bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of cortical locations functionally connected to the hippocampus for personalized multi-target TMS neuromodulation
Authors: Lee Hsin-Ju , Lin Fa-Hsuan
Published: November 2024

Motivation: Personalized TMS targeting based on functional connectivity has been proposed. However, the dispersion of personalized TMS targets remains unknown. Goal(s): Characterize brain areas functionally connected to the hippocampus in a population. Approach: Identify hippocampus-based memory networks using the resting-state fMRI data from the Human Connectome Project. Results: The medial prefrontal cortex (mPFC) and lateral parietal cortex (PPC) were found to be connected to the hippocampus. The centroids of group-average results were separated from the atlas coordinates by about 11 mm. Individualized targets are dispersed around the group-average coordinates (mPFC: 11.1 +/- 3.8; PPC: 3.4 +/- 2.3 mm). Impact: The functional connectivity analysis on the Human Connectome Project resting-state fMRI data with the seed at the hippocampus revealed that the medial prefrontal cortex (mPFC) and lateral parietal cortex (PPC) connected to the hippocampus significantly dispersed across individuals.
From microscopy data to hemodynamic simulations: a vascular graph approach to understand the fMRI signal formation
Authors: Curcic Vanja , Báez-Yáñez Mario , Kara Prakash , Liu Chao , van Osch Matthias , Petridou Natalia
Published: November 2024

Motivation: Understanding the impact of cortical vascular architecture on the spatiotemporal features of hemodynamic responses. Goal(s): Automatic extraction of realistic cortical vasculature models from microscopy data, and simulation of hemodynamic changes across the extracted vascular network. Approach: We present a pipeline that utilizes graph theory for extracting the vasculature from microscopy data, representing it as a vascular graph. Simulations were performed using the extracted vascular graphs by converting the connectivity matrix into a dynamic system modeled by RC circuits. Results: We extracted two realistic vascular graphs and used them to mimic hemodynamic changes resulting from simulated arterial dilation. Impact: Vascular graphs extracted by the developed pipeline could serve to simulate hemodynamic changes across the cortical vasculature. This provides a tool to enhance fMRI signal interpretation and provide valuable insights into the role of vascular dysfunction in cerebrovascular diseases.
Shift-invariant linearity and spatial variation of the negative BOLD response in human with high spatiotemporal functional MRI
Authors: Vinogradov Artemy , Fesharaki Nooshin J. , Jung Minkyu , Yau Jeff , Ress David , Kim JungHwan
Published: November 2024

Motivation: Many fMRI studies have observed a negative BOLD response (NBR) that is often associated with neural suppression. However, the temporal dynamics of the NBR remains unclear. Goal(s): Here, we investigate temporal linearity of the NBR and characterize spatial variations of the BOLD negative hemodynamic response function (nHRF) along cortical surface. Approach: We examine temporal linearity of the NBR with a unilateral visual stimulus with various stimulus durations, then use the same stimulus with 2-s duration for spatial variation of nHRF. Results: We found unique nHRF dynamics varying gradually along cortical surface, and non-linear behavior of the NBR with different stimulus duration. Impact: The unique dynamics of the NBR can confound linear analyses of event-related fMRI experiments. In addition, our results with shift-invariant experiments with different stimulus durations suggest that temporal linearity does not hold for the NBR.
Data-driven analysis of cerebrovascular reactivity mapping with breath-hold challenges in brain tumor patients
Authors: Jen Mu-Lan , Yeh Mei-Yu , Chen Henry , Kumar Vinodh , Liu Ho-Ling
Published: November 2024

Motivation: Cerebrovascular reactivity (CVR) mapping can provide valuable information for the evaluation of lesion and neurovascular uncoupling in brain tumors. Goal(s): To evaluate the robustness of data-driven CVR analysis in patients with brain tumors. Approach: CVR MRI of brain tumor patients (n=18) was performed with a breath-holding task paradigm. CVR map was obtained using GLM with four regressors for comparison: (1) gray matter (GM), (2) GM with lesion removed, (3) whole brain (WB), and (4) WB with lesion removed. Results: Proper temporal and spatial filtering reduced the differences between the four regressors, resulting in similar CVR maps with highly correlated BOLD contrast. Impact: The study demonstrated that with proper temporal processing, robust data-driven CVR analysis can be obtained in patients with brain tumors.
GEM: a unifying model for Gray Matter microstructure
Authors: Uhl Quentin , Pavan Tommaso , de Riedmatten Inès , Nguyen-Duc Jasmine , Jelescu Ileana
Published: November 2024

Motivation: Gray Matter lacks a unified microstructure model, unlike White Matter. This study introduces the Generalized Exchange Model (GEM) to unify Gray Matter models, introducing exchange with simple structures. Goal(s): Evaluate GEM performance, compare it with other Gray Matter models, and assess its potential for clinical MRI. Approach: GEM parameters and equations are detailed and validated with simulated data. GEM is applied on clinical MRI data, and compared to other Gray Matter model estimates. Results: GEM successfully unifies Gray Matter diffusion models, offering plausible estimations in clinical MRI revealing microstructural patterns. Future research will optimize data acquisition and assess accuracy. Impact: The introduction of the Generalized Exchange Model holds significant implications. For scientists, it provides a unified framework, potentially simplifying and enhancing Gray Matter modeling, promoting consistency in research. Clinicians may benefit from improved specificity in diagnosing neurological conditions.
Characterizing Brain Tumor Microstructure with SANDI using 300 mT/m Gradients
Authors: Chu Ying-Hua , Yuan Yifan , Hsu Yi-Cheng , Mei Shuhao , Yu Wenwen , Wang He , Yue Qi
Published: November 2024

