bluuebunny/crossref_metadata_2025 huggingface dataset:
Predict intraoperative hemorrhage during curettage treatment of cesarean scar pregnancy using free-breathing GRASP DCE-MRI
Authors: Wang Zhigang , Yang Fengleng , Liu Chunying , Wang Fang , Xiong Ying Ying , Zhang Qiang , Chen Meining , Lai Hua
Published: August 2024

Cesarean scar pregnancy (CSP) is a rare form of ectopic pregnancy with curettage often being the first-line treatment. However, uncontrollable intraoperative hemorrhage is one of common complications during the treatment, making its prediction a critical for treatment planning. The aim of this study was to explore the feasibility of using GRASP DCE-MRI to characterize peritrophoblastic perfusion and predict intraoperative hemorrhage for CSP. The study found that presurgical Wash-in, TTP, iAUC, Ktrans, and Ve were significantly different between hemorrhage and non-hemorrhage groups identified during curettage. The ROC-AUC analysis further demonstrated their capability of serving as intraoperative hemorrhage predictors for CSP.
Quantitative volumetric mapping of intracellular pH in the human brain at 7 T using endogenous CEST-MRI: A proof of principle study
Authors: Boyd Philip , Kroh Florian , Breitling Johannes , Franke Vanessa , Ladd Mark , Bachert Peter , Goerke Steffen , Korzowski Andreas
Published: August 2024

In this study, our method for quantitative pHi mapping using endogenous CEST-MRI was successfully transferred to examinations of the human brain at B0=7T. Applicability in vivo was demonstrated in n=3 healthy volunteers, showing an overall median pHi,CEST of 7.00 and 6.96 for gray and white matter, respectively. In order to proof the plausibility of the presented approach, the obtained pHi,CEST maps were additionally validated directly in vivo via 31P MRSI at 7T, showing an overall median pHi,31P of 7.02 and 7.01 for gray and white matter, respectively. Consequently, reliable CEST-based pHi mapping is now also possible in the human brain.
Alterations of white matter connectivity in essential tremor with MR-guided focused ultrasound thalamotomy
Authors: Wang Xiaoyu , Lou Xin
Published: August 2024

This is important research to assess the effects of MRgFUS thalamotomy on white matter connectivity in ET. Results showed that MRgFUS might act the topologic properties on brain networks. Rich-club and small-world organizations exist in HC and ET. The right orbital part of the superior frontal gyrus and right putamen were identified as a hub in the ET group only, whereas the left putamen identified as hubs in the group only. Importantly, gamma and sigma correlated tremor improvement after MRgFUS thalamotomy, playing a role in reflecting tremor improvement for clinical treatment.
Normal left ventricular flow dynamics in a paediatric population assessed by 4D Flow MRI
Authors: Callaghan Fraser , Burkhardt Barbara , Geiger Julia , Buechel Emanuela Valsangiacomo , Kellenberger Christian
Published: August 2024

4D flow MRI provides a rich dataset that can make analysis challenging. A new technique of left ventricle (LV) registration is presented and compared with established techniques for analysis of flow dynamics in a normal paediatric population. Averaging of group flow dynamics in a common space permits additional analysis, complementary to established techniques. Our technique demonstrated flow dynamics on a common LV space and identified subtle differences in LV velocities between normal male and female subjects of a paediatric population. This represents a new tool in 4D flow data analysis for potential biomarker development.
Unsupervised denoising of prostate DWI
Authors: Pfaff Laura , Wagner Fabian , Hossbach Julian , Preuhs Elisabeth , Gadjimuradov Fasil , Benkert Thomas , Nickel Dominik , Wuerfl Tobias , Maier Andreas
Published: August 2024

The diagnostic value of diffusion-weighted MR images is often degraded by their inherently low signal-to-noise ratio (SNR), especially for high b-values. In this context, the application of learning-based denoising methods is difficult since most methods require noise-free target images for training. We show how to denoise and evaluate diffusion-weighted MR images in a self-supervised manner by exploiting an adapted version of Stein’s unbiased risk estimator and specific properties of the data. Both quantitative and qualitative evaluations indicate increased performance over state-of-the-art unsupervised denoising methods.
Geometric Constrained Deep Learning for Motion Correction of Fetal Brain MR Images
Authors: Ma Laifa , Chen Liangjun , Zhao Fenqiang , Wu Zhengwang , Wang Li , Lin Weili , Zhang He , Lin Kenli , Li Gang
Published: August 2024

Robust motion correction of fetal brain MRI slices is crucial for fetal brain volume reconstruction. However, conventional methods can only handle a limited range of motion. Hence, a deep learning model based on prior geometric constraints is proposed to predict the motion of 2D slices. It consists of a global and a relative motion estimation network. Sharing features between two networks make the model to learn more unique feature representations for global motion correction. Moreover, we present a control point-based approach to simulate complex fetal motion trajectories. The experimental results demonstrate that the proposed method is effective and efficient.
GROG Gridding using modified VGG-16 CNN model for Non-Cartesian MR Image Reconstruction
Authors: Atif Muhammad , Arshad Madiha , Bilal Yumna , Inam Omair , Shahzad Hassan , Omer Hammad
Published: August 2024

Self-Calibrating GROG (SC-GROG) is a gridding algorithm that maps the k-space MRI data from non-Cartesian to Cartesian domain. The main limitation of SC-GROG is its computational cost to calculate the GROG weights. This paper proposes a customized deep learning framework (based on VGG-16 CNN model) to calculate the 2D-Gridding weight sets for SC-GROG. Initially, the proposed model is trained on human head images, and later fine-tuning is performed using Golden-angle radial Liver Perfusion datasets. The results show that the proposed method significantly reduces the computation time for the estimation of GROG weights while maintaining the image quality.
Automatic Localization of EEG Electrodes from MR Structural Images
Authors: Rezaei-Dastjerdehei Mohammadreza , LeVan Pierre
Published: August 2024

