bluuebunny/crossref_metadata_2025 huggingface dataset:
Correlation of vessel size and cerebral blood volume measurements in glioma genetic subtypes
Authors: Arzanforoosh Fatemeh , Van Der Voort Sebastian , Incekara Fatih , Vincent Arnaud , Van den Bent Martin , Smits Marion , Warnert Esther
Published: August 2023

Deep insight about tumor microvasculature is important for diagnosis and prognosis of glioma patients. Relative Cerebral Blood Volume (rCBV) and vessel size are two parameters, derived from perfusion MRI, used for evaluation of tumor microvasculature in glioma. In this study, we investigated the clinical value of both rCBV and vessel size and their correlation for three subgroups of glioma based on the recent 2021 World Health Organization (WHO) classification scheme. The result showed that neither rCBV nor vessel size differed significantly between glioma subtypes, though correlation of these two parameters sheds light on the microvasculature characteristics of each subgroup.
Using combined DSC and pcASL perfusion imaging to assess treatment response of high-grade glioma.
Authors: Khurtsylava Mariia , Kovratko Maksym
Published: August 2023

To determine the efficacy and feasibility of using combined DSC and ASL perfusion imaging in a routine protocol to assess the response to treatment of high-grade gliomas in adults. Perfusion imaging is performed for perform differentiation of tumor recurrence from radiation necrosis, since it provides information about angiogenesis at the microscopic level. The data obtained show that the combined use of ASL and DSC perfusion in a routine protocol can be considered as possible additional methods in differentiating recurrent tumor from pseudoprogression.
Multiparametric MRI assessment of the sex influence in the development and response to anti-inflammatory treatment of a glioblastoma rat model
Authors: Cabete Inês Veríssimo , Arias-Ramos Nuria , Gómez Maria Guillén , Castro Margarida Catalão Almiro e , López-Larrubia Pilar
Published: August 2023

The assessment of sexual differences in glioblastoma growth and therapy response has received little attention. We assessed the influence of sex in the MRI features of an orthotropic GBM rat model submitted to anti-inflammatory therapy. Multiparametric MRI studies were acquired at an early and advanced tumor stage of development. GBMs in untreated males presented a more aggressive pattern – worsened as the tumor progressed – than females. While treated males revealed a positive response to meloxicam treatment, females did not. Our results highlighted that sex is a relevant factor to be considered in GBM outcome and anti-inflammatory therapy success.
Application of Fast Field-Cycling (FFC) NMR relaxometry in Colorectal Cancer
Authors: Alamri Amnah , Broche Lionel , Samuel Leslie
Published: August 2023

This pilot study was performed to compare healthy and colorectal cancer samples by investigating R1 NMRD profiles acquired with Fast Field-Cycling (FFC) NMR relaxometry. We collected samples from 18 patients and found a significant difference (P=0.001) in the relaxation rates between normal and colorectal cancer tumours below 100 kHz (2.3uT), while this difference became smaller with increasing the magnetic field strengths and disappeared above 1 MHz (23 uT). This dispersion profile may lead to great potential for diagnosis, staging and monitoring treatment response.
Longitudinal hybrid PET/MRI in juvenile-onset Huntington disease (joHD): a pilot study
Authors: Caligiuri Maria Eugenia , Vizza Patrizia , Veltri Pierangelo , Cicone Francesco , Barberio Paolo , Cascini Giuseppe Lucio , Scaricamazza Eugenia , Maffi Sabrina , Migliore Simone , Squitieri Ferdinando , Sabatini Umberto
Published: August 2023

Hybrid PET-MRI is an emerging technique that allows multimodal evaluation of brain structure and function. This study evaluates longitudinal PET-MRI in one patient with stage-2 joHD, to assess changes related to disease progression. This approach might be useful to test the efficacy of disease-modifying drugs.
Multiple System Atrophy Classification via 3D Convolutional Neural Network and Simulated Brain MRI Parametric Maps
Authors: Mattia Giulia Maria , Villain Edouard , Rascol Olivier , Meissner Wassilios G. , Franceries Xavier , Péran Patrice
Published: August 2023

As a rare neurodegenerative disorder, multiple system atrophy (MSA) can be challenging to analyse using a deep learning approach given the limited sample size. A method is submitted to produce cluster-based simulated brain MR parametric maps from healthy controls, using regional intensity distribution belonging to a set of MSA patients. This enabled to train a 3D CNN only with the simulated set. Testing on the MSA data set, the accuracy obtained was comparable to the state-of-the-art. This approach allows to deal with small samples of data in deep learning, while exploiting a-priori knowledge of the disease.
SANDIAMICO: an open-source toolbox for Soma And Neurite Density Imaging (SANDI) with AMICO
Authors: Schiavi Simona , Ocampo-Pineda Mario , Truffet Raphaël , Caruyer Emmanuel , Daducci Alessandro , Palombo Marco
Published: August 2023

The soma and neurite density imaging (SANDI) model has been recently introduced to estimate diffusion MRI indices of apparent neurite and soma density noninvasively in the brain. Here, we introduce SANDIAMICO a fast (10 seconds for whole brain images) and robust implementation for estimating SANDI parameters using the Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework. Using numerical simulations and in vivo human data, we show excellent performances of SANDIAMICO in terms of accuracy, precision, robustness to noise and intra-subject reproducibility.
Acquisition and finite element analysis of 4DFlow-MR functional angiography in brain and neck
Authors: Pópolo María Del , Salcedo Leandro , Lisazo Clara , Nicolini Federico González , Padin Trinidad González , Marañón Rodrigo Alcalá , Boschi Rocío , Caspi Mercedes , Petra Ezequiel , Ariza Pedro , Fialkowski Valdir , Villamil Daniel Fino
Published: August 2023

