfMRI functional connectivity of the insula and correlates with FA of the uncinate fasciculus
Authors: Dessain Quentin , Dricot Laurence , Delinte Nicolas , Daussort Manon , Macq Benoit , de Timary Phillipe , Kupers Ron
Published: August 2024

We used rsfMRI and diffusion imaging to study functional and structural brain changes underlying the psychological trait mood repair in long-term meditators. Results of connectome-based predictive modeling showed that measured “mood repair” scores in meditators could be successfully predicted from rsfMRI data during meditation. The highest degree node in the underlying network was in the anterior ventral insula. Diffusion imaging data further revealed a role of the uncinate fasciculus in the mood repair trait in meditators. The uncinate fasciculus is part of the limbic network, connecting anterior temporal lobe with the inferior prefrontal cortex.
Measurement of blood-brain barrier leakage in AD transgenic mice with aging: Improving sensitivity with capillary input function
Authors: Bae Jonghyun , Das Ayesha , Reyes Isabel , Qayyum Sawwal , Zhang Jin , Masurkar Arjun , Kim Sungheon
Published: August 2024

Recent studies have suggested that the increase in blood-brain barrier (BBB) permeability is associated with both aging and the progression of the Alzheimer’s disease (AD). However, the association of the amyloid pathology with the increased BBB leakage at different disease progression is still poorly understood. In this study, we performed a cross-sectional study to investigate the BBB permeability changes in AD transgenic mice with aging. We also propose the network-aided analysis allows the scan time reduction without compromising the accuracy of the detection of the subtle permeability
Reveal cortical abnormalities by quantitative synthetic MRI in children with beta-thalassemia
Authors: Bu Meiru , Deng Xi , Shi Lingling , Cui Wei , Qian Long , Zeng Zisan , Jiang Muliang
Published: August 2024

Beta-thalassemia (β-TM) is a chronic blood disorder presenting with severe anemia. However, the abnormalities of microstructure in cortical regions are still unclear. Herein, we explored the difference of quantitative MRI parameters in gray matter between β-TM patients and healthy controls. The results showed that altered T1 and T2 values in specific gray matter in β-TM patients, which may be associated with alteration in brain gray matter, such as reduced myelin content and excessive iron deposition. Thus, T1 and T2 quantitative variables may be promising imaging markers for further exploring the pathophysiological mechanisms of β-TM.
T2 heterogeneity of cortex in patients with beta-thalassemia major
Authors: Deng Xi , Bu Meiru , Wu Meiqing , Cui Wei , Qian Long , Zeng Zisan , Jiang Muliang
Published: August 2024

Beta-thalassemia (β-TM) is an inherited blood disorder with severe anemia. In this study, we investigated alterations of T2 heterogeneity in cortical regions caused by β-TM using magnetic resonance imaging (MRI). Compared with healthy controls, β-TM patients showed increased T2 heterogeneities in bilateral inferior orbitofrontal, left calcarine, left cuneus and left superior occipital lobe, while no decreased T2 heterogeneity was observed. Thus, we concluded that T2 heterogeneities could reveal the β-TM-affecting T2 alterations in brain.
An Optimized High Resolution Acquisition and Processing Pipeline for QSM in the Prostate
Authors: Muralidharan Laxmi , Mathew Manju , Clemente Joey , Caselton Lucy , Kaur Sumandeep , Brizmohun Mrishta , Punwani Shonit , Shmueli Karin
Published: August 2024

We aimed to optimize MRI acquisition with 1mm isotropic resolution and Quantitative Susceptibility Mapping (QSM) reconstruction for prostate clinical research. Acquisition parameters optimized in two subjects included fat-water phase artifact removal, parallel imaging acceleration factor, resolution and number of echoes. QSM masking, background field removal and susceptibility calculation were optimized in six subjects and three prostatectomy specimens. In-phase acquisition removed more fat-water phase artifacts than post-processing. VSHARP and excluding rectal gas reduced residual background fields and Iterative Tikhonov regularization reduced noise. This optimized (8.5 minute) protocol and pipeline will allow incorporation of prostate QSM in clinical research studies.
BTX: Simultaneous 3D Quantitative Magnetization Transfer Imaging and Susceptibility Mapping
Authors: Jang Albert , Jang Hyungseok , Liu Fang
Published: August 2024