The localization of EEG sources is one of the fundamental approaches to facilitate the interpretation of EEG data. However, the accuracy of source localization depends on the exact knowledge of the position of the electrodes on the scalp, which currently requires time-consuming and/or expensive approaches. Here, an automatic method is proposed that retrieves the electrode positions by localizing the curvature changes in T1-weighted MRI images caused by electrodes. The results show an average detection sensitivity of ~96.4%, with an average position error of 4.23 mm for all subjects.
A robust image analysis pipeline for high fidelity kurtosis and tensor fitting of 1.2mm isotropic infant brain diffusion MRI
Authors: Zhu Tianjia , Ouyang Minhui , Sindabizera Kay , Kim Juri , Huang Hao
Published: August 2024

High-resolution infant diffusion MRI (dMRI) data poses specific challenges such as severe motion artifacts, long acquisition time for multi-shell data, and low signal-to-noise (SNR). We present a robust image analysis pipeline for high fidelity kurtosis and tensor fitting of 1.2mm isotropic infant brain dMRI that allows us to efficiently analyze in-vivo dMRI data despite the considerable technical challenges specific to infant imaging. State-of-the-art preprocessing including slice-to-volume motion correction and susceptibility-by-movement correction is combined with advanced self-supervised learning-based denoising to produce high fidelity diffusion tensor and diffusion kurtosis fitting.
Identification of Subject-Specific Motion Variations via Atlas-Based Deformation Refinement from Real-Time MRI
Authors: Xing Fangxu , Jin Riwei , Gilbert Imani , El Fakhri Georges , Perry Jamie , Sutton Bradley , Woo Jonghye
Published: August 2024

Dynamic magnetic resonance imaging has become increasingly efficient at capturing speech deformations of the velopharyngeal region in real time. With previously developed dynamic vocal tract atlases, quantification of group deformation statistics of a population in speech has become possible in a common atlas space. However, subject-specific deformation characteristics as an underlying property tend to be hidden in the spatial and temporal alignment process of atlas construction. We present a registration-based deformation characterization method that extracts subject-specific motion variations in two layers of registration steps. A dataset of fifteen human subjects is processed to reveal unique deformation patterns of each subject.
Simultaneous mapping of glycogen and phosphocreatine in human skeletal muscle by saturation transfer MRI
Authors: Bie Chongxue , Zhou Chao , van Zijl Peter , Yadav Nirbhay , Wu Yin , Zheng Hairong , Zhou Yang
Published: August 2024

Glycogen and phosphocreatine (PCr) are essential metabolites for maintaining cellular ATP levels. Recent reports show the possibility of PCr mapping in skeletal muscle using CEST MRI but glycogen levels measured using this approach have been inconclusive. Here we report the high-resolution mapping of glycogen and PCr in human skeletal muscle based on relayed nuclear Overhauser effects (glycoNOE) and CEST, respectively. Results at 5T show homogeneous distributions of glycogen and PCr in the calf at levels corresponding to biopsy. Exciting possible applications include localized studies of cellular energetics and noninvasive in situ evaluation of exercise and muscle metabolism in humans.
CEST Mapping from Undersampled Z-spectra in the Brain Using Deep Learning
Authors: Cheema Karandeep , Han Pei , Lee Hsu-Lei , Han Hui , Xie Yibin , Christodoulou Anthony , Li Debiao
Published: August 2024

Chemical exchange saturation transfer (CEST) imaging uses radio frequency pulses at different frequency offsets to generate CEST maps. In this work, we used deep learning to calculate CEST maps from steady-state CEST (ss-CEST) images at undersampled frequency offsets, reducing the total scan time by a factor of 3.5. The Z-spectrum was undersampled by selecting the top 15 frequency offsets from Fisher information gain analysis. Fitting results from the proposed method were compared with those from multi-pool fitting with fully sampled Z-spectrum. We showed that it is feasible to reconstruct CEST maps from undersampled, field uncorrected ss-CEST images.
Early-stage mapping of macromolecular tissue content in the brain of APPNL-F­ mouse model using nuclear Overhauser enhanced (NOE) MRI
Authors: Swain Anshuman , Soni Narayan Datt , Wilson Neil , Juul Halvor , Benyard Blake , Kumar Dushyant , Nanga Ravi Prakash Reddy , Haris Mohammad , Reddy Ravinder
Published: August 2024

This study utilizes nuclear Overhauser effect (NOE) MRI to map early-stage changes in macromolecular brain content of an APPNL-F model of Alzheimer's disease. NOEMTR and rNOE are the quantitative metrics used to assess lipids and proteins in major regions of the mouse brain. Following ROI analysis, there is a statistically significant decrease in NOEMTR contrast between wild-type and AD mice in the hippocampus, with rNOE showing a similar trend with a strong suggestion of statistical significance. Overall, this study shows that NOE MRI can be used to successfully detect changes in the macromolecular content of mouse brain tissue through NOEMTR.
Assessing CSF secretion by measuring net velocity of CSF in the human subarachnoid space using displacement encoding with stimulated echoes at 7T.
Authors: van der Voort Elisabeth , van der Plas Merlijn , Zwanenburg Jacobus
Published: August 2024

