bluuebunny/crossref_metadata_2025 huggingface dataset:
MRIsim.jl: A framework for end-to-end spin-level MRI simulations with GPU acceleration
Authors: Castillo-Passi Carlos , Coronado Ronal , Uribe Sergio , Irarrazaval Pablo
Published: August 2023

In this work, we proposed a GPU-enabled MRI simulation framework written in Julia. The primary purpose of this simulator is to evaluate imaging pipelines from the acquisition to the reconstruction. To showcase this, we simulated two variations of an MRF sequence with radial acquisitions and then reconstructed using two methods. We demonstrated that this framework aids users to quickly write and test state-of-the-art MRI techniques and showed its potential to compare imaging pipelines in quantitative mapping.
Assessing intrinsic parallel diffusivity changes in pediatric subjects acquired with NODDI.
Authors: Napolitano Antonio , Lucignani Martina , Parrillo Chiara , Espagnet Maria Camilla Rossi , Longo Daniela , Talamanca Lorenzo Figà
Published: August 2023

Investigating optimal NODDI intrinsic diffusivity d|| values in the first years of life would provide accurate diffusion properties estimation. We aimed to investigate d|| for 1-36 months range. Diffusion data from 265 baby Human Connectome Project subjects were processed and used for NODDI model fitting with MDT tool. Among different d|| tested, optimal value was chosen according to maximum LogLikelihood maps and investigated as a function of age. Infants exhibit optimal d|| values of 1.95 µm2 ms-1, where d|| decreases for increasing age. Based on our results, 1.7 µm2 ms-1 represent a suboptimal assumption in the case of infant population.
Towards a high-density packing white matter substrate generator for Monte-Carlo simulations
Authors: Haro Juan Villarreal , Gardier Remy , Canales-Rodríguez Erick , Girard Gabriel , Thiran Jean-Philippe , Rafael-Patino Jonathan
Published: August 2023

One main goal of Diffusion-Weighted Magnetic Resonance Imaging is to infer microscopic tissue properties from the measured signal. The use of Monte-Carlo Simulations for DW-MRI on realistic substrates will help the study of DWI-MRI signals in controlled environments and to investigate, extract, and validate approaches for the understanding of white matter features. In this work, we present a novel framework for creating complex white matter phantoms with unprecedented characteristics like high packing density greater than 90% intra-axonal volume fraction and voxel size of (140 um)3.
Augmentation of Diffusion-Encoding Gradient Directions with Deep Learning is not suitable for dMRI clinical studies
Authors: Rodríguez-Galván Justino , Martín-Martín Carmen , Tristán-Vega Antonio , Alberola-López Carlos , Aja-Fernández Santiago
Published: August 2023

Validation in Deep Learning for enhancement of diffusion Magnetic Resonance Imaging results usually sticks to conventional image similarity metrics. Despite those results, further research on synthetic data may result in discordance with the real one. In this paper we have compared 61 real gradient directions against 61 quasi-identical synthetic gradient directions, obtained by subsampling the real ones, for the assessment of the differences between chronic and episodic migraine patients. Even with high image comparison metrics, differences in t-test are not compelling. For that reason, we do not recommend synthetic images for clinical use.
Multi-nuclear MRI of tissue sodium provides novel measure of treatment response to physical therapy in women with lipedema
Authors: Donahue Paula , Crescenzi Rachelle , Petersen Kalen , Garza Maria , Patel Niral , Lee Chelsea , Chen Sheau-Chiann , Donahue Manus
Published: August 2023

The overall goal of this work is to apply multi-nuclear sodium MRI to evaluate the therapeutic effect of physical therapy in women with lipedema. Lipedema is a fat disorder affecting approximately 11% of women and since it is largely refractory to diet and exercise, objective measures of condition severity and treatment response are required. We applied sodium MRI to evaluate whether abnormal tissue sodium accumulation in the legs, a previously established lipedema biomarker, reduced following physical therapy in persons with lipedema. Results show reduction of skin and subcutaneous sodium, which corresponds with reduced pain and increased function.
Impact of tract propagation stop criteria on skeletal muscle DTI fiber tract completeness and characteristics
Authors: Lockard Carly , Hooijmans Melissa , Zhou Xingyu , Damon Bruce
Published: August 2023

Diffusion-tensor MRI tractography has been applied to characterize skeletal muscle architecture and diffusion characteristics. Ideally, tracking would occur completely for accurate length, angle, curvature, and diffusion property estimation of a bundle of fibers. In practice, it is desirable to end tracts early if poor quality data is encountered and tract termination settings can influence the balance between tract completeness and desirable exclusion of inaccurate tract regions. This work examines the effect of applying a range of fractional-anisotropy and intersegment-angle tract-termination thresholds on muscle architecture and diffusion estimates, and fiber polynomial fit residuals.
Deep-learning based 3D segmentation of thigh muscle and classification of intramuscular fat on T1-weighted axial MRI
Authors: Bharadwaj Upasana , Pirmoazen Amir , Akkaya Zehra , Lynch John , Joseph Gabby , Majumdar Sharmila , Pedoia Valentina , Link Thomas
Published: August 2023

Intramuscular fat is an important biomarker for knee osteoarthritis. Quantitative analysis on routine clinical imaging (T1-weighted MRI) is not feasible without pixel-level annotation, leading to the adoption of Goutallier classification, a semi-quantitative grading system that is time-consuming and has variable reproducibility. This study automates binarized Goutallier classification on patients (n=50) from the Osteoarthritis Initiative cohort with a two-staged process: deep-learning 3D segmentation of quadriceps and hamstrings (dice scores of 0.89[0.88,0.90] and 0.84[0.83,0.87], respectively) followed by histogram features for classification of intramuscular fat (0.93[0.92,0.95] AUROC). With model-reader kappa (0.64[0.61,0.68]) comparable to inter-reader kappa (0.61[0.59,0.64]), our approach shows promise for end-to-end automation.
Overcoming image distortions for DWI of prostate cancer using Spatiotemporal Encoding (SPEN)
Authors: Otikovs Martins , Anaby Debbie , Portnoy Orith , Nissan Noam , Rosenzweig Barak , Frydman Lucio
Published: August 2023