Motivation: Precisely locating tumor regions is challenging for effective surgery and radiotherapy. Goal(s): Enhance tumorous area identification accuracy. Approach: We integrated SANDI to model both stick and spherical cell types, estimating their densities. We introduced a metric quantifying spherical cell ratio relative to total cell volume for characterizing elevated tumor cell density. Results: Our model effectively characterizes microstructural variations in brain tumor areas. The newly proposed cell number density ratio parameter provides a distinctive marker, highlighting high cell density within tumors. This approach holds promise for improving tumor localization, treatment planning, and patient outcomes. Impact: Brain tumor microstructure characterization using SANDI showed microstructure changes in tumors and edema. The introduced metric, sensitive to tumor changes, holds promise for early invasion detection, enhancing diagnostic precision.
Mouse Brain Microstructural Changes by High-resolution Diffusion Magnetic Resonance Imaging and Spatial Transcriptomics During Development
Authors: Han Xinyue , Maharjan Surendra , Chen Jie , White Leonard , Johnson Allan , Wang Nian
Published: November 2024

Motivation: Characterizing developmental brain microstructure changes is important for understanding the mechanism of brain development at cellular level. Goal(s): We aimed to study brain microstructure and to correlate phenotypical diffusivity variations with genotypic expression profiles. Approach: We imaged postnatal mouse brains by high-resolution diffusion magnetic resonance imaging (dMRI) with both DTI and NODDI models to extract quantitative diffusion metrics. dMRI-gene expression correlation was tested by regression model. Results: Distinct growth patterns are observed by quantitative dMRI parameters in white matter bundles, isocortex, hippocampus, and cerebellum. Genes related to nerve system displayed unique spatial and temporal expression patterns corresponding with dMRI alternations during brain development. Impact: This study may improve our understanding of brain microstructure changes during postnatal development at molecular and cellular level. This study also provides non-invasive imaging techniques to quantitatively investigate neurodevelopmental disorders at high resolution.
Submillimeter diffusion MRI using in-plane segmented 3D multi-slab EPI and a denoiser-regularized reconstruction
Authors: Li Ziyu , Miller Karla , Wu Wenchuan
Published: November 2024

Motivation: Submillimeter diffusion MRI is desirable for neuroscientific research but suffers from intrinsically low SNR. Goal(s): To achieve submillimeter isotropic resolution in-vivo diffusion MRI with superior SNR and minimal blurring and distortion. Approach: We quantify the effective resolution and SNR for high-resolution diffusion-weighted EPI, based on which a 3D Fourier encoding-based acquisition with in-plane segmented multi-slab EPI at 7T and a denoiser-regularized reconstruction framework are developed. Results: In-vivo whole-brain experiments at 0.61 mm isotropic resolution reveal more detailed microstructure compared to 1.05 mm data, which also demonstrates great consistency with a previous post-mortem study. The acquired data also exhibit great anatomical fidelity. Impact: Our study achieves 3D Fourier-encoded 0.61 mm isotropic resolution whole-brain in-vivo diffusion MRI with minimal blurring and distortion and superior SNR, showing great potential to reveal more detailed depiction of microstructure of the living human brain and advance neuroscientific research.
Multi-echo NODDI with released intrinsic diffusivity: Initial insights for rat brain tissue
Authors: Farrher Ezequiel , Chiang Chia-Wen , Cho Kuan-Hung , Choi Chang-Hoon , Chen Ming-Jye , Huang Sheng-Ming , Kuo Li-Wei , Shah N. Jon
Published: November 2024

Motivation: The applicability of NODDI and its spinoffs, e.g. multi-echo (MTE) NODDI, is limited to those tissue conditions where the intrinsic diffusivity is known a priori. Goal(s): We propose an estimation approach for MTE-NODDI parameters in which the intrinsic diffusivity is released whilst ensuring fitting stability by adding an l2-norm regularisation term to the cost function. Approach: The regularisation parameter was optimised via the generalised cross-validation approach. The MTE-NODDI with released intrinsic diffusivity was tested in a healthy rat at 3 T. Results: The estimation of MTE-NODDI with released intrinsic diffusivity is well-conditioned if an l2-norm regularisation term is used. Impact: The proposed estimation approach for MTE-NODDI parameters with released intrinsic diffusivity was shown to be stable. Thus, a new range of tissue conditions in which the intrinsic diffusivity is known to be affected, e.g. stroke, can be accurately characterised.
Assessment of the repeatability and stability of NODDI diffusion modelling using phantom and in vivo acquisitions.
Authors: Ricchi Mattia , Axford Aaron , McGing Jordan , Shinozaki Ayaka , Yeung Kylie , Birkhozeler Sarah , Mills Rebecca , Zaccagna Fulvio , Lewis Andrew , Rider Oliver , Tyler Damian , Testa Claudia , Grist James
Published: November 2024

Motivation: The NODDI diffusion-MRI model shows promising results in characterising brain microstructure and capturing neurological disease-related changes. However, the NODDI model lacks validation, limiting its clinical application. Goal(s): The goal is to validate the diffusion MRI NODDI model, assessing its consistency over time and addressing the need for robust methods in clinical research. Approach: By scanning several times phantoms simulating brain-restricted diffusion and healthy volunteers with the same acquisition protocol, we meticulously assess NODDI's stability over time and in the presence of magnetic gradient coil heating. Results: The study confirms the NODDI model's exceptional consistency and stability, establishing its credibility for future clinical applications. Impact: The study confirms the reliability and stability of the NODDI model in assessing brain microstructure over time. This has significant implications for monitoring neurological disease progression and may lead to standardised MRI calibration protocols for collaborative research and clinical applications.
Impact of Rician Bias on biophysical modeling
Authors: París Guillem , Pieciak Tomasz , Jones Derek , Aja-Fernández Santiago , Tristán-Vega Antonio , Veraart Jelle
Published: November 2024

