bluuebunny/crossref_metadata_2025 huggingface dataset:
Benefit of Vessel Size/Architecture Imaging with DSC-MRI for Differentiation of Tumor Recurrence versus Pseudoprogression in Glioma Patients
Authors: Teo Jian Ming , Johnson Jason , Pokhylevych Halyna , Lano Kinsey , Hou Ping , Wang Xinzeng , Liu Ho-Ling
Published: August 2024

Vessel Size Imaging was performed on twenty-five glioma patients to obtain voxel-wise relative vessel size index and peak shift maps. This study aimed to investigate if relative vessel size index and difference in peak shift between lesion vs normal appearing white matter voxels will assist in differentiating pseudoprogression vs tumor recurrence for post-treatment gliomas. It was shown that AUC and accuracy increases when incorporating rVSI and difference in peak shift.
Ultra-high-field 7T Neonatal Proton MRS and Metabolite Relaxation Times
Authors: De Vita Enrico , Yanez-Lopez Maria , Price Anthony , Bridgen Philippa , Malik Shaihan , Quirke Megan , Tomi-Tricot Raphael , Rutherford Mary , Hajnal Joseph , Arichi Tomoki
Published: August 2024

We present 1H-MRS results from a pilot cohort of newborn infants, acquired on a 7T system. Whilst a customised approach is required for patient preparation and sequence calibrations, our preliminary data points to highly improved sensitivity and data quality at ultra-high field compared to typical spectra from adults at the same field or newborn infants at lower field strengths. We also report initial estimates of T1 and T2 for the main metabolites in the neonatal brain at 7T.
qDWI-Morph: Motion-compensated quantitative Diffusion-Weighted MRI analysis for fetal lung maturity assessment
Authors: Zaffrani-Reznikov Yael , Afacan Onur , Kurugol Sila , Warfield Simon , Freiman Moti
Published: August 2024

Quantitative analysis of fetal lung Diffusion Weighted MRI (DWI) data shows potential in providing quantitative imaging biomarkers for assessing fetal lung maturation. However, fetal motion during the acquisition impairs the accuracy and robustness of the analysis. We introduce qDWI-morph, an unsupervised deep-neural network architecture for motion correction and quantitative DWI (qDWI) analysis. We simultaneously estimate the qDWI parameters and the motion model by minimizing a bio-physically-informed loss. The qDWI-morph achieved an improved correlation between qDWI parameters in the fetal lung with the gestational age (R-squared=0.32) over baseline analysis without motion correction (R-squared=0.13) and our network with registration loss solely (R-squared=0.28).
Reducing femoral flow artefacts in radial MR Fingerprinting: A comparison of two methods applied to prostate imaging
Authors: Sørland Kaia , Trimble Christopher , Bathen Tone , Elschot Mattijs , Cloos Martijn
Published: August 2024

High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streaking artefacts from flow in the femoral blood vessels, distorting quantitative T1 and T2 measurements. We here compare two approaches to mitigate these artefacts, namely incorporating regional saturation bands in the MRF sequence (Sat-MRF) or applying region-optimized virtual coils to suppress signal from select spatial regions before image reconstruction (ROVir-MRF). Results from seven asymptomatic volunteers show that both methods efficiently reduce signal in the region of the femoral vessels, but there are differences in retained prostate signal to noise ratio and sensitivity to T1.
Correlation of quantitative synthetic mapping imaging with cervical squamous carcinoma pathology
Authors: Zhao Qi , Pan Zhihua , Jin Mingli , Yu Kebin , Jiang Yin , Zhang Miaoqi
Published: August 2024

Clinical and pathological staging are vital for management of Cervical squamous carcinoma (CSC). In this study, using synthetic MR technique, we investigate quantitative T1, T2 and PD measurements in different clinical and pathological stage groups. Performance of those quantitative measurements in diagnosing poorly-differentiated CSC is also investigated. We find T2 values are higher in late clinical stage CSC. Results also show a correlation between quantitative measurements and the degree of pathological differentiation. ROC analysis demonstrate that T1 and T2 values can differentiate poorly-differentiated CSC from intermediate and well differentiated CSC1.
Latent Diffusion Models Allow Generation of Synthetic Breast MRI DCE-MIPs
Authors: Folle Lukas , Kapsner Lorenz , Maier Andreas , Uder Michael , Ohlmeyer Sabine , Bickelhaupt Sebastian
Published: August 2024

The training of neural networks for classification or segmentation of medical images requires large amounts of training data. Sharing of these datasets is commonly difficult due to legislation and privacy constraints of medical data. In this work, we demonstrate the utility of latent diffusion models that allow the generation of synthetic samples of dynamic contrast-enhanced breast MRI-derived maximum intensity projections of subtraction series. Whilst the image quality of the generated data is high as demonstrated by a radiologist evaluation, further steps are envisioned to derive specific compounds of data, e.g., BI-RADS, FGT, or BPE classes.
Towards Prospective Free-Breathing Abdominal Magnetic Resonance Fingerprinting
Authors: Kretzler Madison , Li Xinzhou , Bittencourt Leonardo Kayat , Griswold Mark , Boyacioglu Rasim
Published: August 2024

A Pilot Tone (PT) based comparison study is presented for abdominal free-breathing MRF using a previously validated PT extraction and vendor developed extraction methods. The initial steps towards prospective processing of the data for immediate availability of the free-breathing MRF quantitative maps on the console are demonstrated. In vivo comparison results for various free-breathing patterns are shown with consistent agreement between respiratory motion in PT extraction methods. Extraction of the respiration signal from PT via the vendor reconstruction software is the first step towards prospective free-breathing abdominal MRF.
Inline calculation of Extracellular Volume Maps using Cardiac Magnetic Resonance Fingerprinting
Authors: Fyrdahl Alexander , Castaings Jenny , Johansson Rebecka Steffen , Chow Kelvin , Nickander Jannike , Seiberlich Nicole , Hamilton Jesse
Published: August 2024

