bluuebunny/crossref_metadata_2025 huggingface dataset:
Background prostate tissue is quantitatively abnormal on T2-weighted MRI in patients with clinically significant prostate cancer
Authors: Conlin Christopher , Karunamuni Roshan , Hussain Troy , Zhong Allison , Kallis Karoline , Do Deondre , Lui Asona , Mani Garnier , Ollison Courtney , Domingo Mariluz Rojo , Shabaik Ahmed , Kane Christopher , Bagrodia Aditya , McKay Rana , Kuperman Joshua , Rakow-Penner Rebecca , Hahn Michael , Dale Anders , Seibert Tyler
Published: August 2024

In this study, we examined whether patients with clinically significant prostate cancer (csPCa) have abnormal T2-weighted signal in prostate tissue outside of index lesions identified on MRI—i.e., in the background prostate (BP). In two independent patient cohorts, normalized T2-weighted signal was systematically lower in the BP of subjects with csPCa compared to those without. Reduced T2-weighted BP signal indicated the presence of csPCa with accuracy comparable to lesion-based measurements. Consideration of T2-weighted signal in the whole prostate improved patient-level detection of csPCa over DWI alone, suggesting that it provides complementary diagnostic value.
18F-PSMA-1007 PET/MR compared to PET/CT in prostate cancer recurrence: impact on clinical management
Authors: Abrahamsen Bendik Skarre , Bogsrud Trond Velde , Hernes Eivor , Tandstad Torgrim , Langørgen Sverre , Castillejo Miguel , Selnæs Kirsten Margrete , Knudtsen Ingerid Skjei , Keil Thomas Morten Ingmar , Johansen Håkon , Bathen Tone Frost , Elschot Mattijs
Published: August 2024

For patients with suspected prostate cancer recurrence, we examined the added value of 18F-PSMA-1007 PET to MR and CT imaging, and whether choice of PET modality, i.e. PET/MR or PET/CT, had an impact on clinical management. An intention-to-treat analysis was performed using findings from MR and CT alone, MR and CT with PET from PET/CT, and MR and CT with PET from PET/MR. Addition of 18F-PSMA PET changed clinical management in over 40% of patients. Differences in clinical management between PET/CT and PET/MR were smaller than adding any PET modality to MR and CT.
Hyperpolarized 13C Pyruvate + Urea Dual Agent MRI Detects Hypoxia-Driven Metabolism Perfusion Mismatch in Patient w/ Aggressive Prostate Cancer
Authors: Chen Hsin-Yu , de Kouchkovsky Ivan , Nguyen Hao , Stohr Bradley , Gebrezgiabhier Daniel , Santos Romelyn Delos , Carvajal Lucas , Ohliger Michael , Wang Zhen , Qin Hecong , Liu Xiaoxi , Simko Jeffry , Gordon Jeremy , Larson Peder , Bok Robert , Aggarwal Rahul , Kurhanewicz John , Vigneron Daniel
Published: August 2024

The first-in-human hyperpolarized [1-13C]pyruvate+[13C,15N2]urea dual-agent MRI demonstrated the safety and feasibility of simultaneous characterization of prostate cancer metabolism and blood flow as a two-minute addition to the standard 1H-multiparametric MRI. Metabolism-perfusion mismatch (i.e. elevated pyruvate-lactate conversion and decreased urea perfusion) in subregions of the high-grade prostate tumor was in agreement with the histopathological and immunochemical markers that reflected lethal phenotypes and their associated hypoxic tumor microenvironment. Correlative analysis of urea and Gadolinium-derived pharmacokinetic parameters found low correlation between the two, which indicates that HP 13C urea’s unique contrast mechanism offers independent information inaccessible through conventional 1H DCE-MRI.
Anatomical-aware Siamese Deep Network for Prostate Cancer Detection on Multi-parametric MRI
Authors: Zheng Haoxin , Qi Miao , Hung Alex , Zhao Kai , Raman Steven , Sung Kyunghyun
Published: August 2024

The study aimed to build a deep-learning-based prostate cancer (PCa) detection model integrating the anatomical priors related to PCa’s zonal appearance difference and asymmetric patterns of PCa. A total of 220 patients with 246 whole-mount histopathology (WMHP) confirmed clinically significant prostate cancer (csPCa), and 432 patients with no indication of lesions on multi-parametric MRI (mpMRI) were included in the study. A proposed 3D Siamese nnUNet with self-designed Zonal Loss was implemented, and results were evaluated using 5-fold cross-validation. The proposed model that is aware of PCa-related anatomical information performed the best on both lesion-level detection and patient-level classification experiments.
An AI-based Pipeline for Prostate Cancer PI-RADS Reporting on Multiparametric MRI using MiniSegCaps Network
Authors: Jiang Wenting , Lin Yingying , Vardhanabhuti Varut , Cao Peng
Published: August 2024

Prostate Imaging Reporting and Data System (PI-RADS) on multiparametric MRI (mpMRI) provides fundamental MRI interpretation guidelines but suffers from inter-reader variability. Deep learning networks show great promise in automatic lesion segmentation and classification, which help to ease the burden on radiologists and reduce inter-reader variability. In this study, we proposed a novel multi-branch network, MiniSegCaps, for prostate cancer segmentation and PI-RADS classification on mpMRI, and a graphical user interface (GUI) integrated into the clinical workflow for diagnosis reports generation. Our model achieved the best performance in prostate cancer segmentation and PIRADS classification compared with state-of-the-art methods.
Myocardial Infarction: An Investigation of Mesostructure using Diffusion Tensor Imaging and Voxel-Based Analysis
Authors: Wilson Alexander , Kang Xiaojian , Cork Tyler , Perotti Luigi , Ennis Daniel
Published: August 2024