Motivation: Rician noise degrades the accuracy of biophysical modeling. Understanding this bias and defining a robust strategy for its mitigation, is important for reproducible and quantitative use of diffusion MRI. Goal(s): To study the impact of noise biases on biophysical models and evaluate methods for more accurate estimation of diffusion metrics. Approach: We compare various parameter estimators (via simulations and MRI data) and evaluate their impact on the accuracy of biophysical model parameters. Results: The use of rotational-invariant spherical harmonics in biophysical modeling is a source of noise bias that can be mitigated by fitting such models directly to the diffusion-weighted signals. Impact: With the advent of higher b-values, Rician bias pose a threat to the reproducibility in diffusion MRI studies. With this work we take a deep look at such bias and propose alternatives to avoid such counfounders from the final estimates.
Brain glymphatic system impairment in multiple sclerosis patients based on diffusion tensor imaging
Authors: Wang Zhuo , Zhang Jing , Zhou Liang , Ai Kai
Published: November 2024

Motivation: Glymphatic abnormalities have been reported in several neurodegenerative disorders. However, glymphatic function has not been thoroughly investigated in multiple sclerosis, especially its relationship with clinical fatigue. Goal(s): We aimed to investigate glymphatic system function in multiple sclerosis and to evaluate its association with clinical fatigue. Approach: We prospectively enrolled 36 multiple sclerosis patients and 31 healthy controls. All subjects underwent diffusion tensor imaging, and the along perivascular space (ALPS) indexes were calculated. Correlations between ALPS indexes and clinical fatigue parameters were analyzed. Results: The brain glymphatic system is impaired in multiple sclerosis. Impaired glymphatic function was associated with multiple sclerosis-related fatigue. Impact: Non-invasive diffusion-based imaging approach could be used as a proxy for displaying an impaired glymphatic system in multiple sclerosis patients, suggesting that glymphatic impairment may be a pathological mechanism underpinning clinical fatigue.
Time-dependent diffusion MRI could distinguish between functioning and non-functioning pituitary adenoma
Authors: Kamimura Kiyohisa , Nakano Tsubasa , Hasegawa Tomohito , Nakajo Masanori , Fujio Shingo , Iwanaga Takashi , Imai Hiroshi , Feiweier Thorsten , Yoshiura Takashi
Published: November 2024

Motivation: Differentiation between functioning and non-functioning pituitary adenoma (PA) is clinically relevant. Feasibility of their microstructural differentiation is undetermined. Goal(s): To investigate whether the time-dependent diffusion MRI can distinguish functioning from non-functioning PA. Approach: Twenty-four patients with functioning and 30 with non-functioning PA were examined. Pituitary DWI was performed using inner FOV EPI based on 2D-selective radiofrequency excitations with oscillating (diffusion time=7.1ms) and pulsed (36.3ms) gradient preparations. ADC change (cADC) and relative ADC change (rcADC) between two diffusion-times were calculated. Results: cADC was significantly higher in functioning than in non-functioning PAs (P=0.012), showing that time-dependent diffusion MRI can distinguish them. Impact: Our results clarified that there are microstructural differences between functional and non-functional pituitary adenomas. Time-dependent diffusion MRI of the pituitary gland can detect their microstructural characteristics, providing clues as to their imaging differentiation.
Correlation Between Longitudinal Changes in Substructure DTI and Neurocognitive Outcomes for Pediatric Brain Tumor Patients
Authors: Oglesby Ryan , Chang Leslie , Olatunji Elizabeth , Chotiyanonta Jill , Uchida Yuto , Onda Kengo , Lee Junghoon , Pathiravasan Chathurangi , Oishi Kenichi , Peterson Rachel , Acharya Sahaja
Published: November 2024

Motivation: The five-year survival of pediatric CNS tumors has increased from 57% in 1975 to 77% in 2015. Despite these improvements, survivors are at risk for cognitive sequelae resulting from disease and treatment exposures. Goal(s): Evaluate the correlations between substructure white matter integrity and neurocognitive outcomes. Approach: The current study examined associations between longitudinal change in substructure DTI and neurocognitive outcomes in 61 pediatric brain tumor patients. Results: Moderate correlations were found between mean diffusivity in the middle cerebellar peduncle and working memory, fractional anisotropy in the inferior cerebellar peduncle and intelligence quotient, and axial diffusivity in the corpus callosum and processing speed. Impact: Quantifying the correlation between longitudinal change in substructure DTI and cognitive outcomes in pediatric brain tumor patients will aid radiation oncologists in the pursuit of substructure-informed treatment planning by limiting dose to brain substructures sensitive to specific neurocognitive domains.
Memory impairment is associated with glymphatic dysfunction in hemodialysis patients
Authors: Chen Hui Juan , Qiu Jie , Guo Yihao , Qin Haodong , Chen Feng
Published: November 2024

Motivation: Glymphatic function assessed by diffusion tensor image analysis along the perivascular space (DTI-ALPS) index might be associated with cognitive function. Goal(s): To examine the glymphatic function in patients who receive regular hemodialysis and its relationship with clinical indices. Approach: Partial correlation analysis was applied to assess the relationship between ALPS index and clinical markers with age and sex as covariates. Results: Left ALPS index is positively correlated with immediate recall scores after adjusting for age and gender. Impact: Glymphatic function and hemoglobin levels are associated with memory dysfunction in hemodialysis patients, offering a potential way to improve memory function in this population.
Impaired glymphatic system function in individuals with Alzheimer's disease demonstrated by DTI-ALPS index
Authors: Mao Xiaohan , Jia Zhongzheng , Han Lu
Published: November 2024

