bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical evaluation of k-space correlation informed motion artifact detection in segmented multi-slice MRI
Authors: Jang Ikbeom , Hoffmann Malte , Singh Nalini , Balbastre Yael , Chen Lina , Rockenbach Marcio Aloisio Bezerra Cavalcanti , Dalca Adrian , Aganj Iman , Kalpathy-Cramer Jayashree , Fischl Bruce , Frost Robert
Published: August 2024

Motion artifacts can negatively impact diagnosis, patient experience, and radiology workflow especially when a patient recall is required. Detecting motion artifacts while the patient is still in the scanner could potentially improve workflow and reduce costs by enabling immediate corrective action. We demonstrate in a clinical k-space dataset that using cross-correlation between adjacent phase-encoding lines can detect motion artifacts directly from raw k-space in multi-shot multi-slice scans. We train a split-attention residual network to examine the performance in predicting motion artifact severity. The network is trained on simulated data and tested on real clinical data.
In vivo Whole-brain Phosphoethanolamine Mapping using SLOW-EPSI at 7T
Authors: Weng Guodong , Radojewski Piotr , Turco Federico , Slotboom Johannes
Published: August 2024

In vivo detection of phosphoethanolamine (PE) using spectral editing has recently been shown to be feasible. This study shows whole-brain PE maps using SLOW-EPSI in a healthy subject with a nominal resolution of 4.3*4.3*10 mm. The result shows that the PE level is high in the cerebral cortex and low in the white matter.
EigenMRS: A computationally cheap data-driven approach to MR spectroscopic imaging denoising
Authors: Shamaei Amirmohammad , Starcukova Jana , Starcuk Zenon
Published: August 2024

The utility of MR spectroscopic imaging (MRSI) can be limited by a low signal-to-noise ratio (SNR) in practice. Averaging multiple coherent repetitions increases the SNR, but at the cost of time-consuming acquisition. Several computationally expensive approaches based on low-rank matrix approximation for denoising MRSI data have been proposed, which do not take advantage of previously acquired spectra. This work demonstrates a novel computationally cheap data-driven approach to MRSI denoising, coined EigenMRS, by learning low-rank structures of MRS data. As proof of concept, EigenMRS was tested against the simulated 1H- MRSI data, and the results showed an increase in denoising performance.
A Multicenter Study of Cervical Cancer using Dynamic Contrast-Enhanced MRI: Are Measurements of Quantitative Imaging Reproducible in Clinic?
Authors: Wang Xue , Li Shujian , Ye Zhijun , Koh Tang-San , Hou Zujun , Yan Zhihan , Han Lu
Published: August 2024

By comparing the distributions of measured DCE kinetic parameters in cervical cancer tissue by three MRI scanners in different clinical centers. It was demonstrated that (i) Each of the three scanners consistently showed similar findings on the characterization of cervical cancer microenvironment. (ii) The difference in MRI3 stemmed from keyhole imaging in the DCE protocol which could lead to underestimation of concentration of contrast media in viable tumor region. (iii) The close distribution between MRI1 and MRI2 indicated that consistent DCE quantitative metrics could be attained in scanners from different vendors if imaging protocol and data postprocessing could be standardized.
Less-distorted cervical ADC maps improved subjective diagnosis efficacy on cervical cancer and reliability of measurements
Authors: hui liu , yin liu , rong ou
Published: August 2024

Differentiation of patients with IB-IIA from those with IIB-IIC assist track treatment selection for cervical cancer. A diffusion-weighted imaging (DWI) sequence based on field-of-view optimized and constrained undistorted single shot (FOCUS) combined with multiplexed sensitivity-encoding (MUSE) technique (named FOCUS-MUSE DWI) was used in our study to explore the differentiation performance on stages of cervical cancer. We found the reliability of apparent diffusion coefficient (ADC) for FOCUS MUSE-DWI is the highest among single-shot DWI (ss-DWI), FOCUS-DWI and MUSE-DWI, and better image quality, SNR, and CNR than the former two. There was no significant difference of ADC values for four DWI sequence between IB-IIA group and IIB-IIIC, but ADC values were consistent with previous studies.
iZoom applying tilted 2D Echo-Planar RF excitation improved the image quality of reduced FOV DWI for uterine cervical cancer: a preliminary study
Authors: Takada Akiyo , Yokota Hajime , Kurosawa Ryuna , Sada Takayuki , Matsumoto Koji , Takashi Namiki , Yoneyama Masami , Wu Adam , Uno Takashi
Published: August 2024

Reduced field-of-view (rFOV) DWI is the essential sequence for the diagnosis and staging of uterine cervical cancer (CC). We compared the image quality of rFOV DWI taken with iZoom, which applies tilted 2D Echo-Planar RF excitation, and that of conventional Zoom combined with Reconstruction with Image-space Sampling (Zoom-IRIS) for CC patients. Reduced FOV DWI with iZoom showed higher image quality than Zoom-IRIS both in quantitative and qualitative evaluation. Anatomical details display and lesion conspicuity were mainly improved in quantitative evaluation. iZoom can be helpful for the diagnosis and staging of CC.
Peri-tumoural lipid composition mapping of the breast for early response to neoadjuvant chemotherapy using chemical shift-encoded imaging
Authors: Cheung Sai Man , Chan Kwok-Shing , Senn Nicholas , Sharma Ravi , McGoldrick Trevor , Gagliardi Tanja , Husain Ehab , Masannat Yazan , He Jiabao
Published: August 2024

