bluuebunny/crossref_metadata_2025 huggingface dataset:
Concurrent 1D line-scan fMRI at multiple cortical locations with a novel non-contiguous, non-coplanar multiline acquisition in humans at 7 Tesla
Authors: Choi Sangcheon , Balasubramanian Mukund , Yu Xin , Polimeni Jonathan R.
Published: November 2024

Motivation: Spin-echo-based line-scanning employing inner-volume excitation has been proposed for line-scan fMRI to avoid artifacts stemming from imperfect saturation RF pulses. Goal(s): To measure non-contiguous and non-coplanar BOLD signals at multiple cerebral cortical areas. Approach: We developed multi-line T2’- and T2-weighted Gradient-echo sampling of a spin-echo (GESSE) line-scanning fMRI method. Results: This novel approach enables the detection of fMRI activation at different visual cortical regions, showing pure T2 and TE-dependent BOLD responses. It provides a proof-of-concept to further examine interactions of high-resolution fMRI signals at multiple cortical locations along feedforward and feedback pathways. Impact: A non-coplanar multi-line gradient-echo sampling of spin-echo (GESSE) line-scanning method was proposed as a novel approach for distinguishing macro- and micro-vascular sensitive fMRI signals by simultaneouslyacquiring T2’- and T2-weighted BOLD fMRI signals at multiple cortical locations.
High Temporospatial-Resolution fMRI in a Focused Brain Volume with (k, t)-Space Undersampling and Temporal Priors
Authors: Luo Qingfei , Dan Guangyu , Zhou Xiaohong
Published: November 2024

Motivation: Three-dimension reduced field-of-view imaging with (k, t)-space undersampling (k-t 3D-rFOVI) can be used for high temporospatial-resolution fMRI acquisition in a focused brain volume. Goal(s): This study aims at developing an image reconstruction method for k-t 3D-rFOVI to improve the fMRI data quality. Approach: Timing information about stimulation tasks was integrated into image reconstruction of k-t 3D-rFOVI. Simulation and human fMRI experiments with a 6-fold acceleration factor were conducted to demonstrate the performance of the reconstruction method. Results: The proposed reconstruction method substantially increased the sensitivity of k-t 3D-rFOVI in detecting fMRI activations and the accuracy in recovering the time course of fMRI signals. Impact: By incorporating stimulus timing information into image reconstruction, high-quality fMRI data can be obtained using k-t 3D-rFOVI with high temporal (480 ms) and spatial (1.5 mm) resolutions over a reduced field-of-view.
Limitations of line-scan MRI for directly measuring neural activity
Authors: Wilson Joshua , Wu Hua , Kerr Adam , Wandell Brian , Gardner Justin
Published: November 2024

Motivation: There are reports that line-scan MRI methods can directly measure neural activity (the DIANA response). Goal(s): In light of replication failures, we sought to understand the noise profile of the line-scan acquisition. Approach: Using the line-scan protocol (3T GE UHP scanner, N=5) we measured human visual cortex while subjects viewed a blank screen. Results: The noise has a 1/f temporal spectrum that can be confused with certain stimulus-driven responses. This noise spreads into the surrounding volume in the phase-encoding direction. We explain the pattern of results with a model of the sequence that incorporates time-varying contrast fluctuations. Impact: Line-scan MRI is particularly susceptible to physiological noise because of its long acquisition time to create a single image. For this reason, the sequence will have difficulty measuring small contrast fluctuations due to neural electrical activity.
Comparison of BOLD and ASL-derived Measures of Cerebrovascular Reactivity Acquired During Breath-Hold
Authors: Biondetti Emma , Chiarelli Antonio , Caporale Alessandra , Di Censo Davide , Driver Ian , Germuska Michael , Wise Richard
Published: November 2024

Motivation: Breath-hold BOLD fMRI may be regarded as a proxy of deoxygenated cerebral blood volume (CBVdHb), instead of cerebrovascular reactivity (CVR) when blood flow changes are uniform in response to breath-hold. Goal(s): We aimed to test this assumption in healthy volunteers. Approach: We measured the spatial uniformity of CVR derived from arterial spin labelling and BOLD fMRI data acquired simultaneously during a breath-holding task. Results: Breath-hold induced a more uniform fractional increase in CBF than in BOLD signal. Thus, the spatial variability in apparent BOLD-CVR is likely due to variation in CBVdHb with little variability arising from spatial differences in vascular reactivity. Impact: Under isometabolic conditions in healthy volunteers, owing to the uniform change in blood flow induced by breath-hold, it is possible to infer maps of deoxygenated cerebral blood volume based on BOLD fMRI breath-hold data.
Changed gray matter volume and functional connectivity in cerebellar subregions in T2DM patients with insulin resistance
Authors: Zhang Huiyan , Shen Guo , Yang Chen , Tan Jian , Zhao Lianping
Published: November 2024

Motivation: The neuropathophysiological mechanisms of cerebellar damage in type 2 diabetes mellitus patients with insulin resistance (T2DM-IR) are not yet fully understood. Goal(s): To investigate how insulin resistance affects the cerebellar structure and function. Approach: We employed voxel-based morphometry analysis based on SUIT template and seed-based functional connectivity (FC) to assess the gray matter volume (GMV) and functional connectivity in cerebellar subregions of T2DM patients with insulin resistance and examine their correlation with clinical variables. Results: We exhibited more pronounced reductions in GMV and FC of specific cerebellar subregions in T2DM-IR and negative correlation between GMV of lobules VIIb-VIII and insulin resistance. Impact: These findings contribute to our understanding of the pathophysiological role of cerebellum damage in T2DM-IR. It provides a new research idea and method for us to elucidate brain impairment of T2DM.
Comparing functional connectivity of small nucleus in brainstem with multi- and single-echo fMRI: A resting state study
Authors: Wang Xinhui , Yu Qiurong , He Naying , Ai Kai , Zhang Youmin , Liu Peng , Li Yan , Wu Peng , Yan Fuhua
Published: November 2024