Motivation: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the brain and leads to diffusion impairment. Goal(s): To evaluate the alterations of glymphatic function in AD and explore its association with cognition and blood biomarkers. Approach: We investigate the functionality of glymphatic system (GS) in patients with AD using diffusion tensor imaging analysis along with the perivascular space (DTI-ALPS). Results: Individuals with AD had a significantly lower ALPS index compared to the healthy controls. Moreover, the decreased ALPS index was associated with impaired cognitive function, as reflected through the Mini-Mental State Examination (MMSE) score and higher blood biomarker ptau-181 levels. Impact: The results demonstrate that the feasibility of DTI-ALPS, which can be used for research on glymphatic system function in AD patients. ALPS-index is expected to become a promising imaging marker and may provide novel targets for clinical diagnosis of AD.
MAP-MRI: a Potential Tool for Investigating Pathophysiological Mechanisms in Pediatric Basic Intermittent Exotropia
Authors: Zhao Ruijia , Shi Qing-lei , Gu Yuchen , Wang Chen , Han Yifan , Zhang Xianchang , Wan Xiang , Wang Ren-zhi , Liu Zhaohui
Published: November 2024

Motivation: To better understand the pathophysiological progression mechanism of childhood basic-type IXT and develop an accurate approach for early diagnosis. Goal(s): To find a valuable tool in reflecting the pathological changes of the visual center pathway in IXT children. Approach: A voxel-wise analysis was performed for MAPMRI-derived parameters between IXT patients and health controls, and a DTI analysis was used as reference.Results: Compared with DTI, MAPMRI-derived parameters demonstrated significant differences in more brain regions associated with visual cortex. Brain regions with microstructural changes include MOG.R, SOG.R, IOG.R, and MTG.R.Impact: We firstly explored MAPMRI’s value in detecting abnormal pathological changes of the primary and higher visual center, and the ocular movement pathway in children with basic IXT. This discovery enhances comprehension of IXT's pathology and offers insights for early diagnosis.
Nonparametric evaluation of diffusion regimes in brain tumours and associated diffusion hyperintensities
Authors: Oros-Peusquens* Ana-Maria , Louçao* Ricardo , Shah N. Jon
Published: November 2024

Motivation: To investigate tumour-associated diffusion hyperintensitiesGoal(s): Might provide some insight into tumour environment leading to restricted diffusion. Approach: Extended diffusion range, with b-values from 0 to 10000 and two echo times, allowing for NNLS decomposition of diffusion spectra and T2 mapping. Results: Restricted diffusion characterised. Impact: Possibly relevant to tumour cell migration and associated changes in the extracellular matrix.
Test-retest Repeatability of Echo Planar Imaging Diffusion-weighted MRI on a 1.5T MR-linac for Head and Neck Cancers
Authors: McDonald Brigid , El-Habashy Dina , He Renjie , Mohamed Abdallah , Mulder Sam , Ahmed Sara , Christodouleas John , Fuller Clifton
Published: November 2024

Motivation: In order to use DWI on MR-linacs to adapt head and neck cancer radiotherapy treatment plans based on response, the variability in ADC must be characterized. Goal(s): To quantify the repeatability of ADC on a 1.5T MR-linac in a large cohort (37 head and neck cancer patients). Approach: Patients were imaged with echo planar imaging-DWI twice before the start of radiotherapy. Mean ADC values of primary tumors and lymph nodes were compared across time points using repeatability metrics. Results: Repeatability coefficients were 53.0%/35.5% for tumors/nodes, indicating that this DWI sequence is insufficient for detecting clinically significant ADC changes and must be further optimized. Impact: Our DWI test-retest results demonstrate that the current widely implemented EPI-DWI sequence for head and neck cancers on 1.5T MR-linacs has substantial ADC variability across time points and needs to be further refined.
The Efficacy of Short Repetition Time DWI in Highlighting Prostate Cancer
Authors: Higaki Atsushi , Tamada Tsutomu , Ueda Yu , Kido Ayumu , Takeuchi Mitsuru , Ono Kentaro , Miyaji Yoshiyuki , Yoshida Koji , Sanai Hiroyasu , Moriya Kazunori , Yamamoto Akira
Published: November 2024

Motivation: Assessing whether short repetition time (TR) diffusion-weighted imaging (DWI) surpasses conventional long TR DWI for prostate cancer detection. Goal(s): To compare the image quality and diagnostic accuracy of short TR DWI to long TR DWI using a 3.0-Tesla MRI. Approach: Twenty-five prostate cancer patients were imaged with both short (1850 ms) and long (6000 ms) TR DWI. We analyzed signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC), with additional qualitative diagnostic assessments. Results: Short TR DWI yielded higher CNR and visual scores with stable SNR, alongside robust ADC correlations, enhancing diagnostic performance notably for non-specialist readers. Impact: Short repetition time diffusion-weighted imaging's improved prostate cancer detection could enhance diagnostic performance for non-specialist readers, influencing treatment and patient outcomes. It invites new magnetic resonance imaging research and may transform standard prostate cancer diagnostic protocols, reducing unnecessary invasive procedures.
A Non-Linear Gradient Insert for Prostate Diffusion Imaging
Authors: Elsaid Nahla , Zhang Horace , Nixon Terence , Constable R. Todd , Weinreb Jeffrey , Galiana Gigi
Published: November 2024