Peri-tumoural lipid composition plays a major role in the disease progression of breast cancer, and novel chemical shift-encoded imaging (CSEI) allows rapid lipid mapping of the whole breast. We have previously observed an imbalance of peri-tumoural lipid composition in postmenopausal women with breast cancer using CSEI. Monitoring of lipid composition for early sign of tumour regression might be crucial for an accurate differentiation of patients responding to neoadjuvant chemotherapy (NACT). We hence set out to elucidate the longitudinal change in lipid composition in the peri-tumoural region and the whole breast in patients with breast cancer using CSEI.
Breast MRI during neoadjuvant endocrine therapy for patients with estrogen-receptor positive/HER2 negative breast cancer
Authors: Onishi Natsuko , Gibbs Jessica , Jones Ella , Bareng Teffany Joy , Liang Jiachao , Carmona-Bozo Julia , Li Wen , Newitt David , Ray Kimberly , Heath Courtney Lawhn , Mukhtar Rita , Joe Bonnie ,   I-SPY 2 Investigator Network,   I-SPY 2 Imaging Working Group, Esserman Laura , Chien A. Jo , Hylton Nola
Published: August 2024

This study aimed to investigate the longitudinal changes in functional tumor volume (FTV) and background parenchymal enhancement (BPE) derived from dynamic contrast-enhanced breast MRI during neoadjuvant endocrine therapy (NET). For comparison, we also evaluated a similar cohort of patients who received standard neoadjuvant chemotherapy (NAC). Similar to the NAC cohort, the NET cohort showed early changes in FTV and BPE as early as three weeks of treatment. In the NET cohort, early BPE decrease was prominent especially for patients with higher baseline BPE and premenopausal patients. These finding illustrate the potential of MRI metrics as early imaging biomarkers for NET.
Prediction of breast cancer response to neoadjuvant chemotherapy via early changes in quantitative DCE-MRI
Authors: Wang Mengyi , Zhang Xiaoling , He Shaofu , Hu Yangling , Mao LiJuan
Published: August 2024

Our study suggests that the percentage change for second visits relative to baseline of enhanced tumor volume-based imaging metrics of DCE-MRI can quantify heterogeneous changes within the tumor as an indicator of therapy response and improve prediction of PCR as early as the first treatment time point in NAC.
A new directional colormap for DTI fiber tractography and its application to bundle recognition
Authors: Zucchelli Mauro , Papageorgakis Christos , Casagranda Stefano
Published: August 2024

We propose a new tractography colormap based on the HSL model to complement the classical RGB colormap used in the field. Our colormap is based on a new feature, called "streamlines normal", an oriented vector that is computed from the tractography. The streamlines normal in combination with the HSL colormap improves tractography data visualization and can be an asset for better and faster bundle segmentation both manually and automatically.
Toward a detailed subject-specific cerebrovascular model using Arterial Spin Labeling (ASL) Magnetic Resonance Imaging (MRI)
Authors: Sharifzadeh-Kermani Alireza , Argus Finbar , Shen Jiantao , Guild Sarah-Jane , Dubowitz David , Scadeng Miriam , Condron Paul , Kwon Eryn , Holdsworth Samantha , Talou Gonzalo Maso , Safaei Soroush
Published: August 2024

Computed flows via haemodynamic models highly depend on peripheral resistances that affect the blood perfusion. To this end, finding a way to estimate these resistances is crucial for having a subject-specific model. Perfusion (CBF) maps produced by Arterial Spin Labeling (ASL)-MRI provide valuable information via which the model can be personalized. This new approach may be promising for providing blood flow measurements of the brain from ASL-CBF data in the absence of a full brain 4D flow sequence.
Dynamic associations between tonic alertness and brain activity during sleep inertia
Authors: Kung Yi-Chia , Chen Shou , Hsiao Fan-Chi , Chang Wei-Chou , Wu Changwei , Lin Ching-Po
Published: August 2024

Sleep inertia (SI) occurs during the transition from sleep to waking, accompanied by temporary hypoalertness and decreased tonic alertness around half an hour. We used the psychomotor vigilance task (PVT) to detect the dynamic alteration of tonic alertness during SI by monitoring the Cingulo-opercular network activity through simultaneous EEG-fMRI scanning. The alteration was greater when comparing the Pre PVT session to early wakefulness than to the late wakefulness, and was easily detectable under the task demands. A dynamic of tonic alertness could be observed during SI under the demands of the task.
Development of an FOD template of the older adult brain for the MIITRA atlas
Authors: Wu Yingjuan , Ridwan Abdur Raquib , Niaz Mohammad Rakeen , Bennett David A. , Arfanakis Konstantinos
Published: August 2024

A high quality FOD template of the older adult brain can enhance the sensitivity and accuracy of white matter investigations in older adults. The present work compared several FOD template construction methods for the purpose of developing a high-resolution FOD template of the older adult brain in the space of the MIITRA atlas. The preferred method employed multichannel registration based on T1w, FA and FOD information, followed by additional FOD single modality registration. The resulting FOD template exhibited high image quality, was constructed based on precisely matched FOD data, and exhibited high spatial matching to other existing MIITRA templates.
Dynamic Changes in Quantitative MRI-based Biomarkers of Alzheimer’s Disease and Its Association with Cognitive Decline – A Longitudinal Study
Authors: Fan Xiang , Cai Yuan , Liu Wanting , Shi Lin , Mok Vincent
Published: August 2024

Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) is a novel MRI-based machine-learning derived imaging biomarker for AD that is valid in detection of early AD. We selected 318 CU and MCI subjects in ADNI with four-year follow-up with 1471 serial MRI scans to assess longitudinal changes of the MRI biomarkers (i.e., AD-RAI, HV, HF, BPV, BPF) in correlation with the change in time and conversion status. We used generalized linear mixed-effects models to compute and show the predictive value. AD-RAI over time showed the highest classification accuracy for predicting converters when compared with other imaging biomarkers.
MRI of Neuroinflammation in the Brain following Meth Addiction using Multiplied, Added, Subtracted and/or Divided (MASDIR) sequences.
Authors: Condron Paul , Tayebi Maryam , Emsden Taylor , Bristow Ben , Ngārimu Tuta , McHugh Patrick , Newburn Gil , Taylor Davidson , Holdsworth Samantha , Cornfeld Daniel , Scadeng Miriam , Bydder Graeme
Published: August 2024