Ex vivo DTI was performed in hearts suffering from myocardial infarction. Data was reconstructed using both tensor-based and voxel-based analysis. The fixel number (FN) consistently showed that there was a single fiber population (FN=1) in both infarcted and healthy myocardium. The complexity (CX) indicates the spread and magnitude of diffusion along different directions, but was not significantly different between infarct and healthy regions. The apparent fiber density (AFD) reveals the density of each fiber population within a voxel, and curiously increased in the infarct region, which may indicate the compaction of fiber populations running through the infarct.
Efficient fat suppression in free-running whole-heart CMR using OptiPulse
Authors: Sieber Xavier , Romanin Ludovica , Roy Chris , Bastiaansen Jessica , Yerly Jérôme , Richiardi Jonas , Stuber Matthias , van Heeswijk Ruud
Published: August 2024

The incomplete or time-inefficient suppression of fat signals is an unsolved issue in 3D cardiovascular MR imaging (CMR). We present a flexible framework named OptiPulse to design spectrally-selective radiofrequency (RF) pulses using numerical optimization of Bloch equation simulations. The RF pulse performance was assessed using a composite loss function for both fat suppression and power requirement. OptiPulse was used to design a B-splines-interpolated pulse for use in a free-running 3D whole-heart pulse sequence. Its fat suppression performance was ascertained both in vitro and in vivo, where it resulted in more homogeneous fat suppression when compared to other WE pulses (P<0.01).
3-Dimensional DANTE-prepared sequence with non-rigid motion-correction for high-resolution dark-blood aortic imaging
Authors: Fotaki Anastasia , Munoz Camila , Hua Alina , Kunze Karl , Neji Radhouene , Ismail Tevfik , Botnar Rene , Prieto Claudia
Published: August 2024

Dark-blood imaging is an important tool for vascular imaging in cardiovascular disease. A novel free-breathing water/fat DANTE-prepared sequence is introduced for 3D dark-blood imaging of the thoracic and abdominal aorta. The framework integrates image navigation to enable translational and non-rigid motion correction resulting in a predictable scan time along with dual-echo Dixon gradient-echo readout for robust fat suppression. Results from healthy subjects and patients demonstrate the feasibility of the sequence for high-resolution, aortic imaging in ~7-minute acquisition time.
Combination of irregular pulsation and aneurysm wall enhancement improved the diagnostic efficiency of symptomatic intracranial aneurysm
Authors: Li Xiao , Zhang Jianjian , Zhao Huilin , Zhu Chengcheng
Published: August 2024

Both aneurysm wall enhancement (AWE) and irregular pulsation have been suggested as potential candidates for intracranial aneurysms (IAs) instability. However, no studies have compared irregular pulsation and AWE for evaluation symptoms in unruptured IAs. By using vessel wall MRI and four-dimensional computed tomography angiography, we found combination of aneurysm wall enhancement and irregular pulsation improve the diagnostic efficiency of symptomatic intracranial aneurysm compared with irregular pulsation or AWE alone. Further longitudinal studies are needed to validate the role of the two imaging markers in predicting aneurysm growth and rupture.
Joint cardiac $$$T_1$$$ mapping and cardiac cine using a deep manifold framework
Authors: Zou Qing , Priya Sarv , Nagpal Prashant , Jacob Mathews
Published: August 2024

The main focus of this work is to introduce a deep generative model for simultaneous free-breathing cardiac $$$T_1$$$ mapping and CINE MRI. The data is acquired by a gradient echo inversion recovery sequence with intermittent delays for magnetization recovery. The joint reconstruction of the image time-series is performed using a patient-specific deep manifold reconstruction algorithm which learns a CNN generative model and its latent vectors from the measured k-t space data in an unsupervised fashion. Following learning, the model can be used to generate synthetic images at specific motion and contrast states.
Comparison of k-space center, FID and Pilot Tone navigators in abdominal motion tracking for optimal XD-GRASP reconstruction
Authors: Ariyurek Cemre , Wallace Tess , Kober Tobias , Kurugol Sila , Afacan Onur
Published: August 2024

Abdominal MRI scans often require breath-holding to prevent image quality degradation, which can be challenging for patients. XD-GRASP enables generation of motion-robust images for free-breathing abdominal MRI by binning the data into respiratory phases. In this study, we compared three navigation techniques, namely k-space center, free induction decay navigators (FIDnavs) and pilot tone (PT), for XD-GRASP reconstruction. FIDnavs and PT have advantages over k-space center navigation since they are insensitive to gradient delays, independent of the imaging plane and acquired more frequently. The image quality ranking means (1=best,2=moderate,3=worst) were 1.4, 1.6 and 2 for FIDnavs, PT and k-space center, respectively.
Stacked UNet-Assisted Joint Estimation for Robust 3D Motion Correction
Authors: Nghiem Brian , Wu Zhe , Kasper Lars , Uludağ Kâmil
Published: August 2024

We showed that accurate 3D retrospective motion correction of T1w MPRAGE data can be achieved with a UNet-assisted joint estimation algorithm. We compared the proposed method to using the UNet on its own and the standard joint estimation algorithm. Joint estimation (with and without the UNet) outperformed using the stand-alone UNet. The UNet-assisted joint estimation algorithm converged faster than its UNet-free counterpart. We demonstrated the importance of adapting to the changing levels of artifacts over the course of the joint estimation algorithm by sequentially employing different UNets trained for correcting different levels of motion corruption.
In vivo Whole-brain Downfield Metabolites Mapping using 2π-CASP-EPSI at 7T
Authors: Weng Guodong , Radojewski Piotr , Turco Federico , Slotboom Johannes
Published: August 2024