This work describes a pipeline for fully inline generation of T1, T2 and extracellular volume (ECV) maps from cardiac Magnetic Resonance Fingerprinting (MRF) data. Reconstruction of multi-parametric tissue property maps using cardiac MRF have recently been made possible directly on the scanner by replacing the need to perform Bloch equation simulations with a neural network. MRF-derived T1, T2 and ECV values were acquired and compared to MOLLI and T2p-SSFP in 5 successive clinical patients.
Characterization of age- and gender-dependent differences in intervertebral disc strain using 3D-GRASP MRI under static mechanical loading
Authors: Menon Rajiv , de Moura Hector , Kijowski Richard , Regatte Ravinder
Published: August 2024

The goal of this study was to assess the effect of age and gender in IVD characterization using a multiparameter MR Fingerprinting technique that can quantify T1, T2 and T1rho in a clinically feasible time. Seventeen healthy subjects were recruited. The goal of this study was to assess the effect of age and gender in IVD characterization using a multiparameter MR Fingerprinting technique that can quantify T1, T2 and T1rho in a clinically feasible time. This study suggests that the use of MR fingerprinting is a useful tool to gain insights to pathology resulting in IVD degeneration.
B1+ inhomogeneity mitigation in slice-selective excitation at 7T with a single-channel RF coil augmented by ΔB0 shim array fields
Authors: Zhang Molin , Guryev Georgy , Arango Nick , Stockmann Jason , White Jacob , Adalsteinsson Elfar
Published: August 2024

We explored the utility of shim array fields in the mitigation of in-plane B1+ inhomogeneity for a slice-selective excitation at 7T and achieved better magnitude of transverse magnetization compared with birdcage transmit using conventional single-channel RF excitation. Approximately 2:1 range of B1+ was mitigated, at the cost of increased peak RF power, shim array current demands up to 20 A, and minor out-of-slice sidelobes.
Tailored multi-dimensional partial saturation pulses for inner/outer-volume spoiled steady-state imaging
Authors: Nielsen Jon-Fredrik , Setsompop Kawin
Published: August 2024

We propose to use short (~1–1.5ms) multi-dimensional spatially selective RF pulses that saturate unwanted signal regions in spoiled gradient echo (SPGR/FLASH/T1-FFE) imaging. These pulses can be inserted at regular intervals in the sequence, e.g., immediately before each imaging excitation pulse. By reducing signal contamination from outside the region of interest (ROI), these pulses should enable more rapid and robust T1- and T2*-weighted imaging in many body and neuro applications.
WHIRLED PEAS: Analytical Equations for Spiral Trajectories and Matching Gradient Waveforms
Authors: Pipe James
Published: August 2024

This work introduces exact time-dependent analytical solutions, for both gradient waveforms and k-space trajectories, for an optimized spiral-based imaging strategy based on maximum frequency, perpendicular slew rate, and gradient magnitude constraints.
DeepRF for simulatneous multislice pulses
Authors: Kim Jiye , An Hongjun , Oh Chungseok , Bilgic Berkin , Lee Jongho
Published: August 2024

DeepRF1 is a recently proposed RF pulse design method2-5 using deep reinforcement learning and optimization, generating an RF pulse defined by a reward (e.g., slice profile and energy constraint) from self-learning. Here, we proposed an improved algorithm for DeepRF that incorporates a modulation function to design an simultaneous multislice6 RF pulse. The new algorithm is tested and compared with the original multiband9 pulses, reporting reduced RF energy while preserving the characteristics of the original slice profile. Additionally, a multiPINS8 like inversion pulse is designed to demonstrate the usefulness of DeepRF for a non-constant slice selective gradient.
Double-echo phase-incrementing SSel-MQC (pi-SSelMQC) in biomarker imaging with full signal recovery and excellent lipid and water suppression
Authors: He Qiuhong , Yuan Hong , Shih Yen-Yu
Published: August 2024

A double-echo pi-SSelMQC method was developed to recover 100% biomarker signals, as compared to spin-echo pulse sequences, with excellent water and lipid suppression. Signals from both ZQ→DQ and DQ→ZQ coherence transfer pathways were detected. By synchronization of phase-encoding steps and RF phase increments of either MQ-preparation or MQ-transfer pulse, the biomarker images from different MQ-pathways were resolved and shifted away from residual lipid and water signals. Full lactate and polyunsaturated fatty acids (PUFA) signals were recovered in pi-SSelMQC imaging using yogurt phantoms, vegetable oil, and murine 344SQ lung tumors grown subcutaneously on the right thigh of syngeneic 129X1/SvJ male mice.
Virtual Scanner Games
Authors: Tong Gehua , Ananth Rishi , Stockmann Jason , Negnevitsky Vlad , Menküc Benjamin , Alipour Akbar , Vaughan John , Geethanath Sairam , Verma Gaurav , Verma Gaurav
Published: August 2024

Access to MRI in low-resource regions is often limited by the lack of local expertise required to sustain long-term MR operation. To help develop interest and understanding in a wider audience from a younger age, we developed Virtual Scanner Games. This web application can be distributed by USBs to run locally and provides eight educational interactive games to introduce MR fundamentals to students at the high school level or higher.
Simulation tool for non-Fourier MRSI reconstruction
Authors: Graf Carina , Rodgers Christopher
Published: August 2024

