bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmented thick-slab 3D DWI with first and second order motion-compensated diffusion gradients
Authors: Johansson Jens , Lagerstrand Kerstin , Hebelka Hanna , Maier Stephan
Published: August 2024

Routine clinical diffusion imaging is generally performed with 2D echo planar sequences. A single thick-slab 3D approach could offer higher signal-to-noise ratio and better slice resolution, but has not been adopted due to the difficulty to avoid motion-induced phase errors that interfere with multi-shot spatial encoding. A new approach to enable 3D DWI is introduced here: rather than relying on navigator echoes for phase correction, first and second order motion-compensated diffusion encoding gradients are used to minimize phase variations at the source.
Time-efficient Relaxation-Incorporated IVIM Diffusion Imaging
Authors: Sun Kaibao , Dan Guangyu , Luo Qingfei , Zhou Xiaohong Joe
Published: August 2024

Overestimation of perfusion volume fraction has been reported in conventional IVIM imaging. In a model known as extended T2-IVIM, compartmentalized relaxation times are incorporated to improve quantification of perfusion volume fraction, which requires acquisition of additional images at different TEs. A main challenge is that the scan time is lengthened, decreasing the efficiency while increasing vulnerability to motion. We herein introduce a novel sequence for time-efficient, relaxation-incorporated (TERI) IVIM imaging to address the aforementioned issues. TERI IVIM imaging uses multiple EPI readouts at different TEs in a single shot. The proposed technique has been demonstrated in the human brain.
Transfer learning of renal cortex segmentation from CT to MRI: facilitated with automatic labeling
Authors: Ni Chang , Mu Xin , Li Yanbin , Qi Haikun , Zhang Jeff
Published: August 2024

Segmentation of renal cortex in MR images is important but challenging. In this study, we proposed to pre-train a ResUNet model with CT images and to use an automatic method for labeling renal cortex for the training data. Such method with transfer learning and automatic labeling performed well in segmenting renal cortex in MR images, with a DICE similarity of 0.85 and volume error of 14%±5%. The proposed method would make labeling of renal cortex for training dataset much more efficiently, and we further confirm the power of transfer learning technique in segmenting renal MR images.
Perfusion MRI using dynamic contrast-enhanced MRI and arterial spin labeling for the characterization of small renal masses: preliminary study.
Authors: Al-Mubarak Haitham , Bane Octavia , Kennedy Paul , Robson Philip , Cuevas Jordan , Reddy Arthi , Prachanronarong Kristina , Meilika Kirolos , Horowitz Amir , Kuhn Bernd , Sourbron Steven , Badani Ketan , Taouli Bachir , Lewis Sara
Published: August 2024

Functional imaging using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and arterial spin-labeling (ASL), which is a non-contrast technique, have been proposed to quantitatively assess perfusion and vascular flow in small renal masses (SRM) and may provide complementary information. In our initial series, we found significant differences in certain DCE-MRI quantitative and semi-quantitative parameters for renal cell carcinoma (RCC) versus benign tumors (Vp, wash-in, wash-out TTP and AUC) and between ccRCC versus non-clear cell (non-cc)RCC (Ve), while no differences existed between groups for ASL. Certain pharmacokinetic parameters derived from DCE-MRI appear promising for SRM characterization
Improved accuracy of triexponential diffusion analysis of the kidney using motion-corrected reconstruction for free-breathing DWI
Authors: Makino Yuki , Ohno Naoki , Peeters Johannes , Yoneyama Masami , Ueda Yu , Miyati Tosiaki , Matsuura Yukihiro , Gabata Toshifumi , Kobayashi Satoshi
Published: August 2024

The clinical application of triexponential intravoxel incoherent motion analysis in the kidney has been limited because the blurring and misregistration of images caused by respiratory motion during acquisition. To solve this issue, we applied retrospective motion-corrected (MC) reconstruction to free-breathing (FB) DWI of the kidney for accurate triexponential diffusion analysis. Our results showed that triexponential analysis using MC FB-DWI can improve the measurement accuracy and repeatability of triexponential diffusion parameters of the kidney.
3D Multichannel Convolutional Neural Network for Differentiating Benign and Malignant Solid Renal Masses with/without Bias Field Correction
Authors: Wawrzyn Peter , Massa Ruben Ngnitewe , Gardezi Jamal , Wentland Andrew
Published: August 2024

A deep learning model was developed for the differentiation of benign and malignant solid renal masses. A representative and balanced dataset was used, and model performance was evaluated with and without bias field correction (BFC). The model input contained multiple channels for various MRI-based tissue contrast weightings. The model achieved an accuracy and AUC of 74% and 71% with BFC and 80% and 59% without BFC. This work showed that a convolutional neural network can be trained to differentiate benign from malignant renal masses with a high degree of accuracy and that BFC improves AUC.
Preliminary study on the influence of renal motion amplitude on APTw image quality of normal kidney
Authors: Ma Ruirui , Jia Min , Wang Xia , Zhang Wei , Zhao Na , Tian Gang , Yu Chanjuan , Yue Xiuzheng , Han Yuedong
Published: August 2024

Respiratory movement is the main reason for upper and middle abdominal organ movement, which significantly affects the quality of MR imaging. This study aims to analyze the influence of renal motion amplitude on renal APT imaging through free breathing (FB), and breath holding (BH) based on multi-phase balanced turbo fast field echo (B-TFE). The results showed that renal motion amplitude was negatively correlated with APTw image quality scores. The renal motion amplitude of bilateral kidneys of BH mode was significantly reduced compared with FB, and the APT image quality of BH mode was better.
The feasibility of distinguishing HSPN from HSP in children using intra-voxel incoherent motion diffusion weighted imaging
Authors: Su# Hang , Zhang# Gang , Wu Jingjing , Xing Wei , Hu Yufu , Shen Zhiwei , Jiang Ke , Sun Yuying , Zhang Xia , Ren* Xianqing
Published: August 2024