The abscence of an angiographic functional analysis of the head and neck regions opens the possibility of applying the 4D Flow technique to quantify hemodynamics and blood flow parameters. Through a Python algorithm using Finite Elements Method the dynamic blood behavior was analyzed, obtaining a complete correlation with the clinical diagnosis.
Hybrid PCA denoising - improving PCA denoising in the presence of spatial correlations
Authors: Henriques Rafael Neto , Jespersen Sune , Shemesh Noam
Published: August 2023

PCA denoising based on the Marchenko-Pastur (MP) distribution has become the state-of-the-art procedure to suppress thermal noise in multi-dimensional MRI. Here we developed a Hybrid-PCA strategy that combines a-priori noise variance estimation and the random matrix theory for PCA eigenvalue classification, to overcome shortcomings of contemporary MP-PCA denoising. Our results show that, while the MP-PCA denoising fails to classify the noise PCA components in data with spatially correlated noise, the Hybrid-PCA algorithm maintains its denoising performance. The Hybrid-PCA denoising can thus be a useful procedure for data corrupted by spatially correlated noise, as typically arises in vendor reconstructed data.
seeVR: an open toolbox for analyzing cerebro-vascular reactivity (CVR) data
Authors: Bhogal Alex
Published: August 2023

The seeVR toolbox is a series of Matlab functions designed help analyze CVR through rapid implementation of processing pipelines. Depending on the type of stimulus used and the properties of the data acquisition, a number of options are available. All code is open-source and freely downloadable from the seeVR github repository (https://github.com/abhogal-lab/seeVR).
T2 mapping for contiguous multi-slice 3D volume: A new EMC-based technique taking into account slice cross-talk effects
Authors: Brui Ekaterina , de Mayenne Charles , Rapacchi Stanislas , Troalen Thomas , Vilmen Christophe , Bendahan David
Published: August 2023

Previously, an elegant method based on the generation of echo modulation curves (EMC) demonstrated a very high accuracy of T2 measurements. However, the original approach considered EMC dictionary modelling only for a single slice mode of multi-echo spin echo (MESE) sequence. For some applications, such as T2 mapping of cartilage in small joints, contiguous MRI is required. As a result, slice cross-talk effect may affect the accuracy of T2 estimation. In this work, we report a modified version of the EMC technique, which can be used to quantify T2 values for zero-gap multi-slice MESE acquisitions in tissues with long T1.
Quantitative magnetization transfer: Estimation of the Semi-Solid Spin Pool's T1
Authors: Flassbeck Sebastian , Assländer Jakob
Published: August 2023

Most magnetization transfer experiments are insensitive to the longitudinal relaxation rate of the invisible semi-solid spin pool and it has become common practice to heuristically assume 1/second. This assumption has, however, been challenged recently. Because this parameter is notoriously hard to estimate, previous studies have relied on the analysis of large white matter regions or the entire brain. Here, we explore the ability to estimate this value on a voxel-by-voxel basis with an MR-Fingerprinting-like pulse sequence.
Effects of temperature in the estimation of inhomogeneous magnetic transfer (ihMT) in post-mortem human brain
Authors: Fritz Francisco J. , Helms Gunther , Vaculčiaková Lenka , Weiskopf Nikolaus , Mohammadi Siawoosh
Published: August 2023

Inhomogeneous magnetic transfer (ihMT) is more sensitive to myelin macromolecules than standard MT proxies. Measuring ihMT in the multi-parameter mapping protocol allows calculating ihMT from MT saturation (MTsat) maps and thus inherently correct for the undesired dependencies on flip angle and the longitudinal relaxation rate. Further validation of this new ihMT metric requires measurement of MPM-based ihMT of human post-mortem material. Here, we showed that ihMT of a whole human post-mortem brain is feasible but can lead to temperature increase in the specimen, which is particularly pronounced in white matter.
CEST MRI at 7T using an optimized parallel transmission saturation scheme
Authors: Delebarre Thaddée , Gras Vincent , Mauconduit Franck , Vignaud Alexandre , Boulant Nicolas , Ciobanu Luisa
Published: August 2023

Compared to the traditional circular polarization (CP) transmission mode, parallel transmission (pTx) excitation allows significant gains in contrast and homogeneity for Chemical Exchange Saturation Transfer (CEST) imaging. Using an in-house developed CEST-EPI sequence incorporating a pTx optimized CEST saturation block, we show that both tailored and universal pTx pulses provide significant improvement at 7T for APT-CEST, GluCEST and GlucoCEST imaging and enable saturation powers unattainable with CP.
Analysis of variability of diffusion tensor imaging measurements using co-electrospun fibre phantom
Authors: Zhou Fenglei , Gao Fei , Xu Longji , Yang Jing , Ren Fuxin , Chen Weibo , Parker Geoff
Published: August 2023

Brain diffusion tensor imaging (DTI) measurements are sensitive to pathological changes, but in order for them to be of greatest use it is vital to understand intra-scanner and inter-scanner variations in DTI metrics. Here we demonstrate a physical phantom with variable pore sizes and fibre orientation that can be used to assess the repeatability and reproducibility of DTI measurements across scanners and protocols and present its application in assessing 9 separate scanner/protocol combinations.
Investigation of sodium alginate- and polyvinyl alcohol-based anisotropic hydrogel phantoms for calibration applications by DWI at 0.6 T
Authors: Mazur Weronika , Stefańska-Bernatowicz Anna , Stodolak-Zych Ewa , Krzyżak Artur
Published: August 2023