Continuous secretion and absorption of cerebrospinal fluid (CSF) cause a net velocity that is important for cerebral clearance. However, measuring this net velocity is hampered by the cardiac and respiratory cycle which induce additional CSF motions. We show, with both simulations and in vivo measurements, that net velocity of CSF in the subarachnoid space can be measured using displacement encoding with stimulated echoes (DENSE), when contributions from heartbeat and respiration are accounted for during the analysis. Measured net velocity was 4.41±1.57 µm/s (6 subjects). Further research is needed to properly account for possible phase wraps in the measurements.
Application of the CT ABC/2 Method for Measuring Intracranial Bleed Volume on mcTFI QSM MRI.
Authors: Sharma Ria , Kim Geunwon , Selim Magdy , Thomas Ajith , Filippidis Aristotelis , Wen Yan , Spincemaille Pascal , Wang Yi , Soman Salil
Published: August 2024

Intracranial hemorrhage (ICH) volume estimation is important for patient management. ABC/2 is a validated method of volume estimation using CT (2). Differing appearance of blood across MRI imaging techniques and blood age limits the ability of MRI to evaluate ICH volume. The QSM technique mcTFI has features well suited to bleed measurement. In this study we show that the widely used ABC/2 CT technique for ICH volume measurement applied to mcTFI QSM MRI yields ICH volumes strongly correlated with those obtained using CT.
Axonal abnormalities in deep brain nuclear pathways across multiple neurotransmitter systems in de novo Parkinson’s disease patients
Authors: Shih Yao-Chia , Seow Pohchoo , Wang Hu-Lin , Kuek Aeden Zi Cheng , Hartono Septian , Yan Sui-Hing , Tan Eng King , Chan Ling Ling
Published: August 2024

The present study systematically and comprehensively reviewed the axonal pathways projecting from the deep brain nuclei that are emerging targets for treating Parkinson’s disease (PD). We tracked 124 deep brain nuclear pathways across different neurotransmitters systems in the high angular HCP-1065 diffusion MRI template using diffusion MRI tractography. With the trajectories of these pathways, we successfully used Parkinson's Progression Markers Initiative (PPMI) diffusion tensor imaging (DTI) data to characterize abnormal DTI changes in noradrenergic and serotoninergic pathways in relation to the severity of non-motor symptoms in de novo PD patients, suggesting a wide neural involvement of clinical PD manifestations.
Major structural abnormalities in the alpha-synuclein mouse model of Parkinson’s Disease revealed with MR Microscopy at 16.4 T
Authors: Baião Ruxanda , Outeiro Tiago , Shemesh Noam
Published: August 2024

Parkinson's disease (PD) is associated with irreparable damage to dopaminergic neurons due to α-synuclein (aSYN) inclusions. Dopaminergic pathways include the nigrostriatal, mesolimbic, mesocortical and tuberoinfundibular systems that play vital roles. Thus, dysregulations of dopamine function may lead to brain-wide consequences. Apart from a mouse PD model of injected aSYN1, brain morphology alterations in genetic mouse models have not been described in detail using MRI. Here we explore brain morphological differences between PD models and healthy controls, crucial for further understanding of the disease. We find major morphological abnormalities in areas such as Lateral Ventricles, Corpus Callosum and the surrounding Cortex.
Impact of gadopiclenol on decision making in patients with brain metastases
Authors: Essig Marco , Giordano Frank , Sarria Gustavo
Published: August 2024

New gadolinium-based contrast agents (GBCAs) with high relaxivity could have an impact on decision making and treatment planning of brain metastases (BM). In this post-hoc analysis, patients with BM who underwent two separate magnetic resonance imaging (MRI) examinations, one with gadopiclenol and one with gadobenate dimeglumine, both at 0.1 mmol/kg, were included. This study showed that gadopiclenol at the dose of 0.1 mmol/kg improved detection and characterization of BM, and led to a change in treatment decisions in 2 of 13 patients.
Dual-site and dual-vendor comparison of cerebral oxygen extraction fraction by ASE and TRUST MRI in identical participants
Authors: Ying Chunwei , Waddle Spencer , Igwe Nkemdilim , Patel Niral , Song Alexander , Balamurugan Charu , Jordan Lori , Jiang Dengrong , Lu Hanzhang , Ford Andria , Donahue Manus , An Hongyu
Published: August 2024

We evaluated dual-site and dual-vendor test-retest repeatability and reproducibility of cerebral oxygen extraction fraction (OEF) measured with asymmetric spin echo (ASE) and T2-Relaxation-Under-Spin-Tagging (TRUST) MRI. The intra-site intra-class correlation coefficient (ICC) of global ASE-OEF were 0.952 and 0.919 for each site. The intra-site ICC of TRUST-OEF based on the bovine and the HbA model were 0.810 and 0.792 at site 1, and 0.928 and 0.924 at site 2. The inter-site inter-vendor correlation was 0.849 for ASE-OEF and 0.814 for TRUST-OEF based on the bovine model. ASE-OEF was significantly associated with TRUST-OEF (p<0.001).
The Use of Quantitative Metrics and Machine Learning to Predict Radiologist Interpretations of Image Quality and Artifacts
Authors: McCullum Lucas , Wood John , Gule-Monroe Maria , Liu Ho-Ling Anthony , Chen Melissa , Shah Komal , Chasen Noah Nathan , Kumar Vinodh , Hou Ping , Stafford Jason , Chung Caroline , Ahmad Moiz , Walker Christopher , Yung Joshua
Published: August 2024

A dataset of 3D-GRE and 3D-TSE brain 3T post contrast T1-weighted images as part of a quality improvement project were collected and shown to five neuro-radiologists who evaluated each sequence for image quality and artifacts. The same scans were processed using the MRQy tool for objective, quantitative image quality metrics. Using the combined radiologist and quantitative metrics dataset, a decision tree classifier with a bagging ensemble approach was trained to predict radiologist assessment using the quantitative metrics. The resulting AUCs for each classification task were above 0.7 for all combinations of sufficiently represented classes and qualitative image metrics.
Repeatability of very low field MRI
Authors: Poojar Pavan , Geethanath Sairam
Published: August 2024