Diffusion weighted imaging (DWI) plays an important role in prostate cancer early detection and characterization. These analyses commonly rely on single shot EPI acquisitions, which can be associated with image distortions induced by field inhomogeneities induced by tissue / air interfaces. Herein we compare the faithfulness of EPI-derived DWI data, against that arising from Spatiotemporal Encoding (SPEN). In general, we find that SPEN delivers more faithful DW representations of the prostate anatomy within comparable scan times, without compromising SNR. SPEN can thus improve the contrast for prostate lesion detection, both in DW images and in calculated ADC maps.
A Follow-up Study On Prospective Para-Clinical Use by Residents of a Re-calibrating Automated Deep Learning System for Prostate Cancer Detection
Authors: Zhang Kevin , Schrader Adrian , Netzer Nils , Görtz Magdalena , Schütz Viktoria , Schwab Constantin , Hohenfellner Markus , Schlemmer Heinz-Peter , Bonekamp David
Published: August 2023

Previously validated fully-automatic detection of prostate cancer by CNNs requires further prospective validation. Para-clinical case-by-case prospective prostate MRI assessment by residents was performed both before and after review of CNN probability maps superimposed on T2w images. A previously and retrospectively validated self-parametrizing nnUNet-architecture CNN trained on more than 1000 voxel-wise annotated prostate MRIs achieved ROC AUC of 0.89. Residents did not substantially change their assessment both at PI-RADS>=3 and >=4 decisions, however achieved excellent working points, indicating success of high reading capability conveyed at an expert center.
Development of a scan-specific quality control acquisition for clinical whole-body MRI (WB-MRI) protocols
Authors: Keaveney Sam , Hopkinson Georgina , Scurr Erica , Olaru Maria-Alexandra , Collins David , Messiou Christina , Koh Dow-Mu , Winfield Jessica
Published: August 2023

A short quality control acquisition was developed to detect hardware issues and receiver coil positioning errors in whole-body MRI (WB-MRI). Individual coil element images were reconstructed to investigate potential broken elements and coil positioning was assessed by comparison with images acquired using the integral body coil.

This approach was implemented in a group of healthy volunteers and patients with myeloma and successfully identified a previously undetected broken coil element. The expected signal difference between coil array and integral body coil images was defined and deviation from this expected profile was used to distinguish images acquired with deliberately imperfect coil set-ups.
Influence of fat suppression and image reconstruction methods on ADC of uninvolved bone marrow in patients with myeloma.
Authors: Hopkinson Georgina , Messiou Christina , Scurr Erica , Kaiser Martin , Collins David , Winfield Jessica
Published: August 2023

The influence of fat suppression methods and image reconstruction parameters on the apparent diffusion coefficient (ADC) in uninvolved bone marrow was assessed in 18 patients with myeloma. ADC estimates from diffusion-weighted MRI acquired using spectral adiabatic inversion recovery (SPAIR) fat suppression were significantly lower than DW-MRI with short-tau inversion recovery (STIR). ADC estimates were significantly lower in data reconstructed using sum-of-squares coil-combination mode compared with adaptive combine, but there was no difference between additional reconstruction filters (raw, elliptical). These results show that differences between imaging protocols should be considered when comparing ADC estimates with established ranges and in multi-centre studies.
Distortion correction of 3D EPI for cortical depth-resolved fMRI at 7T
Authors: Malekian Vahid , Graedel Nadine , Hickling Alice , Aghaeifar Ali , Corbin Nadège , Josephs Oliver , Maguire Eleanor , Callaghan Martina
Published: August 2023

Geometric distortion is a major concern for cortical depth-dependent fMRI using EPI readouts that suffer from low bandwidth in the phase-encoded direction. Distortions are exacerbated at higher field strengths due to increased B0 field inhomogeneity. In this study, we quantitatively compared two distortion correction methods (B0 field-mapping and reversed-PE) applied to submillimeter (0.8mm isotropic) 3DEPI data at 7T. Cortical alignment was evaluated through comparison with an anatomically-faithful MP2RAGE reference by computing the dice coefficient and normalised mutual information. Both distortion correction methods usefully improve alignment. The reversed-PE approach performed better.
Monte Carlo simulations of weighted overlap map thresholds to reduce the risk for type I errors in fMRI
Authors: Van Schuerbeek Peter
Published: August 2023

We performed Monte Carlo Simulations to show that the risk for type I errors decreases if a minimum overlap between the individual results is set in addition to the significance of the group results. The activation maps of a real fMRI experiment showed that the combination of a weighted overlap map threshold in combination with a voxel significance threshold seems to lead to less type II errors compared to applying a family wise error (FWE) correction.
Adaptive non-local means filtering as a drop-in preprocessing step to improve statistical sensitivity in task-based fMRI
Authors: Nemani Ajay , Lowe Mark
Published: August 2023