Motivation: Efforts to characterize the function of DR, MR and LC in humans using functional magnetic resonance imaging (fMRI) have been hampered by their small size and location near a large source of noise. Goal(s): The aim of this study is to compare the functional connectivity (FC) of small nucleus in brainstem with multi- (ME) and single-echo (SE) resting state fMRI. Approach: The whole-brain FC of LC, DR and MR were generated by using ME-fMRI and SE-fMRI. Results: Precuneus was correlated with LC in both methods. Meanwhile, both methods shown cerebellum was correlated with DR, the cingulum was correlated with MR. Impact: It suggests that ME-fMRI may also provide significant advantages over single echo fMRI approaches when investigating the FC of small nucleus of brainstem. ME-fMRI offers substantial advantages over single echo fMRI.
QSM-Guided Functional Connectivity of Subcortical Nuclei: A Robust Approach for Parkinson's Disease Diagnosis
Authors: Qin Jianmei , Guan Xiaojun , He Chenyu , Wu Chenqing , Zhou Cheng , Wu Haoting , Guo Tao , Liu Chunlei , Zhang Yong , Xu Xiaojun , Zhang Minming
Published: November 2024

Motivation: Conventional rs-fMRI analysis of basal ganglia in Parkinson's disease(PD) relies on T1WI atlases, posing challenges to localizing subcortical nuclei in fMRI. Goal(s): This study aims to validate a novel method incorporating Quantitative Susceptibility Mapping(QSM) into fMRI analysis for precise subcortical nuclei segmentation. Approach: fMRI registration to QSM and T1WI respectively in the study. Intraclass Correlation Coefficient and Mutual Information to assess the consistency and accuracy of the two registration approaches. Various Machine learning models utilized functional connectivity derived from two methods for PD classification. Results: Two methods showed measurement inconsistency. The QSM-guided approach displayed superior accuracy and significantly outperformed in classification models. Impact: Our study introduces a groundbreaking approach by incorporating QSM into the fMRI analysis of subcortical nuclei in Parkinson’s disease. Shedding light on the potential of the QSM-guided method in capturing meaningful alterations in Parkinson's disease-related neural networks.
Static and dynamic functional connectivity of the amygdala and serotoninergic activity following bright light in subthreshold depression
Authors: Chen Pan , Wang Ying , Cui Wei
Published: November 2024

Motivation: The presence of subthreshold depression significantly increases the likelihood of developing major depressive disorder and is linked to a higher burden of illness and suicide risk. Goal(s): The objective of this clinical trial was to evaluate the relationship between BLT and the functional connectivity (FC) alterations of the amygdala, as well as the serotoninergic distribution in subthreshold depression. Approach: Subthreshold depression subjects were randomly divided into two groups: the BLT group and the placebo group. Results: BLT group showed increased sFC of right basolateral amygdala (BLA)/superficial amygdala (SFA)-right middle temporal gyrus and dFC of right centralmedial amygdala and right inferior orbital frontal gyrus. Impact: These findings indicated that BLT could relieve depressive symptoms and alter FC of the amygdala in subthreshold depression (StD). Combining baseline sFC and dFC of the amygdala may have the potential to assess the effectiveness of BLT in treating StD.
Dual-FOV MB-SWIFT for simultaneous functional imaging of the brain and spinal cord
Authors: WU Lin , Ponticorvo Sara , Laakso Hanne , Paasonen Ekaterina , Paasonen Jaakko , Kettunen Mikko , Lagore Russell , DeLabarre Lance , Adriany Gregor , Koski Dee , Garwood Michael , Idiyatullin Djaudat , Gröhn Olli , Mangia Silvia , Michaeli Shalom
Published: November 2024

Motivation: Functional neuroimaging target either the brain or the spinal cord, but usually not both because simultaneous acquisitions from distant fields of view are challenging with conventional MRI. Goal(s): To establish a novel MRI approach for artefact-free, quiet fMRI simultaneously from brain and spinal cord, avoiding the need of dynamic shimming. Approach: Our approach is to use MB-SWIFT in a simultaneous dual-FOV configuration with a Dual Amplifier Blanking Selector Unit (DABSU) that employs two transmitters and two receiver channels. Results: The results established feasibility of the novel approach for task-based fMRI and connectivity analyses between lumbar spinal cord and brain in rat. Impact: The method could be used for unprecedented investigations of the central nervous system, and could be extended to any two separate parts of the body.
Modelling the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla
Authors: Zhong Xiaole , Polimeni Jonathan R. , Chen J. Jean
Published: November 2024