Keywords; Neuroinflammation, data acquisition and post processing, contrast mechanisms, white matter, drugs. MR contrast can be enhanced by exploiting the concept of tissue property filters (TPFs) by designing Multiplied, Added, Subtracted, and/or Divided Inversion Recovery (MASDIR) sequences to amplify contrast produced by small changes in white matter T1. The Divided, Subtracted IR (dSIR) sequence provides very high contrast depiction of subtle white matter changes due to disease that are not identified with standard T2-FLAIR imaging. This was demonstrated in patients with a history of methamphetamine addiction. MASDIR sequences could revolutionize the way that neuroinflammation is imaged in clinical practice.
Assessing the effects of hyperpolarized [2-13C]lactate saturation on detectable brain metabolism
Authors: Autry Adam , Vaziri Sana , Chen Hsin-Yu , Kim Yaewon , Dang Duey , Villanueva-Meyer Javier , Chang Susan , Clarke Jennifer , Oberheim-Bush Nancy , Bok Robert , Xu Duan , Lupo Janine , Vigneron Daniel , Gordon Jeremy , Li Yan
Published: August 2024

Following hyperpolarized [1-13C]pyruvate MRI studies that demonstrated insights into brain metabolism using saturation experiments, this study sought to assess whether metabolic pathways probed by [2-13C]pyruvate could similarly be interrogated. Our investigation showed that not exciting [2-13C]lactate led to a 2-fold increase in [5-13C]glutamate signal, which may indicate compartmentalized metabolism in the brain.
Mapping extraversion in brain activation patterns: a functional neuroimaging meta-analysis of resting state studies
Authors: Li Qingyuan , Wang Song , Li Xiao , Gong Qiyong
Published: August 2024

Our meta-analysis reveals that extraversion was linked with resting-state brain activity differences widely distributed across cortical and subcortical regions involved in emotion and behavioral regulation. The meta-regression results suggest an effect of gender on the association between extraversion and neural activity in the right inferior frontal gyrus. Our findings support that extraversion could lead to neural activity changes, which may be correlated with behavioral differences between extraverts and introverts.
Segmentation of Substantia Nigra, Subthalamic and Red Nuclei with a Multi-Modal Quantitative 7T MRI High Resolution Template
Authors: CABANE Alexandre , LE TROTER Arnaud , TESTUD Benoit , GRIMALDI Stephan , GUYE Maxim , RANJEVA Jean Philippe , DE ROCHEFORT Ludovic
Published: August 2024

The segmentation of brain substructures is very useful in the characterization of alterations involved in multiple diseases. From 200 7T brain MRI scan including MP2RAGE and MGRE used to generate quantitative T1 maps (qT1), R2* and QSM volumes, a pipeline was developed to create a high-resolution multi-modal template at (400 µm)3 based on these multiple quantitative imaging modalities. Preliminary results show that multi-modality allows for a more precise parcellation of the SN, RN and STH substructures.
Myelin, Iron, and Free Water Content Quantification Through BIOPHYSICSS Deep Learning
Authors: Benslimane Ilyes , Grabner Günther , Hametner Simon , Jochmann Thomas , Zivadinov Robert , Schweser Ferdinand
Published: August 2024

Clinical translation of quantitative MRI (qMRI) is challenged by the multiple dependencies MR signal has on different tissue compartments. We previously introduced a neural network designed for single subject analysis (BIOPHYSICSS-DL) that overcomes the multiple tissue dependencies of qMRI and produces maps of source content. BIOPHYSICSS-DL has previously focused to myelin and iron quantification in the brain but in this work we expand that model to include a free water compartment. The network also used exclusively quantitative MRI metrics but the expansion of this model was accomplished with weighted MRI data which is another critical step to eventual clinical adoption.
Differential patterns of automatic segmentation of 3T and 7T MRI: Implications in neuropsychiatric disease
Authors: Verma Gaurav , Choi Ki-Sueng , Mayberg Helen , Balchandani Priti
Published: August 2024

Automatic segmentation was performed on T1-MPRAGE structural MRI data acquired at 3T and 7T from 37 and 69 distinct healthy controls, respectively. Additionally, segmentation was performed on imaging acquired from 215 major depressive disorder (MDD) patients at 3T and 40 MDD patients at 7T. Of 259 segmentation-derived imaging features evaluated, 120 showed significant 3T vs. 7T differences among controls, and 153 among patients. 7T imaging metrics showed consistently lower cortical thickness and cortical gray/white matter ratios. Subcortical and cortical volumes measured at 7T were more mixed, with 7T images showing greater frontal lobe volume, but lower cortical volumes elsewhere.
Comparison of whole brain parenchyma fraction (BPF) from T1W and diffusion MRI in the assessment of CLN3, a neurodegenerative disease
Authors: Nayak Amritha , Do An N , Thurm Audrey , Soldatos Ariane , Porter Forbes , Pierpaoli Carlo
Published: August 2024

In this work, we have compared if whole brain parenchyma fraction (BPF) measured from conventionally used T1-weighted (T1W) based brain segmentation method is comparable to signal fraction attributable to parenchymal water (Par-SF) measured from method using diffusion MRI, in assessing the overall disease state of participants with CLN3, a pediatric neurodegenerative disease.
Intensity-Based Segmentation of Tumor on Multiparametric MRI to Aid Response Assessment of High-Grade Gliomas Treated with Immunoradiotherapy
Authors: Ravi Harshan , Hawkins Samuel , Stringfield Olya , Pereira Malesa , Enderling Heiko , Yu H-H Michael , Arrington John , Sahebjam Solmaz , Raghunand Natarajan
Published: August 2024