Low-field MR scanners are low-cost, portable, and requires lesser space. In this study, we performed in vitro phantom repeatability study on a 48 mT scanner (Multiwave technologies) by scanning the phantom 3 sessions in a day (11 AM, 2 PM, and 5 PM) at 3 locations. During each scan, we measured the temperature, humidity, and F0 to see their effect on the image. We scanned 9 sequences in the study to monitor noise, F0 and B0. The difference in temperature and humidity was determined for each session. The line intensity profilesrevealed that VLF scanner produces consistent B0 maps and qualitative images.
Application of diffusion imaging and dynamic contrast-enhanced MRI in evaluating the proliferation status of endometrial carcinoma
Authors: Wang Xuejia , Liu Wangyi , Zhang Gaiyun , Yan Ruifang , Shang Jie , Wang Kaiyu , Guo Jinxia , Han Dongming
Published: August 2024

Intravoxel incoherent motion (IVIM) is able to reflect the true diffusion, microcirculatory perfusion, average diffusion, and structural complexity in tissues. Dynamic contrast-enhanced MRI (DCE-MRI) can be used to analyze the dynamic distribution of contrast agents through the pharmacokinetic model to quantitatively detect the blood supply of biological tissues. Our results showed that IVIM and DCE-MRI-derived parameters such as D, α, Ktrans, and Kep were associated with Ki-67 status in EC, and the combination of D and Kep may serve as a superior imaging marker for the identification of low-proliferation and high-proliferation EC.
Quantitative Magnetisation Transfer Imaging using bSSFP to assess diffuse myocardial fibrosis.
Authors: Pleva Luke , Farrant John , Miller Christopher , Naish Josephine
Published: August 2024

Patients with chronic kidney disease often suffer from cardiac complications where increased diffuse myocardial fibrosis is present. Gadolinium is contraindicated in these patients, so cannot benefit from techniques such as ECV. We present a bSSFP based quantitative magnetisation transfer technique to assess diffuse myocardial fibrosis through the calculation of a pool size ratio and compare against ECV. 6 bSSFP images, T1, and T2 maps were acquired where a two pool model was fitted. No significant correlation between PSR and T1 in healthy patients was found. Significant correlations were found between PSR and T1 and PSR and ECV in clinical patients.
Adiabatic Null Passage for on resonance magnetization transfer preparation
Authors: Abbasi-Rad Shahrokh , Norris David
Published: August 2024

On-resonance bound pool saturation is the most efficient way of generating MTC. However, it suffers from excessive direct free water saturation due to RF pulse instabilities, and potential T2-weighting. We proposed a time-reversed adiabatic pulse (adiabatic null passage) for on-resonance MT preparation, by reversing the time-domain phase modulation function of a symmetric adiabatic pulse at its mid-point. We compared the MTC performance of ANP with binomial pulses using their MTR images. MTR values were reported through lines crossing CSF, showing high values at GM/WM and zero at CSF voxels. ANP improved the excessive saturation at regions with high B0 inhomogeneity.
Asymmetric magnetization transfer ratio of locus coeruleus with sleep disorder: A 7T MRI study
Authors: Yu Wenwen , Chu Ying-Hua , Xie Changyong , Chen Shuanghong , Zhang Jianping , Yang Zidong , Wang He , Qiao Yuchuan
Published: August 2024

Neuromelanin (NM), mainly found in locus coeruleus (LC), is a well-known biomarker for neurodegenerative diseases such as Parkinson's disease (PD) and can be detected with neuromelanin-sensitive MRI (NM-MRI). However, whether NM content is associated with sleep disorders is largely unclear. We acquired 3D turbo flash MTC images from 20 normal and four dyssomnia adult males in a 7T scanner to examine the relationship between the sleep quality scores and the NM content in LC. Our preliminary results reveal that the magnetization transfer ratio (MTR), an indicator of NM concentration, of bilateral LC is significantly asymmetric in the dyssomnia group, and the mean value of MTR is lower in the left LC and higher in the right LC in dyssomnia group than normal group.
Optimization and validation of Creatine- and Glutamate-CEST weighted imaging in the human brain at 7T
Authors: Schmitz-Abecassis Bárbara , Najac Chloé , Plugge Jaimy , van Osch Matthias , Ercan Ece
Published: August 2024

Amine chemical exchange saturation transfer (CEST) is highly sensitive for imaging metabolites in vivo. However, it lacks specificity. We aimed to develop and validate optimal CEST protocols to image creatine and glutamate in the human brain at 7T. Simulations were used to define optimal acquisition parameters, followed by in vitro validation. The optimal B1rms and total saturation (tsat) parameters were determined for creatine (B1rms = 2.5μT & tsat = 1500ms) and glutamate (B1rms = 3.5μT & tsat = 1000ms). These protocols were then used in healthy volunteers to investigate the correlation of glutamate- and creatine-weighted CEST with magnetic resonance spectroscopy results.
Mapping Cortical Diffusion Variations with Normal Aging Using DTI: The Validity of the Tensor Interpretation
Authors: Sun Yutong , Chad Jordan , Chen J. Jean
Published: August 2024

Aging-related changes in diffusion as measured by diffusion MRI (dMRI) of the white matter (WM) are often interpreted as being driven degeneration of myelinated axons and neurites, but the validity of this tensor (DTI) interpretation of the dMRI signal has never been tested in the cortex. In this study, age-related cortical diffusion variations were assessed using metrics derived from DTI and from the orthogonal-moment diffusion-tensor decomposition (DT-DOME) method. We demonstrate that the tensor interpretation of aging-related dMRI variations are most likely inadequate in the cortex.
Quantification of Thalamic Volume in Multiple Sclerosis: From the Multicenter INNI Dataset Towards the Clinical Application
Authors: Storelli Loredana , Pagani Elisabetta , Pantano Patrizia , Tedeschi Gioacchino , De Stefano Nicola , Rocca Maria Assunta , Filippi Massimo
Published: August 2024