Motivation: There has been evidence that macrovasculature may bias the analysis of resting-state functional connectivity (FC) and that such a bias may be difficult to remove. Goal(s): This study intends to demonstrate such an effect can be predicted with a biophysical model. Approach: We used a biophysical model with experimentally acquired vascular maps to simulate macrovascular effects on functional connectivity estimates from BOLD fMRI. Results: Our results show that it is feasible to model the macrovascular BOLD contribution to FC through simulation. While both arteries and veins contribute, our model is more accurately captures effects of veins. Impact: This study aims to demonstrate the feasibility of simulating the BOLD signal in a voxel containing macrovasculature using a biophysical model, which will enable correction of the macrovascular bias in resting-state and other types of fMRI.
Correlation of cerebrovascular reactivity (CVR) with baseline CBF, OEF, and CMRO2
Authors: Zhang Ke , Triphan Simon , Wielpütz Mark , Ziener Christian , Ladd Mark , Schlemmer Heinz-Peter , Kauczor Hans-Ulrich , Sedlaczek Oliver , Kurz Felix
Published: November 2024

Motivation: Positive correlations between baseline cerebral blood flow (CBF) and BOLD-cerebrovascular reactivity (CVR), both between- and within-subjects were reported. However, there are no studies showing the correlation between CVR and other physiological parameters such as oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2). Goal(s): In this study, these baseline parameters were measured using MRI, and the correlations between CVR and baseline CBF, OEF and CMRO2 were investigated. Approach: Arterial spin labeling and quantitative BOLD were performed to quantify CBF and OEF. Results: Positive correlations between CBF and CVR, CMRO2 and CVR were found. Negative correlation between OEF and CVR was found. Impact: This study presents the correlation of CVR in healthy brain with baseline CBF, OEF, and CMRO2. Positive correlations between CBF and CVR, CMRO2 and CVR were found. Negative correlation between OEF and CVR was also found.
Increasing the realism of in silico cortex substrates for diffusion MRI simulation
Authors: Bachiri Anas , Brullé Alexis , USZYNSKI Ivy , Poupon Cyril
Published: November 2024

Motivation: Virtual microstructure has been one of the promising approaches to study and validate diffusion MRI microstructure models. Previous works in generating synthetic substrates have only focused on specific cell types, i.e. axons, neurons. Goal(s): The main goal of this work is to advance modeling of virtual gray matter microstructure and to close the real to simulation gap in brain microstructure geometries. Approach: We extend a framework of microstructure modeling to generate hybrid substrates that combine purely synthetic cells with virtual cells reconstructed from histology. Results: Different virtual substrates have been generated with axons and neurons with similar volume fractions in human cortex. Impact: More realistic virtual microstructure can allow the development of new computational models to map microstructure from diffusion MRI data. It can also be used to validate a whole set of analytical models and evaluate their accuracy.
Investigating the impact of magnetisation transfer and water exchange via permeability on diffusion MRI measurements
Authors: Zheng Zhiyu , Miller Karla , Tendler Benjamin , Cottaar Michiel
Published: November 2024

Motivation: Magnetisation transfer (MT) and water exchange across permeable membranes operate on a similar length scale to diffusion and may impact the measured diffusion-weighted MRI (dMRI) signal. This could bias resulting parameter estimates when performing microstructural modelling. Goal(s): To investigate how magnetisation transfer and water exchange affect dMRI measurements, particularly pore size estimations. Approach: Monte-Carlo simulations were used to model the dMRI signal affected by MT and cross-membrane exchange in a parallel-plate geometry. Errors in plate separation estimations represent their impact on dMRI estimates. Results: MT had a limited effect on dMRI pore size estimation, while cross-membrane water exchange can cause large overestimations. Impact: Pore size estimates from diffusion-weighted MRI have been found to be minimally affected by magnetisation transfer but might be significantly biased by large membrane/structure permeability. New signal models incorporating diffusion and complementary phenomena can now be explored using Monte-Carlo simulations.
TENEXI: Echo time-dependent neurite exchange imaging for in vivo evaluation of exchange time and relaxation time on the Connectome 2.0 scanner
Authors: Lee Hong-Hsi , Chan Kwok Shing , Llorden Gabriel Ramos , Huang Susie
Published: November 2024

Motivation: It is challenging to evaluate both T2 relaxation time and exchange time in intra-neurite and extra-cellular spaces of in vivo gray matter. Goal(s): To evaluate neurite exchange time and compartmental T2 relaxation times using a relaxation-diffusion-exchange protocol on Connectome 2.0. Approach: We acquired in vivo time-dependent diffusion-relaxation MRI data with multiple diffusion times (13-30ms) and echo times (31-120ms) using the Connectome 2.0 scanner with high-performance gradient system. Results: The exchange time and intra-neurite/extra-cellular relaxation times are about 10 ms and 120/80 ms across the cortical ribbon, respectively. Impact: In vivo mapping of water exchange and compartmental relaxation times is achievable in the brain gray matter using the high gradient performance Connectome 2.0 scanner. Multi-contrast MR protocol helps to improve the accuracy and precision in model fitting.
Selective probe of intra- and extra-cellular diffusion with non-invasive MRI using non-uniform oscillating gradients
Authors: Ferrari Ignacio Lembo , Avellaneda Manuel , Saidman Ezequiel , Divi Francisco , Alvarez Gonzalo
Published: November 2024