Confounding appearance of radiographic changes in recurrent high grade glioma (HGG) patients treated with multimodality immunotherapy presents a challenge to the neuro-radiologist. A clinical need exists to improve upon conventional criteria for assessment of GBM on standard-of-care (SOC; T1w, T2w, FLAIR, and T1w-enhanced) MRI to help distinguish treatment-related effects from true disease progression. We have investigated the feasibility of intensity-based segmentation of tumor tissue types on multiparametric MRI (mpMRI) to inform response assessment in HGG patients treated with bevacizumab, hypofractionated stereotactic radiotherapy, and pembrolizumab.
A general framework for analyzing the various contributions to reproducibility in brain morphometry
Authors: Dong Ruifeng , Nayak Amritha , Chan Leighton , Pierpaoli Carlo
Published: August 2024

We propose a framework for differentiating the contributions to the reproducibility in brain morphometry from the true inter-individual differences, experimental procedures, and data-processing methods. As an application, we build a linear mixed-effect model to evaluate and compare two segmentation software tools, Freesurfer and vol2Brain, in their reproducibility in measuring volumes of 32 regions of interest. For both software and for most structures under study, our approach successfully reveals the dominance of inter-subject variability over noise. Vol2Brain introduces less noise than Freesurfer for all subcortical nuclei while Freesurfer shows better performance for gray matter, cortex, cerebral white matter, and cerebellum cortex.
Pre-Excitation Gradients for Eddy Current-Nulled Convex Optimized Diffusion Encoding to Mitigate Distortion in 2D Diffusion Weighted Imaging
Authors: Middione Matthew , Loecher Michael , Cao Xiaozhi , Setsompop Kawin , Ennis Daniel
Published: August 2024

Diffusion encoding gradients produce eddy currents that cause image distortions in DWI. Twice refocused spin-echo (TRSE) and eddy current-nulled convex optimized diffusion encoding (ENCODE) mitigate eddy current-induced image distortions in DWI, but at the expense of extending the TE. Herein, we revise the original ENCODE method by playing additional pre-excitation gradient lobes (Pre-ENCODE). Using simulations, phantom experiments, and in vivo imaging we demonstrate that Pre-ENCODE mitigates eddy current-induced image distortions in DWI with a shorter TE than TRSE and ENCODE.
Motion robust and high resolution DWI utilizing the combination of Multi-shot Reduced FOV imaging with motion-compensated diffusion gradients
Authors: Wu Zhigang , Zhang Yajing , Gilbert Guillaume , Su Wengu , Zhao Yan , Wang Jiazheng
Published: August 2024

Reduced FOV imaging (rFOV) and multi-shot DWI both are very useful techniques to improve spatial resolution for detection of pancreatic lesion. However, respiratory and cardiovascular motion will introduce severe artifacts and ADC bias. Motion compensated diffusion gradients (MOCO) could be used to improve the image quality. In this study, a new sequence named MOCO-rFOV IRIS was developed, which combines the advantages of rFOV, MOCO and image reconstruction using image-space sampling function based multi-shot DWI (IRIS). Results from in vivo data demonstrated that the proposed method could be used to realize motion robust and high resolution DWI for pancreas
Gauge equivariant convolutional neural networks for diffusion MRI
Authors: Hussain Uzair , Khan Ali
Published: August 2024

One shortcoming of diffusion MRI (dMRI) is long scan times as numerous images have to be acquired to achieve a reliable angular resolution of diffusion gradient directions. In this work we introduce gauge equivariant convolutional neural network (gCNN) layers that overcome the challenges associated with the dMRI signal being acquired on a sphere instead of a rectangular grid. We apply this method to upsample angular resolution to predict diffusion tensor imaging (DTI) parameters from just six diffusion gradient directions. Additionally, gCNNs are able to train with fewer subjects and are general enough to be applied to other dMRI related problems.
Patch-CNN provides high-fidelity directional & scalar parameter estimation from 6-directional DWI robust to pathology unseen during training
Authors: Goodwin-Allcock Tobias , Genovese Guglielmo , Zaid Belen , Lehericy Stéphane , Rosso Charlotte , Gong Ting , Gray Robert , Nachev Parashkev , Palombo Marco , Zhang Hui
Published: August 2024

This work evaluates the clinical viability of Patch-CNN for estimating diffusion MRI (dMRI) parameters from only 6 diffusion-weighted images (DWIs). Machine learning (ML) has been proposed to improve fitting from 6-directional DWIs. However, directional measures, e.g. primary fibre orientation, have only been estimated using CNNs. CNNs have not yet been validated on pathology that is not contained within the training dataset. As pathological diversity is difficult to capture in typical applications, ML methods are clinically viable only if they can generalise to unseen pathology. We show that Patch-CNN may generalise to unseen pathology and estimate directional measures.
Size Matters: Automated Quantification of Acute Changes in Kidney Size with Deep Dilated U-Net Segmentation of Dynamic Parametric MRI
Authors: Klein Tobias , Gladytz Thomas , Millward Jason , Cantow Kathleen , Hummel Luis , Seeliger Erdmann , Waiczies Sonia , Lippert Christoph , Niendorf Thoralf
Published: August 2024

Deep learning algorithms enable fast kidney segmentation, which is crucial to establish renal size as a (pre)clinical biomarker for renal diseases. Tackling this challenge, a novel deep dilated U-Net (DDU-Net) was trained, validated, and tested on preclinical ground truth data, benchmarked on simulated data against an analytical model, and applied to longitudinal in vivo MRI scans acquired in rats, with pathophysiological interventions mimicking clinically realistic scenarios. Our DDU-Net reached a Dice score of 0.98 on the ground truth, outperformed the analytical approach, and facilitated rapid detection of acute changes in kidney size upon acute pathophysiological interventions.
Accelerating 2D Kidney Magnetic Resonance Fingerprinting using Deep Learning–Based Tissue Quantification
Authors: Din Huay , MacAskill Christina , Tirumani Sree Harsha , Yap Pew-Thian , Griswold Mark , Flask Chris , Chen Yong
Published: August 2024