Anisotropic hydrogels has been attracting attention for biomedical purposes. These highly-hydrated materials have potential for tissue-mimicking and then, may serve for advanced medical imaging studies. In the work, we present two types of anisotropic hydrogels made from sodium alginate (NA) and polyvinyl alcohol (PVA) in the form of fiber bundle- a single component for larger phantom. We investigated their potential for diffusion-weighted imaging. NA-based phantoms are characterized by highly uniform diffusivity distribution, even higher then water. Single component turned out to be insufficient for the accurate quantification of the microstructure. PVA-based phantom exhibited desirable diffusion properties for tissue-mimicking.
B0 Inhomogeneity Characterization and Correction on an open bore MRI-Linac
Authors: Shan Shanshan , Liu Paul , Waddington David , Dong Bin , Li Mingyan , Tang Fangfang , Liney Gary , Liu Feng , Keall Paul , Whelan Brendan
Published: August 2023

MRI-Linac systems require high fidelity geometric information to localize and track tumors during radiotherapy treatments. B0 field inhomogeneity causes image distortions and can provide inaccurate tumor anatomy. Here, we develop a high-order spherical harmonic method to correct for B0 inhomogeneity induced geometric distortions. Experimental data acquired from a 1T open bore MRI-Linac was used to validate the proposed method.
Brain morphometry abnormalities in children with Childhood Apraxia of Speech.
Authors: Bosco Paolo , Biagi Laura , Fiori Simona , Bombonato Clara , Tosetti Michela , Chilosi Anna
Published: August 2023

Childhood Apraxia of Speech (CAS) is a pediatric speech sound disorder in which precision and consistency of speech movements are impaired in absence of neuromuscular and structural deficit. The cause of CAS remains poorly understood and few neuroimaging studies still exist in children with CAS. In this case-control study we compared both at ROI and voxel level the cerebral gray matter of CAS and healthy controls subjects. The statistical analyses show that gray matter in CAS children is increased in areas of motor circuitries subserving speech and in areas involving sensorimotor learning.
Clinical Implementation of Novel PACS-based Deep Learning Glioma Segmentation Algorithm
Authors: Merkaj Sara , Bousabarah Khaled , MingDe Lin , Pala Andrej , Petersen Gabriel Cassinelli , Jekel Leon , Bahar Ryan , Tillmanns Niklas , Malhotra Ajay , Westerhoff Malte , Aboian Mariam
Published: August 2023

Tumor segmentation is a laborious process, which impedes the progress of data production for development of classification/prediction algorithms. We present a novel PACS-based workflow for deep learning-based auto-segmentation of gliomas that allows generation of annotated images during clinical workflow. We developed a U-Net auto-segmentation algorithm natively imbedded in PACS and trained on BraTS dataset. Subsequent retraining on tertiary hospital dataset was performed and generation of new segmentations, allowing labeling of 440 gliomas in a three-months period. This novel approach for annotated data generation allows real-time building of large, labeled datasets by experts in the field.
Cancer-Induced Metabolic Reprogramming of the Spleen
Authors: Barnett James , Penet Marie-France , Sharma Raj Kumar , Krishnamachary Balaji , Mironchik Yelena , Bhujwalla Zaver
Published: August 2023

Our findings demonstrate that tumors drive metabolic alterations in the spleen. These metabolic changes may contribute to immune suppression and poor prognosis.
Radiomics models based on mDixon for simultaneous liver steatosis, fibrosis and iron deposition quantification of chronic liver disease
Authors: Wang Qing , Sheng Ye , Zhang Jilei , Chen Weibo
Published: August 2023

To assess the diagnostic performance of radiomics analysis based on mDixon Quant in simultaneously quantifying liver steatosis, fibrosis and iron deposition of chronic liver disease (CLD) and eliminating the interaction of histopathological factors.
The effect of Gd-EOB-DTPA on liver IVIM imaging of rabbits with non-alcoholic fatty liver disease
Authors: Wang Xia , Jiang Yu , Zhang Sheng , Wang Si , Wei Wei , Yao Mengzhuo , Zhao Na , Han* Yuedong
Published: August 2023

Hepatobiliary cell-specific contrast agent of Gd-EOB-DTPA hepatobiliary phase acquisition DWI sequence will not affect lesion display and ADC value [1].Few studies have been performed on the effect of IVIM on hepatic parenchyma and have focused on studies in various hepatic occupancy contexts with discrepant findings [2,3].This study modeled a healthy control group and a non-alcoholic fatty liver disease (NAFLD) group. Gd-EOB-DTPA had no significant effect on the image quality and quantitative index of liver IVIM imaging in two groups, and IVIM scanning in the hepatobiliary waiting interval after placing Gd-EOB-DTPA enhancement helped to improve the examination flow rate.
Low Resolution Diffusion Weighted Imaging for the Assessment of Diffuse Liver Disease
Authors: Volety Srijyotsna , Hernando Diego , Pirasteh Ali
Published: August 2023

We evaluated the reproducibility of liver ADC measurements across acquisition parameters using low spatial resolution DWI with M1 optimized diffusion imaging waveforms (MODI) and the routinely clinically utilized monopolar (MONO) waveforms. We also evaluated the effects of various M1 values as well as those of breath-hold and respiratory-triggering on MODI-DWI liver ADC measurements at lower resolutions than utilized in clinical practice. MONO-DWI liver ADC suffered from bias and resolution-dependence in the left lobe while MODI-DWI liver ADC did not demonstrate this effect. MODI-DWI liver ADC did not demonstrate bias with respect to resolution, M1, or breathing technique.
Mouse models of diet-induced obesity allow for optimal magnetic resonance measurements of brown adipose tissue activation and heterogeneity
Authors: Tomaszewski Michal , Haley Hyking , Meng Xiangjun , Miller Corin
Published: August 2023