Motivation: Overcoming MRI resolution limitations is crucial for early-diagnosis of cellular-level pathologies. Achieving non-invasive MRI-images with cellular-resolution promises deeper insights into tissue-microstructure for advancing medical diagnosis. Goal(s): We aim to obtain cellular-resolution by characterizing molecular diffusion within intra- and extra-cellular compartments. We use Non-uniform Oscillating-Gradient Spin-Echo (NOGSE) signal-filtering potential, to address this intricate molecular diffusion problem. Approach: We employ diffusion-theory and the NOGSE-sequence, to quantitatively characterize yeast-cell phantoms mimicking tissue-microstructure. Results: We successfully characterize distinct diffusion-regimes within and outside cells. We introduce an innovative method to discriminate intra- and extra-cellular signals without complex models and analyses, allowing selective measurements of specific tissue-microstructure compartments. Impact: We introduce a transformative approach to non-invasive imaging, allowing cellular-level resolution discriminating different tissue-microstructure features without model assumptions. It offers a tool to investigate intricate cellular structures. Harnessing this technology might benefit patient early-diagnosis of diseases, based on quantitative images.
Unifying b-tensor encoding with compartmental-exchange: A novel analysis framework applied to double diffusion encoding
Authors: Nilsson Markus , Chakwizira Arthur , Szczepankiewicz Filip , Lasic Samo , Westin Carl-Fredrik
Published: November 2024

Motivation: Microstructure imaging with diffusion MRI is substantially improved by going beyond single diffusion encoding, but the methods using such data are divergent. In particular, theories unifying b-tensor encoding and water exchange are lacking. Goal(s): To develop and validate a theory applicable for detecting microscopic anisotropy and diffusional exchange with encoding strategies going beyond conventional diffusion MRI. Approach: Theoretical predictions were compared with results from Monte Carlo simulations of diffusion in exchanging Gaussian environments. Results: Theory and simulations agreed well, except when violating the assumptions of the theory. We show when and why the diffusional kurtosis decrease and when it increases due to exchange. Impact: We identified a key condition in which exchange leads to increased signal. This condition is similar to that incorporated in neurite exchange models. Our work thus offers new experimental designs of relevance for microstructure imaging of gray matter.
Evaluating cortical soma radius and intra-soma and neurite fractions using ultra-high-gradient diffusion MRI data acquired at 500 mT/m
Authors: Lee Hansol , Ma Yixin , Ramos-Llordén Gabriel , Chan Kwok-Shing , Krijnen Eva , Mahmutovic Mirsad , Keil Boris , Klawiter Eric , Lee Hong-Hsi , Huang Susie
Published: November 2024

Motivation: The Connectome 2.0 MRI scanner equipped with 500 mT/m gradient strength and 600 T/m/s slew rate is expected to advance gray matter microstructural characterization within the living human brain. Goal(s): To compare Soma And Neurite Density imaging (SANDI) metrics obtained from Connectome 2.0 and 1.0. Approach: We applied SANDI model fitting to diffusion MRI data acquired from 10 healthy subjects scanned on the Connectome 2.0 and 1.0 scanners. Results: We observed lower soma radius throughout the cortex on Connectome 2.0 compared to Connectome 1.0. SANDI metrics from Connectome 2.0 exhibited considerable contrast within the sensorimotor cortex that wasn’t apparent on Connectome 1.0. Impact: The Connectome 2.0 MRI scanner with 500 mT/m gradients advances non-invasive characterization of gray matter microstructure in the living human brain and enables mapping of real differences in cyto- and myeloarchitecture with greater sensitivity compared to the original Connectome scanner.
Diffusion Imaging for Mapping Hydraulic White Matter Parameters in Convection Enhanced Delivery
Authors: Lilieholm Thomas , Dean Douglas , Weaver Jayse , Alexander Andrew , Raghavan Raghu , Brady Martin , Block Walter
Published: November 2024

Motivation: Intraparenchymal brain infusions using convection enhanced delivery (CED) require predictive modeling to plan catheter locations to visualize end distributions. Currently, diffusion MRI indirectly estimates extracellular volume fraction (ECVF) and creates hydraulic conductivity maps. Goal(s): To directly measure ECVF parameters using advanced biophysical diffusion models. Approach: Quantitative brain maps of ECVF from a pre-existing database were generated with diffusion model SANDI. These were compared with prior ECVF estimates determined via invasive physiological techniques. Results: SANDI modeling predicted ECVF ranges of 0.14-0.26 in white matter across 12 cases, consistent with consensus values around 0.20 estimated from physiology. Impact: SANDI can quantitatively measure extracellular volume fractions in white matter. Previous methods estimated these parameters indirectly. Direct parametrization could be used for more accurate estimates of end-state biologic distributions in proposed trials of monogenic pediatric neurodegenerative gene therapy trials.
Fostering Confidence: Evaluating the Reproducibility and Reliability of Bingham-NODDI Model Measures on Different 3.0 T MRI Scanners
Authors: Sgambelluri Noemi , Ricchi Mattia , Tyler Damian , Testa Claudia , Grist James
Published: November 2024

Motivation: The NODDI model has been proven to be a powerful tool, however it struggles to depict complex brain neurite structures. Goal(s): The Bingham-NODDI model offers a more detailed approach for capturing pathological-related brain changes, although its validation is still ongoing. This study aims to make progress in this direction. Approach: To assess the Bingham-NODDI model's reliability across different MRI scanner systems, this study uses a consistent acquisition protocol, fostering the model's robustness. Results: The outcomes confirm Bingham-NODDI model’s reliability, promising potential clinical applications. By enhancing generalizability and validation, this research clears the path for improved diagnostic and research tools in neuroscience. Impact: The Bingham-NODDI model offers valuable insights into brain microstructure changes. Its integration into clinical practice alongside medical teams and neuroscientists is highly promising. This multi-center study advances this goal by assessing model stability, fostering future collaborations between scientistis and clinicians.
Microstructure and exchange are not always linked
Authors: Williamson Nathan H , Ravin Rea , Cai Teddy , Basser Peter
Published: November 2024