Spatial filtering is an important step in the preprocessing of task-based fMRI to improve sensitivity in statistical analyses. This is usually implemented as a pure distance-based filter such as Gaussian filtering or an optimized matched filter. Adaptive non-local means (ANLM) filtering is a patch-based approach that is sensitive to the local noise model, especially at low signal to noise ratio such as fMRI. We show how ANLM filtering is a simple drop-in replacement at the spatial smoothing step of fMRI preprocessing pipeline that compares favorably to other approaches while better preserving local high frequency features.
Fractal-Based Analysis of fMRI BOLD Signal During Naturalistic Viewing Conditions
Authors: Campbell Olivia , Vanderwal Tamara , Weber Alexander
Published: August 2023

We investigated the difference between the brain’s fractal dynamics during movie-watching and resting-state conditions using 7T fMRI data. During movie-watching, we find that the BOLD signal becomes more scale-invariant and self-similar than during the resting-state. This supports the idea that movie-watching evokes a state of optimal neural functioning that may better reflect the endogenous state of the brain than a fixed cross-hair. We also find that fractal properties differ greatly across functional networks, providing novel information about the temporal dynamics of each network during naturalistic processing. Overall, these findings advance understanding of both fractal dynamics and naturalistic viewing in fMRI.
Ultra-fast 3D fMRI to explore cardiac-induced fluctuations in BOLD-based functional imaging
Authors: Sutton Brad , Anderson Aaron , Zimmerman Benjamin , Camacho Paul , Jin Riwei , Marchini Charles , Salaudeen Olawale , Ramsy Natalie , Boido Davide , Charpak Serge , Webb Andrew , Ciobanu Luisa
Published: August 2023

Leveraging recent developments in high speed imaging, we use a 3D fMRI acquisition with 60 ms TR to examine the impact of physiological signals on spatiotemporal correlations in BOLD imaging. Given the standard sampling of fMRI with 2D slices, coherent slice-by-slice sampling of physiological signals can lead to many additional components in the fMRI time series. The current approach provides a way to explore the impact of these confounding signals and to test correction methods.
Generalizable synthetic multi-contrast MRI generation using physics-informed convolutional networks
Authors: Jacobs Luuk , Mandija Stefano , Liu Hongyan , van den Berg Cornelis , Sbrizzi Alessandro , Maspero Matteo
Published: August 2023

Synthetic MRI aims to reconstruct multiple MRI contrasts from short measurements of tissue properties. Here, a generalizable physics-informed deep learning-based approach for synthetic MRI was investigated. Acquired data were mapped to effective quantitative parameter maps, here named q*-maps, which are fed to a physical signal model synthesizing four contrasts-weighted images. We demonstrated that from q*-maps, MRI contrasts unseen during training could be synthesized. The proposed method is benchmarked to a standard end-to-end deep learning approach. The two deep learning methods generated similar brain images for healthy subjects and patients with different pathologies.
The CALIPR framework comprehensively improves acquisition, reconstruction & analysis of multi-component relaxation imaging
Authors: Dvorak Adam , Kumar Dushyant , Gilbert Guillaume , Laule Cornelia , Moore G.R. Wayne , MacKay Alex , Kolind Shannon
Published: August 2023

We introduce the CALIPR framework, applied here to multi-component T2 relaxation myelin water imaging (MWI) to achieve a simultaneous increase in data quality and decrease in acquisition time. CALIPR showed robust results for data acquired with aggressive under sampling acceleration, strong agreement with a newly developed “gold-standard” reference MWI acquisition, excellent scan-rescan repeatability, and the ability to acquire whole-brain MWI in under 5 minutes.

While this work demonstrates dramatic improvements the CALIPR framework brings to MWI, its utility can be extended to a wide range of both quantitative and qualitative MRI applications across different scanner vendors and field strengths.
SPION relaxivity at low field strengths with hyperpolarized 129Xe
Authors: Bryden Nicholas , McHugh Christian , Kelley Michele , Branca Rosa
Published: August 2023

We provide superparamagnetic iron oxide longitudinal relaxivity measurements at both high (11.7 T) and low (0.6 – 2.1 mT) magnetic field strengths, for both 1H and hyperpolarized 129Xe nuclei. These measurements show significant increase in relaxivity at low field for both nuclei. We also provide some preliminary in vivo results for hyperpolarized 129Xe that suggest a depolarization mechanism similar to that of SPIONs from the hemoglobin found in whole blood.
T2 measured with multiple spin-echo depends on echo spacing as well as orientation
Authors: Doucette Jonathan , Bauer Manuel , Bartels Lara , Jaffray Alexander , Rauscher Alexander
Published: August 2023

The MRI signal in white matter tissue is composed of constituent signals from two different water pools: intra/extracellular water and myelin water. When using a multi spin-echo acquisition, the relaxation rate measured in each pool has been shown to depend on the orientation of the containing white matter fibre with respect to the main magnetic field. Here, we show an additional influence of the acquisition echo spacing on the apparent intra/extracellular rate relaxation rate, and using numerical simulation, we provide evidence that decoherence mediated by diffusion through local field inhomogeneities created by blood vessels cannot explain the observed orientation dependence.
Whole-liver flip angle shimming at 7T using eight-channel parallel transmission kt-points pulses with FPE-DREAM B1+ mapping
Authors: Runderkamp Bobby , van der Zwaag Wietske , Roos Thomas , Strijkers Gustav , Caan Matthan , Nederveen Aart
Published: August 2023

Liver MRI could benefit from the increased SNR at 7T but suffers from severe flip angle inhomogeneity. In this work, eight-channel parallel transmission is used for flip angle shimming, comparing circularly polarized transmission and phase shimming with a kt-points pulse. Fourier phase-encoded DREAM is used for artifact-free B1+ mapping. With kt-points, the nominal flip angle of 8˚ could be achieved with homogeneous signal over the entire liver, while phase shimming only delivers a flip angle of approximately 4˚ with less homogeneity. Future work is directed towards use of universal slab-selective kt-points pulses to make 7T liver MRI clinically feasible.
Exploring Myelin Imaging Biomarkers in Pelizaeus-Merzbacher Disease
Authors: Koehler Caroline , Kuntke Paul , Sahoo Prativa , Wahl Hannes , Deoni Sean C , Kitzler Hagen H. , Dreha-Kulaczewski Steffi
Published: August 2023