In this pilot study, we developed and optimized a spatially-constrained convolutional neural network to accelerate the scan time for 2D kidney Magnetic Resonance Fingerprinting (MRF). Our results suggest that an acceleration factor of 3 can be achieved with the proposed method, which shortens the 2D breath-hold MRF scan from 15 sec to 5 sec. In addition, the deep learning based approach can be applied for T1 and T2 quantification of both normal renal tissues and pathologies including renal cell carcinoma.
Noninvasive assessment of the renal function, the Oxford classification and the prognostic risk stratification of IgAN by DWI and BOLD MRI
Authors: Liang Ping , Xu Chuou , Hu Daoyu , Li Zhen
Published: August 2024

Purpose To explore whether IVIM-DWI and BOLD-MRI can assess the renal function, Oxford classification and prognostic risk stratification of IgAN patients. Methods This retrospective study included 46 IgAN patients and 20 healthy volunteers for renal MRI examinations. T2* values on BOLD images and ADC, Dt, Dp, fp values on IVIM-DWI images were measured. Results: Cortical Dt generated the largest area under the curve for differentiating 5-year risk scores ≤ 10% from 5-year risk scores > 10%, and for differentiating T0 from T1/T2. Conclusions IVIM-DWI and BOLD-MRI can assess the renal function, Oxford classification, and prognostic risk stratification of IgAN patients.
Preliminary exploration of 3D-APTw imaging in renal tumor applications
Authors: Wang Xia , Jia Min , Yue Xiuzheng , Chan Queenie , Ma Ruirui , Zhang Wei , Wang Shanshan , Tian Gang , He Nan , He Jiang guang , Han Yuedong
Published: August 2024

APTw imaging focuses on cranial tumor studies with significant clinical value, with fewer studies in mid-upper abdomen, because of the movement of organs and B0 fields inhomogeneous. Previously used showed that intermittent breath-hold (IBH) could to improve the image quality of 3D-APTw imaging in healthy adults. In this study, we used the IBH respiratory compensation mode to initially explore the feasibility of 3D-APTw imaging of renal tumors. The findings suggested that 3D-APTw imaging with IBH can be not only used for imaging renal tumors, but also showed potential values in renal tumors diagnosis and differential diagnosis.
Investigation of 4D Flow CMR technique for left ventricular hemodynamics in heart failure patients
Authors: Jiaxuan Guo , Xiuzheng Yue , shan Huang , Li Zhu
Published: August 2024

The number of patients with heart failure is increasing. Our study is based on the 4D flow technique of cardiac magnetic resonance and attempts to find cardiac functional parameters that precede structural changes in the heart at the level of the ventricular inflow and outflow tracts. We have found easier methods for visualizing blood flow and have the potential to further advance clinical diagnosis.
Direct imaging of Neuronal Activity (DIANA) in Humans
Authors: Hodono Shota , Rideaux Reuben , van Kerkoerle Timo , Cloos Martijn
Published: August 2024

Here we describe our initial results attempting to observe neuronal activation in humans using the Direct Imaging of Neuronal Activity (DIANA) method. Both visual and auditory paradigms were explored. BOLD and anatomical ROI were tested and dedicated single slice control experiments were performed, but clear DIANA signals remained elusive. The translation of DIANA from animals to humans appears to be non-trivial. Nevertheless, considering the potential payoff continued effort towards this goal may be well worth it. To aid in this quest, parallel studies focused on DIANA’s ability to detect spiking and hyperpolarisation in controlled settings may be of great value.
Comparison of STEAM and sLASER to quantify acetylcarnitine at rest using long TE 1H-MRS in human skeletal muscle with a surface or birdcage coil at 7T
Authors: Veeraiah Pandichelvam , Voncken Rick , Brouwers Kim , Mevenkamp Julian , van den Hurk Job , Wildberger Joachim , Schrauwen-Hinderling Vera
Published: August 2024

Long echo time 1H-MRS has been used to determine in vivo acetylcarnitine (ACCT) concentrations in the skeletal muscle. At ultra-high field (UHF), STEAM-based 1H-MRS was used for this purpose, in combination with a knee birdcage coil. However, STEAM suffers from an inherent 50% signal loss and a knee coil often does not fit around the upper leg in obese volunteers. Here, we demonstrated that sLASER, in combination with a surface coil, provides high signal-to-noise ratio (SNR) and can be used as an alternative method at 7T to detect physiologically low ACCT concentrations at rest in both lean and obese volunteers.
High-Resolution 1H-MRSI of the Brain at 9.4T Integrating Relaxation Enhancement and Subspace Imaging
Authors: Wang Yizun , Rubakhin Stanislav S. , Lam Fan
Published: August 2024

Ultrahigh-field systems offer sensitivity and specificity advantages for metabolite mapping using MRSI. We present here a method that integrates relaxation enhancement acquisition, a unique strategy leveraging higher fields, and subspace imaging, for high-resolution 1H-MRSI at a 9.4 T system. Both in vitro and in vivo experiments have been performed to demonstrate the feasibility of the proposed method. We are able to achieve significantly enhanced SNR compared to no relaxation enhancement and produce high-quality spatially-resolved spectra and high-resolution metabolite images using subspace imaging with 0.6×0.6×2 mm3 nominal resolution in 18 minutes or 1×1×2 mm3 in 10 minutes.
Implementation of Zoom MRSI at 7T for High-resolution GABA and Glutamate Mapping
Authors: Ozyurt Onur , Rotaru Diana , Farley Nicholas , Kourtzi Zoe , Williams Guy , Emir Uzay
Published: August 2024