Thalamic atrophy has been found since the earliest phases of multiple sclerosis (MS). However, this measure is not included in clinical practice, due to the time-consuming manual segmentation and technical challenges. By comparing thalamic segmentations from three available automatic methods in a multicenter dataset, we found that the inclusion of fractional anisotropy maps facilitated the automatic identification of thalamic boundaries increasing robustness of the results. In particular, the multimodal approach (FSL-MIST) showed a better capability to detect small longitudinal variations of thalamic volumes in MS patients and a better correlation with another relevant MRI measure such as the lesion volume.
Quantification of oxygenation levels within biocompatible hydrogels subcutaneously implanted in rats
Authors: Sugamura Yuka , Kodibagkar Vikram , Emerson Amy , Weaver Jessica
Published: August 2024

Cell therapy has the potential to repair irreversible pathologies including infarction and diabetes. High survival rate of the delivered cells is essential for effective treatment, where cell oxygenation is a critical factor. Biocompatible hydrogels are often used as cell delivery vehicles. Here, we propose an approach to quantify the oxygen availability that the cells encapsulated in biocompatible hydrogels experience after cell transplantation. In this study, we demonstrate the feasibility of assessing the pO2 within the hydrogels implanted in rats by combining the hydrogel with a previously developed magnetic resonance imaging (MRI) -based tissue oximetry technique.
Demonstration of motion-dependent magnetic field inhomogeneity in the kidneys and its retrospective correction for renal DWI
Authors: Gilani Nima , Mikheev Artem , Brinkmann Inge , Basukala Dibash , Benkert Thomas , Kumbella Malika , Babb James , Chandarana Hersh , Sigmund Eric
Published: August 2024

Echo planar imaging is highly affected by field map inhomogeneity distortion artifact. Field map inhomogeneity has shown to be motion dependent in the kidneys. In the present work, we propose an alternative method for correction of magnetic field inhomogeneity for renal DWI in respiratory-resolved fashion. Specifically, we collect a series of forward and reverse phase encoded b=0 images to sample kidney motion caused by breathing, map the spatial and respiratory phase dependence of the magnetic field inhomogeneity, and correct each image of free-breathing DWI series according to their respiratory phase.
Association of Ki-67 With Metabolite and Lipid Levels in High Grade Breast Cancer Patients based on Correlated MR Spectroscopic Imaging and Biopsy
Authors: Joy Ajin , Saucedo Andres , Joines Melissa , Lee-Felker Stephanie , Sarma Manoj , Sayre James , Dinome Maggie , Thomas M. Albert
Published: August 2024

Five-dimensional (5D) echo-planar correlated spectroscopic imaging (EP-COSI) combines 2 spectral and 3 spatial dimensions to record two dimensional (2D) correlated spectroscopy (COSY) spectra in multiple regions in multiple slices. In this study, multiple 2D COSY spectra were recorded from breast cancer patients by 5D EP-COSI within practical scan time durations using non-uniform undersampling of one spectral and two spatial dimensions, and compressed sensing-based reconstruction. Different metabolite and lipid ratios were quantified and its association with Ki-67 metric was studied. Findings of this study showed statistically significant association of metabolite and lipid levels with Ki-67 measures in breast cancer patients.
The application of R2 star map of enhanced T2 star weighted angiography (ESWAN) in diagnosis of ovarian cancer
Authors: Song Qingling , Li Ye , Liu Ailian
Published: August 2024

Ovarian cancer is the leading cause of death of gynecological malignant tumors, however, most of BEOTs can be completely cured. The treatment and prognosis of ovarian cancer and BEOTs are very different, so it is very important to accurately distinguish ovarian cancer from BEOTs
Machine learning models using T1-mapping and arterial spin labeling images to identify Alzheimer’s disease and mild cognitive impairment
Authors: Li Shengyong , Wang Xiaonan , Wang Yida , Song Yang , Yang Guang
Published: August 2024

To investigate the added value of T1-mapping to arterial spin labeling (ASL) for computer-aided early diagnosis of Alzheimer’s disease (AD). A total of 97 (45 AD/24 mild cognitive impairment (MCI)/38 normal control (NC)) people were enrolled retrospectively. We extracted features from 24 automatically segmented brain regions based on T1-mapping and ASL MR images and constructed three radiomics models to differentiate AD-NC/MIC-NC/AD-MCI, for which the radiomics models achieved a favorable prediction performance with the AUCs of 0.921/0.764/0.727, respectively.
Reproducibility of quantitative 1H-decoupled, NOE-enhanced 31P-MRS in the human brain at 3 T.
Authors: Svensen Magnus , Dölle Christian , Brekke Njål , Espeland Heidi , Tvedten Nora , Seland John Georg , Riemer Frank , Tzoulis Charalampos
Published: August 2024

1H-decoupled NOE-enhanced 31P-MRS has promising applications in the diagnosis and stratification of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease and amytrophic lateral sclerosis (ALS) due to its ability to longitudinally and noninvasively measure changes to cell metabolism and energy conversion, which is heavily involved in these diseases. To aid clinical translation, this study focuses on assessing the reproducibility of 1H-decoupled NOE-enhanced 31P-MRS by measuring the resonances of metabolites involved in neural energy metabolism.
Autocorrelation of the fMRI signal dynamically changes during different brain states
Authors: Golestani Ali , Bouffard Nichole , Moscovitch Morris , Barense Morgan
Published: August 2024

