bluuebunny/crossref_metadata_2025 huggingface dataset:
T1mapping and MPRAGE for the characterisation of heterogeneous paramagnetic rim lesions and their clinical importance in MS
Authors: Stölting Anna , Bulcke Colin Vanden , Borrelli Serena , Bugli Céline , van Pesch Vincent , Maggi Pietro
Published: November 2024

Motivation: Differentiation of Paramagnetic Rim Lesions, based on T1 values, could allow clinical stratification of patients. Goal(s): To investigate PRL heterogeneity with quantitative T1 and normalised MPRAGE and the resulting impact on clinical outcomes. Approach: White Matter lesions were segmented and categorised based on visual confidence of paramagnetic rim visibility and their T1 values. RF analyses was used to reveal impact of lesion types on clinical disability. Results: Visibility of Rim+ lesions is correlated with increased T1 values. In a Random Forest Model, T1-derived long-T1 Rim+ lesions and number of short-T1 Rim+ lesions could predict clinical disability and clinical progression in next 12 months. Impact: Characterisation of PRL heterogeneity, not only with advanced-quantitative imaging techniques but also with clinically available sequences, allows a better understanding of a patient's current clinical disability and progression over the next twelve months.
Evaluation of Normalization Methods for apparent Myelin Water Fraction Measurements at Ultra High Field
Authors: Huang Xuemei , Nemani Ajay , Sakaie Ken , Oh Sehong , Lowe Mark
Published: November 2024

Motivation: Multiple sclerosis (MS) is characterized by demyelination of the central nervous system. Ultra High Field (UHF) MRI can reveal CNS pathology that is not apparent on conventional MRI in MS patients, but options for measuring myelin density are limited. Goal(s): Calculation of MWF using ViSTa map requires intensity normalization. We evaluate normalization approaches for visualization of short transverse relaxation time component (ViSTa), a semiquantitative measure of apparent myelin water fraction (aMWF). Approach: We compare two types of normalization scan - a turboflash (TFL) and a gradient recalled echo (GRE) on MS patients. Results: We find that normalization with GRE provides better conspicuity of lesions. Impact: Characterization of myelin density has the potential to supplement UHF approaches to evaluating MS.
Linear Regression Modeling of BOLD Response to task activation reflects neurovascular uncoupling in MS
Authors: Shin Wanyong , Balu Krishnan , Nemani Ajay , Ontaneda Daniel , Lowe Mark
Published: November 2024

Motivation: To understand the different BOLD activation pattern in multiple sclerosis patientsGoal(s): To Investigate the neuro-vascular uncoupling of MS patients to be compared with healthy controlsApproach: During the visual task and hypercapnia challenge, BOLD and CBF are measured simultaneously with EEG in patients of MS (n=11) and health controls (n=15). Results: We find that, for healthy controls, only models that included neuronal activity, i.e. EEG power change during task performance, were significantly predictive of BOLD responseImpact: We investigate BOLD activation of MS patients and compare with controls using EEG simultaneously during a visual task and hypercapnia challenge. We find that the BOLD response in MS does not directly depend on the degree of underlying neuronal activity.
Automatic Identification of Potential Cellular MRS Metabolites
Authors: Zhang Ella , Chen Jiashang , Rao Angela , Zhou Jonathan , Zhang Evan , Weissman Andrew , Kobus Zuzanna , Kobus Marta , Su Li , Christiani David , Cheng Leo
Published: November 2024

Motivation: Manual identification of potential metabolites from untargeted MRS-based metabolomics studies is often tedious, labor-intensive, and prone to error. Goal(s): To develop an automated and customizable program to systematically identify metabolites from spectral regions of interest (ROIs) based on databases, such as Human Metabolome Database (HMDB) for specific medical conditions. Approach: We integrated experimental data — including ROIs, statistical significance, group trends/comparisons, and tissue- and disease-specific information — with automated HMDB searching, to output relevant and significant potential metabolites. Results: Given spectral ROIs, and relevant significance and trend data, our program is capable of identifying possible disease- and tissue-specific metabolites. Impact: Our program automates the manual database-searching process required for metabolite identification in MRS-based metabolomics research, enabling fast, robust, and reliable identification and categorization of metabolites based on user-customizable factors such as significance, trend, and tissue- and disease-specificity.
On the impact of eddy-current-induced biases in ΔB0 maps on shimming outcomes
Authors: Bulut Busra , Foudali Ismail , D’Astous Alexandre , Alonso-Ortiz Eva
Published: November 2024