Robust measurement of brown and white adipose tissue physiology in response to treatment is essential in pharmaceutical research. In this work we propose for the first time that the diet-induced obesity (DIO) mouse model can be successfully used in conjunction with both Multi Gradient Echo and Fast Spin Echo based methods for sensitive characterization of changes in brown (BAT) and white adipose tissue following pharmaceutical intervention, showing more consistent responses than lean mice. Spatial heterogeneity within BAT and response dynamics are reported, relevant for future use of the model and the proposed framework in weight loss and drug characterization studies.
Constraint-Based Sequence Optimization in a Scanner-Independent MRI Framework
Authors: Hoinkiss Daniel , Konstandin Simon , Günther Matthias
Published: August 2023

We demonstrate a constraint-based approach of MRI sequence development in the vendor-independent MRI pulse sequence development framework gammaSTAR and demonstrate this concept in arterial spin labeling by optimizing the timings of the background suppression pulses to minimize the signal contribution of chosen T1 values in the human brain. This concept can raise MRI sequence development to a new abstraction level by, instead of providing exact timings and parameter values, defining physical constraints and conditions to be satisfied by the MRI sequence during an automated sequence generation process.
Multi-center, Multi-vendor evaluation of quantitative susceptibility mapping for quantification of liver iron
Authors: Buelo Collin , Zhao Ruiyang , Velikina Julia , Bollmann Steffen , Zhu Ante , Yuan Qing , Ghasabeh Mounes , Ruschke Stefan , Karampinos Dimitrios , Harris David , Mattison Ryan , Jeng Michael , Pedrosa Ivan , Kamel Ihab , Vasanawala Shreyas , Yokoo Takeshi , Reeder Scott , Hernando Diego
Published: August 2023

Quantitative susceptibility mapping (QSM) of the liver is an emerging method to quantify liver iron concentration (LIC). Multiple new methods have recently been introduced for QSM in the liver. These methods include CobraChi, a deep learning-based method, as well as an L2-optimization based method. This work evaluates the performance of these liver QSM methods across multiple centers and MRI vendors.
APT-CEST Scan-Rescan Reproducibility in Healthy Volunteers and Brain Glioma Patients at 3 Tesla
Authors: Wamelink Ivar , Padrela Beatriz , Kuijer Joost , Zhang Yi , Barkhof Frederik , Mutsaerts Henk , van de Giessen Elsmarieke , Keil Vera
Published: August 2023

Amide proton transfer (APT) chemical exchange saturation transfer (CEST) MRI is a potentially useful clinical technique to image brain tumors, but its reproducibility was not yet investigated in detail. Our 3T scan-rescan protocol on volunteers and glioma patients revealed high within-session and slightly lower in-between-session and between-day reproducibility, with highest reproducibility occipitally and centrally in the brain and lowest at the skull base. The within-session reproducibility for patients was also good, both intratumoral and extratumoral. These results show that APT-CEST at 3T MRI renders reproducible values allowing for clinical monitoring of metabolic brain tumors.
Repeatability of ultra-high-resolution Multi-Parametric Mapping across five 7T sites
Authors: sherif siya , Aghaeifar Ali , Pine Kerrin , Ding Belinda , Seif Maryam , Balteau Evelyne , Nanz Daniel , Bastin Christine , Salmon Eric , Maquet Pierre , Vandewalle Gilles , Rodgers Christopher , Freund Patrick , Weiskopf Nikolaus , Phillips Christophe , Callaghan Martina
Published: August 2023

Repeatability is key to the utility of quantitative MRI, which promises standardised measures with biological relevance. Here we tested a candidate ultra-high resolution (0.6mm isotropic) multi-parameter mapping protocol at five 7T sites. Repeatability was good, with B0 and B1+ field inhomogeneities being the limiting factor. MTsat had the lowest repeatability and PD the highest. R1 and R2* were intermediate. Repeatability was also lowest in temporal and occipital cortices. These observations were consistent across sites.
Reproducibility of rapid quantitative multiparameter mapping using skipped-CAIPI 3D-EPI
Authors: Wang Difei , Stirnberg Rüdiger , Stöcker Tony
Published: August 2023

We investigated the reproducibility of multiparameter mapping (MPM) using multi-echo skipped-CAIPI 3D-EPI at 3T. Compared to >15 minutes of FLASH-MPM, EPI-MPM under 3 minutes achieved considerably high repeatability. In only one fifth of the total scan time of FLASH, the resulting CoVs of EPI were only 1.2-2.2 times larger than FLASH for R1, PD and MTsat, while the CoV of EPI for R2* was even smaller. Minor differences of the observed parameter estimates can be attributed to the intrinsic difference between EPI and FLASH sequence timing.
Within‐subject reliability of proton density estimation using quantitative magnetic resonance imaging
Authors: Sreenivasan Karthik , Cordes Dietmar , Mishra Virendra , Hua Le
Published: August 2023

New advances in quantitative MRI (qMRI) techniques provide basic MRI properties such as proton density (PD) that can act as a direct surrogate of the tissue integrity in the voxel. PD may help demonstrate differences on an individual level in patients with multiple sclerosis. In this study, we wanted to compare the within-subject reproducibility of qMRI-based PD measures. Variability in the estimated PD was low and fell within the limits for reliability. These results suggest that in-vivo estimates of PD using qMRI are reproducible within the subject in the same scanner and could play a vital role in clinical studies.
A preliminary investigation into the contribution of Amines to the CEST contrast at 2 ppm and 3 ppm in high-grade gliomas at 7T
Authors: Abecassis Bárbara Schmitz , Najac Chloé , de Bresser Jeroen , Dirven Linda , Taphoorn Martin , van Osch Matthias , Koekkoek Johan , Ercan Ece
Published: August 2023