We propose a novel sequence that enables simultaneous quantitative magnetization transfer (qMT) imaging and susceptibility mapping (QSM) for assessing tissue composition, microstructure, and microenvironment. We extend our BTS sequence to incorporate a multi-echo acquisition scheme for probing tissue susceptibility information. The acquisition allows quantification of B1+, bias-corrected T1, qMT parameters (macromolecule bound proton fraction and proton exchange rate), tissue susceptibility and T2*. The method’s feasibility is demonstrated using an in-vivo brain scan, where 3D concurrent qMT and QSM were obtained for the whole brain at feasible scan time.
Magnetic Susceptibility vs Relaxometry in the Characterization of an Animal Model of Multiple Sclerosis
Authors: Tariq Rehman , Muhammed Rania , Wu Ying , Shafqat Qandeel , Sun Hongfu , Dunn Jeff
Published: August 2024

There is evidence for changes in magnetic susceptibility in the CNS of people with MS. MRI techniques utilizing relaxometry and magnetic tissue properties – R2* and quantitative susceptibility mapping, respectively – can be used to detect these changes. Both techniques were applied to study pathological changes in EAE mice compared to controls. Significant differences were found in the cortex between EAE mice and controls using R2*, while no differences in magnetic susceptibility were found between the two groups. Although this indicates that R2* may be better at detecting differences, perhaps it can be utilized as a complement to QSM analysis.
Mapping brain development : An ex vivo multi-contrast MRI study on the ferret
Authors: Mouton Laura , Ruze Anthony , Valabrègue Romain , Pérot Jean-Baptiste , Soustelle Lucas , Sahu Vaibhav , Heuer Katja , Lehéricy Stéphane , Toro Roberto , Santin Mathieu
Published: August 2024

Brain development during the first weeks after birth in ferrets is similar to the one in the last trimester pregnancy in humans. Studying the ferret brain could thus provide insights about brain development and the underlying processes. We used a multi-contrast MRI approach combining diffusion-weighted and quantitative MRI at 11.7T to investigate normal brain development in the ex vivo ferret brain. We were able to reconstruct fiber tracts even at a very early stage and assess their myelination level based on macromolecular fraction values. Combining diffusion-weighted with quantitative MRI is thus an interesting imaging approach to study normal brain development.
3D-pASL and DWI for detection of the function of transplanted kidneys with 1.5T MRI
Authors: ZHANG LING , Xie Sheng , Yue Xiuzheng , Ding Zhenshan , Pu Xiaoqi , Li Yiwei
Published: August 2024

Kidney Transplanted is the therapyfor patients with end-stage renal disease. Arterial spin labeling (ASL) uses magnetic labeling of water from inflowing blood as an endogenous tracer to acquire maps of absolute regional perfusion. The purpose of this study was to evaluate the blood flow of transplanted kidney allograft using a 1.5T MRI with ASL technique and determine whether renal allograft cortical perfusion by ASL could be a non-invasive biomarker for identifying kidney allograft function. Our data showed DWI and 3D-pCASL could be quantitative non-invasive tools for the clinical translation of identifying kidney allografts with subclinical pathology in further study.
Increasing MT contrast in laminar fMRI using PUSH pTx pulses
Authors: Pfaffenrot Viktor , Leitao David , Verheyen Annika , May Markus , Tomi-Tricot Raphael , Malik Shaihan , Norris David
Published: August 2024

The GRE-BOLD contrast used in laminar fMRI suffers from suboptimal specificity due to unwanted extravascular effects. Recently, efforts were made to increase specificity of GRE-BOLD by means of CBV-weighting using the magnetization transfer contrast. The specificity improvement depends on the amount of selective GM signal reduction. We investigate whether PUSH pTx pulses, designed to maximize MT contrast in a given area, can achieve a higher functional contrast. Our results suggest that when opting for high-power, off-resonant MT pulses, both PUSH and a CP2+ mode perform equally well in increasing the functional contrast at short TE compared to GRE-BOLD in V1.
Analysis of the interactions between a TMS coil and a standard receive-only RF loop for MR imaging at 3T
Authors: de Lara Lucia Navarro , Meng Qinglei , Stockmann Jason , Makarov Sergey , Daneshzand Mohammad , Wald Larry , Nummenmaa Aapo
Published: August 2024