Motivation: To understand the mechanisms of water exchange. Goal(s): To determine the extent that DEXSY-based water exchange measurements depend on changes to tissue microstructure (e.g., cellular swelling/shrinking). Approach: NMR measurements of ADC, exchange rate and light microscopy measurements of intrinsic optical signal (IOS) are acquired simultaneously in real time on viable and dead ex vivo neural tissue during potassium and osmotic perturbations. Results: In dead samples, exchange, ADC, and IOS are similarly affected. In viable samples, however, some perturbations affect exchange differently than they do the ADC and IOS that reflect changes in microsctructure alone. Exchange may be physiologically regulated independently of cell volume. Impact: Water exchange is sensitive to cellular processes distinct from microstructure and blood flow. This measurement possibly could lead to a new fMRI method.
Time-dependent diffusion MRI for quantitative microstructural mapping of common brain tumors
Authors: Du Mingying , Yang Han , Xu Hao , Chen Meining , Yan Xu , Zhou Peng
Published: November 2024

Motivation: Different clinical managements are required for brain tumors such as glioblastoma, meningioma and metastases, with existing MRI techniques showing limitations in distinguishing them. Goal(s): The study aims to validate the utility of td-dMRI to enhance the accuracy of brain tumors characterization, using the IMPULSED model to distinguish microstructural distinctions. Approach: We used td-dMRI to explore microstructural mapping in glioblastoma, meningioma, and lung cancer patients with brain metastases by IMPULSED model, focusing on the parameters Dex, d, and vin to differentiate these brain tumors. Results: The cell size and extracellular diffusivity of these tumors are distinctly different. Impact: This study demonstrated that td-dMRI can non-invasively differentiate between glioblastomas, meningiomas and metastases. It proposes a potential change in diagnostic protocols, offering a pathway to more personalized management while reducing reliance on contrast agents.
Point spread function(PSF) encoding EPI versus BLADE DWI in brain tumor diagnosis
Authors: Zhong Wen , Lian Yuan , Huang Zhimin , Zhao Mangsuo , Zhou Kun , Zhang Xianchang , Weng Dehe , Wang Yishi , Yang Yue , Zhang Yuqi , Guo Hua
Published: November 2024

Motivation: High-resolution DWI plays a crucial role in brain tumor diagnosis. Previous studies have introduced two high-resolution distortion-free DWI techniques: PSF and BLADE. However, no one has yet compared the two in brain MR imaging. Goal(s): To compare the image quality of PSF and BLADE in high-resolution DWI. Approach: In this study, scan parameters were adjusted to achieve the optimized image quality for PSF and BLADE. Subsequently, scans were performed on patients, and the final image quality was compared. Results: With scanning times being similar, PSF exhibits a superior SNR compared to BLADE while its performance is suboptimal at the boundaries of brain tissues. Impact: A preliminary comparison of the image quality between PSF and BLADE has been conducted, paving the way for more in-depth clinical research in areas such as diagnostic accuracy and imaging quality control.
The ReIMAGINE consortium – establishing an infrastructure for the external validation of prostate MRI lesion classification models
Authors: Thorley Natasha , Syer Tom , Srikanthan Swetha , Antunes Jacob , Parry Thomas , Marsden Teresa , Clow Rosemary , Santaolalla Aida , Appayya Mrishta Brizmohun , Brembilla Giorgio , Brew-Graves Chris , Min Zhe , Hu Yipeng , Atkinson David , Mallett Sue , Rodney Steve , Jacobs Paul , Piper Jonathan , Ahmed Hashim , Emberton Mark , Punwani Shonit
Published: November 2024

Motivation: Multiparametric MRI is highly sensitive for identifying clinically significant prostate cancer (csPCa), but has a poorer specificity, meaning many men undergo unnecessary prostate biopsies. Goal(s): To evaluate whether artificial intelligence (AI) could improve the diagnostic accuracy of MRI compared to current clinical methods, including Likert score and PSA density (PSAd). Approach: We carried out independent evaluation of a prostate MRI lesion classifier model using a large multisite and multivendor prostate MRI dataset (1,039 patients). Results: The AI model matched the sensitivity and specificity of Likert score plus PSAd cut-offs on data similar to the training set, but did not generalise to other data. Impact: An infrastructure has been successfully established to allow robust and independent evaluation of prostate MRI lesion classification models to accelerate the development of such tools and to ensure adequate testing pre-deployment.
Improved correction of B0 inhomogeneity-induced distortions in prostate diffusion images
Authors: Conlin Christopher , Rakow-Penner Rebecca , Seibert Tyler , Dale Anders
Published: November 2024

Motivation: The Jacobian intensity correction (JIC) of conventional EPI-distortion correction methods can conceal severe under-correction and even create false anatomical structure. Goal(s): Demonstrate the shortcomings of JIC methods and present an alternative distortion-correction technique that obviates the need for a JIC. Approach: Acquiring DWI images with opposite phase-encoding polarity at multiple b-values and normalizing prior to estimating tissue displacement eliminates the need to account for intensity scaling with the JIC. This approach, referred to as mRPG, was compared against conventional distortion correction methods. Results: mRPG significantly improved the estimation and removal of spatial distortions compared to conventional methods. Impact: Jacobian intensity correction (JIC) can generate misleading improvement of EPI distortion and create false structure in prostate diffusion images. Eliminating the JIC, by acquiring opposed-phase images at multiple b-values and normalizing prior to correction, results in improved EPI distortion correction.
Amide proton transfer weighted imaging histogram analysis for Prostate Cancer Detection Comparison with Mp-MRI: A two center prospective study
Authors: zhang li , zhang jing , li longchao , yang ping
Published: November 2024