Currently, the therapeutic significance of IVIM-DWI has been examined in numerous kidney illnesses such as transplanted kidney, renal tumor, and renal failure; however, the application in purpura nephritis is uncommon. As a result, the purpose of this study was to investigate the clinical feasibility of IVIM-DWI in differentiating purpura nephritis (HSPN) from allergic purpura (HSP) in children by using D and K values obtained from a small-field DWI sequence with respiratory trigger
ABSOLUTE QUANTIFICATION OF RENAL ASL IN DOGS
Authors: Serpa Luis Sanmiguel , Hillaert Amber , Pullens Pim
Published: August 2024

Arterial Spin Labeling (ASL) is a noninvasive fMRI technique that may evaluate canine renal condition. To date, however, the parameters to estimate the renal blood flow (RBF) have not been calculated on dogs. Therefore, λ: blood-tissue water partition coefficient in kidneys and canine at 3T were measured. Measured λ was 0.91[mL/g] and was 1463 ms. With these new values RBF maps were calculated and then compared against the RBF maps given by the scanner. This pilot study demonstrates the relevance of the ASL parameters estimation for the RBF maps calculation in canine kidney.
In-Plane Balanced Phase-Contrast Steady-State Free Precession (PC-SSFP) for All-in-One Diastolic Function Evaluation
Authors: Xiang Jie , Lamy Jerome , Qiu Maolin , Peters Dana
Published: August 2024

Diastolic function evaluation requires estimates of early and late diastolic mitral valve flow velocities (E and A), and mitral annulus tissue velocity (e’). Our goal was to develop a bSSFP phase-contrast (PC) sequence (PC-SSFP) for in-plane flow-encoding, for simultaneous recording of E and A, and estimation of e’ based on tracking mitral valve motion on cine magnitude images, in a single breath-hold. Phantom and in vivo experiments showed agreement of PC-SSFP with velocities on GRE-based PC providing similar velocity curves, while achieving the high SNR and contrast of bSSFP cine images.
Deep learning-based prediction of aortic hemodynamics obtained by 4D flow MRI using seismocardiography of chest vibrations
Authors: Ebrahimkhani Mahmoud , Johnson Ethan , Sodhi Aparna , Robinson Joshua , Rigsby Cynthia , Allen Bradly , Markl Michael
Published: August 2024

We pursued a deep learning approach to investigate the utilization of a wearable seismocardiography (SCG) device to predict measures of flow similar to those obtained using 4D flow MRI. SCG can measure the chest vibrations caused by cardiac mechanical activities such as valve closures and changes of pulsatile flow. We hypothesized that deep learning can be used to infer the pathological changes in blood flow, such as a higher systolic peak velocity (Vmax) in patients with aortic valve diseases, from the SCG signals.
Deformation-ENcoding Transformer (DENT) for High Frame Rate for Phase Contrast MRI
Authors: Morales Manuel , Amyar Amine , Yoon Siyeop , Rodriguez Jennifer , Maron Martin , Rowin Ethan , Nakamori Shiro , Kim Jiwon , Judd Robert , Weinsaft Jonathan , Manning Warren , Nezafat Reza
Published: August 2024

Quantification of blood flow using 2D or 4D phase-contrast (PC) MRI is routinely being used to evaluate blood flow in cardiovascular disease. However, PC has only a modest temporal resolution compared to echocardiography. We sought to develop a deformation-encoding transformer (DENT) model for cardiac frame interpolation and evaluate its potential in increasing temporal resolution. DENT was trained using a large multi-center (centers = 3), multi-vendor (vendors = 3) and multi-field strength (1.5T, 3T) cine MRI dataset (patients = 3178). The model was successfully applied to 2D/4D-PC MRI without modifications, enabling a 2-fold gain in temporal resolution.
Radial phase-contrast FLASH acquisiton with SSA-FARY utilizing a Hadarmad-encoding sheme
Authors: Thiesen Vanessa , Adler Ansgar , Uecker Martin
Published: August 2024

The assessment of flow within a heart cycle places high demands on the temporal resolution of the measurement protocol. With self-gating we can exploit the quasi-periodicity of cardiac and respiratory motion to meet this challenge. We combined a Hadamard flow-encoding scheme together with SSA-FARY to further elaborate on the idea of a flow measurement with a high temporal and spatial resolution. The approach delivered promising results in 2D and can be seen as a basis for further developement towards 3D flow MRI.
Measuring individual vein and artery BOLD responses to visual stimuli in humans with multi-echo single-vessel functional MRI at 7T
Authors: Varadarajan Divya , Wighton Paul , Chen Jingyuan , Proulx Sebastien , Frost Robert , van der Kouwe Andre , Berman Avery , Polimeni Jonathan
Published: August 2024

Here we apply single-vessel fMRI techniques to evaluate BOLD and non-BOLD contributions within individual arteries and veins. First we identified individual vessels from inflow effects in a small set of slices, and distinguished arteries and veins on the basis of their T2* decay. Then we applied a high-inplane-resolution multi-echo single-vessel fMRI approach to examine fMRI responses within these vessels. We find evidence for both BOLD and potentially non-BOLD responses within arteries, suggesting that in some cases BOLD may capture arterial responses BOLD which may be more neuronally specific (in space and time) than effects from downstream veins.
Dependence of the EPI and bSSFP resting-state fMRI signals on the cortical orientation relative to B0: Initial observations at 9.4 Tesla
Authors: Ramadan Dana , Bause Jonas , Stirnberg Rüdiger , Ehses Philipp , Scheffler Klaus
Published: August 2024