CEST allows to non-invasively image metabolites and proteins, and the role of APT and NOE CEST in gliomas has been widely investigated. On the other hand, the contribution of amines to the CEST signal at 2 and 3 ppm, and its relationship to creatine and glutamate concentrations, remain unclear. We evaluated the amine CEST contrast in tumor and contralateral white matter in three glioma patients, and compared it to the MRS data. Overall we found a decrease in amine CEST alongside a decrease in total creatine and glutamate in the tumor compared to the contralateral white matter.
Evaluation of the REFILL dynamic distortion correction method for fMRI
Authors: Robinson Simon , Bachrata Beata , Eckstein Korbinian , Dymerska Barbara , Bollmann Saskia , Bollmann Steffen , Hodono Shota , Cloos Martijn , Tourell Monique , Jin Jin , O'Brien Kieran , Reutens David , Trattnig Siegfried , Enzinger Christian , Barth Markus
Published: August 2023

We evaluate the performance of a recently-proposed dynamic distortion correction (DDC) method for fMRI at 7T, with a task which generates field fluctuations. The Reverse-Encoded First Image and Low resoLution reference scan (REFILL) method generates fieldmaps from the phase of standard, single-echo EPI from fMRI time series, using coil sensitivity information from a fast reference scan and removing other, non-B0-related contributions to the phase, which are calculated from a readout-reverse EPI volume. In contrast to conventional static distortion correction (SDC) with a GE-based fieldmap, REFILL captured dynamic changes to the field, leading to an accurate correction and increased tSNR.
B0 shimming in human brain using rosette encoding at 7T
Authors: Pan Jullie , Moon Chan , Hetherington Hoby
Published: August 2023

With increasing use of ultra-high field, there is a need for fast and efficient field mapping. Towards this purpose, the non-Cartesian circular rosette trajectory is advantageous due to its low gradient demands and its efficiency due to the simultaneous acquisition of spatial and field encoding information. We describe the implementation of the circular rosette trajectory for field mapping at 7T in the human brain and compare this to the highly accurate although slow 5 echo Bolero field map.
Image-based computer simulations of haemodynamics and blood cells distributions: A comparison between MRI and ultrasound
Authors: Sirilapanan Vasit , Chung Yongmann , Harrison Richard , Cameron Clare , Lynn Michael , Hutchinson Charles , Ahmed Farhan
Published: August 2023

MRI-based CFD simulations are compared with ultrasound-based CFD to ascertain the capability of ultrasound.
Deep learning for prostate zonal segmentation robust to multicenter data
Authors: Turco Simona , Blach Hubert , Fernandes Catarina Dinis , Barentsz Jelle , Heijmink Stijn , Wijkstra Hessel , Mischi Massimo
Published: August 2023

Prostate zonal segmentation is an important step for automated PCa diagnosis, MRI-guidedradiotherapy and focal treatment planning. Here we proposed a multi-channel U-Net for automatic prostate zonal segmentation, able to include multiple MRI sequences. Using a small, multicenter, multiparametric MRI dataset, we investigated its robustness towards the acquisition protocol and whether additional imaging sequences improve segmentation performance. Our results show that T2-weighted imaging alone is sufficient for successful prostate zonal segmentation. Despite using a small multicenter dataset, the models were robust towards the acquisition protocol and the performance was comparable to that obtained with larger datasets from a single institute.
Intravoxel Incoherent Motion Combined With DCE-MRI of Endometrial cancer:Correlations Between Multimodal Parameters and Her-2 Expression
Authors: Ma Changjun , Tian Shifeng , Chen Lihua , Wang Nan , Song Qingwei , Liu Ailian
Published: August 2023

At present, there are few reports on the application of imaging methods to predict the Her-2 gene expression of EC. This study will use the two functional sequences of IVIM and DCE-MRI to explore its preoperative prediction of the Her-2 gene expression of EC. Value, at the same time, discuss the correlation between the parameters of the two functional sequences.
Removal of perfusion lag structure before ICA-FIX cleaning boosts both reproducibility and between-subject similarity in fcMRI
Authors: Aso Toshihiko , Hayashi Takuya
Published: August 2023

Removal of the perfusion lag structure in the fMRI signal was combined with independent component analysis (ICA)-based cleaning to evaluate its effect on test-retest reproducibility. In HCP test-retest data from 40 subjects, either treatment and the combined method effectively improved the reproducibility of functional connectivity. However, the effect was more evident in between-subject similarity of the connectivity pattern than within-subject similarity. This finding suggests that the perfusion lag structure may be one of the sources of between-subject variability, that may degrade the functional connectivity.
Mitigation of noise floor in diffusion MRI using deep learning
Authors: Cheng Hu , Wang Jian , Vinci-Booher Sophia , Wen Qiuting , Newman Sharlene
Published: August 2023

Rectified noise floor is a challenging problem for high-resolution diffusion MRI, which cannot be tackled by current denoising methods. We propose a simple deep learning method for correcting noise floor in diffusion MRI. The method is based on 1D CNN model and works on voxel-wise time courses. Therefore, even one dataset of the brain has sufficient number of samples for training, which is a big advantage for practical application. Both simulation and in vivo results show that the method is robust in mitigating the noise floor artifact and restore the true values of diffusion metrics.
NODDI-FAST derived parameters are echo-time independent
Authors: Alsameen Maryam , Gong Zhaoyuan , Kiely Matthew , Triebswetter Curtis , Bouhrara Mustapha
Published: August 2023

In a previous work, we introduced the NODDI-FAST approach to address issues regarding overestimated CSF and neurite density (NDI) fractions in white matter seen with the original NODDI approach. However, in both NODDI-FAST and NODDI signal models, the compartment-specific T2 relaxations are not considered. Therefore, derived parameter estimates, especially NDI, could be dependent on echo time (TE). Here, we show that, as expected, ODI derived values using either NODDI or NODDI-FAST are TE-independent. We also confirm that NDI derived values using NODDI are TE-dependent. More importantly, we show that NDI derived values using NODDI-FAST are TE-independent.
Fat-water separated T1 mapping with multi-echo MP2RAGE
Authors: Fortin Marc-Antoine , Fortier Véronique , Pazmino Jorge Campos , van der Kouwe Andre , Levesque Ives
Published: August 2023