Many interesting metabolites, for instance adenosine triphosphate (ATP), glutathione (GSH) and homocarnosine (hCs), have resonances in the downfield range (>4.7 ppm) in 1H-MRS. Previous studies have studied the downfield spectra of metabolites in human brain using single-voxel spectroscopy (SVS) and, most recently, 2D one-slice MRSI. The study presents a 3D whole brain mapping sequence suited for downfield metabolites which does not require water suppression pulses.
A 3D Fast Multiphase DENSE MRE Sequence with Stack-of-Star Radial Sampling, Interleaved Multi-Slab Acquisition and Hadamard Encoding
Authors: Chen Yu , Wang Runke , Li Ruokun , Yan Fuhua , Feng Yuan
Published: August 2024

Conventional gradient echo (GRE) based Magnetic Resonance Elastography (MRE) suffers from long TE and scan time at low mechanical excitation (<25Hz). Displacement Encoding with a Stimulated Echo (DENSE) can record displacement with short TR, useful for low-frequency excitation. Here, 3D excitation was used to compensate for potential signal loss. A multiphase acquisition scheme with stack-of-star radial sampling was also used along with interleaved multi-slab acquisition and Hadamard encoding for MRE acceleration. Phantom experiments were conducted for validation. 32 slices brain MRE scan at 20Hz can be achieved in 11min30s, 5 folds faster than conventional GRE-based MRE.
Balanced Steady-State Free Precession and Radial Sampling for Arterial Spin Labeled Perfusion Imaging
Authors: Han Paul , Marin Thibault , Zhuo Yue , Ouyang Jinsong , El Fakhri Georges , Ma Chao
Published: August 2024

Arterial spin labeling (ASL) is a non-invasive MRI technique that allows to quantitatively measure cerebral blood flow. However, the major limitation of ASL is in the intrinsically low signal-to-noise ratio (SNR). Balanced steady-state free precession (bSSFP) sequence has been proposed to mitigate this limitation, however, bSSFP is sensitive to off-resonance effects. ASL perfusion imaging with bSSFP can be sensitive to effects from motion and flow when Cartesian sampling scheme is used. This work proposes and investigates radial sampling scheme for ASL with bSSFP to allow perfusion imaging with relatively high SNR and robustness to motion and off-resonance effects.
Analytical model for determination of exchange times in multi-TE velocity-selective Arterial Spin Labeling
Authors: Buck Mareike , Eickel Klaus , Günther Matthias
Published: August 2024

In this work, for the first time, an analytical model for determining the exchange times for obtaining vascular permeability information in velocity-selective Arterial Spin Labeling (VSASL) with multiple echo times (TE) is presented. Signal intensity comparisons were performed between different multi-TE VSASL techniques with each of the standard multi-TE pCASL and multi-TE PASL techniques for different sampling times. This demonstrates that, particularly for longer arterial transit times, the VSASL signal is twice as high compared with standard multi-TE measurements and thus shows promise in the field of non-invasive permeability measurements.
Deep Learning Reconstruction for Combined 8-fold Accelerated Parallel Imaging and Simultaneous Multislice Acquisition
Authors: Mostapha Mahmoud , Koerzdoerfer Gregor , Mailhe Boris , Raithel Esther , Brinkmann Inge , Janardhanan Nirmal , Ringholz Maria , Nadar Mariappan , Fritz Jan
Published: August 2024

Combining parallel imaging (PI) and simultaneous multislice (SMS) acceleration realized a clinical 4-fold accelerated 2D TSE MRI of the knee. However, 8-fold acceleration with conventional reconstruction methods suffers from significant image quality degradation. We propose a complete DL approach for combined slice separation and k-space-to-image reconstruction of SMS-PI-accelerated knee MRI with tunable denoising strength and super-resolution image enhancement. The proposed methods enable artifact-free image reconstruction of 8-fold accelerated 2D TSE MR images in multiple planes and with multiple image contrasts. Clinical evaluations suggest equivalence of image quality and detection rates of 8-fold S2P4 DL reconstructions compared to the reference standard.
Undersampling reconstruction of ferumoxytol-enhanced cardiac cine MRI using a spatiotemporal neural network
Authors: Gao Chang , Ming Zhengyang , Nguyen Kim-Lien , Zhong Xiaodong , Finn John
Published: August 2024

Ferumoxytol can support high quality SGE cardiac cine with blood-myocardial CNR similar to SSFP cine, but free of off-resonance artifact. Much work is ongoing to accelerate the acquisition of multi-slice, breath held cardiac cine. Deep learning-based reconstruction methods can accelerate the image acquisition and reconstruction but needs a large amount of data to train. When compared with compressed sensing and low rank reconstructions, our network showed sharper images and higher consistency with the reference and significantly better quantitative evaluation metrics. We showed that a network trained with non-contrast images could generalize to accelerated ferumoxytol-enhanced cardiac cine MRI with 10x acceleration.
An Open-Source Self-navigated Multi-Echo Gradient Echo Acquisition for R2* and QSM mapping using Pulseq and Model-Based Reconstruction
Authors: Wang Xiaoqing , Bilgic Berkin , Gallichan Daniel , Chan Kwok-Shing , Marques José
Published: August 2024