The spatial specificity of fMRI with GRE-EPI is significantly affected by large draining veins on the cortical surface. They cause susceptibility changes that are strongest when the veins are oriented perpendicular to B0. Since they follow the cortical curvature, their orientation to B0 can be approximated by the cortical orientation. Previous studies have shown a high dependence of the GRE-EPI signal on the cortical orientation, reflecting its disadvantage of being sensitive to these veins. In this preliminary two-subject study, this phenomenon is investigated with GRE-EPI and bSSFP in different cortical depths to experimentally explore the sensitivity of bSSFP to microvasculature.
Application of SLR pulses to short-TR spin-echo fMRI at 7T: SNR considerations and a direct demonstration of reduced cardiac noise
Authors: Balasubramanian Mukund , Berman Avery , Mulkern Robert , Wald Lawrence , Grissom William , Polimeni Jonathan
Published: August 2024

We show that SLR pulses provide much better slice profiles (and thus much higher SNR) than standard sinc pulses for short-TR spin-echo (SE) acquisitions, even when there is substantial B1+ inhomogeneity. As one application, we used SLR pulses and a TR of 300 ms in SE-EPI acquisitions at 7T, enabling the “direct” measurement of cardiac frequencies at ~1 Hz without aliasing. Far less cardiac fluctuation was seen in SE- versus GE-EPI data. While SE-fMRI is known to have reduced macrovascular weighting and thus improved spatial specificity relative to GE-fMRI, our results suggest that it may also have better temporal specificity.
Isolating the arterial blood volume change to probe fMRI spatial specificity
Authors: Priovoulos Nikos , Oliveira Icaro , Poser Benedikt , Norris David , van der Zwaag Wietske
Published: August 2024

BOLD fMRI is widely used in neuroscience, but has limited spatial specificity while alternative approaches based on tissue cerebral blood volume (CBV) change have limited sensitivity. Recently, arterial CBV change (Arterial Blood Contrast; tracked through magnetization-transfer) was suggested as an fMRI mechanism, but its localization and sensitivity remain unexplored, since efficiently isolating the arterial CBV is challenging. Here, we combine temporally-efficient saturation with center-slice-out readouts and BOLD-correction to isolate arterial CBV for high-resolution 7T human fMRI. Our novel sequence shows much-improved specificity compared to BOLD and similar sensitivity to VASO, suggesting Arterial Blood Contrast to be a promising fMRI approach.
Multi-echo EPI for improving temporal resolution in task-based fMRI at 7T- a dynamic phantom study
Authors: Baz Guy , Furman-Haran Edna , Shmidt Rita
Published: August 2024

Ultra-high field MRI provides increased sensitivity, which we aim to utilize for improving the temporal resolution in functional studies. To investigate the achievable resolution at 7T MRI, a dynamic phantom that can generate an fMRI-like time-series was used. A dataset based on block-design with defined time shifts and a range of contrast-to-noise values was used to characterize the effective temporal resolution. Estimated temporal resolution was x1.7 times better for multi-echo compared to single-echo EPI, estimated as 146ms for a scan with TR of 600ms. This study offers a novel approach of optimizing protocols and new insights into fMRI temporal resolution.
Investigating the feasibility of functional MRI using GRE EPI on a high performance 0.5 T Scanner
Authors: Halder Arjama , Harris Chad , Wiens Curtis , Curtis Andrew , Handler William , Soddu Andrea , Chronik Blaine
Published: August 2024

fMRI is typically not performed at field strengths < 1.5T due to low magnetic susceptibility contrast and inadequate gradient performance. Leveraging the high-performance gradient set of a head-only 0.5T MRI, the feasibility of motor task based fMRI was evaluated using a 4mm isotropic GRE-EPI acquisition. Activated regions within the PMC were consistent with expected behaviour. Furthermore, a significant change in signal during activation of 1.8+/-0.4% was measured within an ROI of activated voxels. These results suggest that motor task based BOLD fMRI is possible at 0.5T.
Feasibility of a multi-site and cross-platform liver 31P MRSI processing pipeline for three 7T clinical MRI vendors
Authors: Karkouri Jabrane , Wildenberg Lieke , Runderkamp Bobby , Prompers Jeanine , Cecchi Paolo , Tosetti Michela , Klomp Dennis , Rodgers Christopher
Published: August 2024

We present preliminary baseline results from three-vendor 7 T MRSI for applications on liver 31P MRS. Liver scans were performed on 21 healthy volunteers, at 4 sites and 3 different 7T MR scanner platforms. Data were analysed using a new Matlab pipeline combining the best methods from our labs. This pipeline is operator independent and we report here the liver metabolites as ratios of PME/PDE and Pi/ATP concentrations. The cross-site average PME/PDE was 0.63 ± 0.12, and the cross-site average Pi/ATP was 0.76 ± 0.11. This compares favourably with literature reports [Purvis et. al., 2017].
Comparison of short-interval afferent inhibition measures with tonic GABA and Glutamate levels
Authors: Považan Michal , Madsen Mads , Tomasevic Leo
Published: August 2024

The neurochemical substrate of the measures observed with transcranial magnetic stimulation remains unclear. MR spectroscopy may provide valuable insights into understanding the synaptic GABAergic and glutamatergic activity, however studies comparing these methods haven’t provided an adequate explanation. We aimed to compare GABA and glutamate concentrations with short-interval afferent inhibition measured with TMS. We found positive correlation between the amount of inhibition and tonic GABA levels, however this finding needs to be carefully scrutinized.
Theoretical guaranteed unfolding method for k-space interpolation in a self-supervised manner
Authors: Luo Chen , Cui Zhuoxu , Wang Huayu , Jin Qiyu , Chen Guoqing , Liang Dong
Published: August 2024