High-resolution neurochemical mapping using 2D zoom or reduced field of view (rFOV) magnetic resonance spectroscopy (MRSI) enables the high-resolution metabolic assessment of brain regions that is difficult to probe with standard MRSI sequences. To our knowledge this is the first study to have demonstrated the application of zoom MRSI at 7T for GABA and glutamate mapping.
Feasibility of Deep Learning Reconstruction in Prostate Multiparametric MRI: a Preliminary Prospective Study
Authors: Wang Yichen , Zhang Xinxin , Wang Sicong , Zhao Xinming , Chen Yan
Published: August 2024

In this prospective study, feasibility of deep learning reconstruction (DLR) in axial FSE-T2WI and axial reduced-FOV DWI (FOCUS DWI) were evaluated compared with standard protocols. Fast protocol with DLR substantially reduced scanning time (axial FSE-T2WI: -32.1%; FOCUS-DWI: -36.8%). Fast FOCUS DWI with DLR showed the highest SNR and CNR for prostate PZ, TZ and lesion. Fast FSE-T2WI with DLR showed the highest SNR and CNR for prostate PZ and TZ. Moreover, fast FOCUS-DWI and FSE-T2WI with DLR demonstrated equivalent or better image quality than standard images. DLR may be useful in prostate multiparametric MRI protocol optimization and high-quality image acquisition.
Perturbation loss with carrier image reconstruction: A loss function for optimized point spread functions
Authors: Lebel R. Marc
Published: August 2024

Deep learning (DL) assisted image reconstructions are becoming state-of-the art, producing better image quality and/or enabling higher acceleration rates than achievable with conventional methods. DL networks are used to mitigate noise amplification while retaining important signal characteristics. However, typical loss functions produce object-dependent noise alterations and non-uniform point-spread functions. Here we present a method for training networks that prioritizes maximizing the point spread function to ensure maximal detail retention.
Relative noise variation with Unrolled Neural Networks for Accelerated Cardiac Cine Reconstruction
Authors: Kaushik Suryanarayanan , Zhu Xucheng , Lebel Robert , Manickam Kavitha , Li Ke , Saravanan Kailash , Wiesinger Florian , Janich Martin
Published: August 2024

Deep Learning (DL) based reconstructions help alleviate the longer scan times seen in bSSFP Cine acquisitions by offering higher acceleration factors. This work analyzes the spatial and temporal variations in the noise as a function of acceleration factors in DL reconstructions of highly accelerated bSSFP Cine data.
Feasibility of Deep Learning Reconstruction in the Clinical Application of MRI for patients with Bladder Cancer： a preliminary prospective study
Authors: Zhang Xinxin , Wang Yichen , Wang Sicong , Li Min , Chen Yan , Zhao Xinming
Published: August 2024

The application of DLR significantly shortened scan times and improved the overall image quality score and image artifacts score and SNR and CNR of FSE-T2WI. DLR fast FSE-T2WI demonstrated significantly higher SNR (256.7±102.9 VS 94.7±40.8, p < 0.05) and CNR (168.0±77.3 VS 59.6±29.8, p < 0.05) and overall image quality scores (median, 4.0 vs. 3.0 for reader1 and 4.0 vs. 3.5 for reader2) than those of conventional FSE-T2WI. DLR may be useful in reducing the acquisition time of bladder MRI without compromising image quality.
Universal sequence-invariant deep learning image reconstruction for cardiovascular MR Multitasking
Authors: Hu Zheyuan , Chen Zihao , Lee Hsu-Lei , Xie Yibin , Li Debiao , Christodoulou Anthony
Published: August 2024

Cardiovascular MR (CMR) Multitasking can quantify various parameter combinations without breath-holding or ECG monitoring. Clinically practical reconstruction time is viable using supervised deep subspace learning, but it depends on sequence-specific training. Here we explore whether universal, sequence-invariant CMR Multitasking deep learning reconstruction is practical by trading temporal awareness (breadth) for added depth in spatial domain. We evaluated the performance and generalizability of both strategies by training on T1 mapping data only and testing on two datasets: a) a matched-sequence T1 mapping data; and b) a novel-sequence T1-T2 mapping data.
Design of a high power RF amplifier with configurable number of channels
Authors: Chen Jifeng , Li Ye , Shen Zhenhua , Liu Bin , Zhang Xiaoliang , Cao Bin , Liu Xin , Chu Xu , Zhen Hairong
Published: August 2024

UHF (Ultra high field) MRI requires high RF power from RF Power Amplifier (RFPA), especially for whole-body imaging1. Some studies on body imaging reported limitation on available RF power. In this study, we present works to provide RFPA with highest peak power capability known for UHF MRI with configurable number of transmit channels so as to meet different RF coil requirements. Feasibility and performance of the new method in UHF MRI was demonstrated on the bench and 5T whole-body scanner.
A Novel MRI Platform for Long-term Stem Cell Tracking In Vivo
Authors: Zhuang Keyu , Romagnuolo Rocco , Szulc Daniel , Cheng Hai-Ying Mary , Laflamme Michael , Cheng Hai-Ling Margaret
Published: August 2024

To extend our previously reported bright-ferritin cell tracking platform to monitoring stem cell therapy, we investigated tracking human embryonic stem cells transplanted intramuscularly in immune-compromised mice. With this technology, the stem cells impart a bright, T1-induced contrast. In-vitro assays of viability and pluripotency, and imaging both in vitro on cell pellets and in vivo in mice were performed. Monitoring mice on MRI over two months confirmed the ability to assess cell survival and teratoma formation non-invasively.
Assessment of mouse brain creatine kinase rate using 31P-MRS at 7 Tesla
Authors: Cherix Antoine , Tachount Mohamed , Lerch Jason
Published: August 2024