Motivation: A sensitive imaging method that distinguishes benign or low-grade prostate lesions from aggressive ones is one of the greatest needs in prostate cancer. Goal(s): To develop new prostate DWI technique using a non-linear gradient (NLG) to improve the diagnostic accuracy of prostate cancer. Approach: Using an NLG coil, we can circumvent the challenge of high b-value requirements by having a gradient with a high amplitude within a limited field of view, which applies to prostate imaging. Results: We demonstrate feasibility of using an NLG for prostate imaging, after validation with a polyvinylpyrrolidone (PVP) phantom and testing SE and EPI sequences with prostate ADC-mapping. Impact: To better diagnose prostate cancer with high sensitivity, we use an NLG insert coil. Using only one DWI and one non-diffusion image we showed comparable ADC maps to those produced using gold standard multi-shell linear gradient sequences.
Detecting Response of Metastatic Prostate Cancer to Chemotherapy in PDX Models using Hyperpolarized 13C MRI
Authors: Mali Ivina , Sahin Sule , Ji Xiao , Byrne Will , Nolley Rosalie , Sinha Avantika , Bok Robert , Santos Romelyn , Larson Peder , Aggarwal Rahul , Peehl Donna , Kurhanewicz John , Sriram Renuka
Published: November 2024

Motivation: Diagnosis and treatment assessment of aggressive small cell neuroendocrine prostate cancer (SCNC) is challenging due to its admixture presence in conjunction with adenocarcinoma phenotype and differential response to treatments subjective to the metastatic sites. Goal(s): This study aims to assess the therapeutic efficacy of platinum-based chemotherapy in preclinical SCNC metastatic models using patient derived xenografts. Approach: Hyperpolarized 13C MRI was used to measure the apparent rate of change in glycolysis (kPL) in PDX models of SCNC in metastatic sites. Results: kPL values clearly demonstrated a decrease upon treatment concordant to the change in tumor volume in both the liver and bone metastatic models. Impact: kPL, measured by hyperpolarized MRI, can be used to assess treatment efficacy yielding a non-invasive, potentially early biomarker readily translatable for use in patients with metastatic tumors for optimal therapeutic approaches.
Value of feature-tracking myocardial strain analysis in evaluation patients with immune checkpoint inhibitor (ICI) associated myocarditis
Authors: Zhao Kai , Liu Jia , Li Wei , Lian Jianxiu , Qiu Jianxing
Published: November 2024

Motivation: Myocarditis is a potentially fatal complication of immune checkpoint inhibitors (ICI). More diagnostic tools are needed beside enzymes. Goal(s): Data on CMR characteristics of ICI myocarditis is limited, especially the new strain analysis. Approach: The study compared the cardiac functional and stain parameters between patients with ICI associated myocarditis and controls. The parameters included LVEF, CO, CI, EDV/BSA, ESV/BSA, and SV/BSA, incidence rate of myocardial edema and LGE, LS, CS, RS (global and segmental). Results: For patients with ICI associated myocarditis, LVEF, ESV/BSA, CS (basal, mid, apical and global) and LS (mid, apical and global) may be effective parameters to identify myocardial injury. Impact: Some CMR strain parameters and cardiac function indicators significantly impaired, which may be helpful for early detection and to evaluate treatment effectiveness of ICI associated myocarditis.
Exploring the additive effects of hypertension on left cardiac structure and deformation in type 2 diabetes mellitus patients using CMR-FT
Authors: Bai Miaomiao , Zhang Chen , Lyu Jianbo , Zhao Endong , Zhang Jiahui , Qu Xiaofeng
Published: November 2024

Motivation: Hypertension and type 2 diabetes mellitus (T2DM)-related cardiac damage have a partial common pathological mechanism[1]. Goal(s): To investigate the effects of hypertension on left cardiac structure and deformation in patients with T2DM using cardiac magnetic resonance feature tracking. Approach: The balanced steady-state free precession cine sequence and commercial software, cvi42, were used for image acquisition and post-processing. Covariance and multivariate linear regression were used for statistical analysis. Results: Hypertension has additive effects on left atrial and left ventricular geometry and strain in patients with diabetes. Impact: Our findings regarding the additive effect of hypertension in patients with diabetes provides a basis for clinical management and treatment of these comorbidities.
Impact of pegloticase on cardiovascular function in young-onset Type 2 Diabetes
Authors: Park Sungho , Fujiwara Takashi , Choi Ye Ji , Rountree-Jablin Callyn , Pyle Laura , Bjornstad Petter , Barker Alex
Published: November 2024

Motivation: Increasing prevalence of youth-onset type 2 diabetes (T2D) is a global concern and characterized by a higher risk for hyperuricemia, a strong risk factor for cardiovascular disease (CVD). Goal(s): Studies have shown that serum uric acid (SUA) lowering in the general population may confer cardiovascular protection, but there have been no studies on its effectiveness in young adults with T2D. Approach: Here, we hypothesized aggressive SUA lowering using single intravenous infusion dose of the uricase, pegloticase, will attenuate cardiac magnetic resonance imaging (CMR) markers of CVD in young adults with T2D. Results: Unexpectedly, we documented impaired CMR-based global longitudinal strain after pegloticase infusion. Impact: Our study demonstrates the impacts of a drug therapy to reduce serum uric acid in youth-onset T2D and its impact on cardiovascular function using CMR. A comprehensive examination of the cardiovascular effects of the therapy is required for youth-onset T2D.
3D image-navigator based Whole-Heart Imaging at 0.55T: comparison to 1.5T
Authors: Fotaki Anastasia , Castillo-Passi Carlos , Crabb Michael , Kunze Karl , Chiribiri Amedeo , Botnar Rene , Prieto Claudia
Published: November 2024