Recently, iterative algorithm driven deep neural network unfolding methods have been successfully applied to MRI. However, the network replaces the original algorithm structure and mathematical properties such as interpretability and convergence of the original algorithm are not guaranteed. Fortunately, the k-space-filled Hankel low rank can naturally be associated with convolutional networks. Given this, we propose an unfolding method for k-space-filling, which guarantees convergence to the unique real MR image. Furthermore, we train this network in a self-supervised manner to cope with scenarios where fully sampled data are difficult to obtain. Finally, numerical experiments validate the effectiveness of the proposed method.
Deep learning-based acquisition protocol optimization and parameter estimation for diffusion exchange spectroscopy
Authors: Cheng Zhaowei , Han Guangxu , Hu Songtao , Fang Ke , Bai Ruiliang
Published: August 2024

We propose a deep-learning-based method to optimize acquisition protocol and estimate parameter for diffusion exchange spectroscopy. A unified framework has been carefully designed to achieve both goals simultaneously. Using this framework, the acquisition protocol can be directly optimized with an objective function that minimizes the parameter estimation errors, regardless of its degree of freedom. The experimental results from Monte Carlo simulations show that the proposed method outperforms the existing methods in both accuracy and precision of parameters’ estimation. Besides, it speeds up the calculation by 480 times.
Deep learning reconstruction algorithm for 100-second rapid Ischemic stroke imaging
Authors: Fang Xin , Liu Ailian , Song Qingwei , Li Guobin , Zhang Shuheng
Published: August 2024

Head Computed Tomography (HCT) is a common imaging method for the diagnosis of emergency cerebral infarction. However, it is easy to miss the diagnosis due to the poor performance of the ultra-early or early cerebral infarction lesions. Compared with CT, head Magnetic Resonance Imaging (MRI) has the characteristics of high tissue contrast, no ionizing radiation damage and can make functional imaging sequences, so it has significant advantages in the diagnosis of posterior fossa lesions and ultra-early cerebral infarction
Impact of sampling strategies and residual U-net reconstruction on preserving high spatial frequencies in accelerated low-field MRI
Authors: Ayde Reina , Senft Tobias , Fiorito Marco , Spreiter Mauro , Salameh Najat , Sarracanie Mathieu
Published: August 2024

Low signal-to-noise (SNR) ratios inherent to low-field (LF) MRI challenge its relevance in clinical applications. Accelerating the acquisition by undersampling k-space followed by reconstruction techniques has already shown promising results. Yet, undersampling is usually done by skipping high-frequency information which can lead to misdiagnosis as small lesions can be missed. In this study, we exploited a specificity of low-SNR regimes, that is signal averaging, to explore different acceleration strategies without skipping crucial information in k-space. The DL-reconstructed images arising from those sampling schemes have been evaluated on acquired in-vivo and ex-vivo LF-MRI datasets, showcasing high-frequency preservation and potential for generalization.
A deep learning approach for compressed sensing reconstruction using adaptive shrinkage threshold
Authors: Lian Yuan , Guo Hua
Published: August 2024

Compressed Sensing is widely used for accelerating acquisitions of MR images. Deep learning methods have been introduced to CS-MRI reconstruction to improve image quality and computation speed. Here we introduce a new shrinkage function with adaptive threshold selection for Model-driven deep learning networks to suppress aliasing artifacts by utilizing the information on each feature map. We combine our adaptive threshold selection module with ISTA-Net, and demonstrate that the method can reduce reconstruction errors while preserving structural details effectively.
Rapid multi-slice whole-brain B1+-mapping at 7T using deep learning
Authors: Krueger Felix , Aigner Christoph Stefan , Lutz Max , Riemann Layla Tabea , Degenhardt Katja , Ittermann Bernd , Schaeffter Tobias , Hammernik Kerstin , Schmitter Sebasian
Published: August 2024

In this work we utilize deep learning to estimate multi-slice whole-brain B1+-maps in sub-seconds from initial localizer scans at 7T. The investigated neural networks use the receive profiles of the individual coil elements of an 8Tx/8Rx transceiver head coil as input information. The networks are trained on seven volunteers and tested in 2 unseen subjects for transversal/coronal/sagittal slices by comparing the prediction with the acquired B1+-maps. Subsequently, the feasibility of using the DL-based B1+-maps in a subject-specific calibration pipeline is demonstrated.
Quadrature Transceiver RF Arrays Using Double Cross Magnetic Wall Decoupling for Ultrahigh field MR Imaging
Authors: PAYNE KOMLAN , Bhosale Aditya , Ying Leslie , Zhang Xiaoliang
Published: August 2024

Circularly polarized or quadrature transceiver coils can significantly increase overall signal reception and reduce the excitation power over linearly polarized RF transceivers. Due to the wave propagation of two modes owing to their electromagnetic field properties, it is challenging to achieve sufficient decoupling in multichannel quadrature coil arrays. In this work, we proposed a double cross magnetic wall decoupling for quadrature transceiver RF arrays based on a common-mode differential-mode (CMDM) resonator at UHF 7T. The proposed method comprised of two orthogonal decoupling elements is able to reduce the mutual coupling between the multi-modes in a pair of CMDM resonators.
Comparing 8-channel and 4-channel head array coils for 7T human brain Deuterium MRS imaging (DMRSI) applications
Authors: Li Xin , Soon Soo Han , Waks Matt , Wiesner Hannes , Zhu Xiao-Hong , Chen Wei
Published: August 2024