With the wider availability of ultra-high field MR systems, metabolic imaging using MRSI is a fast-developing area of research. Frequently used sequences use non-uniformly sampled trajectories to achieve high-acceleration factors e.g. concentric-ring trajectories (CRT). In this work, we demonstrate the from-scratch implementation of a simulation and reconstruction tool for CRT-MRSI using (1) a regridding, (2) an iterative L2 linear solver as well as (3) applying the non-uniform FFT implementation from the BART-toolbox to simulated non-cartesian MRSI data with a known Fourier-transform pair. The exact sampled data permits the evaluation of the impact of different reconstruction implementations.
Novel 3D Post-Processing for 1H Magnetic Resonance Spectroscopy: Fast and Accurate Metabolite Ratios
Authors: Mugler Dale
Published: August 2024

Brain tumor metabolic maps are one application of non-invasive MR Spectroscopy (MRS), although there are many other areas of patient treatment and surgery planning that would benefit from improved MRS analysis. A fast, accurate new method for MRS is used here to estimate the ratio of Choline to NAA from simulated spectra modeled on those near a brain tumor, using simple formulas for determining the FID amplitudes that relate to metabolite intensities and concentrations. No approximate numerical integration is required. The time of computation of 0.052 seconds per voxel speeds the construction of a metabolic 3D brain map.
GPU-accelerated JEMRIS for extensive MRI simulations.
Authors: Nurdinova Aizada , Ruschke Stefan , Stelter Jonathan , Gestrich Michael , Karampinos Dimitrios
Published: August 2024

Bloch simulations is a powerful tool in MRI research and education as it allows predicting the signal evolutions in magnetic resonance experiments for various applications. However, Bloch simulations require solving ordinary differential equations for the whole spin ensemble and can thus become infeasible for realistic scenarios with large total number of spins. Therefore, the present work investigates the potential of a GPU-based implementation for accelerated Bloch simulations as an extension to the open source Juelich Extensible MRI Simulator (JEMRIS) in comparison to the existing MPI CPU implementation.
The value of whole volume radiomics machine learning model based on multi-parameter MRI in predicting triple negative breast cancer
Authors: Xu Tingting , Zhang Xueli , Hua Ting , Tang Guangyu , Zhang lin , Zhao Xiance
Published: August 2024

43 TNBCs and 84 Non-TNBCs were allocated in this retrospective study. The lesions were manually segmented with ITK-SNAP software then whole volume radiomics features were extracted with Radcloud radiomics platform based on DCE-MRI and ADC maps, respectively. Three prediction models were constructed by using support vector machine (SVM) classifier, including Model A (based on the selected features of ADC maps), Model B (based on the selected features of DCE-MRI), and Model C (based on the selected features of both combined). The radiomics features model combining DCE-MRI and ADC maps can improve the diagnostic performance of predicting TNBC.
MRI biomarkers of neurofluid production and egress provide support for aberrations in the neurofluid circuit in Huntington’s disease
Authors: Hett Kilian , McKnight Colin , Eisma Jarrod , Hernandez Adreanna , Leguizamon Melanie , Elenberger Jason , Considine Ciaran , Claassen Daniel , Donahue Manus
Published: August 2024

The overall goal of this work is to apply novel MRI methods, sensitive to CSF production and clearance, to test fundamental hypotheses regarding altered neurofluid circulation in patients with Huntington’s disease (HD). In participants with HD and healthy age- and sex-matched controls, we applied multi-modal MRI to investigate deviations of neuroimaging biomarkers of the neurofluid circuit at different locations: choroid plexus, cerebral aqueduct, and PSD. Analyses show a significant increase in ChP volume and PSD volume, and a decrease in ChP perfusion and CSF net flow, in HD participants relative to healthy controls.
Associated high-order resting-state functional connectivity network for diagnosis of schizophrenia
Authors: Shi Dafa , Zhang Haoran , Wang Guangsong , Ren Ke
Published: August 2024

Schizophrenia (SZ) is one of the most prevalent mental disorders; however, its accurate diagnosis is difficult in clinical practice. Currently, the underlying mechanism of SZ remains poorly understood. The associated higher-order functional connectivity (HOFC) which constructed based on the conventional FC is promising for understanding pathological changes of brain connectome. In our study,we found the model constructed with associated HOFC outperformed the model constructed with conventional FC. SZ-related brain regions were widely distributed in frontal, parietal, insula, occipital, subcortical, and limbic lobes, which are the core brain areas of the subcortical, fronto-parietal, sensorimotor, limbic, and default mode networks.
Volumetric analysis of Brain Regions: A cross-sectional study on a large healthy dataset
Authors: Akbari Nasrin , Garg Saurabh , Nguyen Thanh-Duc , Basar Saqib , Fatehi Mostafa , Chodakiewitz Yosef , Attariwala Rajpaul , London Sean , Hashemi Sam
Published: August 2024

Cross-sectional neuroimaging studies have indicated hemispheric asymmetry, gender differences and a decline in brain volume with advancing age. However, these studies often have a small sample size (≤ 500) and unbalanced groupings, resulting in contradictory findings that might not be reproducible. Precise estimates on a large cohort will facilitate the assessment and quantification of brain volume, resulting in improved diagnostics and establishing statistical norms. In this study we analyze 6739 individuals to draw normative conclusions about typical patterns of age-related brain changes. We provide whole-brain and regional volume aging-curves for males and females for raw and head-size adjusted data.
Longitudinal Modeling of Stroke using Stochastic Distances and NODDI Diffusion Model
Authors: Sharma Anuja , DiBella Edward
Published: August 2024