Motivation: Low-field MRI is promising to enhance equity in medical care and accessibility for obese, claustrophobic patients and patients with implanted electronic devices. The investigation of the performance of 3D whole-heart imaging at low-field is still limited. Goal(s): To implement and evaluate a free-breathing image-navigator based framework for 3D whole-heart imaging with isotropic resolution at 0.55T. Approach: A 3D whole-heart free-breathing framework including image-based navigation, respiratory motion-correction reconstruction and patch-based denoising was implemented at 0.55T. The diagnostic performance of 3D whole-heart imaging was evaluated versus its counterpart at 1.5T. Results: 3D whole-heart imaging at 0.55T offers good image and diagnostic quality, comparable to 1.5T. Impact: This study demonstrates that high-quality 3D whole-heart imaging can be achieved at 0.55T showing comparable image and diagnostic quality to the current clinical standard in ­both healthy subjects and clinical patients, paving the pathway for affordable and accessible MRI.
Imaging the 3D Structure of Sinoatrial Node Using Rotating Frame Relaxation Maps in the Swine Heart
Authors: Li Yi , Casula Victor , Liimatainen Timo
Published: November 2024

Motivation: Rotating frame relaxation mapping can detect fibrotic tissue and may offer contrast agent-free method for imaging the sinoatrial node (SAN). Goal(s): To identify SAN from the surrounding myocardium using RAFF2 and T1ρ maps. Approach: RAFF2, T1ρ, T1 and T2 maps, and MT imaging were performed on ex vivo swine hearths at 7T and 3T. SAN location was validated with Masson’s trichrome histology sections. Results: Relaxation time differences between SAN and myocardium were found in all imaging methods. TRAFF2 and T1ρ demonstrated higher contrast than other methods. SAN can be distinguished as area with elevated relaxation times in TRAFF2 maps. Impact: Detection and visualization of 3D SAN structure can be done using RAFF2 and T1ρ relaxation time maps without contrast agents.
Assessment of early anthracycline-induced cardiotoxicity and liver injury with T2 and T2* mapping in rabbit models
Authors: Feng Xiaolan , Qi Wanyin , Xiao Zhengyuan , Zheng Xue , Zhang Xiaoyong , Chen Jing
Published: November 2024

Motivation: Chemotherapy-related cardiotoxicity has garnered more attention, an early assessment of cardiac injury to delay or prevent the occurrence and development of irreversible cardiac injury is vitally important. Goal(s): T2 mapping and T2* mapping are expected to be used for evaluating early anthracycline-induced cardiotoxicity (AIC) and anthracycline-induced liver injury (AILI). Approach: We established a rabbit model of anthracycline-induced cardiotoxicity and dynamically observed the occurrence and progression of AIC and AILI using T2 and T2* mapping. Results: Preliminary results show T2 and T2* mapping showed value one-stop assessment of AIC and AILI. Impact: Anthracycline-induced cardiotoxicity could be detected by T2 mapping as earlier as the second week, mainly focusing on the 7th, 11th and 12th segments of left ventricle. Combined with T2* mapping, hepatoxicity and supplementary cardiotoxicity were assessed by one-stop scan.
Feasibility of Knee MR Fingerprinting at 0.55T and comparison with 3.0T MAPSS: Hip-OA cohort with probable early knee cartilage-loss
Authors: Bhattacharjee Rupsa , Cao Xiaozhi , Liao Congyu , Zhu Zheren , Li Zhitao , Majumdar Sharmila , Setsompop Kawin , Yang Yang
Published: November 2024

Motivation: Low-cost 0.55T-scanners pose an excellent opportunity to formulate efficient, fast, and quantitative T2 mapping methods that could enhance the reach of early OA-diagnosis. Goal(s): To analyze the feasibility of a novel, fast, and high-resolution MRF-scanning technique to quantify knee cartilage-T2 overcoming the low SNR and inefficient gradient systems at 0.55T and compare against the MAPSS approach at 3.0T. Approach: A suite of techniques was leveraged for MRF, including an optimized-sampling-trajectory, subspace-reconstruction, locally-low-rank-constraint, gradient-waveform-correction, Cramer-Rao-Lower-Bound (CRLB)-optimization for flip-angle-patterns, motion-correction, and deep-learning-based-denoising. Results: The average T2 increase at 0.55T compared to 3.0T provides a wider range for the depiction of granular regions of elevated cartilage-T2 Impact: In this study, advanced techniques including CRLB-optimization, gradient trajectory correction, subspace reconstruction, attention-based denoising, and motion correction were included to demonstrate the feasibility and benefits of a faster, higher-resolution Knee MRF acquisition on a cost-effective 0.55T scanner compare with 3.0T MAPSS.
MR Fingerprinting-based myelin water fraction: stability, spatial consistency and sensitivity to alterations in pediatric leukodystrophies
Authors: Lancione Marta , Cencini Matteo , Scaffei Elena , Cipriano Emilio , Buonincontri Guido , Schulte Rolf , Pirkl Carolin , Buchignani Bianca , Pasquariello Rosa , Canapicchi Raffaello , Battini Roberta , Biagi Laura , Tosetti Michela
Published: November 2024

Motivation: Multicomponent Magnetic Resonance Fingerprinting (MRF) provides Myelin Water Fraction (MWF) maps in clinically-compatible scan time. However, it still requires validation and assessment of sensitivity and robustness. Goal(s): We aimed to assess MWF stability to model parameters variations, its spatial consistency in healthy children, and sensitivity to alterations in leukodystrophies. Approach: Two-pool relaxation times and exchange were varied in a 10% range. MWF profiles were computed in main WM tracts. MWF sensitivity to alterations was compared to FA, R1, and R2. Results: Model parameters changes led to minimal MWF variations. MWF revealed consistent spatial patterns in controls and showed the highest sensitivity to pathology. Impact: MRF provides robust and sensitive measurements of MWF. As it also allows the simultaneous acquisition of high-resolution R1 and R2 maps in a short scan time, it may represent a clinically-applicable metric to assess and monitor WM disorders.
Evaluating 0.55T FISP MRF using EPG-X Formalism
Authors: Zhu Zhibo , Nayak Krishna
Published: November 2024