Specialized MR hardware is needed to combine non-invasive brain stimulation methods (e.g., TMS) and concurrent acquisition of functional MR images. Such integrated hardware systems enable studying causal relationships between the cortical and subcortical nodes of large-scale brain networks. For best possible imaging performance, all interactions of the stimulation coils on the transmit, encoding and receive system of the MR system should be analyzed on detail. The presented approach enables quantitatively assessing the influence of the TMS coils on MR imaging receive hardware. Understanding the effects could lead to improved design strategies for integrated TMS/MRI systems.
Automatic brain extraction on multi-contrast dogs and cats MRI images
Authors: Eddin Jamil Nour , Dorez Hugo , Curcio Valentina
Published: August 2024

Brain extraction in an MRI image is the first pre-processing step of a neuroimaging quantification pipeline. Once the brain is extracted, further post-processing becomes faster, more specific, and easier to implement and interpret. Existing brain extraction tools are mostly adapted to work on the human anatomy, or on specific animal species. This gives poor results when applied to animal brain images. We developed an atlas-based Veterinary Images Brain Extraction (VIBE) algorithm that is fully automatized and was successfully tested on different cats and dogs breeds, 3D and 2D MRI images, different contrasts (T1-weighted, T2-weighted and T2 FLAIR) and acquisition planes.
­­A deep neural network framework of few-shot learning with domain adaptation for automatic meniscus segmentation in 3D Fast Spin Echo MRI
Authors: Li Siyue , Zhao Shutian , Xiao Fan , Cahil Dόnal G. , Ho Kevin Ki-Wai , Ong Michael Tim-Yin , Chan Queeie , Griffith James F , Hong Jin , Chen Weitian
Published: August 2024

Automatic meniscus segmentation is highly desirable for quantitative analysis of knee joint diseases. As three-dimensional Fast Spin Echo (3D FSE) is a promising MR (magnetic resonance) imaging technique to evaluate the tissues of the knee joint. In this study, we explore meniscal segmentation on 3D FSE MRI. Manually annotating 3D knee images is challenging since it is time-consuming and requires clinical expertise. In this study, we propose a domain adaption-based few-shot learning method for meniscal segmentation on 3D FSE images using only one annotated MRI data. We demonstrate that the proposed method outperformed the fully supervised segmentation model.
Using ‘P-scores’: a novel percentile-based normalization method to accurately assess individual deviation in heavily skewed neuroimaging data
Authors: Hafiz Rakibul , Nayak Amritha , Irfanoglu M. , Chan Leighton , Pierpaoli Carlo
Published: August 2024

We propose a novel quantity to correctly assess the extent individuals deviate from the median of a heavy-tailed distribution. We compute a percentile-based score, we call ‘P-score’, which normalizes the deviation of an individual from the sample median by incorporating the individual’s position in the left/right tail of the sample distribution and the corresponding length between the sample median and the 5th/95th percentile edge values of the sample distribution, respectively. We demonstrate the skewness present in diffusion MRI data and the bias introduced when Z-scores are used and further show the control of this bias using the proposed ‘P-scores’ approach.
Flow Displacement and Wall Shear Stress in Individuals with Mild-to-Moderate Aortic Dilation and Tricuspid Aortic Valves
Authors: Trenti Chiara , Hammaréus Filip , Ebbers Tino , Swahn Eva , Jonasson Lena , Dyverfeldt Petter
Published: August 2024

Altered hemodynamics may play a role in the development of ascending aortic aneurysms. In this study, we sought to investigate wall shear stress and flow displacement in patients with tricuspid aortic valve and mild-to-moderate dilatation of the ascending aorta, and age-and sex- matched non-dilated controls. Dilated patients had lower average velocity and wall shear stress in the ascending aorta, and higher flow displacement. This study shows that individuals with dilatation have altered hemodynamics even in an early stage of the disease.
Reproducibility of wall shear stress in abdominal aortic aneurysms estimated by 4D flow magnetic resonance imaging
Authors: Aalbregt Eva , Nederveen Aart , Yeung Kak Khee , Planken R. , Balm Ron , van Ooij Pim
Published: August 2024