Limited prior work has explored longitudinal modeling of human brain stroke using advanced diffusion techniques. We aim to address this gap by analyzing longitudinal stroke data from diffusion spectrum imaging for modeling and predicting clinical markers of stroke recovery. Our proposed data analysis method uses a mixed-effect model which exploits stochastic distances from these images for improved regression model statistics and handling of imbalanced, inconsistent longitudinal data. We also demonstrate that this aids in differentiating between population-level and patient-level effects and the corresponding key contributing predictors at each of these levels.
Magnetic resonance imaging radiomics to differentiate ovarian sex cord-stromal tumors and primary epithelial ovarian cancers
Authors: Meiying Cheng , Shifang Tan , Tian Ren , Zitao Zhu , Kaiyu Wang , Lingjie Zhang , Lingsong Meng , Xuhong Yang , Zhexuan Yang , Xin Zhao
Published: August 2024

Ovarian sex cord-stromal tumors (SCSTs) are rare nonepithelial neoplasms that usually are benign or at early stages, but sometimes they are confused with malignant tumors such as epithelial ovarian cancers (EOCs). We constructed five models including clinical model, conventional MR model, traditional model, radiomics model and mixed model based on logistic regression classifier to distinguish SCSTs and EOCs. The performance of each model was evaluated. The radiomics approach showed excellent prediction results, and the mixed model stood out among all the models.
Evaluation of renal function in chronic kidney disease using histogram analysis based on diffusion multi-models
Authors: Zhong Guimian , Wang Mengzhu , Han Qijia , Xiang Zhiming
Published: August 2024

This study established and validated a predictive model based on histogram features of four diffusion models to identify and evaluate early renal impairment in CDK. The results suggested that the model based on the ADC and MK could distinguish the normal and mild CDK well, and could accurately and noninvasively evaluate and predict early CDK renal dysfunction.
Prediction for aggressiveness and recurrence of hepatocellular carcinoma using gadoxetic acid-enhanced magnetic resonance imaging
Authors: Lu Mengtian , Zhang Xueqin , Zhang Tao , Qu Qi , Xu Lei , Zhang Jiyun , Liu Maotong , Jiang Jifeng , Shen Wei , Zhao Xiance
Published: August 2024

This study explores the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) features on the pathologic grade, microvascular invasion (MVI), and cytokeratin-19 (CK19) expression in hepatocellular carcinomas (HCC), and evaluates their association with postoperative recurrence of HCC. The main method is to investigate whether there are independent predictors of the above aggressive indicators in the gadoxetic acid-enhanced MRI features and clinical parameters. Our study shows that peritumoral enhancement, peritumoral hypointensity and rim enhancement could independently predict poor pathological grade, MVI and CK19, respectively. Consequently, these results may help HCC patients develop more appropriate treatment options.
The value of diffusion kurtosis imaging for predicting two-year early recurrence (ER) of hepatocellular carcinoma after curative resection
Authors: Xiong Yanxi , Zhao Ying , Liu Ailian , Ren Xue , Xu Qihao , Song Qingwei
Published: August 2024

Hepatocellular carcinoma (HCC) is viewed as the most frequent primary liver cancer and the third cause of cancer related death worldwide [1]. The 5-year overall survival rate is only 30–40% after surgical resection and 70% of patients have a tumor recurrence within 5 years [2]. we evaluated the discrimination power of Diffusion Kurtosis Imaging for predicting two-year early recurrence (ER) of hepatocellular carcinoma (HCC) after curative resection. Our resuts showed that DKI-based quantitative parameters might have acertain value inpredicting two-year early recurrence (ER) in HCC.
Values of stretched exponential model and fractional order calculus model in predicting microvascular invasion in hepatocellular carcinoma
Authors: Xie Jinhuan , Long Liling , Li Chenhui , Zhang Huiting
Published: August 2024

This study aimed to evaluate the potential value of stretched exponential model (SEM) and fractional order calculus (FROC) diffusion model in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) before surgery. Our results showed that compared with MVI-negative group, MVI-positive group had significant lower DDC from SEM and D from FROC and significant higher α from SEM. DDC had the best diagnostic performance for MVI, D was next, and α was last. SEM and FROC models can predict the MVI of HCC, and the DDC, α, and D values were potential biomarkers in future clinical practice.
Multi-shot Abdomen Diffusion Imaging using external navigators with volume coil
Authors: Reddy Ashok , Jain Nitin , Agarwal Harsh , Das Rajdeep , Sundaresan Rajagopalan , Rajamani Sajith , Guidon Arnaud , Sudhir Ramanna , Baolian Yang , Mani Merry , Reddy M Ramasubba , Venkatesan Ramesh
Published: August 2024

Diffusion MRI in liver is key to detecting liver pathology. However, diffusion in abdomen is limited by its inability to use multi-channel surface coil for obese liver patients. Here we present a novel use of external gradient echo and spin echo navigators for diffusion imaging with a single channel volume coil for providing distortion less diffusion images. We also extend and demonstrate this technique on multichannel coil for Diffusion in Brain.
Bi-exponential 3D UTE-T1rho relaxation mapping of ex-vivo human knee patellar tendon at 3T
Authors: Malhi Bhavsimran , Moazamian Dina , Carl Michael , Athertya Jiyo , Jerban Saeed , Jang Hyungseok , Ma Yajun , Chang Eric , Du Jiang
Published: August 2024