Motivation: MT effects influence MRF T1 and T2 quantifications and are stronger at lower field strength. Goal(s): To evaluate the impact of EPGx dictionary generation on relaxometry performance for 0.55T FISP MRF. Approach: We applied the EPG-X formalism with a two-pool model which incorporates MT parameters for dictionary simulation for 0.55T FISP MRF and covered a range of realistic MT parameters values. We applied the approach on 4 healthy subjects. Results: Use of EPGx reduced T2 bias (compared to single-echo spin echo) by 25% at a cost of 80% worse precision. Impact: Simulating dictionary using the EPG-X formalism with a two-pool model can partially mitigate MT effects and may reduce T2 bias.
Motion-robust Three-dimensional Magnetic Resonance Fingerprinting (MR-3DMRF) for Quantitative Abdominal Imaging
Authors: Liu Chenyang , Wang Lu , Cao Peng , Li Tian , Cai Jing
Published: November 2024

Motivation: Current abdominal magnetic resonance fingerprinting (MRF) techniques require breath-hold acquisition to avoid motion artifacts, which is difficult for patients with breathing difficulties. Goal(s): This study aims to develop a motion-robust three-dimensional MRF (MR-3DMRF) technique for abdominal patients and evaluate the repeatability of tissue property quantification. Approach: MR-3DMRF incorporates a non-smooth motion modeling method and a dynamic weighting strategy to allow free-breathing MRF acquisition and motion-resolved reconstruction. Results: Full-width half-maximum of organ boundaries in MR-3DMRF-derived tissue maps is 3.1mm±1.8mm, significantly lower than motion-blurred tissue maps (10.1mm±4.3mm). The linearity of test-retest MRF measurement for T1, T2, and PD was 0.982, 0.894, 0.925, respectively. Impact: This study, for the first time, investigates the feasibility of free-breathing MRF acquisition and motion-resolved MRF reconstruction on abdominal patients. The MR-3DMRF-derived tissue map are highly repeatable and accurate, potentially contribute to abdominal disease diagnosis and treatment assessment.
Spinor-EPG: an improved EPG algorithm for fast simulation of the non-ideal slice-profile effect in MRF
Authors: Li Zhongsen , Zou Jing , Liu Chuyu , Li Rui
Published: November 2024

Motivation: Non-ideal RF slice-profile can affect the accuracy of MRF. However, correcting this effect in dictionary simulation is time-consuming. Goal(s): To propose an improved simulation algorithm which can correct the RF slice-profile effect in MRF simulation accurately and efficiently. Approach: We propose an improved MRF simulation method which combines the spinor rotation representation and the extended-phase-graph(EPG) algorithm. The proposed method is validated by retrospective experiments on brain T1 and T2 maps, compared with the EPG algorithm. Results: The proposed method can correct the non-ideal slice profile effect in MRF dictionary simulation with much faster computational speed. Impact: We propose an improved simulation algorithm for MRF simulation, which is able to correct non-ideal slice-profile and is as efficient as the EPG algorithm. The proposed method may be helpful for all kinds of MRF imaging applications.
Partial Diffusion-weighted MR Fingerprinting for the simultaneous quantification of relaxation time and diffusion coefficient
Authors: Wang Yiang , Lee Elaine , Cao Peng
Published: November 2024

Motivation: Subspace reconstruction has the potential to generate high-resolution images from highly undersampled data at each time point. Goal(s): To develop an MRF-based approach to simultaneously measure relaxation time and diffusion coefficient. Approach: This sequence was composed of two parts: conventional MRF and DW-SSFP. The central k-space was fully sampled, and the peripheral k-space was under sampled with 24 interleaves, using a dual density spiral trajectory. The subspace reconstruction was applied using the temporal basis obtained from central k-space data. Results: T1, T2, PD, and ADC can be accurately quantified for both phantom and in-vivo scans. Impact: This work indicate that full-resolution DWI can be reconstructed at each time point for a multi-shot multi-dynamic sequence using the subspace reconstruction. Our proposed sequence can be used to estimate relaxation time, proton density and diffusion coefficient simultaneously.
Improved 3D Prostate MR Fingerprinting with Cross-Domain Spatio-Temporal Reconstruction Network
Authors: Kim Jae-Yoon , Lee Jae-Hun , Han Dongyeob , Choi Moon Hyung , Kim Dong-Hyun
Published: November 2024

Motivation: 3D Magnetic Resonance Fingerprinting is time-consuming, requiring full-time measurements. Shortening scan time while maintaining data quality enhances MRF's clinical utility. Goal(s): Our goal was to develop reconstruction process for prostate MRF based on the neural network. This approach aims to improve image quality and parameter map accuracy. Approach: We introduced the neural network composed of a combination of CNN and ANN and utilized compressed dictionary, enabling efficient cross-domain utilization of information. Results: Our approach enhances quality and accuracy of generated parameter maps, demonstrating the potential to expedite MRF scans for prostate imaging. Impact: Our proposed scheme for accelerated MRF reconstruction can improve quantitative imaging, thus providing faster and more accurate prostate diagnosis and treatment. This development has positive impacts on patient care, reduces scanning times, and promotes additional research in medical image reconstruction.
Creation of Voxelwise 2D Lookup Tables (LUTs) for MRF-based Synthesis of Qualitative Images
Authors: Dupuis Andrew , Chen Yong , Griswold Mark , Boyacioglu Rasim
Published: November 2024