Motivation: The diagnostic utility of whole tumor amide proton transfer–weighted (APTw) imaging analysis for predicting prostate cancer(PCa) has not been reported. Goal(s): The purpose of this study was to evaluate the diagnostic performance of whole tumor APTw histogram analysis, for the depiction of PCa compared with multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Approach: Diagnostic performance was assessed by ROC with AUC analysis. Results: We found that combining PI-RADS version 2.1 and APTw histogram achieved the best results in distinguishing transition zone PCa from benign prostatic hyperplasia and peripheral zone PCa from chronic prostatitis. Impact: Whole-tumor histogram analysis of APTw images improved the diagnostic performance of multiparametric MRI with PI-RADS version 2.1 in detecting prostate cancer in both the peripheral and transition zones.
Development of a Whole Abdominopelvic Variable Resolution Hyperpolarized 13C MRI Approach for Advanced Prostate Cancer Clinical Research
Authors: Nickles Tanner , Chen Hsin-Yu , Kim Yaewon , Lee Philip , Gebrezgiabhier Daniel , Bok Robert , de Kouchkovsky Ivan , Ohliger Michael , Wang Zhen , Larson Peder , Kurhanewicz John , Aggarwal Rahul , Gordon Jeremy , Vigneron Daniel
Published: November 2024

Motivation: Monitoring the progression or response of advanced prostate metastases is a current clinical unmet need that is not reliably delineated with current CT and PET. Goal(s): Here, we developed a high-resolution whole abdominopelvic [1-13C]pyruvate HP MRI approach for the metabolic biomarker characterization of metastases in prostate cancer patients. Approach: A variable-resolution imaging approach was used to provide high-resolution [1-13C]pyruvate, robust spatiotemporal denoising and B1+ variation correction methods were used to quantify the rate-constant for the conversion of [1-13C]pyruvate to lactate, kPL. Results: Improved conspicuity of [1-13C]pyruvate distribution and kPL conversion maps of metastatic lesions were achieved with the new approach. Impact: The improvement in [1-13C]pyruvate resolution and clear delineation of highly metabolically active metastatic lesions in kPL maps demonstrated the potential of [1-13C]pyruvate HP MRI in advanced prostate cancer.
Annotation of Benign Prostatic Hyperplasia Lesions Can Improve the Detection of Prostate Cancer
Authors: Yi Yinqiao , Ding Zhenwei , Huang Guoquan , Wu Dongmei , Song Yang , Yang Guang
Published: November 2024

Motivation: Accurate interpretation of prostate MRI demands a high level of expertise and deep learning models for prostate cancer (PCa) detection often suffer from low specificity. Goal(s): To explore the value of annotation of benign prostatic hyperplasia (BPH) to prostate cancer (PCa) detection. Approach: We retrospectively collected 96 patients with PCa and 92 patients with BPH, all scanned with PI-RADS protocol. Two deep learning models were built: Model1 only detected PCa while Model2 simultaneously detected BPH and PCa. Results: Model2 achieved superb performance with test AUC of 0.995, outperforming Model1 whose test AUC was 0.770. Impact: Explicitly using the BPH label improved the performance of PCa detection significantly, implying multi-task deep learning models targeting multiple diseases are not only more in line with the needs of clinical applications, but can also bring about performance improvement.
Evaluating Subclinical Myocardial Injury in Systemic Lupus Erythematosus Patients Using CMR Feature Tracking
Authors: Huang Lingling , Wang Xiaojuan , Lin Qi , Wu Peng , Xu Yongzhou
Published: November 2024

Motivation: Early detection of myocardial injury in Systemic lupus erythematosus (SLE) patients is important. Goal(s): Find a clinical biomarker for preclinical myocardial injury in SLE patients. Approach: CMR-FT (Cardiac Magnetic Resonance Feature Tracking) technology and CVI 42 software were used to measure cardiac functional parameters and myocardial strain parameters for SLE patients with/without subclinical myocardial injury and healthy controls. Results: Compared to the control group, the circumferential strain (CS) and longitudinal strain (LS) were found to be reduced in patients with subclinical myocardial injury in SLE. The CMR-FT technology was able to detect changes in myocardial strain before a decrease in ejection fraction occurred. Impact: Early detection of myocardial injury in SLE patients and proactive treatment are important for improving patient outcomes. This study found that CMR-FT quantitative technique can identify subclinical myocardial damage in patients with SLE.
MRI and fluorescence imaging of perfluorohexane loaded nanoparticles targeting atherosclerosis and their effects on activated macrophages
Authors: Ye Man
Published: November 2024

Motivation: Cardiovascular disease is the main cause and disease of morbidity and mortality in the world, and atherosclerosis causes more than 90% of cardiovascular diseases. Goal(s): Early diagnosis and timely treatment of atherosclerosis to reduce the morbidity and mortality of residents. Approach: In the development of atherosclerosis, reducing the content of macrophages which derived foam cells can reverse the formation of atherosclerotic plaque. Results: The dextran sulfate in the nanoparticles can target SR-A of activated macrophages in atherosclerosis, and then the nanoparticles undergo phase transformation in macrophages to induce apoptosis. Impact: The nanoparticles have multi-mode molecular imaging capabilities, and have excellent targeting performance. Under LIFU, it can undergo phase transformation and induce apoptosis of macrophages, providing a promising strategy for the diagnosis and treatment of atherosclerotic plaque in the future.
Using cardiac MRI quantification in identifying subtle cardiac structural and functional changes in patients with liver cirrhosis.
Authors: Zhang Yu , Yang Yiming , Chen Zhiyuan , Zhou Dongjing , Zhang Shuping , Huang Ruhang , Qin Haodong , Liu Yupin
Published: November 2024