We propose an open-source multi-echo GRE sequence and reconstruction algorithms for rapid acquisition and harmonization of QSM. This is implemented using Pulseq, where different sampling patterns are used across echoes to provide complementary information and facilitate the proposed MOdel BAsed (MOBA) reconstruction. MOBA estimates M0, R2* and frequency maps using nonlinear optimization and is implemented in BART to facilitate dissemination. B0 correction is performed using 1D navigators acquired during the crusher gradients in each repetition. Motion navigators inserted in the sequence permit robust estimation of motion parameters with time frames of ~13seconds, and will lend themselves to retrospective motion correction.
Cerebrovascular reactivity (CVR) MRI as a biomarker for small vessel disease related cognitive decline: validation in the MarkVCID Consortium
Authors: Liu Peiying , Lin Zixuan , Hazel Kaisha , Pottanat George , Xu Cuimei , Jiang Dengrong , Lucke Emma , Bauer Christopher , Gold Brian , Greenberg Steven , Helmer Karl , Jann Kay , Jicha Gregory , Kramer Joel , Maillard Pauline , Mulavelil Rachel , Rodriguez Pavel , Satizabal Claudia , Seshadri Sudha , Singh Herpreet , Velarde Angel , Wang Danny , Kalyani Rita , Moghekar Abhay , Rosenberg Paul , Yasar Sevil , Albert Marilyn , Lu Hanzhang
Published: August 2024

Small vessel disease (SVD) related vascular contributions to cognitive impairment and dementia (VCID) represent a major factor in cognitive decline in older adults. However, there has not been a validated biomarker for the diagnosis and treatment monitoring of this condition. Recently, the US National Institute on Neurological Disorders and Stroke (NINDS), a branch of NIH, funded a MarkVCID consortium, the goal of which is to identify and validate clinical-trial-ready biomarkers for VCID. Cerebrovascular reactivity (CVR) MRI was one of the selected biomarkers that underwent multi-site testing. The present work reports the relationship between CVR and cognitive function, and examines whether the pre-specified hypothesis can be reproduced at each of the sites.
Alzheimer's disease neuropathology contributes to perivascular and parenchymal free water diffusion characteristics
Authors: Lynch Kirsten , Toga Arthur , Choupan Jeiran
Published: August 2024

Disruption of perivascular and interstitial fluid transport in the brain may contribute to the accumulation of toxic metabolic deposits observed in neurodegeneration. However, the relationship between AD neuropathology and free water fluid dynamics are not well understood. Using multi-compartment diffusion models, we assessed the relationship between PET tau and Aβ uptake and free water diffusion properties. We found tau deposition was associated with reduced free water anisotropy in brain regions that undergo neurodegeneration in pre-clinical AD. These findings provide a preliminary link between AD pathology and fluid transfer that may indicate waste clearance functional alterations.
Topological properties of individual gray matter morphological network effectively identify the preclinical stages of Alzheimer’s disease
Authors: Wang Zhihao , Ding Hongyuan , Tang Yin , Tang Yao , Qi Ming , Dou Weiqiang , Qian Long , Gao Yaxin , Wang Tong , Zhong Qian , Yang Xi , Tian Huifang , Zhang Ling , Zhu Yi
Published: August 2024

In this study, the topology of normalized individual morphological network (IMN) has been investigated for patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI) and healthy controls (HCs), respectively. Significantly different topology has been revealed among SCD and MCI patients and HCs, both at global and regional level. Moreover, the alterations of the regional topological metrics, including degree centrality and nodal efficiency, at the caudate nucleus exhibited significant correlations with all clinical scales and statistically predicted the cognitive performances. Therefore, the alterations of IMN can be regarded as an effective biomarker in early detection of SCD and MCI.
Synthesizing Complex Multicoil MRI Data from Magnitude-only Images
Authors: Deveshwar Nikhil , Rajagopal Abhejit , Shimron Efrat , Sahin Sule , Larson Peder
Published: August 2024

Obtaining paired, diverse and expert annotated medical data is extremely challenging especially for MRI reconstruction since raw data, including phase information is typically discarded from the scan leaving only the magnitude image for clinical assessment and diagnosis. Phase information contains valuable information about physiology, pathology and other tissue characteristics that are useful in developing more robust deep learning MRI reconstruction methods. In this work, we show that state of the art physics-based image reconstruction networks trained on synthetic raw MRI data consisting of synthetic phase and coil information perform comparably to image reconstruction networks trained on ground truth k-space data.
Combining T2-weighted and synthetic double inversion recovery magnetic resonance imaging improved rectal cancer T staging
Authors: Wang Zi , Dai Jiankun , Hu Shudong
Published: August 2024

This study aimed at investigating the role of synthetic double inversion recovery (SyDIR) magnetic resonance imaging (MRI) in staging rectal cancer (RC). 79 pathologically confirmed RC patients were retrospectively selected. Our results showed SyDIR can provided RC anatomical features for muscular infiltration detection. Compared with using T2WI alone, the combination of T2WI and SyDIR improved the diagnose performance of muscle layer invasion and significantly increase the staging consistency between MRI and pathology for both junior and senior radiologist. Our study indicated the combination of T2WI and SyDIR would be beneficial for RC treatment selection.
Endometriosis targeted MRI imaging using bevacizumab-modified nanoparticles aiming at vascular endothelial growth factor
Authors: Zhang Qi , Fu Caixia , Li Qing , Li Yajie
Published: August 2024

In vivo, NPBCNs generated strong signal enhancement in endometriosis lesion in rat on T1-weighted images via MRI.
Radiomics of Multiparametric MRI in Tumor Grading of Endometrial Cancer
Authors: Wang Yiang , He Mengge , Cao Peng , Lin Chien-Yuan , Liu Weiyin , Lee Chia-Wei , Lee Elaine
Published: August 2024

Random forest models were constructed to predict tumor grade (grade 1-2 vs. grade 3) of endometrial cancer based on radiomics features extracted from quantitative T1, T2, proton density maps generated by synthetic MRI and apparent diffusion coefficient maps generated by diffusion-weighted imaging. The classification model based on features extracted from all the quantitative maps achieved the highest area under the curve of 0.804 compared to models constructed based on single quantitative map.
Simultaneous Measurements of GABA, Glx and GSH in the Thalamus in Patients with Mild Traumatic Brain Injury: A Preliminary Study
Authors: Liang Xiao , Saleh Muhammad , Tchoquessi Rosy , Colinco Alexa , Roys Steve , Raghavan Prashant , Gullapalli Rao , Zhuo Jiachen
Published: August 2024