Motivation: Eddy-currents can bias magnetic field (∆B0) maps. Goal(s): To assess the impact of eddy-current-biased ∆B0 maps on B0 shimming and T2* measurements. Approach: Measure the shimmed ∆B0 field after having used a ∆B0 map that is thought to be affected by eddy currents vs. one that is obtained using the gradient-reversal technique for canceling eddy-currents. Measure T2* values after using both shimming conditions. Results: Eddy-currents arising from spatial-encoding gradients have a measurable impact on shim quality and can reduce T2* values in the brain by up to 10 ms. Impact: Scientists and clinicians interested in measuring T2* in areas that are affected by strong magnetic field inhomogeneities may want to consider that eddy-current-induced biases in ∆B0 maps could lead to reduced T2* in those regions.
Deep Learning Framework for Quantifying High-Resolution MRSI Data of the Human Brain at 7T
Authors: Shamaei Amirmohammad , Niess Eva , Hingerl Lukas , Strasser Bernhard , Bogner Wolfgang , Motyka Stanislav
Published: November 2024

Motivation: Addressing challenges in ultra-short TE MRSI data quantification of the Human Brain at 7T utilizing deep learningGoal(s): Develop a Variational Physics-Informed Autoencoder (VPIAE) to enhance MRSI metabolite quantification, ensuring faster, robust, and efficient metabolite mapping with uncertainty estimates. Approach: Combine a variational autoencoder with a physics-informed decoder, training on 7T MRSI brain data, and benchmark against a traditional method (LCModel)Results: VPIAE outperforms conventional MRSI methods in speed by 6 orders of magnitude, offers comparable accuracy, and provides uncertainty estimates for reliable interpretation, promising advancements in clinical and research applications. Impact: VPIAE enables swift MRSI analysis, crucial for clinicians diagnosing neurological conditions and researchers studying metabolic brain changes. It opens avenues for exploring brain metabolite dynamics with greater fidelity and advancing the field's understanding of brain metabolism.
Quantification of in vivo magnetic resonance spectroscopy data with pyAMARES, an open-source python library for flexible and robust MRS fitting
Authors: Xu Jia , Schulte Rolf , Yang Baolian , Magnotta Vincent
Published: November 2024

Motivation: As a mainstream time-domain fitting algorithm for quantifying MRS data, to date, AMARES has been confined to Java and MATLAB, while the dominant language for deep learning, Python, does not yet have an AMARES implementation. Goal(s): To develop pyAMARES, a python package implementing the AMARES, providing the MRS community with flexible and robust MRS data fitting capabilities. Approach: PyAMARES imports prior knowledge from spreadsheets as initial values and constraints for fitting MRS data according to the AMARES model function. Results: PyAMARES effectively fits in vivo MRS data with varied algorithms, proving its versatility as a versatile fitting tool. Impact: PyAMARES provides accessible, flexible, and robust time-domain MRS fitting in Python, bridging the gap between advanced data analysis and deep learning by Python and the AMARES algorithm, previously limited to Java and MATLAB implementations.
A Linear Model approach for treating partial volumes in quantitative 1H MRS of cortical grey matter – application to an osteoarthritis pain study
Authors: Howe Franklyn , Law Amber , Sofat Nidhi
Published: November 2024

Motivation: The accuracy of absolute quantitation of metabolites by 1H MRS in grey-matter is compromised in the presence of partial volumes of CSFGoal(s): To develop a linear model of metabolite concentration estimates as a function of partial volumesApproach: The effects of varying tissue fractions and relaxation times on metabolite concentrations were modelled to investigate how they affected the variability in metabolite concentration estimatesResults: A general linear model with parameters relating to tissue partial volume as covariates enables statistical comparisons of absolute metabolite levels between patient sub-groups without a priori knowledge of tissue relaxation times. Impact: A General Linear Model statistical approach enables robust comparison of cortical grey matter metabolite concentrations between patient groups, and minimises the propagation of errors that occurs when the tissue partial volume properties are inaccurately estimated.
Comparing Myocardial Strain in Healthy Individuals of Different Ages: An Assessment of Two Vendor Software Tools
Authors: Zhao Ye tong , Liu Ying , Mu Xiao lin , Song Yang , Zhu Jing , Wang Wen jia
Published: November 2024