UTE sequences have been previously used to image short T2 tissues. T1ρ has shown promising results in assessing macromolecules and has been proposed as a potential biomarker for tissue degeneration. In this study, we aimed to demonstrate bi-exponential relaxation of the patellar tendon at 3T, using the 3D ultrashort echo time T1ρ (UTE-T1ρ) sequence. Five ex-vivo knee joints were scanned, and we were able to demonstrate better fitting with a bi-component model and better discern the long and short relaxation components of the tissue, along with their respective fractions
Microstructural and microvascular alterations in the non-NPSLE patients: a DKI and 3D pCASL study
Authors: Wang Xiaojuan , Huang Lingling , Lin Qi , Yu Lian , Wu Peng , Zhao Xiance
Published: August 2024

DKI and 3D pCASL were employed to investigate whether white/gray matter microstructure and cerebral microcirculation were altered in patients suffering from non-neuropsychiatric systemic lupus erythematosus (SLE). MK, MKT and CBF values were obtained from 25 brain areas, including gray and white matter. We demonstrated decreased MK, MKT, and elevated CBF in some regions in SLE compared to controls. This study suggested that the brain lesions existed in SLE, DKI and pCASL might be useful for depicting SLE brain early damages, and MK seems to be more sensitive and helpful.
4DFlow Leap-Frog and FFE-DIXON analysis for aneurysm endovascular image-guided treatment
Authors: Popolo María Del , Alcalá Rodrigo , Lombardo Chiara , Petra Ezequiel , González Federico , Balédent Olivier , Moguilner Sebastián , Isoardi Roberto , Fialkowski Valdir , Fino Daniel
Published: August 2024

4Dflow has become a widely used sequence for dynamical characterization of the vascular system. This work shows that it is feasible to implement Leapfrog to acquire results that are colse to those obtained with Finite Volume Methods with excelent results in velocity, vortex and energy, but with certain limitations when estimating the WSS. In order to diminish the acquisition time, we will implement a postprocessing tool using only a 2D Phase Contrast acquisition and implement FSI (CFD), this results will be compared with those given by the LF method.
The effect of different expressions of Delta-catenin on the properties of small world brain network in breast cancer patients before chemotherapy
Authors: Xue Mingtuan , Cao Jiajun , Du Wei , Wang Wenjia , Miao Yanwei
Published: August 2024

This work aimed to explore the effects of different expressions of Delta-catenin in breast cancer(BRCA) patients based on small-world brain network. The results showed that the expression status of Delta-catenin proteins had significant differences on the small-world brain network properties of patients.
Spatial Habitats Analysis based on Multiparametric Physiologic MR Imaging Predicts Survival of Patients with Glioblastoma
Authors: Cao Mengqiu , Fang Liu , Wang Xiaoqing , Liang Xinyue , Dai Yongming , Yan Zhou
Published: August 2024

Glioblastoma (GBM) is characterized remarkably high tumors heterogeneity which contribute to its poor survival and effective therapies. We build the spatial habitats based on multiparametric physiologic MRI (diffusion-weighted and perfusion-weighted MRI) to describe the intratumoral heterogeneity of gliomas and explore the possibility of the link between theses habitats and progression-free survival (PFS). This shows the spatial correspondence with molecular histological features and MRI images. This also provide valuable information to identify tumor progression areas that may require biopsy and potential treatment resistance subregions which tend to be the target areas of treatment.
Combined new molecular signature and radiological signature for risk stratification in IDH wild-type lower-grade glioma
Authors: Zhang Zhiyi , Zhang Hui , Tan Yan
Published: August 2024

When radiological signature was combined with new molecular signature, higher performance was achieved in predicting the prognosis of IDH wild-type lower-grade glioma patients. The combined model showed great risk stratification ability, which improving survival prediction in patients with IDH wild-type lower-grade glioma.
Brain Network Topology: The Missing Link Between Early Childhood Screen Time Utilization and Executive Function Performance
Authors: Tan Ai Peng , Huang Pei , Chan Shi Yu , Ngoh Zhen Ming , Ong Zi Yan , Low Xi Zhen , Law Evelyn C. , Gluckman Peter D. , Kee Michelle Z.L. , Chong Yap Seng , Zhou Juan H. , Meaney Michael J.
Published: August 2024

Excessive screen time utilization in childhood has been linked to executive dysfunction. Our primary aim was to investigate the potential influence of screen time in early childhood on brain network topology and later executive function (EF). We collected data on screen time (between ages 0-4 years) (n = 950), followed by MRI brain at age 6 (n = 414) and assessment of executive function at age 7 (n = 620). Screen time in early childhood was significantly associated with emotion processing-cognitive control network integration which mediates the effect of screen time on EF performance.
Association of socio-economic status and perceived parental stress effects with infant cortical development
Authors: Hyland Jessica , Sindabizera Kay , Ouyang Minhui , Zhu Tianjia , Kim Juri , Huang Hao
Published: August 2024

Environmental factors such as socio-economic status (SES) and parental stress have significant impacts on cognitive performance, but their links to brain development during infancy are not known. We collected high-resolution structural MRI, SES and perceived stress scales (PSS) of 70 infants and their caregivers aged 0-20 months to investigate the association of these environmental factors and brain development. The total brain, gray matter, and white matter volumes all increase rapidly with age. Higher SES is significantly correlated with greater cortical volume, particularly in the right hemisphere. Lower PSS tends to be associated with higher cortical volume, though not significantly.
Mesoscale myelin-water fraction and T1/T2/PD mapping using optimized 3D ViSTa-MR Fingerprinting
Authors: Liao Congyu , Cao Xiaozhi , Iyer Siddharth , Schauman Sophie , Zhou Zihan , Yan Xiaoqian , Chen Quan , Gong Ting , Wu Zhe , He Hongjian , Zhong Jianhui , Kerr Adam , Grill-Spector Kalanit , Setsompop Kawin
Published: August 2024