In this study, we report the preliminary results of simultaneous measurements of GABA, Glx (glutamate + glutamine), and GSH in the thalamus using HERMES in the mTBI patients. HERMES was acquired in the thalamus for patients in acute, subacute, and chronic stages, and control subjects as reference using optimized acquisition and processing. Metabolite fitting were performed in Gannet with spectral alignment. The results demonstrate that HERMES can maintain the spectral and fitting quality in the mTBI patients versus the control subjects. Differences in the metabolite levels warrant accruing a larger number of patients for a more definite evaluation.
MRE-based assessment of impairment of mechanical isolation at the skull-brain interface resulting from sports-related head impact exposure
Authors: Shan Xiang , Murphy Matthew , Sui Yi , Zheng Keni , Manduca Armando , Ehman Richard , Huston John , Yin Ziying
Published: August 2024

Increasing recognition of the effect of repeated head impacts (RHI) in leading to neurologic impairment and higher risk of subsequent traumatic head injury, has motivated for developing technology to assess the status of the mechanism of mechanical isolation provided by the structures within the skull-brain interface, known as the pia-arachnoid complex (PAC). To evaluate the RHI-induced PAC alternations, we compared MR elastography-based measures (rotational transmission ratio [Rtr] and cortical normalized octahedral shear strain [NOSS]) between healthy and sports-related RHI subjects. Significantly higher Rtr and cortical NOSS were found among RHI individuals, showing their potential in assessing the effect of RHI.
Comparing self-reporting concussion assessments with an objective Diffusion Tensor Imaging (DTI) and resting state MRI (rsMRI) based measure
Authors: Simard Nicholas , Noseworthy Michael , Kumbhare Dinesh , Ulmer Stephan , Danielli Ethan
Published: August 2024

Traditional concussion self-reporting has significant limitations due to its subjectivity and inconsistency, therefore a more objective MRI-based approach is proposed in this research. A concussion population was assessed using the traditional PCSS method versus DTI anisotropy analysis and rsMRI complexity analysis. Concussed patients were compared to large age and sex matched datasets and a Z-transform was used on white and gray matter ROIs to identify injured areas in the cerebrum. A weighted mean equation was then used to compare Z-scores to the 7-point PCSS. Results confirmed sex differences in self reporting and shows promise as a future objective assessment tool.
Longitudinal QSM imaging reveals disrupted subcortical white matter maturation in football vs volleyball college athletes
Authors: Georgiadis Marios , Karimpoor Mahta , Spincemaille Pascal , Dimov Alexey , Mills Brian , Goubran Maged , Taghavi Hossein Moein , Mouchawar Nicole , Sami Sohrab , Wintermark Max , Grant Gerald , Camarillo David , Wang Yi , Zeineh Michael
Published: August 2024

Head impacts in sports may cause long-term brain changes. Here, we assessed quantitative susceptibility mapping (QSM) changes over multiple seasons in high-contact American football vs low-contact volleyball college athletes using the multi-echo complex total field inversion (mcTFI) method. We found widespread changes over time (likely developmental) in all athletes, while time-independent sports differences were detected by R2*. mcTFI revealed an altered QSM trajectory in the white matter (total and subcortical) between sports: QSM increased in volleyball athletes but changed minimally in football, likely indicating disrupted subcortical white matter maturation in football. QSM can sensitively detect longitudinal changes in contact sports.
Brain white matter alterations in military service members after a remote mild traumatic brain injury
Authors: Yeh Ping-Hong , Song Chihwa , Srikanchana Rujirutana , Koay Cheng Guan , Liu Wei , Bonavia Grant , Ollinger John
Published: August 2024

In this study, we applied non-Gaussian diffusion MRI, including bi-tensor diffusion tensor imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging and fixel-based analysis, to assess white matter disruption after a remote brain injury. The findings of both increased and decreased orientation distribution index over the forceps major and forceps minor of the corpus callous, along with increased fiber density and fiber cross-sectional area of fiber bundle over the anterior frontal region suggests a mixed pattern of white matter alterations, e.g. loosely white matter such as gliosis along with neuroplasticity and brain repair after a remote mild traumatic brain injury.
Structural covariance in subcortical regions in MS and NMOSD: An MRI-based study with automated brain volumetry
Authors: Xie Yan , Zhang Yan , Liu Chengxia , Zhu Wenzhen
Published: August 2024

MS and NMOSD, as two major demyelinating diseases of the CNS, both could cause brain structural volume changes. Moreover, the synergistic volume changes between brain regions can reflect the intrinsic connection network between these regions, which is helpful to further explore the underlying pathophysiological changes of the disease. Our study identified volumetric changes and structural covariance in subcortical regions in MS and NMOSD patients. Furthermore, MS and NMOSD patients had distinct patterns of anatomical connection in brain regions, which reflected the different underlying damage to brain structures in the two diseases.
Separation of Macromolecules and Metabolites in Ultrashort-TE MRSI Data with Learned Probabilistic Subspaces
Authors: Zhao Yibo , Li Yudu , Jin Wen , Guo Rong , Li Wenli , Li Yao , Luo Jie , Liang Zhi-Pei
Published: August 2024

Separation of macromolecules and metabolites in ultrashort-TE MRSI data has been very difficult due to limited SNR and strong spectral overlap. In this work, we proposed a new solution to the problem using a subspace-based approach aided with long-TE navigator signals. Physics-based prior information was incorporated through pre-learned spectral bases and probability distributions of spatial coefficients. The proposed method has been validated using experimental data from healthy and brain tumor subjects, producing impressive results.
Evaluation of Deep Learning Models for Processing Lactate-Edited MR Spectroscopic Imaging in Patients with Glioma
Authors: Vaziri Sana , Autry Adam , Lafontaine Marisa , Lupo Janine , Chang Susan , Li Yan
Published: August 2024