Motivation: Patients with liver cirrhosis often have heart-related physiological and pathological changes. Goal(s): The aim of this study is to investigate the effectiveness of using multiple parameters for cardiac MRI quantification in identifying subtle cardiac structural and functional changes in patients with liver cirrhosis. Approach: Cardiac MRI methods were employed, along with Mann-Whitney U tests and Spearman correlation analyses for Statistical analyses. Results: Our results indicated that MRI showed an increase in myocardial fibrosis parameters, and there was a positive correlation between liver T1 relaxation time and myocardial T1 relaxation time. Impact: This study could lead to improved understanding of heart diseases associated with cirrhosis, helping to create better diagnostic and treatment plans, ultimately improving patients' quality of life.
Association between neutrophil/lymphocyte ratio and MR myocardial first pass perfusion in patient with coronary microvascular dysfunction
Authors: Zhang Gang , Xing Wei , He Junjing , Shen Zhiwei , Sun Jiemei , Zhou Geli
Published: November 2024

Motivation: The study on correlation between blood neutrophil-to-lymphocyte ratio (NLR) and cardiac magnetic resonance perfusion imaging (CMRI) quantitative indexes in patients with cardiac syndrome X (CSX) is few. Goal(s): To investigate the relationship between the blood neutrophil/lymphocyte ratio (NLR) and the mean value and coefficient of variation of the magnetic resonance myocardial first pass perfusion parameters in patients with cardiac syndrome X. Approach: A total of 53 patients with CSX and 43 patients with unstable angina pectoris (UAP) were evaluated using MR myocardial perfusion and blood routine examination. Results: A negative correlation was observed between the myocardial perfusion index in CSX and blood NLR. Impact: It is provided further evidence for the potential utility of NLR as a diagnostic marker for CSX.
Pressure gradient before and after transcatheter pulmonary valve implantation for repaired tetralogy of Fallot: a new 4D flow MRI measurement
Authors: Nagao Michinobu , Kogure Tomohito , Hamano Hiroshi , Goto Yashuhiro , Shiina Isao , Kodaira Kazuo , Kato Mana , Yoneyama Masami , Inoue Akihiro , Yamamoto Atsushi , Inai Kei , Sakai Shuji
Published: November 2024

Motivation: Estimating pressure gradients due to valvular disease using 4D flow MRI in repaired TOFGoal(s): Identify the location and extent of the pressure gradientApproach: new 4D flow MRI software for pressure gradient measurementResults: In right heart catheter-defined pulmonary hypertension, this software showed a right ventricular outflow tract to pulmonary artery pressure gradient. Impact: Whereas pressure gradients used to require invasive catheterization, our method is a noninvasive test that does not use contrast media. It also has the advantage of being able to locate the site of the pressure gradient.
Native T1 Mapping Radiomics for Classification of Pulmonary Valve Replacement Risk Factors in Patients with Repaired Tetralogy of Fallot
Authors: Peng Jo-Hua , Wu Ming-Ting , Pan Nai-Yu , Huang Teng-Yi , Liu Yi-Jui , Weng Ken-Pen , Peng Hsu-Hsia
Published: November 2024

Motivation: Right ventricular (RV) dilation and exercise intolerance are important prognostic indicators in repaired Tetralogy of Fallot (rTOF) patients. The conventional native T1 value may ignore subtle changes of myocardial fibrosis patterns in rTOF patients. Radiomics uncovers concealed insights regarding cardiomyopathy. Goal(s): To establish a radiomics model using native T1 mapping for identifying rTOF patients with severe RV dilation and exercise intolerance. Approach: We extracted 623 radiomic features from native T1 mapping and employed machine learning for feature selection and classification that enhance diagnostic accuracy in identifying cardiac involvements. Results: Optimal performance was achieved in the segmental mid-slice T1 mapping model. Impact: The radiomic analysis of myocardial native T1 can reveal the different myocardial T1 distribution patterns between different severity of RV dilation and exercise intolerance before substantial changes of conventional native T1 values.
Evaluating the Diagnostic Efficacy of Cardiac MRI Quantitative Imaging Parameters in Hypertensive Heart Disease During Compensation
Authors: Tang Lusong , Wang Fang , Yang Lili , Yue Xiuzheng
Published: November 2024

Motivation: Early detection of hypertensive heart disease (HHD) in the compensatory stage is clinically challenging, necessitating novel evaluative parameters for cardiac function alterations due to HHD. Goal(s): This research aimed to ascertain the diagnostic value of multiparametric cardiac magnetic resonance (CMR) imaging in this phase. Approach: We compared cardiac functional parameters, T1 mapping, extracellular volume fraction (ECV), and myocardial strain metrics obtained via CMR among compensatory HHD, decompensated HHD, and a normotensive control group. Results: Findings reveal that both circumferential and longitudinal strains in the compensatory HHD cohort were significantly reduced compared to the control group (P<0.05). Impact: Employing quantitative CMR parameters facilitates the assessment of myocardial functional impairments in hypertensive heart disease, potentially unmasking subclinical cardiac dysfunction and providing prognostic value for disease progression.
Magnetization Transfer Magnetic Resonance Fingerprinting Using Spin Lock Preparations
Authors: Wyatt Cory , Barbara Thomas , Guimaraes Alexander
Published: November 2024