To design a novel fat-water separated T1 mapping technique from a multi echo (ME) version of the Magnetization Prepared Two Rapid Acquisition of Gradient Echoes (MP2RAGE) sequence by adapting the MP2RAGE sequence to shorter T1 values resembling values observed for fat (between 200 and 800 ms) and introducing a 3-point Dixon fat-water separation step in the analysis.
An initial multi-parametric imaging experience of MULTIPLEX at 5T whole body system
Authors: Ye Yongquan , Liu Xiaodi , Wu Ying , Zhang Zhongqi , Xu Jian
Published: August 2023

In this work, we evaluated the performance of a recently proposed high resolution multi-parametric method, i.e. MULTIPLEX, on a state-of-the-art 5T whole body scanner. Comparing to the 3T counterpart, MULTIPLEX on 5T generally offers improved SNR, image quality and imaging efficiency, while maintaining satisfactory performance on B1/T1 mapping.
Practical and readily-available relaxometry method
Authors: Madore Bruno , Jerosch-Herold Michael , Cheng Cheng-Chieh , Mukundan Srinivasan , Guenette Jeffrey , Mihai Georgeta
Published: August 2023

Although many methods already exist to map T1, T2 and M0, these often involve special sequences not readily available on clinical scanners and/or may require long scan times. In contrast, the proposed method can run on most scanners, it offers flexible tradeoffs between scan time and image quality, and it generates spatially-aligned parameter maps. Validation was performed in gel phantoms with varying concentrations of contrast agents, and in vivo examples are presented from three neuroradiology patients. Compared to other quantitative mapping methods, the present method is meant to stand out in terms of its practicality and availability.
Calibration of saturation prepared turbo FLASH B1+ maps by actual flip angle imaging at 7T.
Authors: Sedlacik Jan , Tomi-Tricot Raphael , Wilkinson Tom , Bridgen Pip , Mauconduit Franck , Amadon Alexis , Giles Sharon , Hajnal Joseph , Malik Shaihan
Published: August 2023

A fast and accurate B1+mapping method is essential for making proper use of a parallel transmit array with high number of coil elements in a clinical setting. The saturation-prepared turbo FLASH method offers this capability and is implemented in the fully automated pre-scan adjustments of the currently only clinical ultra-high magnetic field strength MRI system. However, some parallel transmit methods require an even higher accuracy. This can be achieved by calibrating the fast B1+measurements with a more accurate but longer B1+mapping method.
Inter-coil applicability of trained neural networks for B1+ prediction in parallel-transmit.
Authors: Plumley Alix , Kopanoglu Emre
Published: August 2023

Motion-resolved parallel-transmit (pTx) B1-maps can be predicted using neural networks, facilitating online pulse re-design – a prospective solution to motion. However, networks require large training-datasets. Since different pTx coils inherently produce different B1-distributions, it is unclear whether coil-specific training-datasets are needed. Here, we train networks on simulated data from one coil-model and test on 6 differently-sized coil-models. While performance was optimal for the coil on which networks were trained, B1-prediction yielded lower error than that caused by motion in ≥91% of magnitude, and ≥55% of phase evaluations for 5 out of the 6 models, demonstrating some generalisability across coils.
Respiration robust universal pulses in the human heart at 7T for shallow and deep breathing
Authors: Aigner Christoph , Dietrich Sebastian , Krüger Felix , Lutz Max , Schmitter Sebastian
Published: August 2023

This study demonstrates the design and application of a new class of universal pulses (UP) designed for a library of 22 non-respiration resolved (NRR) B1+-maps acquired in-vivo during shallow breathing (SB) and 30 respiration resolved (RR) B1+-maps acquired during deep breathing (DB). The proposed UP was tested on 9 NRR SB (test-cases-SB) and 15 RR DB B1+-maps (test-cases-DB) and was applied experimentally in five volunteers (test-cases-DB) along with tailored pulses in multiple gradient echo measurements. Compared to tailored pulses, UP resulted in a slightly overall decrease of the FA homogeneity but similar image quality across all test-cases.
Eight Channel, Dual-Matrixed, Parallel Transmit RF Power Amplifier for 1.5T MRI
Authors: Vaughan Thomas , Garwood Michael , Suddarth Steve , DelaBarre Lance , Myer Dan
Published: August 2023

A new, laboratory grade RF power amplifier that offers eight channels of low, CW power for simultaneous transmit and receive applications, and eight channels of high, peak-pulsed power for conventional MRI is presented. These FPGA controlled, multiple transmit channels can be matrix switched into 1, 2, 4, and 8 channel combinations for a range of 2W, 4W, 8W and 16W CW, and 2kW, 4kW, 8kW and 16kW peak power pulses. Further each channel can be used for independent phase, gain, frequency, space and time for maximum flexibility in RF field modulation. This power amplifier meets our wide ranging experimental requirements.
Characterising Brain White Matter Alterations in Type 2 Diabetes: A UK Biobank Study of Neurite Orientation Dispersion and Density Imaging.
Authors: Alotaibi Abdulmajeed , AlTokhis Amjad , Podlasek Anna , Tench Chris , Lee Sieun , Constantinescu Cris , Dineen Rob
Published: August 2023