Deuterium MRS imaging (DMRSI) has emerged as an important neuro-metabolic imaging tool. We compared the performance of 4-channel and 8-channel deuterium head array coils for 7T human brain DMRSI through electromagnetic simulation, phantom and in vivo measurements. Both simulation and phantom studies show that the 4-channel array coil produced more than twice the RF magnetic field (B1) than the 8-channel array coil. Whole-brain DRMSI data with high spatial (0.7 cc nominal voxel) and temporal (2.5 min) resolutions was collected from five healthy subjects using a 4-channel head array coil, showing excellent SNR throughout the human brain.
Can a 38-channel dipolectric antenna array compete with a 32-channel commercial head coil at 7T?
Authors: Dardano Thomas , Xin Lijing , Wenz Daniel
Published: August 2024

In this work we explore a concept of dipolectric antenna array up to 38 receive channels. We constructed and evaluated an 8-channel version of dipolectric antenna array for human brain MRI at 7T and benchmarked its receive performance against a commercial 1Tx/32Rx head coil. In vivo data obtained for 8-channel array along with simulations (16- and 38-channel) indicate that a 38-channel dipolectric antenna array could provide significantly higher SNR than the current state-of-the-art solutions for human brain at 7T.
Twisted pair coils as flexible receive elements for 7 T - SNR and active detuning efficiency
Authors: Czerny Raphaela , Frass-Kriegl Roberta , Cap Veronika , Laistler Elmar , Nohava Lena
Published: August 2024

Form-fitting coil designs demand highly flexible coils such as twisted pair or coaxial transmission line resonators. Both of these designs and respective interfacing circuits were investigated as receive-only coils at 7 T. Similar signal-to-noise ratio and active detuning performance compared to a standard copper wire coil were demonstrated in bench and MRI experiments.
Toward a Size-Adaptable 128-Channel Receive RF Coil for Human Head Imaging at 3T Using a Flexible Plate Approach
Authors: Mathieu William , Matta Charbel , Popović Milica , Farivar Reza
Published: August 2024

We present a size-adaptable flexible-plate 128-channel receive coil design with initial results. Our approach allows for increased element density as elements can be placed closer to the surface of the scalp. Arrays are built on semi-flexible plates with boundaries roughly following cranial sutures. The aim is to accommodate at least 99% of head shapes and sizes. Our 18-channel “occipital” plate array (1 of 8 plates) was compared to the posterior portion (40-channels) of the Siemens 64 Head/Neck coil using SNR maps. Results show that our design improves average and max SNR by 1.9- and 7.4-fold, respectively.
ALAw-CEST MRI of the ASCT2 transporter in a mouse model of prostate cancer
Authors: Ghaemi Behnaz , Li Yuguo , Pomper Martin , Bulte Jeff , van Zijl Peter , Thomas Aline
Published: August 2024

Increased utilization of glutamine is characteristic of many advanced, aggressive cancers. Established glutamine imaging strategies require the use of labeled probes (positron emission tomography, hyperpolarized spectroscopy) that can limit their accessibility. Here, we investigated the utility of chemical exchange saturation transfer (CEST) MRI upon intravenous injection of unlabeled alanine to monitor differences in cellular glutamine uptake as a potentially complementary imaging biomarker for profiling cancers and monitoring their progression.
Fractional order calculus model in liver cancer with immunohistochemical indexes CK19 and Hep par-1: a preliminary animal study
Authors: Xie Jinhuan , Long Liling , Li Chenhui , Zhang Huiting
Published: August 2024

The purpose of this study was to explore the feasibility of preoperative non-invasive evaluation of immunohistochemical indexes of hepatocellular carcinoma, CK19 and Hep par-1 positive, with Fractional Order Calculus (FROC) model using nude mice model. Results showed that the diffusion coefficient D and fractional order derivative in space β had statistically significant differences and good diagnostic performances between the CK19 and Hep par-1 positive groups. These finding showed that FROC is useful diffusion model and D and β are useful biomarkers in liver cancer with expression of the immunohistochemical indexes CK19 and Hep par-1.
MR Molecular Imaging of Pancreatic Cancer Reveals Differences in Tumor Microenvironment during Therapeutic Monitoring with Immunotherapy
Authors: Laney Victoria , Lu Zheng-Rong
Published: August 2024

PDAC is a highly aggressive malignant cancer and the 3rd leading cause of cancer related deaths in the US. The aggressive nature of PDAC is in part due to the desmoplastic tumor microenvironment, which promotes rapid tumor growth and impedes therapeutic efficacy of conventional therapies. Immune checkpoint inhibitors have showed specific efficacy in PDAC promotes extracellular remodeling for effective treatment of aggressive tumors. In this study we investigated the ability of an MR molecular imaging technology for image guidance and therapeutic monitoring of PD-L1 treated PDAC tumors.
Three-dimensional CUBE MR imaging accurately quantified lipid accumulation in reflection of longitudinal fish health
Authors: Liu Dong , Pan Lei , Liu Weiyin , Zhu Wenzhen
Published: August 2024

Quantitative methods of fish lipid accumulation have attracted a lot of attention in ecotoxicology. Traditionally, invasive approaches were time-consuming and generally required animal sacrifice, drastically restricting applicability in ecotoxicology. In this study, a noninvasive MRI approach was proposed to quantify lipid accumulation in two represented fish species with IDEAL-IQ and Cube-Flex-T2 sequences. We demonstrated the accuracy of our novel MRI approach in quantifying fish lipid accumulation. In addition, we conducted cadmium exposure experiment and observed no significant differences in lipid deposition between MRI and traditional methods. Thus, this MRI method could have a wide range of applications in ecotoxicological research.
Age Related Changes of Organs and Muscles Using a Deep Learning Based Whole Body Segmentation Technique Applied to a Healthy Adult Population
Authors: Gouda Ahmed , Basar Saqib , Chodakiewitz Yosef , Attariwala Rajpaul , London Sean , Hashemi Sam
Published: August 2024