Motivation: There is no uniform standard for the value of myocardial strain of different software vendors. Goal(s): The study utilizes cardiac magnetic resonance feature tracking technique to assess the differences in myocardial strain parameters among healthy individuals of different age groups while employing two distinct vendor software tools. Approach: The study utilizes cardiac magnetic resonance feature tracking technique to assess myocardial strain parameters while employing two distinct vendor software tools. Results: The findings indicate variations in strain parameters across healthy individuals of varing age groups based on measurements obtained from CVI42 and Medis. Significant disparities in certain parameters are observed between the two suppliers. Impact: The normal reference values of myocardial strain from different suppliers can not be unified, and large samples and multi-center studies are needed in the future.
Quality Assurance of Diffusion and Fat Imaging using System Phantoms: Reproducibility for Multivendor Neuromuscular Studies
Authors: Wang Ping , Frazier Noah , Dortch Richard
Published: November 2024

Motivation: Our multi-site studies require quality assurance for diffusion and proton density fat fraction (PDFF) imaging across vendors. Goal(s): To establish DWI and PDFF protocols and analysis tools to evaluate reproducibility and reliability. Approach: DWI and PDFF protocols were conducted on two 3T MRI systems (Philips and GE) on a diffusion phantom and a PDFF phantom. The measured ADC and PDFF values were compared across the scanners and also compared with the phantom reference values. Correlation coefficient and root-mean-square error (RMSE) were reported. Results: High reproducibility and high accuracy were achieved across the MRI vendors as indicated by the correlation coefficients and RMSE. Impact: Our results showed that quality assurance can be well maintained between the two MRI scanners, both DWI and PDFF measured on the two scanners at our institute are reliable and accurate, this has important implications for our future multi-site studies.
Assessing Image Quality Metric Alignment with Radiological Evaluation in Datasets with and without Motion Artifacts
Authors: Marchetto Elisa , Eichhorn Hannah , Gallichan Daniel , Schwarz Stefan , Shekhrajka Nitesh , Ganz Melanie
Published: November 2024

Motivation: A quantitative evaluation of image quality is crucial in various aspects of MRI, such as developing and validating new image reconstruction and artifact correction techniques. Currently, no image quality metric covers all possible artifacts, making it difficult to choose the right quality measure. Goal(s): Evaluate consistency and reliability of image quality metrics in relation to image pre-processing and radiologists assessment. Approach: We studied the correlation of ten commonly used quality metrics with radiological evaluations in datasets with and without motion. Results: SSIM and PSNR had the strongest correlation with observer scores. Among reference-free metrics, Image Entropy and AES consistently showed strong correlations. Impact: Automatically evaluating the quality of MR images is crucial. Our results show variability in the correlation between image-quality metrics and radiologists scores across datasets, highlighting the need for preprocessing optimization especially when no reference image is available.
“Crafting” the olfactory atlas with brain regions and axonal bundles: application to COVID-19 subjects with anosmia
Authors: Gaviraghi Marta , Lupi Eleonora , Grosso Elena , Monteverdi Anita , Battiston Marco , Grussu Francesco , Kanber Baris , Carrasco Ferran Prados , Samson Rebecca S. , Makaronidis Janine , Yiannakas Marios C , D'Angelo Egido , Palesi Fulvia , Wheeler-Kingshott Claudia Gandini
Published: November 2024

Motivation: Several pathologies, including COVID-19, affect the sense of smell, causing anosmia. Goal(s): The goal is to create an atlas that includes grey matter regions and white matter tracts involved in the olfactory circuit. Approach: Grey matter regions involved in the olfactory circuit were selected and an atlas of tracts connecting pairs of regions was extracted using tractography. The atlas was used on subjects with anosmia caused by COVID-19 to investigate changes in grey matter density (voxel-based analysis) and quantitative microstructural maps (mean diffusivity and fractional anisotropy). Results: Structural alterations were found in subjects with anosmia, mainly in the cerebellum. Impact: The created olfactory circuit atlas, which includes grey matter regions and axonal bundles, can be crucial for studying pathologies involving alterations in the olfactory circuit. The atlas was useful to detect structural alterations in subjects with anosmia caused by COVID-19.
Automatic Quantitative 3D Aneurysm Wall Enhancement Mapping Based on Magnetic Resonance Imaging: a pilot study
Authors: Wei Haining , Fu Mingzhu , Wei Hanyu , Li Zhongsen , Li Rui
Published: November 2024