Motivation: Magnetization transfer (MT) techniques allow for quantitative measurement of the macromolecular proton fraction (MPF) of tissues. However, the process of measuring these MT parameters can be lengthy and require many assumptions of T1 and T2. Goal(s): In this study, a magnetic resonance fingerprinting sequence is proposed that acquires T1, T2, and MPF using spin lock preparations. Approach: An MRF sequence was created using spin lock preparations of various off-resonance frequencies to create MT contrast. The sequence was acquired in agarose phantoms and the human brain. Results: Results showed increased MPF with increasing agarose concentration and in white matter. Impact: This study demonstrates the effectiveness of using spin lock pulses for magnetization transfer MRF and allow for quick acquisition of MPF maps that are corrected for the T1 and T2 of the tissue.
Unlocking Data-Consistent Synthesis of Clinical Contrasts from Magnetic Resonance Fingerprinting with Semi-Supervised Learning
Authors: Yurt Mahmut , Zhou Zihan , Liao Congyu , Alkan Cagan , Cao Xiaozhi , Wang Nan , Oscanoa Julio , Schauman Sophie , Gao Mengze , Li Zhitao , Cukur Tolga , Soares Bruno , Syed Ali , Vasanawala Shreyas , Pauly John , Setsompop Kawin
Published: November 2024

Motivation: We aim to introduce an end-to-end, ultra-fast acquisition and synthesis protocol for contrast-weighted image generation from magnetic resonance fingerprinting. Goal(s): Our objective is to facilitate data compilation from large patient cohorts to enhance generalizability and accuracy of synthesis. Approach: We leverage a semi-supervised framework to enable model training using highly-accelerated ground-truth data of the target contrasts, and introduce data-consistent synthesis in inference by performing subject-specific fine-tuning and validation. Results: Our experiments indicate that the proposed method enables high-quality synthesis using network models trained on prospectively undersampled data of the contrast-weighted images. We show that data-consistent synthesis helps improve synthesis quality and mitigate hallucinations. Impact: Conventional synthesis models for MRF perform a single-shot inference and are prone to hallucinations and inaccuracy. We introduce semi-supervised learning that enables data-consistency in inference, by merely getting an additional, ultra-fast 1-2min data of the target contrasts for subject-specific fine-tuning.
TransUnet Based Deep Learning with Tissue-weighted Loss Function for Accelerated Magnetic Resonance Fingerprint Reconstruction
Authors: Wei Jintao , Zhou Zihan , Dong Bo , Wongkornchaovalit Paween , Ye HuiHui , He Hongjian
Published: November 2024

Motivation: MRF data with short time frames make dictionary matching challenging with large quantitative errors. Goal(s): We proposed a deep learning method by taking account in global Information and tissue-specific relaxometry, for better quantitative results using shorter frames than dictionary matching with good reproducibility. Approach: We proposed to combine Unet with an embedded transformer and a tissue-weighted loss function. We compared our approach to dictionary matching and examined various levels of reduced scan time. Results: The proposed method has less error with shorter frame data comparing dictionary matching. This is more effective for the gray matter and for scan times shorter than 300 frames. Impact: The proposed method improves the problem of poor quality of reconstructed images for dictionary matching in shorter frames, in addition this method has good repeatability and provides a powerful reconstruction algorithm for MRF sequence acceleration.
Deep Structure-Preserved Graph Embedding for Improved MRF Reconstruction
Authors: Li Peng , Ji Yuping , Hu Yue
Published: November 2024

Motivation: Improve MRF Reconstruction. Goal(s): Introduce a novel deep-learning framework based on the structure-preserved graph embedding for improved MRF reconstruction. Approach: We propose a reconstruction framework based on graph embedding, modeling the high-dimensional MRF data and the parameter maps as graph data nodes. To improve the accuracy of the estimated graph structure and the computational efficiency of the proposed framework, we unroll the iterative steps into a deep neural network and introduce a learned graph embedding module to adaptively learn the graph structure. Results: Numerical experiments demonstrate that our approach can reconstruct high-quality parameter maps within reduced computational cost. Impact: By redefining the MRF reconstruction problem as a structure-preserved graph embedding problem, the proposed method can effectively reduce the computational complexity of MRF reconstruction compared to data-priors-driven methods.
MR Vascular Fingerprinting with Deep Learning to Estimate Brain Physiological Parameters
Authors: Lin Chieh-Te , Wheeler Gregory , Fan Audrey
Published: November 2024

Motivation: Magnetic resonance vascular fingerprinting quantitatively measures microvascular blood oxygen saturation, cerebral blood volume, and vessel radii. Matching simulated signals to in-vivo data is computationally expensive, therefore, we leverage deep learning to alleviate the burden. Goal(s): Build a model to simultaneously and accurately estimate three physiological parameters from a GESFIDE (gradient echo sampling of free induction decay and echo) sequence. Approach: The model has two fully-connected layers to estimate three parameters, and was validated with synthetic signals and healthy subject parameter mapping. Results: The model achieves comparable root-mean-squared-error to traditional fingerprint matching in test signals. We show physiological reasonable values in healthy subject maps. Impact: We leverage deep learning in MR vascular fingerprinting to simultaneously estimate brain physiological parameters through training with simulated vascular dictionaries. The model enables quantitative measurements of oxygenation, blood volume and vessel radius in test signals and in-vivo mapping.