One of the vital indicators of normal functioning physiology and anatomy, is the volume and size of body organs and muscles. Overtime due to aging and chronic illnesses, the volume of organs and muscles decreases, and quantifying this reduction would help us in predicting the rate of decline, and making efforts to improve this rate. Artificial intelligence 3D segmentation techniques allow us to measure the average age-related volume loss over a large population. They provide statistical norms which help radiologists to identify abnormal volume changes, and establish a normal age related rate of volumetric decline.
Learning diffusion MRI fiber orientation distribution functions of the developing human brain
Authors: Kebiri Hamza , Gholipour Ali , Karimi Davood , Cuadra Meritxell Bach
Published: August 2024

Diffusion MRI of fetal and newborn brains is constrained by short scanning time allowing only a small number of diffusion measurements to be acquired. Methods going beyond the diffusion tensor model require multi-shell and multiple gradient directions in order to unveil more accurate white matter properties. We propose a learning based framework to reconstruct fiber orientation distribution functions from only six diffusion measurements by leveraging existing high-quality datasets. Quantitative evaluation on 15 newborn subjects show that our framework achieves competitive results with state-of-the-art methods. Qualitative evaluation on a fetus shows the model ability to translate to this challenging population.
Denoising Enables Faster 1 mm Isotropic Diffusion Tensor Imaging of the Human Hippocampus at 3T
Authors: Stack-Sanchez Pablo , Gross Donald , Beaulieu Christian
Published: August 2024

A hippocampus-focused, 1 mm isotropic, diffusion tensor imaging 5.5 minutes 3T protocol has yielded high-quality diffusion images and maps. Post-processing with denoising can potentially reduce the scan time considerably. Compared to the previously used 10 direction/10 average protocol, denoising enabled the use of 4 averages for a scan time of only 2.2 minutes to yield acceptable 1 mm isotropic diffusion image quality and mean diffusivity maps (MD) of the whole hippocampus in healthy controls. This rapid protocol was then able to delineate focal and small hippocampal lesions with elevated MD in temporal lobe epilepsy patients.
Correlation between Shifted Apparent Diffusion Coefficient of the Renal Parenchyma and Estimated Glomerular Filtration Rates: A Pilot Study
Authors: Nakamoto Atsushi , Onishi Hiromitsu , Tsuboyama Takahiro , Ota Takashi , Fukui Hideyuki , Yano Keigo , Honda Toru , Kiso Kengo , Matsumoto Shohei , Tatsumi Mitsuaki , Tomiyama Noriyuki
Published: August 2024

This retrospective study investigated the correlation between shifted apparent diffusion coefficient (sADC) of the kidney measured using diffusion-weighted imaging obtained with b = 200, 1500 and estimated glomerular filtration rates (eGFR), and the performance in discriminating patients with impaired renal function was compared between sADC and ADC. sADC of the renal cortex showed the highest correlation coefficient in correlation with eGFR. In discriminating cases with eGFR <45, <60, or <90, sADC of renal cortex showed higher area under the curve compared to ADC, although the difference was not significant. sADC might be more useful in predicting renal function than ADC.
Kidney T2 can be used as a biomarker for disease progression and functional decline in mouse models of polycystic kidney disease
Authors: Schmid Florian , Koukos Georgios , Sooknah Matt , Assili Sanam , Riegler Johannes
Published: August 2024

We investigated quantitative T2 mapping as an MRI biomarker for disease progression in mouse models of autosomal dominant polycystic kidney disease and its correlation with kidney function. Our results show a good correlation between the fraction of the kidney tissue with elevated T2 and cyst load quantified by histology. There was also a good correlation between high T2 values and kidney function decline indicated by reduced glomerular filtration rates.
Diffusion tensor imaging-based quantitative assessment of renal function in early-stage lupus nephritis
Authors: He Chutong , Wang Ye , Pang Xinrui , Wei Ruili , Liang Fangrong , Xu Yongzhou , Zhang Aaron , Yuan Shiwen , Yang Ruimeng
Published: August 2024

Lupus nephritis (LN) is a substantial cause of death in patients with systemic lupus erythematosus (SLE). The purpose of this study was to explore the value of Diffusion tensor imaging (DTI) in evaluating renal function in patients with early-stage LN. The results showed apparent diffusion coefficient (ADC) values in the cortex and fractional anisotropy (FA) values in the cortex and medulla were significantly lower in early-stage LN patients compared with healthy volunteers. Furthermore, FA values in the cortex and medulla were also independent predictors of early-stage LN, suggesting that FA values can be a potentially sensitive imaging biomarker.
Assessment of renal lipid deposition and abnormal oxygen metabolism of type 2 diabetes mellitus based on mDixon-Quant
Authors: Yang Chun , Wang Yishi , Li Wei , Wang Yuxin
Published: August 2024

mDixon-Quant adopts a multi-echo 3D fast GRE sequence that can be used to obtain fat fraction, T2* and R2* mapping in a single breath hold. The variation of deoxyhemoglobin in the kidney can reflect the oxygen metabolism in patients with diabetic nephropathy under pathological and physiological conditions. FF maps can be used for fat quantification. mDixon-Quant provides the assessment both fat metabolism and oxygen metabolism of the kidney at the same time and may be valuable in detecting changes in renal function and pathology.
3D free-breathing renal DCE MRI with high spatial and temporal resolution using Multitasking
Authors: Liu Qing , Liu Qi , Li Jing , Zhang Zhongqi , Xu Jian , Zhang Jeff , Sun Haoran
Published: August 2024