Advanced MRI techniques bear great potential to explore myelination in hypomyelinating leukodystrophies such as Pelizaeus-Merzbacher disease (PMD) in-vivo. Quantitative imaging biomarkers which reflect myelin, its spatial distribution, and dynamics during brain maturation are not readily available i.e. to monitor natural disease courses. In a pilot study including three PMD patients, multi-component relaxation which enables the evaluation of relative myelination by estimating the myelin water fraction (MWF) was obtained from 56 region of interest (ROI). Determination of ROIs was facilitated by coregistration of the patients data to a pediatric atlas and compared to age matched healthy controls.
Early MRI biomarkers in amyotrophic lateral sclerosis (ALS): DTI and functional connectivity.
Authors: Quizhpilema Juan , Lecumberri Pablo , Vidorreta Marta , Laxe Tamara , Miguel Mikel San , Díaz Javier , Pagola Inmaculada , Gómez Marisol , Jericó Ivonne , Cabada Teresa
Published: August 2023

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by damage to motor neurons. The search for early biomarkers is relevant due to their rapid progression.This study aims to analyze structural and functional measures in a group of newly diagnosed ALS patients, compare them with a group of healthy controls, and evaluate changes longitudinally at a 6-month follow-up.Twenty patients and 15 controls were recruited. The MRI examination included a T1-weighted scan, DTI, rs-fMRI. ALS shows involvement in motor and non-motor areas as shown by DTI in cortical activity in the early phase and in time progression.
Investigations of the effects of differently trained subject cohorts
on T1 and T2 of the lumbar spine muscles
Authors: Maggioni Marta , Krämer Martin , Anders Christoph , Reichenbach Jürgen
Published: August 2023

The majority of studies investigating changes in skeletal muscle parameters with MRI have focused on analyzing the effects before and after exercise training. In this work, we analyze the effects of regular repetitive training on low back muscle by determining T1 and T2 parameters in three cohorts of subjects characterized by different levels of physical activity.
Comparison of AI-assisted Compressed Sensing (ACS) and Conventional Two-Dimensional Sequences on Lumbar Spine Imaging
Authors: Sui He , Gong Yu , Zhang Yunfei , Dai Yongming , Mo Zhanhao
Published: August 2023

MRI is widely used in the diagnosis of spinal diseases, but due to the limitation of long scanning time, it is often difficult for patients to tolerate. This study aims at exploring whether the ACS (AI-assisted Compressed Sensing) accelerated sequences can assure similar image quality and diagnostic accuracy of lumbar spine diseases compared to 2D conventional sequences. Results suggested that 2D ACS sequence has become a well-anticipated technique for routine examination of lumbar spine and lumbar spine lesions diagnosis, while ensuring high image quality and reduced scan time effectively than traditional 2D sequences in MRI.
Evaluation of Deep-Learning Reconstructed High-Resolution 3D Cervical Spine MRI to Improve Foraminal Stenosis Evaluation
Authors: Jardon Meghan , Tan Ek , Chazen J. Levi , Sahr Meghan , Wen Yan , Vanderbeek Alyssa , Sneag Darryl
Published: August 2023

Isotropic 3D MRI, with the addition of deep-learning based reconstruction algorithms (DLRecon), facilitates faster acquisition times and multiplanar reformatting. We compared interobserver agreement for cervical spine neural foraminal (NF) stenosis assessment of 3D T2-weighted fast spin echo (T2w-FSE) MR images with DLRecon to those of standard-of-care (SOC) 2D T2w-FSE images. We demonstrated that inter-observer agreement was high for both 2D and 3D sequences in the assessment of NF stenosis, but agreement was more consistent between readers at each level for the 3D acquisition. 3D DLRecon images were also more frequently free of motion, when compared to corresponding 2D sequences.
Noninvasive Detection and Assessment of Treatment Response in Multiple Myeloma using Whole-body DETECT: Preliminary Findings
Authors: Lin Sheng-Qing , Fonseca Sebastian , De Leon Alberto Diaz , Oz Orhan , Udayakumar Durga , Kaur Gurbakhash , Anderson Larry , Kansagra Ankit , Madhuranthakam Ananth
Published: August 2023

We present the preliminary findings on the ability of our novel whole-body MRI using Dual-Echo T2-weighted acquisition for Enhanced Conspicuity of Tumors (WBMRI-DETECT) for detection and longitudinal assessment of therapy response in multiple myeloma (MM). Data from 4 MM patients undergoing induction therapy at 4 timepoints in an ongoing prospective research study are presented. Our results show that WBMRI-DETECT provides higher SNR, improved lesion conspicuity with shorter scan times compared to WBMRI-STIR and WBMRI-DWIBS, and minimal geometric distortions compared to WBMRI-DWIBS. In addition, quantitative FF measurements from WBMRI can serve as a prognostic imaging biomarker for the treatment response assessment.
Image quality in MY-RADS whole-body MRI protocols applied in a prospective multi-centre multiple myeloma study
Authors: Keaveney Sam , Dragan Alina , Rata Mihaela , Blackledge Matthew , Scurr Erica , Winfield Jessica , Koh Dow-Mu , Porta Nuria , Candito Antonio , King Alexander , Rennie Winston , Gaba Suchi , Suresh Priya , Malcolm Paul , Davis Amy , Nilak Anjumara , Shah Aarti , Gandhi Sanjay , Albrizio Mauro , Drury Arnold , Roberts Sadie , Jenner Matthew , Brown Sarah , Kaiser Martin , Messiou Christina
Published: August 2023