The aim of this study was to assess the reproducibility and inter- and intra-observer agreement for estimating wall shear stress (WSS) in abdominal aortic aneurysms (AAAs) based on 4D flow magnetic resonance imaging (MRI). Asymptomatic AAA patients were included and scanned twice with a one-week interval. Phase-contrast angiographies were acquired by voxel-wise multiplication of magnitude and phase data. Based on statistical analyses the reproducibility was good. An inverse correlation was found between WSS and lumen diameter. Both vorticity and intraluminal thrombus volume were associated with minimum WSS in AAA. 4D flow MRI is robust for estimating WSS in AAAs.
Assessment of Altered Hemodynamics in Patients with Hypertrophic Obstructive Cardiomyopathy using 4D Flow MRI
Authors: Zhao Yun , Huang Lu , Zhou Xiaoyue , Xia Liming
Published: August 2024

Hypertrophic Obstructive Cardiomyopathy (HOCM) is characterized by dynamic obstruction of blood flow in the left ventricular outflow tract. 4D flow MRI can be used for comprehensive evaluation of cardiac and aortic hemodynamics by visualization of the complex spiral LVOT 3D blood flow patterns. This study used 4D flow MRI to evaluate the degree of LVOT obstruction and the flow energy loss in patients with HOCM. The results showed that spiral flow and viscous energy loss were associated with the LVOT pressure gradient, and played a role in structural remodeling of the left ventricle.
Evaluation of neuronal feed-forward control of cerebral blood flow in negative BOLD response
Authors: Devi Ratnamanjuri , Lepsien Jöran , Lorenz Kathrin , Schlumm Torsten , Mildner Toralf , Möller Harald
Published: August 2024

The application of a simplistic model of neuronal control of changes in cerebral blood flow and oxygen metabolism to experimental data in regions of the positive and negative BOLD response, suggested differences in neuronal contributions and inhibitory control of changes in cerebral blood flow between the two regions.
Toward vessel-suppressed cerebrovascular reactivity (CVR) mapping by using crusher gradients
Authors: Cao Yimei , Fan Hongli , Xu Cuimei , Lu Hanzhang
Published: August 2024

Cerebrovascular reactivity (CVR) is an indicator of cerebrovascular reserve and provides important information about vascular health in a range of brain conditions and diseases. However, current CVR maps often have artifactual bright spots in arterial/venous areas due to the complexity of the BOLD signal mechanism. In this work, we proposed a novel CVR acquisition scheme by adding single-direction or varying-direction crusher gradients to the BOLD sequence. The results demonstrated that these modified sequences could successfully suppress large-vessel artifacts in CVR map.
Joint Estimation of Coil Sensitivity and Image by Using Untrained Neural Network without External Training Data
Authors: Saju Gulfam , Li Zhiqiang , Abiri Reza , Liu Tianming , Chang Yuchou
Published: August 2024

Training data for MRI reconstruction are difficult to be acquired in clinical practice. In addition, machine learning or deep learning-based MRI reconstruction suffers the distribution shift problem between training data and testing data. Generalization error always exists, so reconstructed images are unstable. We proposed a joint estimation of coil sensitivity and image using the prior of an untrained neural network (UNN). Coil sensitivity map improvement gradually enhances the UNN prior and the image to be reconstructed in an iterative optimization process. The method outperforms other MRI reconstruction methods by suppressing noise and aliasing artifacts.
MRI detection of gene expression in the mammalian brain using the Manganese transporter Zip14
Authors: Rallapalli Harikrishna , McCall Eleanor , Bouraoud Nadia , Koretsky Alan
Published: August 2024

We report the use of Zip14, a Manganese transporter, as an MRI-visible gene expression reporter system. Mice were intracranially injected into various brain areas with AAVs carrying a plasmid construct of Synapsin promoter for neuronal-specific expression, Zip14, and histological marker. MRI was performed immediately after, 2 weeks after, and 4 weeks after injection. Significant, large magnitude hyperintensity was observed 2 and 4 weeks after injection, but not immediately after, at the injection site and areas projecting away or towards the injection site. This gene expression reporter system is viable without the use of additional contrast agents or non-standard imaging protocols.
Identifying spreading depression during coma induction with multi-modal fMRI
Authors: Jiang Yuanyuan , Xie Zeping , Yang Wenchao , Zhang Bei , Hike David , Liu Andy , Edlow Brian , Yu Xin
Published: August 2024