Motivation: Aneurysm wall enhancement visualized on high-resolution magnetic resonance imaging is considered as an indicator of inflammation. Goal(s): Recently, there has been increased attention on 3D AWE mapping, which is seen as an objective tool for examining rupture risk of aneurysms.However, the roughly estimated vessel wall location and thickness result in some measurement errors. Approach: In this study, we propose a fast measurement method that can automatically access wall thickness and generate the 3D spatial distribution of wall enhancement ratio. Results: The automatic method simplifies and accelerates the workflow of aneurysm wall identification and analysis. Impact: We propose a fast measurement method that can automatically access wall thickness and generate the 3D spatial distribution of wall enhancement ratio. The automatic method simplifies and accelerates the workflow of aneurysm wall identification and analysis.
VISTA: Visualization of Image Segmentation by Transformation and Analysis
Authors: Evans James , Davey Connor , Anderson Aaron , Bramlet Matthew , Sutton Bradley
Published: November 2024

Motivation: Complex medical procedures often require clinicians to construct a (3D) three-dimensional mental model of a patient's anatomy from 2D medical imaging data. Goal(s): Our goal was to develop a set of tools which convert 2D imaging data into 3D objects to view in virtual reality (VR). Approach: Two pipelines were created, one for brain imaging data and another for label mask images, which automatically segment the images, convert them to objects, and merge them into a VR viewable model. Results: Our software has been successfully used to transform a variety of medical imaging data into 3D files which are viewable on VR platforms. Impact: Some of the challenges with mentally visualizing two-dimensional medical imaging data should be alleviated by using our software to automatically make the data viewable in a three-dimensional format.
A Novel Method to Estimate 23Na Triple Quantum (TQ) Signal: Spin Echo Sequence, Impact of Noise and Proof-of-Concept Imaging
Authors: Reichert Simon , Kleimaier Dennis , Zehender Dominik , Zöllner Frank , Schad Lothar
Published: November 2024

Motivation: Sodium TQ-signal is potential viable biomarker for cell viability. However, TQ acquisition requires phase-cycling sequences with long scan times, which currently hinder clinical application. Goal(s): We present a novel method to estimate the TQ-signal directly from the FID without phase-cycling. Approach: Compare the our method's TQ-signal with the TQTPPI sequence and theoretical prediction. Investigate the impact of noisy data on our method and provide a proof-of-concept imaging sequence. Results: The TQ-signal of our method was in close agreement with the TQTPPI TQ-signal and the theoretical prediction. Even for low SNR, our method performed well. Proof-of-concept imaging with our method was successfully demonstrated. Impact: With our method scan time of sodium TQ imaging can be dramatically reduced. This approach may expand TQ imaging applications and thus may leverage the full potential of sodium TQ signal.
Hyperpolarized 13C 3D MRSI using Radial Multi-echo bSSFP and k-Space-based IDEAL
Authors: Wang Zirun , Grashei Martin , Fischer Johannes , Sühnel Sandra , Setzer Nadine , Awenius Marcel , Korzowski Andreas , Zaitsev Maxim , Bock Michael , Schilling Franz , Schmidt Andreas , Müller Christoph
Published: November 2024

Motivation: 3D Metabolic imaging of hyperpolarized (HP) 13C agents demands specialized signal excitation and acquisition strategies. Goal(s): This study introduces the combination of multi-echo bSSFP and radial readout with a spiral phyllotaxis pattern to rapidly image 13C-labeled contrast agents. Approach: We implemented the novel sequence in a rodent in vivo experiment using HP [1-13C]pyruvate. Results: Employing iterative signal decomposition and radial data reconstruction, we successfully captured the global signal dynamics with an unprecedented temporal resolution of 16 ms. Besides, we generated concentration maps for pyruvate, lactate, alanine, and calculated area-under-the-curve (AUC) metabolite ratio maps for Lac/Pyr and Ala/Pyr. Impact: Hyperpolarized 13C 3D metabolic MRI is challenging due to the short-living magnetization. With 3D spiral phyllotaxis radial multi-echo bSSFP MRI and post-scan metabolite separation, large areas of interest can be acquired and reconstructed into signal time-curves and 3D metabolite maps.
Boosting SNR for sodium bSSFP imaging
Authors: Brnawi Haneefah , Balaji Krithika , Kukran Simran , Connor Steve , Hajnal Joseph , Bangerter Neal , Lally Peter
Published: November 2024