The use of deep learning models for frequency and phase correction of spectral data was evaluated to reduce processing time of 3D MRSI datasets acquired from patients with glioma. Models for frequency and phase offset estimation were trained for data prior to coil-combination. Separate models for baseline removal of coil-combined data were similarly trained and evaluated. The voxel-wise peaks for spectra processed using the standard approach were evaluated and compared to the spectra processed using the proposed deep learning approach. Compared to standard processing, deep learning processing produced spectra with comparable SNR and linewidths in a shorter processing time.
Targeted Gastric Electrical Stimulation Modulates Functional Connectivity of the Interoceptive Network in the Rat Brain
Authors: Alkaabi Fatimah , Cao Jiayue , Yee Angela , Wang Xiaokai , Scheven Ulrich , Tsai Chih Hsuan , Saavedra Ana , Liu Zhongming
Published: August 2024

Gastric Electrical Stimulation (GES) is an FDA approved therapy for gastroparesis with unspecified working mechanisms. One plausible mechanism is that it activates the vagal afferents to engage the brain’s interoceptive network in regulating the stomach. Orientation and location-specific stimulation that targets the vagal-gastric receptors can effectively activate the brainstem. We asked whether and how this type of GES can engage interoceptive regions and modulate their interactions, especially the anterior cingulate (ACC) and insular cortices (IC), the primary visceromotor and viscerosensory processing regions, respectively. Therefore, we evaluated the functional connectivity in the rat brain before, during, and after targeted GES.
Reproducibility of conventional and GABA-edited multi slice MRSI in the human brain at 3T
Authors: Senapati Dillip K. , Zöllner Helge J. , Özdemir Ipek , Oeltzschner Georg , Lin Doris , Barker Peter B.
Published: August 2024

Reproducibility of both conventional and GABA-edited multi-slice MRSI of the human brain recorded at 3T was investigated in 11 healthy adult volunteers. GABA-edited data were post-processed using a retrospective motion compensation (MoCo) scheme. Test-retest coefficients of variation(CV) were calculated. Overall reproducibility was good for conventional MRSI for selected brain regions, but edited-MRSI data showed significant variations. Edited-MRSI scans may benefit from both improved post-doc correction schemes to minimize subtraction artifacts, as well as better B0 field homogeneity over the brain, and possibly also prospective MoCo schemes.
Prospective motion-corrected spectroscopy in the human cervical spinal cord
Authors: Adanyeguh Isaac , Henry Pierre-Gilles , Deelchand Dinesh
Published: August 2024

Proton magnetic resonance spectroscopy in the spinal cord is particularly challenging and motion remains one of biggest obstacles. Although several prospective motion correction techniques currently exist in the human brain, none have yet been reported in the spinal cord. Here we report prospective motion correction in the spinal cord using reduced-field-of-view 2DRF excitation. Results show than spectral quality were similar with and without motion. This study demonstrates the feasibility of prospective motion correction for spinal cord MRS.
Use of fast B1 shimming to enable localized MR spectroscopy in different regions of the human brain on a clinical platform at 7 Tesla
Authors: Ipek Özlem , Clement Jeremie , Arridge Marzena , Bridgen Philippa , Wilkinson Tom , Mancini Laura , Tomi-Tricot Raphael , de Vita Enrico , Mekle Ralf
Published: August 2024

We demonstrated that applying a fast implementation of an RF phase shimming method enabled the acquisition of localized MR spectra in different regions of the human brain including B1 challenging areas, such as the hippocampus and prefrontal cortex, using a commercially available pTx coil on a clinical platform at 7T. RF efficiency was increased by ~100% cerebellum and PFC while ~50-75% for pons and hippocampus. The most favorable flip angle distributions were obtained for the cerebellum and the prefrontal cortex. Fast B1 shimming with advanced MRS methodology enables high-quality single voxel spectra at 7T using a commercially available setup.
Single-shot SLOW-editing for Downfield α-Glucose MRSI at 7T Utilizing SNR-Enhancing Glucose Mutarotation Effect
Authors: Weng Guodong , Radojewski Piotr , Slotboom Johannes
Published: August 2024

Changes in brain glucose occur in many neurological disorders as well as during aging. Most studies on the uptake of glucose in the brain use positron emission tomography, which requires injection of a radioactive tracer. Our study shows that ultra-high-field 1H-MRS single-shot SLOW-editing can be used to measure α-D-glucose at 5.22 ppm in vivo, and thus that α-D-glucose might have the potential to be used as a an economic radiation free tracer in the human brain.
Toward the Use of MRS Methodological Consensus by the Clinical Research Community - An Early Assessment of Dissemination Results
Authors: Weinstein Jodi , Dalton Abigail , Kaufman Jack , Choi In-Young , Kreis Roland , Juchem Christoph
Published: August 2024

The MRS community recently established a set of expert Consensus Recommendations. To date, however, knowledge on their implementation beyond anecdotal reports is largely lacking. Here we report a preliminary assessment of the achieved dissemination and, more importantly, the level of acceptance of the established guidelines and standards by the clinical MRS research community. We compiled feedback from 22 editors-in-chief of major clinical journals, together accounting for more than 100 (>12%) of the in vivo clinical MRS publications from 2021.
Prospective frequency correction with metabolite cycling for improved spectral quality in the prefrontal cortex at 7T
Authors: Chan Kimberly , Dimitrov Ivan , Trivedi Madhukar , Henning Anke
Published: August 2024