We have demonstrated spreading depression as a key event contributing to coma induction following the ET-1 injection to the brainstem of rats. Multi-modal fMRI enables the whole brain functional mapping to present the spatial dynamic changes during coma induction, in particular, paired with the incidence of SD events.
A water-exchange dynamic contrast-enhanced MRI protocol optimized for AQP4 measurement in glioma
Authors: Han Guangxu , Jia Yinhang , Wang Zejun , Hsu Yi-Cheng , Bai Ruiliang
Published: August 2024

A dynamic contrast-enhanced MRI (DCE-MRI) protocol was optimized to measure transmembrane water exchange rate (kio), which was correlated kio with aquaporin-4 (AQP4) immunohistochemistry results in a rodent subcutaneous glioma model. From the acquired results, a significant correlation was demonstrated between the optimized kio and AQP4, indicating that kio measured by DCE-MRI could reveal the expression of AQP4.
2D spectral-temporal fitting of synthetic fMRS data improves the precision of fitted glutamate temporal dynamics parameters three-fold
Authors: Liu Yiling , Zhang Zhiyong , Tal Assaf
Published: August 2024

It has been suggested that fitting dynamic MRS data in tandem (2D fitting) should be more precise than conventional 1D fitting, without impairing its accuracy. Functional MRS (fMRS) is a dynamic method used for detecting endogenous metabolic changes in the brain. In this work, we implemented a 2D spectral-temporal fitting framework for the synthetic fMRS data. Preliminary experiments confirm that 2D fitting improves precision approximately three-fold compared to the conventional 1D fitting in terms of fMRS data.
Accelerated Rosette Spectroscopic Imaging with semi-LASER Localization
Authors: Joy Ajin , Emir Uzay , Macey Paul M. , Thomas M. Albert
Published: August 2024

Limiting the total data acquisition time to a clinically feasible runtime has been a major challenge in MR spectroscopic imaging. Recently rosette based non-cartesian encoding of k-space has been used for spectroscopic imaging due to their fast encoding speed and lower gradient/slew rate requirements. While rosette spectroscopic imaging has been attempted for 2D and 3D spectroscopic imaging, feasibility of undersampling the petals in rosette is not shown. In this study, we implemented a rosette 2D and 3D spectroscopic imaging sequence and shown the feasibility of acceleration factors up to 8x using compressed sensing reconstruction.
Comparison of uniform-density, variable-density and dual-density spiral samplings for multi-shot diffusion-weighted imaging
Authors: Li Guangqi , Ma Xiaodong , Li Sisi , Ye Xinyu , Börnert Peter , Zhou Xiaohong , Guo Hua
Published: August 2024

Different multi-shot spiral sampling schemes have been developed for high-resolution DWI. However, the performances of these sampling strategies such as variable-density spiral (VDS), dual-density spiral (DDS) and uniform-density spiral (UDS) have not been compared comprehensively. In this study, we compare multi-shot UDS, VDS and DDS in brain DWI in terms of inter-shot phase error correction, overall image quality and SNR performance. Both theoretical analysis and in-vivo results demonstrate that UDS exhibits the best off-resonance performance among the three spiral sampling patterns. Additionally, UDS achieves the highest SNR in diffusion imaging over the VDS and DDS acquisitions.
AcceleraTed deep-LeArning for model-free and multi-Shell (ATLAS) DWI
Authors: Martin Phillip , Altbach Maria , Bilgin Ali
Published: August 2024

In this work, we aim to accelerate diffusion weighted MRI (dMRI) by predicting diffusion -weighted images (DWIs) across different shells using deep learning (DL), while remaining independent of a diffusion-model constraint. The proposed approach enables the predictions of unacquired DWIs in multiple shells from a small set of acquired DWIs from a given shell. This relaxes the need for applying multiple diffusion gradient weightings for obtaining a fully-acquired dataset over multiple shells. Without the constraint of a diffusion model, accurate diffusion metrics over multiple diffusion models can potentially be obtained by acquiring a small number of DWIs.
Robust Complex Signal Averaging for Diffusion Weighted Imaging
Authors: Wang Xinzeng , Litwiller Daniel , Guidon Arnaud , Lan Patricia , Sprenger Tim
Published: August 2024