An assessment of image quality is presented from a multicentre WB-MRI study. A radiologist assessed image quality and the presence/severity of several common artefacts/image quality issues and metrics were also defined to measure these quantitatively. Image quality was consistently good or excellent, with only one DWI examination deemed non-diagnostic. In the case of most artefacts, the quantitative measurements were found to correlate with radiological assessment and a statistically significant ordinal regression model was found to predict DW image quality score using the quantitative measurements. These measurements could form part of an automated quality control pipeline for multi-centre WB-MRI studies.
MR-guided high intensity focused ultrasound of extra-abdominal desmoid tumors: a retrospective study of 61 patients
Authors: Duex Daniel , Sheth Vipul , Brunsing Ryan , Ganjoo Kristen , Avedian Raffi , Bitton Rachelle , Ghanouni Pejman
Published: August 2023

We reviewed MR-guided high intensity focused ultrasound treatments (MRgFUS) of extra-abdominal desmoid tumors (DTs) in our institution from 02/2013 until 12/2020. The primary endpoints for assessing efficacy are post-treatment change in tumor volume, response based on RECIST and mRECIST; secondary endpoints are change in pain and quality of life. Complications are also reported. Our study demonstrates MRgFUS is an effective treatment option for first line and salvage therapy of desmoid tumors.
Anatomic changes during head and neck radiotherapy observed with automated MRI tracking
Authors: Aliotta Eric , Hu Yu-Chi , Zhang Peng , Lichtenwalner Phil , Caringi Amanda , Allgood Natasha , Tsai Jillian , Zakeri Kaveh , Zhang PengPeng , Lee Nancy , Cervino Laura , Aristophanous Michalis
Published: August 2023

Longitudinal MRI is an ideal tool for tracking anatomic changes that occur during head and neck radiotherapy. We have implemented an image tracking system that monitors volumetric changes in gross tumor volumes (GTV) and parotid glands to identify and alert of major changes early in treatment. In a cohort of 91 patients, this system identified systematic shrinkage of GTVs (9.2±8.3% per week) and parotids (3.1±3.7% per week) during treatment. Importantly, GTV changes observed in the first week of treatment were strongly predictive of larger changes that would occur later in the course (P<1x10-5, two-tailed t-test).
Early response evaluation of neoadjuvant chemotherapy in locally advanced rectal cancer using T1 and T2 mapping
Authors: Gong Xiaoling , Shen Yu , Wen Daguang , Wei Mingtian , Zhang Xiaoxiao , Zhang Xiaoyong , Wang Ziqiang , Wu Bing
Published: August 2023

Neoadjuvant chemotherapy can improve oncologic outcomes and overall survival rate. However, not all patients respond well during treatment, and continuous treatment will be painful, costly, and even increase risk of progression. Thus, early stratification of treatment response and screening of patients who may not be effective in treatment is very important. We investigated the value of T1 and T2 mapping MRI in response evaluation and found that T2 value showed a significant difference between groups of pre and 1-week post-treatment, while the T1 value had no statistical difference. T2 mapping may be a useful functional biomarker for early responses evaluation.
Constructing a Mesh-Based Template of the Liver is Consistent as a Function of Cohort Size in the UK Biobank
Authors: Thanaj Marjola , Basty Nicolas , Cule Madeleine , Sorokin Elena , Bell Jimmy , Thomas Elizabeth , Whitcher Brandon
Published: August 2023

Computational atlases provide many advantages in quantifying and modeling differences in the size and shape of internal organs between individuals in population imaging studies. A cohort of UK Biobank participants were analyzed to explore the consistency of templates, which is the average labeled image from a number of subjects constructed across different population sizes, and investigate whether this has an impact on the statistical analysis. We found no differences in our significance areas between templates. Although, for the statistical parametric mapping, a larger sample size that involves multiple hypothesis tests, results in a higher representative power.
Disentangling apparent discordance between ASL-MRI and [18F]-FDG PET following a single dose of the β2-agonist clenbuterol
Authors: Bishop Courtney , Rizzo Gaia , Lodeweyckx Thomas , de Hoon Jan , Van Laere Koen , Koole Michel , Vandenberghe Wim , Rabiner Eugenii , Martin Renee , Ford Anthony , Vargas Gabriel
Published: August 2023

Here we demonstrate that an apparent discrepancy in CBF (from ASL) and CMRglu (from [18F]-FDG PET) following high-dose administration of clenbuterol in healthy volunteers is caused by within-scan rising plasma glucose concentrations. With simulation-based correction, post-clenbuterol CBF changes from ASL agree with blood flow estimates from [18F]-FDG PET, without increase in CMRGlu. ASL-MRI may therefore provide a valuable tool for monitoring the central effects of β2-adrenergic receptor activation in larger, future studies on both healthy volunteers and patients with neurodegenerative disorders.
Automatic selection of the optimal kernel size for Helmholtz-based EPT
Authors: Arduino Alessandro , Mandija Stefano , Pennecchi Francesca , Van Den Berg Cornelis , Zilberti Luca
Published: August 2023

In this work, a procedure for the automatic selection of the optimal kernel size in Helmholtz-based electric properties tomography (MR-EPT) with phase-based approximation is presented and tested on experimental data acquired on a phantom with a 3 T MRI scanner. The procedure is exclusively based on the map of the transceive phase, making no assumptions on the data in addition to those used in the derivation of the Helmholtz-based MR-EPT technique. As a by-product, the approach provides a map indicating the reliability of the reconstructed electric conductivity pixel-by-pixel.
Mapping of weak current-induced magnetic fields in a 3D volume of the human brain at high resolution: 2D vs. Simultaneous multi slice
Authors: Göksu Cihan , Scheffler Klaus , Gregersen Fróði , Eroğlu Hasan , Heule Rahel , Siebner Hartwig , Hanson Lars , Thielscher Axel
Published: August 2023