In this work, we developed an optimized ViSTa-MRF method, which combined Visualization of Short Transverse relaxation time component (ViSTa) technique with MR Fingerprinting (MRF), to achieve high-fidelity whole-brain myelin-water fraction (MWF) and T1/T2/PD mapping at sub-millimeter isotropic resolution. To achieve high image quality, fast acquisition, and memory-efficient reconstruction, the proposed ViSTa-MRF sequence leverages a CRLB-optimized flip-angle (FA) protocol, SNR-efficient 3D spiral-projection sampling scheme and a GPU-based subspace reconstruction. We also applied the proposed method to enable high-resolution assessment of MWF/T1/T2 for infant brain development as well as for post-mortem brain sample.
MRGazerII: Camera-free Decoding Eye Movements from Functional Magnetic Resonance Imaging
Authors: Hu Rongjie , Liang Jie , Ding Yiwen , Jian Shuang , Wu Xiuwen , Wang Yanming , Zhang Yong , Liang Zhen , Qiu Bensheng , Wang Xiaoxiao
Published: August 2024

Eye movements reflect changes in human behavior and thought to some extent, but many functional magnetic resonance imaging (fMRI) studies are limited by equipment and do not perform eye movement tracking. Recently, a deep learning method has been proposed for the regression problem of a single volume's gaze point. In this paper, we propose an end-to-end pipeline called MRGazerⅡ, which includes eye signal extraction, eye-movement behavior recognition and gaze point regression from fMRI scanning slices. The method was tested on the human connectome project (HCP) fMRI dataset and achieved the desired performance.
Harmonization of Multi-Site rs-fMRI data using CovBat
Authors: Breedlove Katherine , Arciniega Hector , Bouix Sylvain , Shenton Martha , Lin Alexander
Published: August 2024

Multisite studies are an important feature of modern neuroimaging research as they allow the study of larger and more diverse populations, which is essential to obtain clinically relevant insight and sensitivity to subtle effects. However, due to the variability among scanner platforms, even when utilizing the same acquisition protocols, harmonization is needed to remove site-to-site variability in order to improve signal-to-noise ratio and improve statistical power. By implementing CovBat as a BIDS application, we have created a turnkey application that quickly minimizes confounding signals in multisite fMRI studies.
Preliminary Functional Quantitative Susceptibility Mapping with Multi-Echo EPI
Authors: Nassar Jannette , Kiersnowski Oliver , Fuchs Patrick , Shmueli Karin
Published: August 2024

Functional QSM (fQSM) detects changes in blood oxygenation in response to neuronal activation, providing complementary information to conventional magnitude-based fMRI. For standard structural gradient-echo QSM, multi-echo (ME) acquisitions are more accurate than single-echoes. Preliminary work suggests this holds for ME-EPI. Previous fQSM studies used single-echo EPI with physiological noise correction but with ME-EPI, we observed fQSM activations in the visual cortex with a visual stimulus without physiological noise correction. ME and single-echo EPI fQSM were compared, showing that ME-EPI might be preferable. fQSM activations were weaker (maximum T-score=4 compared to 10 in fMRI) and more localised than fMRI, as expected.
Impact of B0 field imperfections correction on BOLD sensitivity in 3D-SPARKLING fMRI data
Authors: Amor Zaineb , Le Ster Caroline , G.R. Chaithya , Daval-Frérot Guillaume , Thirion Bertrand , Boulant Nicolas , Mauconduit Franck , Mirkes Christian , Ciuciu Philippe , Vignaud Alexandre
Published: August 2024

Static and dynamic ∆B0 field imperfections are detrimental for fMRI applications as they degrade the temporal SNR (tSNR) and the sensitivity to the BOLD contrast. In this work we propose an experimental protocol for field imperfection monitoring and correction on 3D-SPARKLING fMRI data using the Skope Clip-on field camera in an alternative setting challenging its long TR constraint. We demonstrate the viability of our protocol and the reproducible gain in image quality, tSNR and retinotopic maps when correcting static and dynamic field imperfections on resting-state and task-based fMRI data for 3 healthy volunteers
Noise Reduction for Task-Based Functional Magnetic Resonance Imaging using NORDIC and KWIA
Authors: Zhang Ru , Chen Zhifeng , Zhao Chengyang , Wang Danny , Jann Kay
Published: August 2024

We quantitatively evaluate the performance of NORDIC and KWIA methods in denoising of high-resolution task-fMRI data from 7T in comparison to the standard manufacturer reconstruction. We found that both techniques improve single run statistics as well as improved consistency across runs. Analysis of tSNR confirmed improved data quality in the time domain that facilitates time-series analysis for task-fMRI.
A consensus Protocol for task-free Anesthetized Rat functional Magnetic Resonance Imaging and Data Analysis
Authors: Vrooman Roël , Desrosiers-Gregoire Gabriel , Devenyi Gabriel , Shih Yen-Yu Ian , Lee Sung-Ho , van den Berg Monica , Keliris Georgios , Grandjean Joanes
Published: August 2024

fMRI in rats is performed under diverse protocols that span different animal handling practices and preprocessing steps. The disparity in image acquisition and preprocessing hampers the interoperability and comparison of the results between studies. Importantly, it is unclear what factors lead to superior acquisition and detection of functional networks. We detail a consensus-based task-free fMRI acquisition protocol in the rat that has been validated in 21 datasets. Along with the animal handling protocol and MRI sequence, we provide a detailed path for data conversion, preprocessing, and analysis.
Factors Affecting Cancer Detectability on Standalone Diffusion Weighted Imaging for Non-contrast Breast Cancer Screening
Authors: Biswas Debosmita , Kim Jin , Li Isabella , DelPriori Michaela , Turley Dallas , Bryant Mary , Huang Wei , Rahbar Habib , Partridge Savannah
Published: August 2024