In the past decade, complex signal averaging has been investigated for diffusion weighted imaging to address the well-known noise floor issue. The robustness of complex signal averaging highly depends on the performance of phase correction to remove the shot-to-shot background phase variations. To achieve optimal phase correction, parameters (kernel size, regularization terms, etc.) need to be tuned for different anatomies, SNR levels and/or image size. In this work, we evaluated a deep-learning based phase correction method for various DWI applications, including brain, liver, prostate and showed improved complex signal averaging with lower noise floor and less artifacts.
Prediction for P53 Status Using Intravoxel Incoherent Motion Imaging in Rectal Cancer
Authors: Dong Deshuo , Chen Anliang , Ma Changjun , Liu Ailian , Song Qingwei
Published: August 2024

Mutant P53 promotes tumor cell proliferation, invasion, and resistance to chemotherapy. The purpose of this study was to evaluate the value of intravoxel incoherent motion (IVIM) imaging for prediction of P53 expression status in rectal cancer. The results indicate that D and f values for positive P53 status were significantly lower than those for negative P53 status, while D* was higher. The combination of D, D* and f improved diagnostic efficiency than single parameters. IVIM imaging allows non-invasive visualization and quantification of tissue composition for prediction of P53 status in rectal cancer.
T1 mapping and extracellular volume for evaluating myocardial fibrosis in animal models with ischemia with non-obstructive coronary artery
Authors: Ren Zilong , Wen Didi , Lian Jianxiu , Liu Jiantao , Huang Zhe , Zheng Minwen
Published: August 2024

To investigate whether T1 mapping and extracellular volume (ECV) can be used as predictors of myocardial fibrosis for ischemia with non-obstructive coronary artery disease (INOCA). Results showed pigs models with INOCA had higher native T1 mapping and ECV (mean native T1 mappingnormal = 1068.3 ± 111.5 ms, mean native T1 mappingINOCA = 1291.7 ± 109.2 ms, P = 0.018; mean ECVnormal = 23.0 ± 1.7 %, mean ECVINOCA = 46.6 ± 10.4 5, P = 0.006). T1 mapping technology could be a noninvasive way for assessing the myocardial fibrosis for INOCA models.
Venous blood oxygenation measurements using TRUST and T2-TRIR during hypoxic and hypercapnic gas challenges
Authors: Baas Koen , Vu Chau , Shen Jian , Coolen Bram , Strijkers Gustav , Wood John , Nederveen Aart
Published: August 2024

TRUST and T2-TRIR can be used to measure venous blood oxygenation (Yv) and oxygen extraction fraction (OEF). T2-TRIR also offers simultaneous blood T1 (T1b) measurements for hematocrit calculation in lieu of invasive blood samples. Here, TRUST and T2-TRIR were compared across a broad Yv range using hypoxic and hypercapnic challenges in healthy volunteers, while T2-TRIR-derived hematocrit estimates were compared with venipuncture results. T2-TRIR- and TRUST-derived Yv and OEF values exhibited a small constant bias (-5.4±3.5% and 6.0±4.0% respectively, both p<0.01) across all stimuli. Hematocrit by venipuncture and from T1b were unbiased but had broad confidence intervals (1.7±6.3%, p=0.20).
Performance Evaluation of Deep Learning-based Image Reconstruction for Head and Neck Imaging Protocol
Authors: Konar Amaresha Shridhar , Shin Jaemin , Paudyal Ramesh , Dave Abhay , Fung Maggie , Banerjee Suchandrima , Hatzoglou Vaios , Shukla-Dave Amita
Published: August 2024

MRI has excellent extracranial soft-tissue contrast to detect tumors in the head and neck (HN) region. Technical challenges arise due to MRI related artifacts. In routine radiological practice, HN MR imaging protocols are optimized specifically to the subsites. We aimed to evaluate the performance of the HN imaging protocol that include qualitative T1w, T2w, and quantitative diffusion MRI powered by a novel deep learning (DL) based reconstruction (recon) using the ACR and QIBA diffusion phantoms. This phantom study showed that qualitative T1w and T2w images and multiple b-value DWI data powered with DL recon substantially improves the image quality.
Background Field Inhomogeneity Correction for High-Resolution T2* Mapping of the Human Cervical Spinal Cord at 7T
Authors: Adnani Seyedeh Nasim , Mahmud Sultan Zaman , Denney Thomas , Bashir Adil
Published: August 2024