Exact knowledge of current distributions induced by transcranial electrical stimulation (TES) in the brain is important for effective clinical use of TES. MRCDI uses MRI to measure the TES-induced magnetic fields for estimating the underlying current flow distributions. The estimation methods can benefit from highly sensitive volume MRCDI measurements at a high spatial resolution. Here, we advanced our 2D spoiled gradient-echo-based MRCDI method for a sparse volume acquisition by using simultaneous-multi-slice (SMS) acquisition. Our SMS strategy demonstrated 25% improvement in noise floors against 2D. We test the performance of our methods by phantom and human in-vivo experiments using cable-loop currents.
A semi-realistic and reusable 3D printed brain phantom for MR-based Electrical Properties Tomography
Authors: Meerbothe Thierry , Florczak Sammy , Stijnman Peter , van den Berg Cornelis , Levato Riccardo , Mandija Stefano
Published: August 2023

This work presents a semi-realistic and reusable 3D printed brain phantom to benchmark MR-Electrical-Properties-Tomography reconstruction methods. We show that the hollow compartments of this phantom can be refilled multiple times with different water-based solutions of known electrical properties, which are otherwise not available from in-vivo measurements. Additionally, these brain phantoms can be used inside electromagnetic simulation software, allowing for MR-EPT reconstructions in controlled, simulation settings. In this way, a database comprising of simulated and measured data using these brain models and corresponding 3D printed phantoms will be generated and shared for the first MR-EPT reconstruction challenge.
Oxygen induced T1 changes in head and neck anatomical structures
Authors: McCabe Alastair , Borys Damian , Christian Judith , Pereira Solange , Rowe Selene , Morgan Paul , Shah Jagrit , Blackshaw Elaine , Martin Stewart , Panek Rafal
Published: August 2023

Oxygen enhanced MRI (OE-MRI) is a proposed tumour hypoxia imaging technique that is yet to be widely applied in the head and neck. 7 participants, 3 with suspected head and neck squamous cell carcinoma (HNSCC) were scanned using 3D spoiled GRE-DIXON. After on air scans, oxygen was delivered via a non-rebreather mask. T1 times were determined on in-phase images. Oxygenation led to statistically significant T1 shortening in CSF, thyroid and neck nodes. OE-MRI shows promise in identifying hypoxic regions in the head and neck. Further work investigating the feasibility of OE-MRI to detect hypoxic regions in HNSCC is warranted.
OptiPulse: a flexible optimization framework for short water-selective radiofrequency pulse design
Authors: Sieber Xavier , Bastiaansen Jessica , Roy Christopher , Richiardi Jonas , Stuber Matthias , van Heeswijk Ruud
Published: August 2023

We present a flexible optimization framework to design spectral-selective radiofrequency pulses using numerical optimization on Bloch equation simulation. The RF pulse performance is assessed using a composite loss function for both fat suppression and power requirement. The framework was used to design three binomial (1-1, 1-2-1 and 1-3-3-1) and one cubic B-splines interpolated RF pulses. These pulses were then tested in vitro as well as in vivo in the knee and in the heart, where they demonstrated robust fat suppression comparable to a state-of-the-art water-selective pulse.
Accelerated DeepRF using modified optimal control
Authors: Kim Jiye , Shin Dongmyung , An Hongjun , Jeong Hwihun , Kim Minjun , Lee Jongho
Published: August 2023

DeepRF1 is a recently proposed RF pulse design method using deep reinforcement learning and optimization, generating RF defined by a reward (e.g., slice profile and energy constraint) from self-learning. Here, we proposed an accelerated algorithm for DeepRF that utilizes a modified optimal control, replacing the computationally complex gradient ascent-based optimizer. The new algorithm is tested for slice-selective inversion and slice-selective excitation and compared with original DeepRF and SLR RF pulses, reporting improved computation efficiency while preserving performances. Additionally, a short-duration B1-insensitive inversion pulse, which was difficult to produce in conventional RF algorithms, is designed to demonstrate the usefulness of DeepRF.
Investigating a residual neural network to generated customizable RF pulses for MRI
Authors: Nelson Seger , Feldman Rebecca
Published: August 2023

We investigate a method for the design of radio frequency (RF) pulses for custom simultaneous multi slice spatial profiles. We trained a variation of residual neural networks on a dataset of 96,000 generated adiabatic “power independent of the number of slices” (PINS) RF pulses, varying parameters such as gradient duty cycle, number of pulse lobes, quadratic phase strength, and transition and filter bandwidth. We compared the direct-design RF pulses to those generated by our model.
Simultaneous Multislice Imaging Using Multiphoton MRI
Authors: Ipek Tanya Deniz , Han Victor , Chen Jingjia , Liu Chunlei
Published: August 2023

Simultaneous multislice (SMS) imaging accelerates data acquisition by exciting several slices simultaneously but has a higher specific absorption rate (SAR) due to additional radiofrequency (RF) pulses required to excite multiple frequencies. Multiphoton excitation achieved by oscillating gradient fields provides frequency sidebands, eliminating the need for additional excitation pulses. We have demonstrated SMS imaging for multiphoton MRI and used SENSE reconstruction to separate simultaneously acquired slices with the help of coil sensitivity profiles. Multiphoton SMS images achieve a similar quality to standard one-photon SMS images but offer the benefit of reduced SAR as they do not require extra RF power.
Post-Therapy cortical normalization for phonological processing in developmental dyslexia
Authors: Gudwani Sunita , Mehta Manju , Sagar Rajesh , Behari Madhuri , Narang Vaishna , Dwivedi Sadanad Sadanad , Jagannathan N.R. , Kumaran S.Senthil
Published: August 2023