31P-MRS experiments in mouse brain are scarce and often limited to ultra-high field scanners. We have recently reported that 31P-MRS is feasible in mouse brain at 7T as well. We now tested the potential of using saturation transfer experiments in the same setting to measure the creatine kinase rate in mouse brain.
Complementarity-aware multi-parametric MR image feature fusion for abdominal multi-organ segmentation
Authors: Li Cheng , Osman Yousuf , Huang Weijian , Xue Zhenzhen , Han Hua , Zheng Hairong , Wang Shanshan
Published: August 2024

T1-weighted in-phase and opposed-phase gradient-echo imaging is a routine component in abdominal MR imaging. Organ segmentation with the acquired images plays an important role in identifying various diseases and making treatment plans. Despite the promising performance achieved by existing deep learning models, further investigation is still needed to effectively exploit the information provided by different imaging parameters. Here, we propose a complementarity-aware multi-parametric MR image feature fusion network to extract and fuse the information of paired in-phase and opposed-phase MR images for enhanced abdominal multi-organ segmentation. Extensive experiments are conducted, and better results are achieved when compared to existing methods.
Deep learning-based auto-segmentation of neck nodal metastases on longitudinal MR images using self-distilled masked image transformer
Authors: Jiang Jue , Paudyal Ramesh , Diplas Bill , Han James , Riaz Nadeem , Hatzoglou Vaios , Lee Nancy , Deasy Joseph , Shukla-Dave Amita , Veeraraghavan Harini
Published: August 2024

Manual segmentation of normal and tumor tissues on MRI is a traditional approach that is still used, but it is a very challenging and time-consuming method requiring a high level of precision and has shown inter-reader contouring variability. Therefore, semi- or fully automated segmentation algorithms are essential to segment tumors such as neck nodal metastases. The present study aimed to apply the previously developed deep learning-based self-distilled masked image transformer method for auto-segmenting neck nodal metastases on longitudinal T2-weighted MR images.
Assessing the Impact of Upstream Reconstruction Models on Downstream Image Analysis: A Workflow-Centric Evaluation
Authors: Viggiano Ben , Desai Aashna , Rubin Elka , Schmidt Andrew , Boutin Robert , Stevens Kathryn , Gold Garry , Ré Christopher , Chaudhari Akshay , Desai Arjun
Published: August 2024

Deep learning (DL) techniques have shown promise for both reconstruction and image analysis stages of MRI workflows. However, traditional benchmarking methods evaluate each stage separately. As a result, the impact of reconstruction on downstream image analysis tasks and biomarker quantification remains unknown. In this study, we explore how changing aspects of upstream reconstruction affects the downstream analysis. We find that insights from evaluating reconstruction models as a component of a broader end-to-end workflow do not correlate with conventional, task-specific image quality metrics. We use these findings to motivate the discussion of evaluating DL methods at the workflow level.
Iterative model-based Rician bias correction and its application to denoising in diffusion MRI
Authors: Tournier J-Donald , Jeurissen Ben , Christiaens Daan
Published: August 2024

Rician bias is a long-standing problem in diffusion MRI. We propose a simple iterative strategy to mitigate the problem when a voxel-wise model of the signal is available, and demonstrate its efficacy when fitting spherical harmonics and when included in a denoising strategy.
Value of Reversed Polarity Gradients and Multiplexed Sensitivity Encoding in improving diffusion weighted imaging quality of uterus
Authors: Wang Wenjuan , Zhao Wenjing , Pylypenko Dmytro
Published: August 2024

The aim of this study is to investigate the application of multiplexed sensitivity encoding diffusion weighted imaging with reversed polarity gradients in improving the image quality of uterine tumors. 10 patients with uterine lesions in our hospital were enrolled. Conventional SS-EPI DWI, MUSE DWI, and RPG-MUSE DWI sequences were employed. The subjective image quality assessment and objective data measurement of uterine lesions scanned by different DWI sequence was evaluated by three radiologists using double-blind method. The results of this study showed that RPG-MUSE DWI can greatly improve the image quality of the uterus.
Quantitative assessment of split renal function in early lupus nephritis using BOLD-MR: an initial study
Authors: Wang Ye , Hu Zexuan , He Chutong , Wei Ruili , Pang Xinrui , Liang Fangrong , Zhang Aaron , Xu Yongzhou , Yuan Shiwen , Yang Ruimeng
Published: August 2024

Lupus nephritis (LN) is one of the most severe manifestations of systemic lupus erythematosus (SLE) that can progress to end-stage kidney disease. This study aimed to detect the split-renal function changes in early-LN by using BOLD-MRI. The results demonstrated the R2*, as a biomarker for tissue oxygenation, was significantly lower in cortex and medulla in the early-LN patients compared to the healthy volunteers. Moreover, The R2* in medulla remained a considerable good power in predicting early-LN, suggesting it has the potential to be employed as a noninvasive imaging biomarker for early-LN patients with SLE.
Assessment of the relationship between APTw values and R2* and PDFF values in renal tumor
Authors: Wang Xia , Ma Ruirui , Zhang Wei , Zhao Na , Tian Gang , Yu Chanjuan , Yue Xiuzheng , Han Yuedong
Published: August 2024

Renal tumors are often containing lipid components, ischemic-hypoxia and hemorrhage. These components can be reflected by the proton density fat fraction (PDFF) and R2* levels of the mDIXON_Quant. Amide proton transfer-weighted (APTw) imaging has made breakthroughs in tumor research, however, its signal intensity is affected by many factors. This study focused on the effect of PDFF and R2* values on APTw values in renal tumors. The preliminary results showed that renal tumor APT values were correlated with PDFF and R2* values. Thus, precision APTw imaging studies of renal tumors need to consider the effects of differential composition.
Oscillatory Wall Shear Stress in patients with Bicuspid Aortic Valve and Aortic Regurgitation
Authors: Trenti Chiara , Dyverfeldt Petter , Fedak Paul , White James , Garcia Julio
Published: August 2024