A 3D, free-breathing renal DCE MRI technique is developed using MRI Multitasking. It produces motion-resolved, high spatial and temporal resolutions images, thus does not require image registration post-processing. The feasibility of this technique in renal DCE MRI is evaluated on healthy subjects.
Quantitative characterization of hemodynamic parameters in pediatric patients with connective tissue disorders
Authors: Sodhi Aparna , Johnson Ethan , Weiss Elizabeth , Berhane Haben , Robinson Dr. Joshua , Popescu Dr.             Andrada , Markl Dr.             Michael , Rigsby Dr.             Cynthia
Published: August 2024

Quantitative overview of 4D flow derived aortic hemodynamic parameters such as kinetic energy, peak velocity, and pulse wave velocity in a cohort of pediatric patients with connective tissue disorders such as Marfan Syndrome (MFS), Loeys-Dietz Syndrome (LDS), and Vascular Ehlers-Danlos Syndrome (EDS), using a fully automated pipeline. A statistically significant trend of increased pulse wave velocity - an important measure of vessel stiffness, with increasing age was observed for this cohort. No association was found between PWV and all mean aortic diameters when controlled for age.
Evaluation of turbulent Kinetic energy and Viscous energy loss on 4D flow MRI in patients with hypertrophic cardiomyopathy
Authors: Sekine Tetusro , Kumita Shinichiro
Published: August 2024

The purpose was to validate whether turbulent kinetic energy (TKE) and viscous energy loss (VEL) reflect the condition of hypertrophic cardiomyopathy (HCM). We included consecutive 32 HCM patients. They were classified into HOCM (HCM with left ventricular outflow tract obstruction [LVOTO]) (n=21) and HNCM (HCM without LVOTO) (n=11) based on cardiac ultrasound. Both TKE and VEL were significantly higher in HOCM than HNCM. The strong correlation was observed between normalized LVmass and normalized TKEpeak in asymptomatic HCM (nTKEpeak r=0.879, p<0.001), but not in symptomatic HCM. The TKEpeak had the strongest correlation to each disease condition than the others.
FMRI-based language mapping at 1.5 and 3T: the influence of methodological choices.
Authors: Bolhassan Khaliesah , Franklin Rachael , De Vita Enrico , Jarosz Jozef , Borri Marco
Published: August 2024

This work aims to assess the influence of methodological aspects in fMRI language mapping at 1.5T and 3T. Probability maps from healthy volunteer cohorts were compared to a published reference using a Dice Index vs probability threshold plot. T-value normalisation to the peak within the classic Broca/Wernicke’s language area as well as the inclusion of additional language tasks increased overlap to the reference. The extent of reproducible activation was larger at 3T.
Dynamic analysis of resting-state brain fMRI signal from a novel perspective: Avalanche
Authors: Guo Junlin , Khairi Nazirah , Xu Lyuan , Wilkes Don
Published: August 2024

The human brain, at rest, is complex and many functional studies focus on the brain patterns around criticality. This work addresses a novel perspective, the avalanche, in resting-state fMRI. In this work, we design two data-driven signal modeling approaches that dynamically measure and visualize the signal entropy from both spatial and temporal aspects. The first approach applies a clustering-based scheme with the Markov chain. The second method utilizes the autoregressive model with a sliding window. The results show a consistent, less complex pattern at the avalanche state, from which the interpretation of the brain can be clearer than at criticality.
Investigation of cerebral blood flow and volume changes during positive and negative BOLD responses at 3T
Authors: Devi Ratnamanjuri , Schlumm Torsten , Mildner Toralf , Möller Harald
Published: August 2024

CBF and CBV changes were measured sequentially, in regions of positive and negative BOLD responses, using a multi-echo center-out readout, known to reduce BOLD contaminations in pCASL and VASO measurements due to its short echo times. The CBV-CBF coupling was found to differ between positive and negative BOLD regions. The temporal relation of the CBF and VASO timecourses to their corresponding T2* timecourses, on the other hand, was found to be almost identical in the two ROIs.
Neurovascular coupling of the human brain in complex naturalistic stimuli viewing
Authors: Lee Hsin-Ju , Rutledge Emily , Cheng Jiahui Veron , Nummenmaa Lauri , Santavirta Severi , Lin Fa-Hsuan
Published: August 2024

Simultaneously acquired EEG and fMRI data allow for elucidating the neurovascular coupling. Here, we use temporally sparse fast fMRI and continuous EEG to study the correlations between hemodynamic signals and neural oscillations across the cerebral cortex during movie watching.
Quantifying Organizational Changes of Functional Connectivity Linked to Hypertension in Resting-State Functional MRI
Authors: Reeves William , Ahmed Ishfaque , Jackson Brooke , Sun Wenwu , Brown Michelle , Williams Celestine , Davis Catherine , McDowell Jennifer , Yanasak Nathan , Su Shaoyong , Zhao Qun
Published: August 2024

Using a graph theory approach, functional connectivity differences in a 52 (32 hypertensive, 20 normotensive) subject cohort were tracked using resting-state fMRI. A null generation modification to a difference degree test (DDT) is profiled that resulted in increased true positivity rates in simulations while maintaining nominal false positivity rates. Applying the modified DDT to the hypertension cohort resulted in the discovery of 7 brain regions that exhibit significant groupwise differential expression along with 33 unique differentially expressed connections to other areas in the brain. The results presented agree with previous studies and represent a promising application of the modified DDT.
Bayesian and lagged general linear modelling strategies in breath-hold induced cerebrovascular reactivity mapping with muti-echo BOLD fMRI
Authors: Hayes Genevieve , Pinto Joana , Moia Stefano , Craig Martin , Chappell Michael , Caballero-Gaudes Cesar , Bulte Daniel
Published: August 2024