Dyslexia is a neurodevelopmental disorder with complex spectrum and continuum of cognitive deficits leading to academic and emotional life-long burden, so optimal remediation becomes essential and challenging. Pre- and post- functional imaging studies show the recovery changes in brain with rehabilitation, but can fMRI biomarkers be explored and utilized for customizing therapeutic strategies in dyslexia. In present study at baseline we randomly allocated dyslexic children to therapy (Rx) and waitlist (nonRx) groups. Based on the potential (positive and negative) neural-markers at baseline, we tailored cognitive modules for phonological intervention. Remediation resulted in improved performance and cortical normalization
Alterations in ALPS index and choroid plexus volume after lumboperitoneal shunt in patients with idiopathic normal pressure hydrocephalus
Authors: Kikuta Junko , Kamagata Koji , Taoka Toshiaki , Takabayashi Kaito , Uchida Wataru , Wada Akihiko , Kawamura Kaito , Akiba Chihiro , Nakajima Madoka , Miyajima Masakazu , Naganawa Shinji , Aoki Shigeki
Published: August 2023

Idiopathic normal pressure hydrocephalus (iNPH) is a condition resulting from impaired cerebrospinal fluid (CSF) absorption and excretion that is characterized by a triad of symptoms comprising cognitive decline, gait disturbance, and urinary incontinence. By improving CSF turnover through shunt surgery, symptoms of iNPH can become less severe. However, many mysterious points still exist in the mechanism of CSF dynamics in patients with iNPH. We examined alterations in ALPS index and choroid plexus volume after lumboperitoneal shunt (LPS) surgeries in patients with iNPH. Our results showed improvements in ALPS index and choroid plexus volume in these patients after LPS.
Clinical Feasibility of Compressed SENSE Artificial Intelligence Accelerated SWI in Cerebral Hemorrhage Imaging
Authors: Shi Zhenzhen , Ning Cong , Zhai Chang , Tong Dan , Zhu Yi , Jiang Ke
Published: August 2023

Susceptibility weighted imaging (SWI) is more sensitive than T2* gradient echo MRI in detecting intracranial hemorrhage, but its acquisition time is too long. The purpose of this study is to prospectively assess the clinical feasibility of Compressed SENSE Artificial Intelligence (CS-AI) SWI by comparing it with SENSE SWI and Compressed SENSE (CS) SWI. The results suggested that the CS-AI SWI with an acceleration factor 8 was able to reduce the acquisition time of SWI by 74.58% while maintaining the image quality and accuracy of the diagnosis of intracerebral hemorrhage, except for the diagnosis of cerebral microbleeds.
Automated volumetry of amygdala subregions in Parkinson’s disease patients
Authors: qu mingrui , gao bingbing , jiang yuhan , liu yangyingqiu , li yuan , song qingwei , miao yanwei
Published: August 2023

Cognitive impairment is very common in patients with Parkinson’s disease (PD). The amygdala in the limbic system of midbrain has been proved to play a unique role in cognitive function. However, there are almost no studies on changes in amygdala structure, especially the volume of amygdala subregions, in PD patients. In this study, automated volumetry of amygdala subregions in PD patients was performed and compared with healthy controls, and found that PD patients have amygdala subregions atrophy, especially in bilateral accessory basal nucleus, bilateral cortical nucleus and right medial nucleus.
Predicting Peritumoral Edema Development after Gamma Knife Radiosurgery of Meningiomas Using Radiomics: A Multicenter Study
Authors: Li Xuanxuan , Lu Yiping , Wu Pu-Yeh , Yu Tonggang , Yin Bo
Published: August 2023

The aim of this study is to adopt machine learning and deep learning methods to predict the risk of post-GKS edema for meningiomas. 595 multicenter cases were included to train and validate 38 random survival forest (RSF) and DeepSurv models. The RSF model incorporating clinical, semantic, and ADC radiomic features achieved the best performance with a C-index of 0.861 in internal validation, and 0.780 in external validation. The derived nomogram had excellent discrimination and calibration. The proposed RSF model with a nomogram represents a non-invasive and cost-effective tool to predict post-GKS edema risks, thus facilitates personalized decision-making in meningioma treatment.
Brain Dynamic Functional Connectivity are linked with Attention-Deficit/Hyperactivity Disorder Related Cognitive and Behavioral Dimensions
Authors: Luo Lekai , Chen Lizhou , Li Qian , He Ning , Li Yuanyuan , You Wanfang , Wang Yuxia , Wang Yaxuan , Sweeney John A. , Guo Lanting , Gong Qiyong , Li Fei
Published: August 2023

Sparse canonical correlation analysis (sCCA) was used to delineate multivariate relationship between dynamic functional connectivity (dFC) and behavior or cognition scores in a cohort of children with and without Attention-Deficit/Hyperactivity Disorder (ADHD). We identified four distinct patterns of dFC, each corresponded to a specific dimension of behavior (inattention/hyperactivity, somatization) or cognitive function (inhibition and flexibility, fluency and memory). Altered dFC within the default mode network (DMN) and between DMN and sensorimotor network (SMN) were common to all dimensions.
Radiomic approach for predicting short-term postoperative recovery of cervical spondylotic myelopathy based on NODDI and T2*WI
Authors: Zhang Meng-Ze , Ou-Yang Han-Qiang , Wang Chun-Jie , Liu Jian-Fang , Jin Dan , Zhang Xian-Chang , Zhao Qiang , Liu Xiao-Guang , Liu Zhong-Jun , Lang Ning , Sun Xing-Wen , Jiang Liang , Yuan Hui-Shu
Published: August 2023