Motivation: Sodium MRI (23Na-MRI) holds significant potential, but its clinical use is still limited due to challenges arising from low signal-to-noise ratio (SNR). Balanced steady-state free precession (bSSFP) sequences are particularly suited for 23Na-MRI, being highly SNR efficient, but there are opportunities to extract more signal components. Goal(s): We aim to improve SNR in sodium bSSFP acquisitions and produce additional tissue contrasts. Approach: We propose a strategy to extract additional information from a series of phase-cycled bSSFP images using different linear combinations. Results: Three different signal components were extracted from phase-cycled bSSFP data and combined. Results showed an SNR boost in fluid. Impact: This offers a simple way to improve the SNR in sodium MRI images, with potential applications being pathologies that alter biofluid sodium concentrations.
Advancement of a novel 31P MRS-based approach for the in vivo determination of pH and magnesium ion content
Authors: Seng Bela , Franke Vanessa L. , Platek Justyna , Bangert Renate , Ladd Mark E. , Bachert Peter , Korzowski Andreas
Published: November 2024

Motivation: The reliability of conventional 31P MRS-based methods for the determination of pH and magnesium ion content (Mg) is hampered when applied to pathologies due to their calibration for physiological conditions. Goal(s): The aim of this study was the advancement of a novel approach for pH and Mg mapping to improve its reliability for application in vivo. Approach: This advancement was performed by incorporating an additional input parameter into the approach and tested on in vivo 31P MRSI brain datasets. Results: Compared to the original algorithm, the advanced version resulted in robust mapping of pH and Mg yielding homogeneous brain maps for healthy volunteers. Impact: The advancement of a novel approach for the in vivo determination of pH and magnesium ion content under different chemical conditions improves its reliability and can now potentially be used for the investigation of pathologies such as cancer.
Enabling SENSE Accelerated 2D CSI For Hyperpolarized Carbon-13 Imaging
Authors: Shinozaki Ayaka , Hansen Esben , Sanchez-Heredia Juan , Schulte Rolf , Dang Duy Anh , Andersen Markus , Laustsen Christoffer , Tyler Damian , Grist James
Published: November 2024

Motivation: For hyperpolarized 13C metabolic imaging studies, a challenge is to achieve high temporal resolution without decreasing spatial and/or spectral resolution. Goal(s): To accelerate hyperpolarized 13C MRI by combining a 2D Chemical Shift Imaging (CSI) sequence with SENSitivity Encoding (SENSE) reconstruction. Approach: Due to the low natural abundance of 13C, the sensitivity maps needed for SENSE reconstruction cannot be pre-acquired. As such, in this work, the novel approach of using sodium sensitivity maps was demonstrated. Results: SENSE reconstruction corrected aliased images, where in-vivo metabolic information was acquired with a 4-fold temporal acceleration. Impact: As hyperpolarized 13C metabolic imaging is clinically translated, there is a need for easy-to-implement, fast, and robust imaging techniques. Therefore, this study implemented a novel 13C technique to accelerate Chemical Shift Imaging: a ubiquitous and robust sequence.
Development and optimization of deuterium metabolic imaging in the human abdomen at 3T
Authors: McLean Mary , Horvat-Menih Ines , Wodtke Pascal , Kaggie Joshua , Grimmer Ashley , Latimer Elizabeth , Wylot Marta , Zamora-Morales Maria , Birchall Jonathan , Khan Alixander , Wang Huanjun , Armitage James , Mitchell Thomas , Stewart Grant , Gallagher Ferdia
Published: November 2024