The prefrontal cortex plays a central role in controlling executive functions such as decision-making and emotional-monitoring and has thus been the subject of several 1H-MRS studies on psychiatric illnesses. This region, however, is sensitive to motion-induced increases in linewidths due to the voxel moving away from the originally shimmed location. Here, we combined metabolite cycling (MC) with continuous prospective frequency correction to better account for frequency instabilities when performing single-voxel brain MRS at 7T. We find that MC sLASER with continuous prospective frequency correction reduces frequency instability, water linewidths, and N-acetylaspartate linewidths relative to semi-LASER acquisitions without prospective frequency correction.
Synthetic phase-sensitive inversion-recovery imaging for assessing extramural venous invasion in patients with rectal cancer
Authors: yuxi Ge , Jiankun Dai , Shudong Hu , Yanlong Jia
Published: August 2024

This study aimed to investigate the feasibility of synthetic phase-sensitive inversion recovery (SyPSIR) vessel for extramural venous invasion (EMVI) detection in patients with rectal cancer. One hundred and six histologically confirmed rectal cancer patients (35 EMVI+ and 71 EMVI−) were evaluated. Compared with using T2WI alone, the area under the receiver operating characteristic curve using the combination of T2WI and SyPSIR was increased from 0.86 to 0.96 and from 0.65 to 0.88 for the senior and junior radiologist, respectively. Therefore, SyPSIR can provide additional information to improve EMVI diagnostic efficiency of in rectal cancer.
Preoperatively Grading Rectal Cancer with the Continue Time Random Walk DWI model.
Authors: Geng Zhijun , Li Shaolei , Zhang Yunfei , Dai Yongming , Xie Chuanmiao
Published: August 2024

This study evaluates a new pre-operatively method to grade rectal cancer based on Continue Time Random Walk (CTRW) model. The method is to calculate three parameters of the CTRW model by fitting the model with DWI signal and a series of b-values and to differentiate low- and high-grade tumors by fitting a logistic regression with different combinations of parameters. An additional k-mean clustering analysis is performed to evaluate how differentiable the low and high-grade groups are in the CTRW parameters’ phase space. Our study shows that CTRW model has the potential to accurately grade rectal cancer.
Comparison of 31P MRS in human pancreas and liver at 7 Tesla
Authors: Seelen Leonard , van den Wildenberg Lieke , Gursan Ayhan , Gosselink W.J. Mark , van der Kemp Wybe , Hoesein Firdaus Mohamed , Mohammad Nadia Haj , Molenaar I. Quintus , van Santvoort Hjalmar , Klomp Dennis , Prompers Jeanine
Published: August 2024

31P MRS could be valuable for the assessment of treatment response in pancreatic cancer. Using a 31P whole-body transmit coil in combination with a 16-channel receive array at 7T, we could obtain 31P MRSI data covering both the whole liver and the deeply lying pancreas. The aim of this study was to compare 31P metabolite levels in the pancreas and liver in healthy volunteers. The PME/PDE ratio, which has been used as a tumor marker, was 2.1-fold higher in the pancreas compared to the liver. This will be important to take into account when applying 31P MRS in pancreatic tumors.
Magnetic resonance elastography-derived stiffness: potential biomarker for differentiation of benign and malignant pancreatic masses
Authors: Liu Dingxia , Chen Jiejun , Zhang Yunfei , Dai Yongming , Yao Xiuzhong
Published: August 2024

Magnetic resonance elastography (MRE) is a noninvasive technique capable of quantifying tissue mechanical properties (stiffness) in vivo. Given its specialty, it is supposed to be potential for identifying malignant tumors that are characterized by a marked desmoplastic reaction and build-up of fibrotic tissues in cancer cells and tumor microenvironment. However, the field has been largely restricted to studies in pancreatic MRE. This study sought to determine the diagnostic performance of MRE for pancreatic solid masses, compared with diffusion-weighted imaging (DWI) and serum CA19-9, to establish a threshold for differentiating between pancreatic ductal adenocarcinoma (PDAC) and benign tumors in pancreas.
Two-Stage Deep Learning with Multi-Pathway Network for Brain Tumor Segmentation and Malignancy Identification From MR Images
Authors: Choi Yoonseok , Al-masni Mohammed , Park Hyeok , Kim Jun-ho , Kim Dong-Hyun , Yoo Roh-Eul
Published: August 2024

Accurately segmenting contrast-enhancing brain tumors plays an important role in surgical planning of high-grade gliomas. Also, precisely stratifying malignancy risk within non-enhancing T2 hyperintense area helps control the radiation dose according to the malignancy risk and prevent normal brain tissue from being unnecessarily exposed to radiation. In this work, we 1) segment brain tumors using deep learning, and 2) provide more detailed segmentation results that can show the malignancy risk within the T2 high region. We utilize a two-stage framework where we make images with restricted ROI through foreground cropping so that the model can focus on only tumor part.
Multi-Task Radiomics Approach for Prediction of IDH Mutation Status and Early Recurrence of Gliomas from Preoperative MRI
Authors: Yang Hongxi , Gao Ankang , Wang Yida , Zhang Yong , Cheng Jingliang , Song Yang , Yang Guang
Published: August 2024

We retrospectively enrolled 243 patients to develop a multi-task radiomics approach to predict IDH mutation status and early recurrence simultaneously in patients with WHO II-IV gliomas from preoperative multi-parametric MRI (mp-MRI). Firstly, multi-task LASSO was performed to find features shared between the two tasks, which were then combined with task-specific features selected recursively to build radiomics models. The models achieved test AUCs of 0.826 and 0.770 for IDH mutation status identification and early recurrence prediction, respectively. Shared features enabled the models to achieve satisfactory performance with minimum number of features, avoiding overfitting and making the models more interpretable.
Differentiation of recurrent tumor from post-treatment changes in Glioblastoma patients using Deep Learning and Restriction Spectrum Imaging
Authors: Gagnon Louis , Gupta Diviya , White Nathan , Goodwill Vaness , McDonald Carrie , Beaumont Thomas , Seibert Tyler , Hattangadi-Gluth Jona , Kesari Santosh , Schulte Jessica , Piccioni David , Dale Anders , Farid Nikdokht , Rudie Jeffrey
Published: August 2024