This study used radiomics based on T2*-weighted imaging (T2*WI) and neurite orientation dispersion and density imaging (NODDI) to predict the short-term recovery of patients with cervical spondylotic myelopathy (CSM). By classifying patients into good and poor outcomes based on the 3-month recovery rate, we found both T2*WI- and NODDI-based radiomic features to have good prognostic power. Furthermore, radiomic score based on NODDI was an independent predictor, whereas the other features were not. These findings suggest that radiomics based on NODDI has good prognostic power for CSM.
Focused ultrasound-modulated left dorsolateral prefrontal cortex of the non-human primate assessed by functional MRI
Authors: Xu Yu , He Tingting , Wang Haiming , Yu Xiao , Qu Boyi , Li Ssu-Ju , Lai Hsin-Yi
Published: August 2023

Focused ultrasound (FUS) has shown its unique advantages in the field of non-invasive neuromodulation. The dorsolateral prefrontal cortex (DLPFC) is a key node in brain networks involved in cognitive, emotional and sensory processing. Here we evaluated the immediate and latency effects of DLPFC-FUS by functional magnetic resonance imaging (fMRI). The results showed that DLPFC-FUS induced a 3% increase in positive BOLD signal, and decreased FCs in bilateral primary and secondary visual cortices, supported by visual stimuli-evoked BOLD change. Moreover, FCs significantly decreased in left thalamus at 5-min post-FUS and in bilateral anterior cingulate cortex (ACC) at 30-min post-FUS. These results may help to elucidate the effect of FUS neuromodulation.
Establishing causal relationship between resting-state network and behavior
Authors: Li Zengmin , Athwal Dilsher , Chuang Kai-Hsiang
Published: August 2023

Collective influence (CI) analysis provided optimal ranking list of nodes which fastest reduced the giant component of the resting-state networks (RSNs).

Post-learning inhibition of brain regions which were top CI nodes caused retrograde amnesia in the probe test eight days after spatial learning task.

Data-driven approaches were used to explore the role of RSNs in memory consolidation.
Aberrant cortical gyrification in adolescent major depressive disorder
Authors: Bao Weijie , Cao Lingxiao , Feng Ruohan , Gao Yingxue , Li Hailong , Hu Xinyue , Qiu Hui , Liang Kaili , Zhou Zilin , Huang Xiaoqi
Published: August 2023

Evidence has emerged to suggest the important role of cortical gyrification morphology in adult major depressive disorder (MDD). However, little is known about how the altered cortical gyrification contribute to adolescent patients who is at a critical period of brain development. We address this gap by examining the difference of local gyrification index (LGI) between adolescent MDD patients and HCs. We found that MDD patients showed significant increased LGI in the left PCC and bilateral lingual gyrus, which characterize the neurobiological mechanisms of adolescent MDD and may be important to understand the developmental effect of this disorder.
Abnormal dynamic functional connectivity in new-onset, drug-naïve adolescent idiopathic generalized epilepsy
Authors: Yuan Yizhi , Wang Yuting , Mou Jingping , Mei Lan , Liu Chunyang , Qiu Lihua
Published: August 2023

Dynamic functional connectivity (dFC) is a newly developed analysis strategies which could provide novel understandings of the pathophysiological mechanisms of neuropsychiatric disease. 45 adolescents diagnosed with IGE and 32 well-matched healthy controls completed this study using dynamic functional connectivity (dFC). The decreased dFC between two seed regions(MCC and ParaHipp) and PCC and IPL were part of default mode network(DMN). The impaired DMN in adolescent IGE patients suggest dFC might be more sensitive to reflect the changes of brain function in the early stage of disease and dFC analysis was a promising avenue to deepen our understanding of this disease.
Microscopic Fractional Anisotropy Estimation of Spinal Cord in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorder
Authors: Hori Masaaki , Kamiya Kouhei , Hagiwara Akifumi , Yokoyama Kazumasa , Fukunaga Issei , Katsuhiro Sano , Kamagata Koji , Katsutoshi Murata , Fujita Shohei , Andica Christina , Wada Akihiko , Cohen-Adad Julien , Aoki Shigeki
Published: August 2023

We investigated the microstructural changes in the spinal cords of patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) using micro fractional anisotropy (μFA) derived from both double diffusion encoding (DDE) and 2-shell single diffusion encoding data with spherical mean techniques (SMT). There was no significant difference in μFA between MS and NMO. SMTs were not correlated with μFA derived from DDE. Therefore, SMT may be better treated as a separate diffusion MRI metric from μFA to investigate the microstructural alterations of spinal cord in patients with MS and NMOSD in vivo.
Micro- and macro-structural alterations of white matter following sleep deprivation: a longitudinal fixel-based analysis
Authors: Jiang Chunxiang , Bigica Marco , D’Onofrio Ilenia , Liu Zhishan , Zhang Lijuan , Song Chen
Published: August 2023

We examined the effect of sleep deprivation (SD) on human brain white matter（WM） using advanced fixel-based analysis. MRI data collected at four morning time points (7-8am, before and after SD, one night recovery and 3 days recovery). Compared to the session before SD, several WM tracts involving in sleep and wakefulness regulation, memory consolidation and emotion response showed varied fiber density (FD), fiber cross-section (FC) and the combined measure of FD and FC (termed FDC) at different time points. These findings demonstrated the heterogeneous sensitivity of WM tracts in response to SD and the microstructural homeostasis.