The autocorrelation (AC) of fMRI signal is affected by brain function and state. We used fMRI data acquired during working memory, mathematical computation, visual attention, and rest, and showed that the AC signal of gray matter dynamically changes across different task blocks. The dynamic AC (dAC) can be used to estimate brain-state changes with high accuracy. Classifier accuracy is correlated with the task performance; Subjects with better task performance have better accuracy in the dAC-based brain state classification. This study shows that the AC of the fMRI signal over time dynamically changes by the cognitive processes.
The value of diffusion kurtosis imaging in evaluating the mild cognitive impairment of occupational aluminum workers
Authors: Xu Wenji , Wang Xiaochun , Zhang Hui , Tan* Yan
Published: August 2024

In this work, we focused on the Al-exposed workers and confirm the findings that DKI can discriminate MCI from NC, furthermore we assess the severity of cognitive impairment in Al-exposed workers, and find the MK, Kr, MD and FA values are correlated with MoCA scores，which may provide quantitative imaging biomarkers for Al-exposed MCI workers.
Diffusion tensor subspace imaging (DiTSI) delineates small fibers and gray matter microstructure invisible to single-encoding techniques
Authors: Hutchinson Elizabeth , Galons Jean-Pierre , Comrie Courtney , Solders Seraphina , Serrano Geidy , Beach Thomas , Galinsky Vitaly , Frank Lawrence
Published: August 2024

Double diffusion encoding (DDE) MRI provides unique sensitization to microscale anisotropy although scalar representation of DDE data is challenging. The diffusion tensor subspace imaging (DiTSI) framework generates metrics from DDE images. In this study, post-mortem human brain tissue specimens were imaged and comparative analysis found that DiTSI but not DTI was able to provide distinct contrast in gray matter regions and at the gray/white interface. Additionally, small cranial nerve fibers of the brain stem were detectable using DiTSI, but not DTI or NODDI approaches and also showed remarkable abnormalities in Alzheimer’s disease tissue that were absent for DTI.
Quantitative Gradient Recalled Echo (qGRE) MRI enables preatrophic neurodegeneration measurement in a mouse model of Alzheimer’s Disease
Authors: Tomaszewski Michal , Sukstansky Alexander , Haley Hyking , Meng Xiangjun , Miller Corey , Yablonskiy Dmitriy
Published: August 2024

There is an unmet need for non-invasive technique for measurement of neurodegeneration in Alzheimer’s Disease (AD). Quantitative Gradient-Recalled-Echo (qGRE) MRI showed promise to address this in patients through quantification of tissue specific R2* relaxation showing neurodegeneration before atrophy. Here qGRE is optimized and applied for the first time to measure progression of this preatrophic neurodegeneration in Tg4510 mouse model of AD. Histological neuronal density quantification and test-retest measurements validated R2* measurements. We showed significant decrease in normalized median hippocampus R2* between 3, 5 and 6 month-old Tg4510 mice. The method can be applied in AD drug discovery and model development.
Fixel based analysis to investigate white matter alterations in individuals with Mild cognitive impairment and Alzheimer’s disease
Authors: Bhattarai Anjan , Maillard Pauline , DeCarli Charles , Fan Audrey
Published: August 2024

We investigated fibre tract-specific changes in the whole-brain white matter in individuals with Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) using Fixel Based Analysis (FBA). The results show significant reduction in microstructural fibre bundles in AD, in regions including splenium of the corpus callosum, fornix, and the uncinate fasciculus. FBA-derived measures, including fibre density (FD), and combination of fibre density and cross-section (FDC) demonstrated sensitivity in detecting microstructural white matter alterations in AD. These findings highlight the utility of FBA as a potential biological marker for providing valuable insights into pathophysiologic changes in AD.
Reproducibility of Diffusion Microstructures Over Different Diffusion Gradient Directionalities
Authors: Shah Apurva , Saini Jitender , Pal Pramod , Ingalhalikar Madhura
Published: August 2024

Medical imaging can offer several clinically valuable biomarkers which require accuracy across the acquiring technologies. Our study investigated the variability and reliability of diffusion microstructures over different diffusion gradient direction schemes, including high angular resolution diffusion imaging sequences and a parallel slice acquisition technique. The study's results demonstrated the 20-directional parallel slice acquisition clinically feasible sequence for standard DTI analysis with less variability and more reliability in matrices, while multishell sequences are more suitable for microstructural and tractography analysis.
Disrupted Functional Connectivity of the Visual Cortex in Dysthyroid Optic Neuropathy Due to Thyroid-Associated Ophthalmopathy
Authors: Liu Ping , Jiang Gui-Hua , Zheng Wan-Yi
Published: August 2024

Dysthyroid optic neuropathy (DON) due to thyroid-associated ophthalmopathy (TAO) is characterized by visual dysfunction and with a risk of blindness. Visual cortex is crucial for visual information, and visual impairments can affect brain activity. We investigated visual cortex functional connectivity (FC) alterations in DON and its associations with visual performance. The DON showed disrupted FC in the visual cortex, and the FC in primary rather than the secondary visual cortex associated with clinical parameters. It helps to uncover the neurological mechanisms underlying visual dysfunction and provides insight into novel therapeutic regimens to slow or prevent the neuropathy.
Comparison of image-based and statistical approaches for brain volumetry harmonization
Authors: Lu Yuan-Chiao , Dewey Blake , Chou Yi-Yu , Greenman Danielle , Shinohara Russell , Reich Daniel , Prince Jerry , Butman John , Pham Dzung
Published: August 2024