Ultra-high-field (UHF) Spinal Cord (SC) imaging could be helpful in detecting subtle pathological changes in the human SC. The increased effect of magnetic field inhomogeneity at UHF on T2* renders the quantification unreliable. Therefore, the field correction methods are critical. We have demonstrated the application of the Voxel Spread function method, to address this issue in human SC at 7T. F-term correction was applied to the pre-processed SC images, and the T2* values were reported for SC GM and WM both before and after field inhomogeneity correction. VSF reduces magnetic field inhomogeneity effects for quantitative T2* mapping in human SC.
Enhancing performance of a bio-inspired surface coil wtih a flexible metasurface for preclinical MRI at 7 T
Authors: Solis-Najera Sergio , Lazovic Jelena , Vazquez Fabian , Martin Rodrigo , Rodriguez Alfredo
Published: August 2024

A bio-inspired surface coil was built for preclinical MRI applications at 7 T. Images were acquired with and without a flexible metasurface partially cover a cylindrical phantom. Images obtained with the metamaterial showed an important improvement of coil performance. No electronic components were used for tuning the metasurface. This easy-to-implement approach offers an alternative to improve the SNR for preclinical applications at high field.
Applications of artificial intelligence-assisted compressed sensing cardiac cine in left heart function imaging: Quality and Efficiency
Authors: Zhang Zijing , FENG Fei , Qi Yulong , Zhang Hui , Cheng Guanxun
Published: August 2024

Cardiac magnetic resonance (CMR) imaging is the gold standard for non-invasive evaluation of cardiac structure and function. Conventional 2D segmented steady-state free precession cine imaging(Standrad-Cine)is widely used but the scanning time is long. Artificial intelligence-assisted compressed sensing(ACS)is a new technology that can reduce the scanning time and improve image quality. By comparing the image quality and left ventricular function (LVF) of CMR sequence based on Standrad-Cine and ACS-Cine, we found that the use of ACS-Cine can significantly reduce the scanning time while obtaining high-quality and accurate parameters images.
Time-dependent diffusion MRI study of chemoradiation treatment response in patients with HPV positive oropharyngeal carcinoma
Authors: Solomon Eddy , Baete Steven H. , Kim Joseph K. , Tam Moses , Li Zujun , Hu Kenneth , Zan Elcin , Kim Sungheon
Published: August 2024

In this study, we evaluated the time-dependence of diffusivity and kurtosis in HPV-positive oropharyngeal squamous cell carcinoma patients before and during chemo-radiation treatment, as part of a study for adaptive de-escalation of the therapy. The non-deescalated patients with less than 40% nodal shrinkage had significantly higher diffusivity and lower kurtosis at pre-treatment than the de-escalated patients with more than 40% nodal volume shrinkage. The water exchange times were longer in the de-escalated patients than in the non-deescalated patients, although not significant. The prognostic accuracy of the pre-treatment imaging parameters was between 0.7 and 0.85.
Detection of multiple sclerosis by extraction of quantitative parameters of brain tissue microstructure in ex-vivo cerebellum samples
Authors: Varma Gopal , Grant Aaron , Girard Olivier , Duhamel Guillaume , Alsop David
Published: August 2024

Extraction of quantitative parameters of brain tissue microstructure is possible with DTI, inhomogeneous MT (ihMT), and MWF MRI. We examine the ability of the parameters from these techniques to distinguish ex-vivo specimens of the cerebellum from donors with MS relative to non-MS tissue. Significant differences were found for DTI and MT/ihMT metrics in WM, but only for MT/ihMT in GM. Differences between quantitative MT parameters from fits to ihMT data were not significant.
Successful generalization for data with higher or lower resolution than training data resolution in deep learning powered QSM reconstruction
Authors: Ji Sooyeon , Park Juhyung , Shin Hyeong-Geol , Yoon Joonhyeok , Kim Minjun , Lee Jongho
Published: August 2024

A pipeline to reconstruct multiple resolution QSM data using a QSM network trained at a single resolution is proposed. The local field map is re-sampled multiple times in different spatial locations, and the re-sampled local field maps are used to reconstruct QSM maps at training data resolution. The reconstructed maps are then combined, and corrected for using a procedure named “dipole compensation”. When compared to two scenarios to reconstruct different resolution data using network trained at a single resolution, the proposed pipeline demonstrated the best performance both qualitatively and quantitatively.