Motivation: Address the challenge of integrating MRF data into existing MRI analysis via synthetic images without introducing spatial artifacts or hallucinations possible with CNNs. Goal(s): Generate static lookup tables (LUTs) mapping from T1/T2 value space directly to grayscale visualizations matching clinical contrasts. Approach: A simple pixel-wise regression network was trained on a public dataset of MRF data and weighted images. Static LUTs were generated from dictionaries of T1/T2 combinations, then applied to MRF-derived maps for visualization and processing via FSL. Results: Successful generation of synthetic contrast LUTs ensures reproducibility and allows instantaneous visualization or registration of MRF maps in a more conventional grayscale format. Impact: Integration of MRF into traditional analysis pipelines suffers because quantitative maps have inherently different contrasts from weighted images. LUTs for instant, deterministic generation of weighted contrasts from T1/T2 maps allow for direct use of tools like FSL with MRF data.
Temporal Low-Rank based k-space Sampling Pattern Optimization for MR Fingerprinting
Authors: Horger Felix , McElroy Sarah , Hajnal Joseph , Malik Shaihan
Published: November 2024

Motivation: MRF can estimate tissue parameters with high efficiency, requiring optimization of sequence parameters alongside k-space sampling patterns. A comprehensive optimization framework was not established yet. Goal(s): Develop a framework for optimizing k-space sampling and understanding reconstruction errors for MRF using temporal low-rank reconstruction. Approach: We quantify MRF performance with the condition number of temporal low-rank system matrices and show suitability in simulation and phantom experiments. Results: We derive optimality-criteria for schedule and sampling, and provide an algorithm for sampling optimization. We demonstrate that systematic deviations from the signal model are a major source of errors in MRF, and address these with center-weighted sampling. Impact: Our results are relevant for researchers interested in the fundamental understanding of MR Fingerprinting. Our theory helps designing MRF sequences, guiding future aspirations to jointly optimize sampling and flip-angle schedule, and identifying significant sources of errors in existing implementations.
Mitigating MR fingerprinting undersampling errors is more effective through sequence optimization than via low rank reconstruction
Authors: Nagtegaal Martijn , Vos Frans , van Osch Matthias , Heesterbeek David
Published: November 2024

Motivation: To reduce undersampling errors in MR Fingerprinting maps, both sequence optimization and low rank (LR) reconstruction methods have been proposed , but these have not been compared or combined. Goal(s): To compare the effectiveness of LR-reconstruction and sequence optimization for reducing undersampling errors. Approach: Undersampled 2D spiral MRF data as acquired with 7 different flip angle patterns in 6 healthy subjects are reconstructed with the standard vendor reconstruction and an in-house LR-reconstruction and compared to fully-sampled MRF T1- and T2-maps. Results: Undersampling-optimized sequences showed a reduced error compared to other sequences, even after LR-reconstruction. Impact: We show that optimized flip-angle patterns with or without LR-reconstruction outperform traditional schemes with LR reconstruction. Inclusion of LR-reconstruction in the optimization step is not essential, when designing sequences that minimize undersampling artifacts.
Fractality and Lacunarity of Tumor subcomponents is a Measure of Overall Survival: A novel approach to decipher Tumor Geometry and Survival
Authors: Mohanty Ankit , Yadav Neha , Tiwari Vivek
Published: November 2024

Motivation: Gliomas of similar histologic grade show a lot of difference in the growth and development. And the survival of patients with similar histologic grades also vary. Goal(s): The shape variations of gliomas impact survival or not. Approach: We calculated the fractal dimension and lacunarity of the subcomponents of gliomas and analyzed them along with survival data to obtain differences in overall survival. Results: Variations in fractal Dimension and Lacunarity also present variations in overall survival. Subjects with higher enhancing fractal dimension had shortened survival and it was opposite for nonenhancing fractal dimension and enhancing lacunarity. Survival did not depend on edema subcomponent. Impact: The study's results could revolutionize glioma patient care. Clinicians may integrate fractal dimension and lacunarity as prognostic markers for tailored treatment decisions. Scientists may explore their use in combination with genetic factors for accurate survival predictions and improving patient outcomes.
Reevaluating the Role of T2/FLAIR Mismatch Sign: Improving Diagnostic Accuracy With Qualitative MRI Features?
Authors: Willms Klara , von Reppert Marc , Lost Jan , Tillmanns Niklas , Merkaj Sara , Huttner Anita , Schrickel Elisabeth , Memon Fatima , Aboian Mariam
Published: November 2024

Motivation: There is a critical need for improved diagnostic precision in distinguishing between IDH-mutant, 1p/19q non-codeleted astrocytomas and 1p/19q co-deleted oligodendrogliomas. While the T2/FLAIR-mismatch sign is specific for IDH-mutant astrocytomas, its limited sensitivity calls for enhanced diagnostic methods in glioma cohorts. Goal(s): To evaluate the role of T2/FLAIR-mismatch in combination with qualitative VASARI features to classify IDH-mutant glioma. Approach: We analyzed VASARI features and the presence of T2/FLAIR-mismatch in 179 IDH-mutant gliomas and determined the predictive accuracy of these features. Results: Findings indicate the limitations of the T2/FLAIR-mismatch sign for accurate preoperative diagnosis, emphasizing the need for refined noninvasive methods to enhance diagnostic accuracy. Impact: This research underscores the critical need for improved diagnostic tools in distinguishing glioma subtypes, as the T2/FLAIR-mismatch sign exhibits limitations, risking misclassification. Addressing these challenges is essential for accurate patient management and treatment planning in the context of IDH-mutant gliomas.