Image harmonization approaches have been proposed for reducing the variation of brain image measurements in studies involving acquisitions from multiple scanner protocols and hardware. This study compares two harmonization methods, DeepHarmony, a deep learning-based image synthesis approach, and ComBat, a statistical batch correction tool, based on their ability to yield consistent brain volume measurements from two different T1-weighted acquisitions. Our study showed that DeepHarmony outperformed the ComBat approach, although both approaches significantly improved consistency when compared to unharmonized images.
Robust thalamic nuclei segmentation from T1 MRI data
Authors: Vidal Julie , Danet Lola , Péran Patrice , Pariente Jérémie , Pfefferbaum Dolf , Sullivan Edith , Barbeau Emmanuel , Saranathan Manojkumar
Published: August 2024

This work presents a methodology for thalamic nuclei segmentation from T1w MRI. Thalamus Optimized Multi-Atlas Segmentation (THOMAS), which was originally developed for white-matter nulled (WMn) MPRAGE, is adapted for standard T1 MRI by employing synthesis techniques to make the T1 images closer to WMn contrast. Robustness is tested across image contrast, MRI manufacturer, and field strength.
Improving Early Post-Operative Glioblastoma Segmentation With Semi-Supervised Deep Learning
Authors: Luque Lidia , Skogen Karoline , MacIntosh Bradley , Emblem Kyrre , Larsson Christopher , Vik-Mo Einar , Bjørnerud Atle
Published: August 2024

Improving automatic segmentation of glioblastoma on early post-operative MRI is key to study the effect of resection volumes on patient outcomes. We curate a dataset of over 700 MRI examinations, of which 87 include annotations, and train a supervised and a semi-supervised deep-learning model. Semi-supervision improves the segmentation of the high-intensity FLAIR signal with 3% to a Dice score of 0.83 (p=0.031), while the segmentation of the enhancing tumor increases with 9% to 0.55 (p=0.056). However, enhancing tumor segmentations show high variability, possibly due to imperfect annotations. Segmentation of enhancing tumor on early post-operative MRI remains a challenging task.
Deep-learning auto-segmentation and subtype classification of pituitary adenoma based on MRI radiomics
Authors: Lin Bing-Fong , Lin Dao-Chen , Lu Chia-Feng
Published: August 2024

Pituitary adenoma (PA) accounts for approximately 15% in intracranial neoplasms. The classification of PA generally based on the hormone level of blood as the gold standard test, while the analysis of hormone condition using neuroimaging biomarkers was less explored. Accordingly, our study developed a model to automatically segment PA and further used the quantitative and non-invasive MRI technique as image biomarkers to classify the three types of hormone pattern, focusing on corticortroph, gonadotroph, and plurihormonal type. We aimed to provide a feasible classification model based MRI to benefit the clinical management of patients with PA.
Correlation of Monopolar ADC and Bipolar ADC measurements to MRE Estimates in Healthy Human Kidney
Authors: McClanahan Gregory , Kolipaka Arunark
Published: August 2024

Kidney disease and injury can be assessed using tissue stiffness measurements determined by Magnetic Resonance Elastography (MRE), a method that uses MRI. Similarly, diffusion measurements such as apparent diffusion coefficient (ADC) can also provide useful information regarding tissue health. Our goal is to assess the health of the cortex, medulla, and whole kidney by comparing ADC measurements from monopolar and bipolar diffusion gradient schemes against MRE derived stiffness values. Preliminary results indicate a strong correlation between MRE derived stiffness values and monopolar derived ADC measurements and a fair correlation between MRE derived stiffness values and bipolar derived ADC measurements.
Evaluation of PC-MRI Flow in Adults Using a Deep Learning-Based Reconstruction Trained on Pediatric Data
Authors: Middione Matthew , Oscanoa Julio , Mao Xianglun , Ruiz Christina , Salerno Michael , Vasanawala Shreyas , Ennis Daniel
Published: August 2024

We have previously trained a deep learning-based (DL) reconstruction for 2D PC-MRI using fully-sampled (n=194) raw k-space pediatric datasets. This DL-based reconstruction provided up to 9x undersampling with ≤5% error in accuracy and precision of peak velocity and total flow. Herein, we analyze this pediatric trained DL-based reconstruction in adult volunteers (n=3) and adult patients (n=8) and show that our DL-based reconstruction provides ~5% error in accuracy and precision of peak velocity and total flow for up to 7x undersampling.
Potential of diffusion fMRI for detecting white matter activity in the human brain
Authors: Nguyen-Duc Jasmine , Olszowy Wiktor , Lopez Jonathan Patino , Jelescu Ileana
Published: August 2024

Diffusion functional Magnetic Resonance Imaging (dFMRI) may be used to study the white matter activation in a more direct way than BOLD. The aim of this work is to extract the decrease in apparent diffusion coefficient (ADC) in the white matter observed in real data, and compare to that in a simulation of realistic axon swelling. Results suggest that the decrease is of low amplitude (<0.5%) but nonetheless detectable.
PIFN EPT: MR-Based Electrical Property Tomography Using Physics-Informed Fourier Networks
Authors: Yu Xinling , Serralles Jose , Giannakopoulos Ilias , Liu Ziyue , Daniel Luca , Lattanzi Riccardo , Zhang Zheng
Published: August 2024

We introduce physics-informed Fourier networks (PIFNs) for Electrical Properties (EP) Tomography (EPT). Our novel deep learning-based method is capable of learning EPs globally from noisy magnetic resonance (MR) measurements, i.e, the magnitude of the magnetic transmit field and the transceive phase. Our proposed method also provides noise-free transmit field reconstructions. Two separate Fourier neural networks are used to efficiently estimate the transmit field and EPs at any location. We show that PIFN EPT accurately infers the EPs distribution of an inhomogeneous phantom from noisy simulated measurements.
A-Eye: Towards a large-scale MRI-based model of the complete eye
Authors: Barranco Jaime , Kebiri Hamza , Esteban Óscar , Sznitman Raphael , Stachs Oliver , Langner Sönke , Franceschiello Benedetta , Cuadra Meritxell Bach
Published: August 2024