Individuals with bicuspid aortic valve (BAVs) and aortic regurgitation have higher rate of aortic complications compared to individuals with stenotic and functioning BAVs. We sought to investigate wall shear stress (WSS) and oscillatory shear index (OSI) in the ascending aorta of BAVs with functioning valves, stenotic and regurgitant valves, as well as controls with tricuspid aortic valves. BAVs with regurgitation had similar WSS compared to all other groups, but OSI was almost twice as high. This finding may be related to the pendulum volume between the aorta and the left ventricle. Studying OSI may improve the understanding behind BAV aortopathy.
Hemodynamics of common iliac arteries is associated with the risk of abdominal aortic aneurysm: assessment using 4D flow MRI
Authors: Zeng Wen , Xia Chunchao , Zhang Xiaoyong , Li Zhenlin
Published: August 2024

Studies have confirmed the interaction between iliac arteries and abdominal aortic aneurysms. Four-dimensional (4D) flow MRI can reveal the hemodynamic changes of common iliac arteries in abdominal aortic aneurysm and health controls. In this study, we tried to explain the relationship between the changes of iliac artery hemodynamics and the asymmetry of the left and right iliac artery blood flow and the occurrence and development of abdominal aortic aneurysms in patients.
Exploration of age-related hemodynamic and mechanical changes in the human thoracic aorta using an atlas based approach
Authors: Piot Elodie , Duchateau Nicolas , Menut Marine , Bou-Said Benyebka , Clarysse Patrick , Douek Philippe , Kunze Karl , Botnar Rene , Boccalini Sara , Prieto Claudia , Sigovan Monica
Published: August 2024

Understanding the hemodynamic involvement in a vascular pathology requires inter-subject comparisons that are not straightforward due to variability in terms of aorta morphology. Hemodynamic atlases can facilitate detection of intra-group characteristics. We propose here a workflow to create a hemodynamic atlas using 4D Flow MRI. In addition, we propose to investigate the aorta wall stiffness using non-rigid image registration and inverse mechanical modeling. This type of analysis is expected to improve pathophysiological understanding of vascular disease, by enabling the investigation of potential correlations between hemodynamic and wall mechanical properties at each point of the aorta.
Clinical Functional MRI-derived Probabilistic Template of Primary Language Areas of Patients with Brain Tumors
Authors: Teo Jian Ming , Lee Jina , Hou Ping , Kumar Vinodh , Noll Kyle , Prabhu Sujit , Liu Ho-Ling
Published: August 2024

This study aims to develop a functional template of primary language areas based on 306 presurgical language fMRI scans from 102 patients with brain tumors. The template was constructed from voxelwise probabilistic distribution of fMRI results of three common clinical language paradigms. An independent dataset of 38 patients was used to test the template from this study and compare with a template derived from the meta-analysis of 1101 published studies. The results showed that our template agreed better with the test dataset, with significantly higher dice coefficients in both anterior and posterior primary language areas, comparing with the literature-based template.
Comparing 7 T FID-CRT-MRSI with 3 T MRF in High-Grade Gliomas
Authors: Lazen Philipp , Sharma Sukrit , Cadrien Cornelius , Marik Wolfgang , Roetzer-Pejrimovsky Thomas , Niess Eva , Hingerl Lukas , Gruber Stephan , Strasser Bernhard , Kiesel Barbara , Wöhrer Adelheid , Preusser Matthias , Furtner Julia , Bogner Wolfgang , Widhalm Georg , Trattnig Siegfried , Rössler Karl , Hangel Gilbert
Published: August 2024

We compared 7T MRSI-derived metabolic ratios with T1 and T2 maps from MR fingerprinting in a cohort of glioma patients by defining hotspots and calculating Dice similarity coefficients (DSCs) between them and a segmentation. Notable high DSCs were 0.799 for tCho/NAA vs T2 and 0.753 for Gln/NAA vs T1. We also investigated values for T1, T2, and metabolite ratios in tumors, hotspots, and a control region, with the median relaxation times being T1=1610 ms and T2=79 ms in the tumor, and T1=964 ms and T2=46 ms in NAWM.
2H MR measurement of amino acid uptake in glioblastoma multiforme
Authors: McClendon Samantha , Song Kyu-Ho , Ge Xia , Ackerman Joseph , Garbow Joel , Beeman Scott
Published: August 2024

Glioblastoma (GBM) brain tumors are among the most lethal of all human cancers, with a median survival of ~15 months. Standard-of-care radiologic methods fail to detect infiltrating GBM, which leads to undertreatment. We report a 2H MR method to better resolve/characterize GBM based on its enhanced uptake of branched-chain amino acids (e.g., leucine). We measure relaxation time constants for deuterated leucine in agarose phantoms and show the ability to detect d10-leucine at ~200 mM in a 4x4x4 mm3 voxel in phantoms. Finally, we demonstrated 2H MR measurement of enhanced deuterated leucine uptake in a rodent model of GBM.
Accurate Estimation of Background Phase in Virtual Conjugate Coil Expansion Combined with Wave Encoding
Authors: Liu Congcong , Cui Zhuoxu , Jia Sen , Qiu Zhilang , Liu Xin , Zheng Hairong , Liang Dong , Wang Haifeng
Published: August 2024

The wave encoding model with virtual conjugate coil (Wave-VCC) extension can provide more powerful MRI-accelerated imaging performance. However, estimating the background phase covering the full frequency range is un-tractable by only acquiring the middle auto-calibration signals (ACS) line during reconstruction. Here, combining a neural network without training, a new method to generate more accurate background phase in Wave-VCC is proposed. Including ablation experiments and comparison, experiments were carried out to verify the feasibility and performance of the proposed methods, respectively.