Diffusion weighted imaging (DWI) is emerging as a viable tool for non-contrast MRI breast cancer screening, but it is unclear what factors on DWI impact lesion detectability. In this prospective clinical trial, we evaluated lesion and imaging factors that affected cancer detection. Cancers were overall more detectable at higher b=1200 vs b=800 s/mm2, but the background parenchymal signal (BPS) impacted cancer visibility at the higher b value. Cancer histologic type also impacted detectability on DWI. Overall, our findings suggest that interpretation at higher b values and further technical refinements to reduce appearance of BPS may help improve DWI sensitivity.
Diagnostic value of 5b and 2b-value-DWI in breast tumors: comparison with combined MRI
Authors: Okazawa Aika , Iima Mami , Kataoka Masako , Okumura Ryosuke , Takahara Sachiko , Noda Tomotaka , Nishi Taro , Ishimori Takayoshi , Honda Maya , Nakamoto Yuji
Published: August 2024

We propose a DWI-reading method based on the an adjusted BI-RADS lexicons using five b values of 0, 200, 800, 1000, and 1500 s/mm2 (5b-value-DWI). Diagnostic performance was evaluated in comparison with BI-RADS lexicons from standard BI-RADS DCE MRI and a DWI-reading method based on the adjusted BI-RADS lexicons using two b values of 0, 800 s/mm2 (2b-value-DWI). Our proposed DWI reading methods achieved diagnostic performance comparable to the standard BI-RADS. With higher sensitivity and NPV in 5b-value-DWI compared to 2b-value-DWI, DWI reading with 5b-values has the potential to increase diagnostic confidence in differentiating malignant and benign breast tumors.
Breast cancer diagnosis and prognosis by using a high b-value continuous-time random-walk model
Authors: Feng Hui , Liu Hui , Wang Qi , Song Mengyu , Yang Tianshu , Zheng Liyun , Wu Dongmei , Shao Xian , Shi Gaofeng
Published: August 2024

Breast cancer is a common cancer that severely threatens the health of women worldwide. The advanced diffusion model using high b-values enables a more comprehensive description of the tumor tissue by cellularity and heterogeneity. In current study, a continuous-time random-walk (CTRW) model was applied to identify malignancy of breast lesions and the association between model-derived parameters and immunohistochemical indices was evaluated. All model-derived parameters could identify tumor malignancy, combined parameter could further discriminate ER+/ER- and PR+/PR- patients, while temporal heterogeneity parameter was significantly correlated with PR expression. The CTRW model has demonstrated potential value in breast cancer diagnosis and prognosis.
Image quality ranking for breast diffusion-weighted MRI in a multi-center clinical trial
Authors: Li Wen , Carmona-Bozo Julia , Wilmes Lisa , Onishi Natsuko , Liang Jiachao , Gibbs Jessica , Le Nu , Zimmermann Judith , Newitt David , Joe Bonnie , Kornak John , Partridge Savannah , Bolan Patrick ,   I-SPY 2 Investigator Network,   I-SPY 2 Imaging Working Group, Hylton Nola
Published: August 2024

Acquiring breast diffusion-weighted MRI (DWI) with adequate image quality is a challenge in multi-center clinical trials. The most common issues are inadequate fat suppression, image artifacts, and poor signal-to-noise ratio (SNR). We developed and evaluated a DWI quality ranking system for identifying data with quality issues while preserving analyzable data. The identification of artifacts and adequate SNR had the highest and lowest inter-reader agreement, respectively. Removing inferior quality data improved prediction of pathologic outcome following neoadjuvant treatment in a multi-center clinical trial. The quality ranking system standardizes identification of poor quality data and informs recommendations for improvement to clinical sites.
Synthetic high-b-value reduced field-of-view DWIs in breast cancer elevates lesion clarity and CNR
Authors: Feng Qianqian , Liu Weiyin , Sang Ling , Wang Kejun , Yu Xingyao , Chen Wen , Xu Lin
Published: August 2024

Our study showed synthetic DW images (syDWIs) with high b-value provided better lesion conspicuity, image quality and contrast to noise (CNR), reduce scan time of DWI acquisitions especially at very high b-value, and improved lesion visualization particularly in dense breast. Moreover, derived ADC values showed good consistency between scanned and synthetic DWIs. Therefore, syDWIs with b value of 800 s/mm2 have great potential in elevation of diagnosis confidence and efficacy on tumors and high repeatability of ADC values is helpful in replacement of scanned high-b-value DWIs in clinics despite existed intra-modality, but not inter-modality, difference of manual ROI measures.
Optimal PLD selection for White Matter perfusion measurements at 7T.
Authors: Roefs Emiel , Hirschler Lydiane , Petridou Natalia , van Osch Matthias
Published: August 2024

White matter (WM) perfusion measurements are challenging because of the generally lower perfusion in combination with a longer bolus arrival time (BAT). We investigated the use of long-PLD perfusion measurements at high-field (7T) to compensate for longer BAT in WM. We showed that 3D background suppressed FAIR at 7T with a PLD of 2300ms provides robust perfusion measurement in almost 80% of deep WM within 4min of scan time.
The value of ASL combined with DTI for detection of impaired renal allograft function
Authors: Jiang Bin , Tian Yangyang , Wang Ximing , Wu Peng , Wan Jiayi , Yin Mengjiao , Wang Ning , Xu Rui , Hu Linkun , Zhu Mo
Published: August 2024