Type 2 diabetes is a metabolic disorder associated with subtle microstructural alteration of brain white matter. Diffusion tensor imaging (DTI) has been widely applied to evaluate white matter microstructural pathology in type 2 diabetes; however, DTI has limitations and lacks specificity. Using UK Biobank data, we applied neurite orientation dispersion and density imaging (NODDI) as an alternative advanced diffusion method to overcome DTI limitations. In this study, NODDI showed its potential role in giving a better biophysical characterisation of white matter neuroaxonal pathology in type 2 diabetes compared to DTI.
Longitudinal Fixel-Based Analysis of diffusion MRI in the zQ175 Huntington’s disease mouse model
Authors: Vidas-Guscic Nicholas , van Rijswijk Joëlle , Van Audekerke Johan , Jeurissen Ben , Missault Stephan , Pustina Dorian , Tang Haiying , Cachope Roger , Liu Longbin , Dominguez Celia , Munoz-Sanjuan Ignacio , Van der Linden Annemie , Verhoye Marleen
Published: August 2023

Huntington’s disease (HD) is a neurodegenerative disorder that affects motor and cognitive abilities. In this study, we present the outcome of a longitudinal multi-shell DWI investigation of the zQ175 HD mouse model using the diffusion tensor, diffusion kurtosis, and fixel-based analysis. This study reveals microstructural deficits at an early stage of the disease that mainly affect the diffusion tensor in corpus callosum and kurtosis in caudate putamen and grey matter, while fiber cross-section is reduced in major fiber bundles. At a late stage, many white matter fiber bundles show deficits that are indicative of differential myelination and potential axonal pathology.
Myelin Alterations during the Development of an Absence Seizure Mouse Model
Authors: Kung Gustavo Chau Loo , Knowles Juliet , Ni Lijun , Huguenard John , Monje Michelle , McNab Jennifer
Published: August 2023

Maladaptive myelination may be related to the increasing frequency of absence seizures. To explore this connection, we performed MRI microstructural measurements in ex vivo mouse brains from the Scn8amed+/- model of absence epilepsy in two cohorts of mice at two points of their development, both before and after seizures were well established. Our MRI g-ratio results strongly agree with our previous findings based on electron microscopy and show a clear alteration of myelination throughout the anterior portion of the corpus callosum.
Abnormal Cerebral Microstructures in Amyotrophic Lateral Sclerosis: a Diffusion Kurtosis Imaging Study
Authors: Shi Jia , Chen Hua
Published: August 2023

Our study aim to investigate cerebral microstructural changes in Amyotrophic lateral sclerosis (ALS) using diffusion kurtosis imaging (DKI) for the first time. ALS patients showed mean kurtosis metrics (MK) reductions in several gray/white matter areas. The spatial distribution of the regions with reduced radial kurtosis(RK) was similar to those with decreased MK. No significant axial kurtosis(AK) difference was found between groups. The correlation analysis revealed significant associations between DKI metrics and clinical assessments. Additionally, several white matter regions showed between-group differences in conventional diffusion metrics; but the spatial extent was smaller than that with reduced DKI metrics.
Towards improving high-grade gliomas diagnostic surveillance on T2-weighted images using weak labels from radiology reports
Authors: Di Noto Tommaso , Atat Chirine , Teiga Eduardo Gamito , Hegi Monika , Hottinger Andreas , Hagmann Patric , Cuadra Meritxell Bach , Richiardi Jonas
Published: August 2023

Manual annotations are a major bottleneck in supervised machine learning. We present a method that leverages Natural Language Processing (NLP) to generate automatic weak labels from radiology reports. We show how weak labels can be used for the image classification task of high-grade-glioma diagnostic surveillance. We apply a convolutional neural network (CNN) to classify T2w difference maps that either indicate tumor stability or instability. Results suggest that pretraining the CNN with weak labels and fine-tuning it on manually-annotated data leads to better performance (though not statistically significant) when compared to a baseline pipeline where only manually annotated data is used.
A multiplicative denoising method based on compressed sensing for magnetic resonance spectroscopy and imaging
Authors: Martinho Ricardo , Koprivica David , Novakovic Mihajlo , Jaroszewicz Michael , Frydman Lucio
Published: August 2023

2D MRI/S are commonly affected by changes in temperature, field drifts, or motions, leading to multiplicative noise. We introduce here CoSeM (Compressed Sensing Multiplicative) denoising, a method that converts instability-related “t1” noise, into additive noise liable to signal averaging. CoSeM evaluates and discards indirect-domain points that may have been strongly influenced by instabilities, and makes up for this discarding by compressed sensing reconstructions. 2D localized MRS in the brain and 2D abdominal MRI experiments liable to instabilities, evidence 2-3 fold increases in SNR by CoSeM processing. CoSeM is also shown to retain quantitative information –e.g., in T1 mapping experiments.
Conductivity mapping at 0.55 T with balanced steady state free precession
Authors: Iyyakkunnel Santhosh , Bieri Oliver
Published: August 2023

Conductivity mapping depends sensitively on the signal-to-noise ratio (SNR) of the transmit phase estimation. It is thus questionable, whether conductivity mapping can be performed at low field. Due to reduced off-resonances, however, a possible solution for the reduced SNR might be offered by balanced steady state free precession (bSSFP). Brain conductivity mapping with bSSFP was investigated at 0.55 T and appears to be feasible but besides SNR also the reduced curvature of the transmit field becomes challenging.
Robust measurements of current-induced magnetic
fields in the human brain by EPI
Authors: Gregersen Fróði , Göksu Cihan , Eroğlu Hasan , Zuo Zhentao , Thielscher Axel , Hanson Lars
Published: August 2023