This work comparatively evaluates two approaches for the automated segmentation of eye structures from 3D T1-weighted MRI data of the whole human head (N=1210). Quantitative results on a validation sub-set with manual annotations provide accurate results for lens and globe and set the first median Dice (DSC) benchmarks for optic-nerve (0.91), muscles (0.58 to 0.76) and fat (0.67 and 0.75). The ability of our framework to automatically extract state-of-the-art measurements, such as the axial length, paves the way to accurately identify and compute new biomarkers of the eye via MRI.
Deep Learning-based Prostate Lesion Segmentation and Classification Using Haralick Texture Maps on MR images
Authors: Le Dang Bich Thuy , Narayanan Ram , Sadinski Meredith , Nacev Aleksandar , Venkataraman Srirama
Published: August 2024

By quantifying pixel relationships from frequencies of local signal intensity spatial variations, Haralick texture features have shown promise for prostate cancer detection. In this study, axial, T2-weighted MR images combined with extracted Haralick texture feature maps were used in a deep learning framework to identify lesion locations and predict Gleason Grade. Results demonstrate potential of Haralick texture features to segment and classify prostate lesions with AUC/sensitivity/specificity of 0.87/0.923/0.776 on patient-level evaluation.
DIMOND：DIffusion Model OptimizatioN with Deep learning
Authors: Li Zihan , Bilgic Berkin , Lee Hong-Hsi , Ying Kui , Liao Hongen , Huang Susie , Tian Qiyuan
Published: August 2024

The accurate estimation of diffusion model parameter values using non-linear optimization is time-consuming. Supervised learning methods using neural networks (NNs) are faster and more accurate but require external ground-truth data for training. A unified and self-supervised learning-based diffusion model estimation method DIMOND is proposed. DIMOND maps diffusion data to model parameter values using NNs, synthesizes the input data from the predictions using the forward model, and minimizes the difference between the raw and synthetic data. DIMOND outperforms conventional ordinary least square regression (OLS) and has a high potential to improve and accelerate data fitting for more complicated diffusion models.
Three-Dimensional Multifrequency MR Elastography: clinical application for Chronic Kidney Disease
Authors: Pi Shan , Scott Jonathan , Li Yin , Wen Huiquan , Murphy Matthew , Chen Jingbiao , Yin Meng , Chen Jun , Glaser Kevin , Ehman Richard , Peng Hui , Wang Jin
Published: August 2024

Chronic kidney disease (CKD) is increasing in incidence and prevalence worldwide around the world, and early detection of CKD is a major challenge. MR elastography (MRE) is a noninvasive technique capable of quantifying the mechanical properties of tissue that has shown potential for assessing kidney diseases. Our results showedthe stiffness and damping ratio were significantly correlated with eGFR and biopsy score in CKD patients. The stiffness and damping ratio also decreased along with the progression of CKD. MRE using 60-Hz and 90-Hz vibration frequencies can provide potential quantitative biomarkers for evaluating kidney function and pathological injury in CKD patients.
Preliminary exploration of the influence of B0 drift caused by the change of examination orientations on renal APT images
Authors: Zhang Wei , Wang Xia , Ma Ruirui , Zhao Na , Tian Gang , Yu Chanjuan , Jia Min , Yue Xiuzheng , Han Yuedong
Published: August 2024

Amide proton transfer-weighted (APTw) is a promising molecular imaging technique that has been employed in clinics for the detection and grading of tumors. APT value is easily influenced by B0 inhomogeneity causing image artifacts; This variation becomes more complex in abdominal motion organs than that in the brain. This study focused on the effect of variation in B0 field drift with different examination orientations on renal APT image quality. The results showed when head-first and foot-first scanning were used on 3D-APT imaging of normal kidneys, the change of B0 drift on the quality of renal APT image should be noticed.
Hemodynamic analysis of intracranial aneurysms before and after flow diverter stents implantation based on 4D Flow MRI
Authors: Liu Yuxin , Wei Haining , Bing Tian , Yuxi Hou , Fu Mingzhu , Li Rui
Published: August 2024

Intracranial aneurysm has become an important issue because of the high morbidity and the high mortality rate due to aneurysm rupture. Recently, the flow diverter stent has been considered as an effective device for the treatment of aneurysms by modifying the hemodynamics of the aneurysm. 4D Flow MRI can can offer three-dimensional visualization of blood flow pattern and a comprehensive analysis of hemodynamics. In this study, we calculated and analyzed the hemodynamics in aneurysm hemodynamics before and after the implantation of flow diverter stents based on 4D Flow MRI.
Evaluation of diastolic ventricular interdependence using simultaneous left and right heart transvalvular real time phase contrast CMR
Authors: Thalén Simon , Sörensson Peder , Giese Daniel , Sigfridsson Andreas , Ugander Martin
Published: August 2024

Diastolic ventricular interdependence occurs in several clinical settings, most notably pericardial effusion and constrictive pericarditis. It is measured using Doppler echocardiography or invasive cardiac catheterization where the respiratory variation in velocity or pressure is measured. In pericardial effusion it is an early sign of hemodynamic significance which is not always correlated to the volume of effusion. In constrictive pericarditis, it is used to separate constrictive and restrictive physiologies. In this study a method to measure diastolic ventricular interdependence by simultaneously quantifying the respiratory variation in mitral and tricuspid early inflow velocities using real time phase contrast CMR is presented.