Allograft injury continues to be a major problem in renal allograft recipients, which leads to eventual graft loss. Non-invasive and reliable detection of impaired renal allograft function is crucial to preventing irreversible nephron loss and graft failure. This study aims to investigate the value of ASL combined with DTI for the detection of impaired renal allograft function. Results showed that a higher diagnostic efficacy could be achieved through the combined use of ASL and DTI.
Resting state neurovascular coupling patterns estimated using advanced multiband multi-echo BOLD/ASL imaging
Authors: Cohen Alexander , Wang Yang
Published: August 2024

Impaired neurovascular coupling (NVC) plays a critical role in many neurovascular pathological processes. Several resting state fMRI methods have been used to estimate NVC including BOLD/CBF coupling and, to a lesser extent, ALFF and fALFF. In this study, resting state BOLD/CBF coupling was evaluated using advanced multiband multi-echo BOLD/ASL sequence and correlated with ALFF and fALFF in healthy volunteers. Significant correlation between BOLD/CBF coupling and ALFF and fALFF was seen in major brain network hubs. These results indicate MBME BOLD/ASL may provide similar, but complimentary measures of NVC compared to traditional RS metrics.
A novel registration strategy to transform skeletal muscle architecture during passive shortening
Authors: Hooijmans Melissa , Lockard Carly , Coolbaugh Crystal , George Mark , Zhou Xingyu , Damon Bruce
Published: August 2024

In this study we explored if displacement fields, derived from registration of high-resolution anatomical images in different foot positions, could be used to transform muscle fiber architecture from plantar-flexed to dorsi-flexed foot position (passive shortening). Our data revealed that muscle fiber architecture from one foot position can be transformed in the other foot position and that the original and transformed fibers demonstrate similar architectural characteristics, i.e. fiber lengths, pennation angle, curvature, and physiological cross-sectional area.
Automated quantification of intervertebral disc volume loss, ADC and normalized T2 using convolutional neural networks
Authors: Muftuler L. Tugan , Rokos Tomas , Appalaraju Srivishnu , Tran Tyler , Goldshteyn Joshua , Jankowski Garin , Bukowy John
Published: August 2024

Intervertebral disc degeneration is the leading cause of chronic low back pain (CLBP). However, there are no objective measures of the disc degeneration process. The current gold standard for grading disc degeneration relies on visual assessment of discs using MRI, which may not adequately capture complex physiological changes in degenerating discs. We developed a deep convolutional neural network to automatically segment vertebral structures and calculate quantitative MRI metrics. Results show significant changes in ADC and normalized T2 values with disc volume loss.
A pilot study of quantitative T2* mapping in intervertebral lumbar disc patients with lower back pain
Authors: Karthik Adiraju , Devappa Apoorwa , Kapoor Aakaar , Singh Dharmesh , Kumar Dileep
Published: August 2024

The human lumbar spine is comprised of multiple tissue components that serve to offer structural stability as well as optimal nutrition. Traditional magnetic resonance (MR) imaging techniques have been beneficial in assessing intervertebral disc (IVD). Quantitative T2* mapping has recently been used to diagnose and characterize abnormalities associated with IVD, particularly water content variations. However, this approach remains in research settings, and its clinical application has not been thoroughly investigated. This study quantitatively evaluate the clinical value of T2* mapping of intervertebral lumbar disc patients with lower back pain using 3T magnetic resonance imaging (MRI).
Dynamic dextran-enhanced CEST MRI reveals the size effect of BBB disruption associated with neuroinflammation
Authors: Aafreen Safiya , Wang Wenshen , Xu Jiadi , van Zijl Peter , Thomas Aline , Bulte Jeff , Liu Guanshu
Published: August 2024

Prevailing imaging methods primarily focus on detecting blood-brain barrier (BBB) dysfunction utilising tracers of small molecular weight. Robust imaging methods suitable for assessing BBB permeability in the macro-molecular size range are still lacking. Our study aimed to develop and optimize a dextran-based MRI approach for detecting size-dependent BBB permeability. Demonstrated in an EAE MS mouse model, we established a dextran-based CEST MRI protocol for measuring the intracerebral distribution of non-labeled dextrans, validated the results using immunohistochemistry, and compared the CEST MRI results with conventional Gd-enhanced MRI.
MRI characterization of a mouse model of Staphylococcus aureus infection
Authors: Goldman Hannah , Le Katherine , Aristizabal Orlando , Aristizabal Matias , Weissman Mia , Torres Victor , Wadghiri Youssef
Published: August 2024

Staphylococcus aureus is of particular concern due to the deaths associated with antimicrobial resistance and the emergence of antibiotic-resistant strains. There is not currently a vaccine as translation from preclinical models to humans has been unsuccessful. Acquiring reproducible and comparable spinal images that offer non-invasive visualization of the extent and impact of the infection are important for successful intervention or vaccine development. 3D-printed, MRI-compatible cradles enable reproducible positioning and analysis for both in vivo and ex vivo MR spinal imaging in mouse models while allowing for nondestructive analysis of the potential additional benefits to visualization associated with ex vivo MEMRI.
The effects of magnetization transfer on fast and slow diffusion compartments in myelinated white matter
Authors: Li Chenyang , Fieremans Els , Novikov Dmitry , Zhang Jiangyang
Published: August 2024

Myelin, although not directly visible in conventional diffusion MRI (dMRI) due to its short T2, still affects the dMRI signal indirectly through exchange processes with nearby water compartments. In this study, we investigated how a magnetization transfer (MT) preparation affects dMRI signals, in particular, the fast and slow diffusion compartments in myelinated white matter of ex vivo mouse brain. Our result demonstrated that the MT preparation altered the volume fractions, but not the diffusivities, of the fast and slow compartments. Examining the change in volume fractions with MT preparation can provide insights into exchange processes involving myelin and water compartments.