Differentiating recurrent tumor from post-treatment changes is challenging in glioblastoma. Using restriction spectrum imaging (RSI) and deep learning, we were able to accurately identify and segment residual and recurrent enhancing and non-enhancing cellular tumor in post-treatment brain MRIs. Including RSI in the deep learning model improved tumor segmentation due to the ability of RSI to separate cellular tumor from peritumoral edema and treatment related enhancement. The volume of cellular tumor was also predictive of survival. Our results suggest that combining deep learning and RSI may identify recurrent tumor in glioblastoma patients, which could improve targeted treatments and guide clinical decision-making.
VISIBLE: Improvement in Vessel Visibility and Application of Machine Learning to Detect Brain Metastases
Authors: Kikuchi Kazufumi , Togao Osamu , Yamashita Koji , Obara Makoto , Ishigami Kousei
Published: August 2024

This study aimed to improve vessel visibility by modifying k-space filling and to verify the usefulness of volume isotropic simultaneous interleaved bright- and black-blood examination (VISIBLE) in detecting brain metastases using machine learning (ML). We tested three types of VISIBLE in different k-space fillings, and counted the number of vessels. We also tested the ML model by using VISIBLE. The number of vessels was lower in Centric and Reversed centric sequences than that in MPRAGE, but comparable in the Startup echo 30 sequence. Our ML model was achieved high sensitivity (97%) and there were no differences among three sequences.
Semi-Randomized Trajectories to the Rescue: Reducing Artifacts from Fluctuating Physiological Signals in 3D Steady-State MRI
Authors: Seginer Amir , Schmidt Rita
Published: August 2024

Rapid 3D steady-state sequences such as SWI are sensitive to semi-periodic physiological fluctuations (e.g., cardiac pulsation, breathing, and eye movement) resulting in repeating artifacts in the images. Randomization of the phase-encoding order reduces the above artifacts but results in apparent noise from slow global changes (like motion or eddy currents changes). We propose a new semi-randomized acquisition order that allows to set a cutoff frequency for artifact suppression; above which artifacts are suppressed, whereas artifacts from slower changes are unaffected. Simulations and SWI human brain scanning at 7T validate the method.
Rapid Mesoscale MP2RAGE Imaging at Ultra High Field with Controlled Aliasing
Authors: Varela-Mattatall Gabriel , Lo Wei-Ching , Oran Omer , Polimeni Jonathan , Mareyam Azma , Gagoski Borjan , Menon Ravi , Bilgic Berkin
Published: August 2024

MP2RAGE is considered the workhorse sequence at ultra-high field (UHF) as it provides high-contrast and bias-free structural imaging for both anatomical and segmentation purposes. However, high-resolution MP2RAGE imaging is hampered by lengthy acquisitions, which can be partially mitigated using parallel imaging, but this comes at the cost of g-factor and √R penalties on SNR; thus, limiting the usefulness of this sequence at the submillimeter scale. In this work, we show preliminary results on how wave encoding, and blipped-controlled aliasing could allow efficient MP2RAGE acquisitions at up to 560 um isotropic resolution at 7T.
Multiband T-Hex spirals for rapid and SNR-efficient diffusion-weighted MRI
Authors: Engel Maria , Müller Lars , Döring André , Jones Derek
Published: August 2024

Diffusion weighted imaging (DWI) for advanced modelling of tissue microstructure is notoriously short in SNR and requires long scan times. In this work we boost the SNR of DWI by combining highly efficient T-Hex sampling with multiband imaging and spiral readout schemes. This allows for an unprecedented SNR efficiency and holds promise for advanced microstructural scans especially in clinical populations.
4D aortic motion maps from isotropic high-resolution 3D CINE balanced steady state free precession at 3T and automated segmentations
Authors: Merton Renske , Bosshardt Daan , Strijkers Gustav , Nederveen Aart , Schrauben Eric , van Ooij Pim
Published: August 2024

In this study we introduce 4D aortic displacement and diameter change estimations from isotropic high-resolution 3D CINE CMR as novel biomarkers for aortic stiffness. These could potentially be used as an alternative to pulse wave velocity stiffness measurements which can be unreliable for very stiff aortas as found in for example Marfan syndrome patients. Using deep learning for segmentation, visualization and quantification of aortic motion is demonstrated through 4D aortic motion maps. Time curves of displacement showed the typical cyclic behavior of cardiac motion, with a maximum displacement median of 10.3 (3.6) mm over 14 healthy volunteers.
Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MRA by deep learning constrained compressed sensing
Authors: Wu Xi , Sun Jiayu , Zhang Xiaoyong
Published: August 2024

The balanced steady-state free precession (bSSFP) sequence is widely used for navigated whole-heart coronary magnetic resonance angiography (MRA) for the evaluation of coronary anatomy and abnormalities due to its inherently high blood signal intensity and blood-myocardial contrast. However, the main drawback of this approach is that the scan time is longer and prone to interference with motion artifacts. In this study, we investigated the utility of whole-heart coronary MRA using accelerated bSSFP with compressed sensing artificial intelligence (CSAI) technique at 3 Tesla. The results demonstrated the adopted CS-AI technique yielded high image quality within a clinically feasible acquisition time in healthy subjects and patients with suspected CAD.