Magnetic resonance current density imaging (MRCDI) can measure the magnetic fields created in the human brain from currents injected via surface electrodes. Previous methods have demonstrated high sensitivity sufficient for low current strengths (~1 mA). However, they have also proven susceptible to physiological noise. Here we increase the temporal resolution of the method and thereby the robustness to physiological noise by using echo-planar imaging (EPI) for the acquisition. We show that the method produces reliable magnetic field measurements with an average sensitivity of 52 pT for a 2 minutes scan with 3 mm isotropic resolution.
A deep learning-based background field removal method for brains containing high susceptibility sources
Authors: Zhu Xuanyu , Gao Yang , Liu Feng , Crozier‬ ‪Stuart , Sun Hongfu
Published: August 2023

Background field removal (BFR) is a critical step in quantitative susceptibility mapping (QSM). Eliminating the background field in brains containing high susceptibility sources, such as intracranial hemorrhages, is challenging due to the relatively large scale of the local field induced from these sources. This study proposed a new deep learning-based method, "BFRnet", and compared it with several conventional BFR methods in processing two simulated and two in vivo brain datasets. The BFRnet method was effective in background field removal for acquisitions of arbitrary orientations and performed significantly better than other methods in the regions with high susceptibility sources.
Accelerating brain susceptibility weighted imaging using compressed-SENSE
Authors: Ding Jinli , Lin Liangjie , Wang Jiazheng
Published: August 2023

Susceptibility weighted imaging (SWI), acquiring both magnitude and phase information for tissues using a 3D gradient-recalled echo sequence, is advantageous to detect microhemorrhages and microvasculature and useful in diagnosing small vessel diseases etc., but can be suffering from the long acquisition time. This study evaluated the effectiveness of brain SWI accelerated by compressed SENSE (CS-SENSE), and the CS-SENSE factor 4 is recommended in routine practice. Besides, the CS-SENSE factor 10 maybe a fast surrogate for distinguishing CMBs but sacrificing SN-RN visualizations.
Increased Brain Iron Deposition in Moderate and Severe Obstructive Sleep Apnea using Quantitative Susceptibility Mapping
Authors: Li Xinchun , Wang Peng , Wan Qi , Guo Yihao , Hu Jianfeng , Peng Yu , Xia Xiaoying , Liu Jieqiong , Xie Xiaobin , Wang Mengzhu
Published: August 2023

In the current study, we assessed the possible alterations of iron accumulation in the brain of patients with Obstructive Sleep Apnea (OSA) using quantitative susceptibility mapping (QSM). We found that there was increased iron accumulation in the bilateral hippocampus for patients with OSA, compared to controls. And the QSM value of the bilateral hippocampus was related to the course of disease in patients with OSA. The QSM values of the right hippocampus were correlated with multiple clinical indicators and may therefore be used as potential biomarkers to further understand the pathophysiological mechanisms of moderate to severe OSA.
Stratified Parkinsonism classification based on multi-modality MRI
Authors: Leng Yijun , Liu Xueling , Geng Daoying , Liu Fengtao , Wu Pu-Yeh , Li Yuxin , Yang Liqin
Published: August 2023

For differential diagnosis between PD and atypical parkinsonisms, we designed a stratified automated method based on SVM and multi-modality MRI, including T1WI, QSM and DTI. 163 patients (96 PD, 27 MSA, 40 PSP) and 65 healthy controls were recruited. Features including volume, cortical thickness, magnetic susceptibility, FA and MD of 124 ROIs were calculated for SVM classification. The result showed that SVM classification based on susceptibility enabled accurate differentiation of patients with parkinsonian disorders and controls, and classification of PD, MSA and PSP was allowed by using T1 and DTI.
Altered Visual Network and Global Fluctuation in the Resting-state fMRI of Patients with Parkinson’s Disease
Authors: Mekbib Destaw , Dai Weiying , Cai Miao , Liu Xiaoli , Zhao Li
Published: August 2023

Resting-state fMRI plays an increasing role in understanding the neural mechanisms of Parkinson's disease (PD). However, neural network alterations, regional and global signal associations are not fully understood in PD patients. Here, we studied the whole-brain neural networks including the inter-network and their correlations with the global fluctuation in 37 PD patients and 20 healthy controls. Our findings revealed that the visual cortex had reduced neural network connectivity in PD patients and altered connections from default mode network to other networks. Weaker correlations were observed between the global signal and regional networks in the PD patients than healthy controls.
Optimization of TE and Postprocessing for Nigrosome-1 Imaging using Wave-CAIPI Susceptibility Weighted Imaging at 3T
Authors: Fu Caixia , Zhang Youmin , Li Qing , Liu Wei , He Naying , Liu Yu , Polak Daniel , Haacke E. Mark , Yan Fuhua
Published: August 2023

In this work, Wave-CAIPI accelerated 3D SWI has been used to achieve whole brain imaging in about 3min 30s. Both short-TE and long-TE protocols were compared for the detection of the Nigrosome-1(N1) sign. The phase-mask formula and number of phase mask multiplications were adjusted to explorer their influence on the contrast-to-noise (CNR) of the N1 sign relative to adjacent tissues. The result showed that long-TE protocol had better CNR and made it easier to recognize the N1 sign. The adjusted phase-mask formula with an increased number of phase mask multiplications also helped to improve the CNR of the N1 sign.
White matter microstructure alterations using Generalized Q-Sampling Imaging in Moderate and Severe Obstructive Sleep Apnea
Authors: Wang Peng , Li Xinchun , Wan Qi , Zou Wenjin , Guo Yihao , Wang Mengzhu , Hu Jianfeng , Peng Yu , Xia Xiaoying , Xie Xiaobin , Liu Jieqiong
Published: August 2023

In the current study, we assessed possible alterations of brain white matter (WM) microstructure in patients with obstructive sleep apnea (OSA) using generalized q-sampling imaging (GQI). We found higher normalized quantitative anisotropy values of the bilateral superior longitudinal fasciculus, uncinate fasciculus, fornix, and corpus callosum bundle in the OSA group vs controls, which were related to multiple clinical indices of OSA.