Cerebrovascular reactivity (CVR), the ability of blood vessels to dilate and constrict in response to a vasoactive stimulus, is an important indicator of cerebrovascular health and can be estimated using BOLD functional MRI. In this work, we evaluated a novel variational Bayesian method for mapping CVR dynamics which yielded similar CVR results and reproducibility to a time-shifted, “lagged” general linear model approach, and uncovered the need for more research into negative CVR. This novel approach is more time efficient and has the potential to improve CVR mapping by incorporating non-linear modelling and physiologically meaningful information (in the form of priors).
Comparison of Magnetic Resonance Spectroscopy Data Acquired with Hybrid PET-MRI and Standalone MRI Scanners
Authors: Bhattacharya Aditya , Risk Benjamin , Fleischer Candace
Published: August 2024

Magnetic resonance spectroscopy (MRS) is a powerful tool for quantifying metabolite concentrations, but spectral quality has not been thoroughly explored in hybrid MRI scanners. Using repeated measurements in a brain phantom and healthy volunteer, we determined the reproducibility and accuracy of MRS data on two systems, a hybrid GE PET-MRI (3.0 T) and Siemens 3.0 T MRI. Spectra acquired using the PET-MRI scanner produced metabolite concentrations with higher accuracy and lower variance across repeated measurements compared to the standalone MRI, suggesting spectral quality is not hindered by the hybrid system.
High spatiotemporal resolution whole-brain 2H MRS imaging (DMRSI) to differentiate grey and white matter metabolic dynamics in human brain at 7T
Authors: Li Xin , Zhu Xiao-Hong , Li Yudu , Wiesner Hannes , Liang Zhi-Pei , Chen Wei
Published: August 2024

Deuterium MRS imaging (DMRSI) is a promising tool to quantitatively study brain glucose metabolism, but it is challenging to simultaneously achieve high spatial and temporal resolution to capture metabolite dynamics in the human brain. In this study, we applied advanced RF head coil and post-processing techniques to perform high spatiotemporal-resolution (0.7cc nominal voxel and 2.5 min) DMRSI covering entire human brain at 7T with oral administration of deuterated glucose. The results show superior DMRSI sensitivity for mapping and differentiating the TCA cycle activity in grey and white matters. This capability is critical for disease applications including brain tumor.
Improving SNR in deuterium metabolic imaging of cancer: spatial denoising, joint spectral/metabolic-kinetics processing, and beyond
Authors: Montrazi Elton , Bao Qingjia , Martinho Ricardo , Peters Dana , Harris Talia , Sasson Keren , Agemy Lilach , Scherz Avigdor , Frydman Lucio
Published: August 2024

As DMI is a promising cancer screening approach but is challenged by low sensitivity, this study assesses multiple approaches to increase its SNR. Some of these –apodization, Compressed Sensing Multiplicative (CoSeM), Block-matching/3D filtering (BM3D)– involve image denoising. Others take into account the metabolic kinetics, and include it as dimension to be denoised. This can be achieved by smoothing the kinetic data axis via regularization, or by using subspace-constrained representations to concurrently solve for the 4D spatial/spectral/kinetics set. These methods can be further denoised –e.g., by CoSeM– leading to much clearer observations of lactate generated by in vivo tumor models.
Parallel Proton and Deuterium Metabolic Imaging
Authors: Liu Yanning , Kumaragamage Chathura , Nixon Terry , McIntyre Scott , De Feyter Henk , de Graaf Robin
Published: August 2024

1H MRSI and DMI can provide crucial metabolic information to facilitate evaluations of neurological diseases. In this work, we applied interleaved 1H/2H methodology to achieve time-efficient, parallel 1H MRSI and DMI acquisition. We first describe the necessary sequence adjustments for both nuclei, including the re-optimization of the VAPOR water suppression scheme and the incorporation of a 2H equilibrium pulse. Phantoms were then used to demonstrate that high quality 1H MRSI and DMI data can be acquired in parallel. The interleaved 1H MRSI-DMI sequence is compatible with other interleaved MRI-DMI sequences and can be implemented for a complete MRI-DMI protocol.
Estimating Uncertainty of Deep Learning for Tomographic Image Reconstruction Through Local Lipschitz
Authors: Bhutto Danyal , Zhu Bo , Liu Jeremiah , Koonjoo Neha , Rosen Bruce , Rosen Matthew
Published: August 2024

As deep learning approaches for image reconstruction become increasingly used in the radiological space, strategies to estimate reconstruction uncertainties become critically important to ensure images remain diagnostic. We estimate reconstruction uncertainty through calculation of the Local Lipschitz value, demonstrate a monotonic relationship between the Local Lipschitz and Mean Absolute Error, and show how a threshold can determine whether the deep learning technique was accurate or if an alternative technique should be employed. We also show how our technique can be used to identify out-of-distribution test images and outperforms baseline metrics, i.e. deep ensemble and Monte-Carlo dropout.
Data-adapted Neural Network Denoisers as a Regularization Engine for Low-latency Image Reconstruction in Accelerated Cardiac Perfusion MRI
Authors: Yalcinkaya Dilek Mirgun , Unal Hazar Benan , Raman Subha , Hashemi Abolfazl , Dharmakumar Rohan , Sharif Behzad
Published: August 2024

In this work, we demonstrated that a deep-learning based denoiser trained on a limited dataset of first-pass myocardial perfusion MRI studies enables low-latency image reconstruction using the plug-and-play iterative reconstruction framework. Our proof-of-concept results suggest that the data-adapted denoiser resulted in superior performance versus a generic denoiser especially if there are constraints on the number of iterations (total computation time) which is the case in certain clinical settings specifically interventional MRI. Our findings also imply that radial sampling may be a more desirable data acquisition strategy for PnP-based image reconstruction in first-pass MP MRI studies.