Motivation: Abdominal imaging of orally-administered deuterium-labelled tracers can be hindered by artifacts arising from excessive stomach signal. Goal(s): To establish and optimize methods for acquisition of abdominal deuterium metabolic imaging in conjunction with orally-administered tracers. Approach: A flexible transmit-receive surface coil was used to image naturally abundant deuterium in healthy volunteers and orally-administered D2O in a patient with renal cancer. Results: Water and lipid peaks were repeatably fit with high confidence both in unlocalised spectra and voxels extracted from MRSI in the liver, kidney, and spleen. Artifacts were minimal even 12 minutes after tracer ingestion. Impact: Feasibility of abdominal deuterium imaging at 3T was demonstrated using a flexible surface coil. We obtained consistent water measurements in healthy volunteers and good images in a patient with a left-sided renal tumour even just 12 min after drinking D2O.
Towards cardiac DMI at clinical field strengths
Authors: Xiang Jie , de Graaf Robin , De Feyter Henk , Thomas Monique , Baldassarre Lauren , Kwan Jennifer , Coman Daniel , Herman Peter , Peters Dana
Published: November 2024

Motivation: Deuterium metabolic imaging (DMI) might permit mapping of cardiac metabolism by MRI. Goal(s): To port DMI tools developed at 11.7T for mice to 3T, and develop methods for cardiac DMI. Approach: Simulations, phantoms, and in vivo studies were conducted to measure SNR at 3T, develop an optimized protocol, and account for B0 inhomogeneity. Results: At 11.7T, cardiac DMI was tested in a control mouse. At 3T, phantom studies showed that multi-echo bSSFP methods yield increased SNR vs. GRE. B0-mapping helps in isolating the metabolites in phantoms. Impact: Development of DMI tools for use in cardiac DMI at clinical field strengths.
Evaluation of Anatomical Guided Reconstruction for Improving the Spatial Resolution of Deuterium Metabolic Imaging
Authors: Rojas Ernesto , Adamson Philip , Boada Fernando , Schramm Georg , Spielman Daniel
Published: November 2024

Motivation: The inherently low SNR of DMI hinders clinical viability at 3T. Goal(s): We evaluate an anatomically guided reconstruction (AGR) approach to enhance the spatial resolution of DMI scans via exploiting correlated anatomic information in corresponding 1H images. Approach: We used segmented MRI scans of patients with CNS tumors to simulate DMI metabolic maps and corresponding ground truth, which were then used to evaluate AGR performance with respect to both SNR and the targeted spatial resolution. Results: Findings demonstrated that this AGR approach is largely robust to noise and most successful at upsampling factors between 2-4, after which the reconstructions starts to fail. Impact: DMI can uncover novel metabolic information about CNS lesions. We demonstrate that mutual anatomic information from 1H MRI can bring 3T DMI closer to clinically-viable spatial resolutions. Further work is needed to assess its utility across lesion sizes and pathologies.
Fluorinated gelatin-based scaffolds traceable by 19F MRI
Authors: Herynek Vít , Kolouchová Kristýna , Karela Jiří , Van Damme Lana , Šefc Luděk , Van Vlierberghe Sandra
Published: November 2024

Motivation: Gelatin-based scaffolds may be seeded by cells or may serve as depots for drugs and ensure their slow release. Goal(s): The goal of the study was to prepare scaffolds with tunable properties and monitor their stability in time in a mouse model in vivo. Approach: The scaffolds implanted to mice were monitored by 1H/19F MRI, fluorine content was quantified by 19F MR spectroscopy. Results: The scaffolds can be easily monitored by 19F MRI/MRS. The study confirmed that the design of the scaffolds can be fine-tuned for future applications, biodegradation rates may be set from several weeks up to one year. Impact: Gelatin-based scaffolds pave the road towards qualitatively different drug applications and regenerative medicine. The study evaluated their applicability, traceability by 1H/19FMRI, and stability in vivo. Future work should investigate release speed of different compounds (drugs) both hydrophilic and hydrophobic.
Fast repeated administrations of PHIP hyperpolarized [1-13C]pyruvate enables averaging of in vivo metabolism in a single MRI exam
Authors: Müller Christoph , Nagel Luca , Gierse Martin , Gottwald Wolfgang , Ahmadova Zumrud , Grashei Martin , Wolff Pascal , Josten Felix , Karaali Senay , Lucas Sebastian , Scheuer Jochen , Müller Christoph , Blanchard John , Topping Geoffrey , Wendlinger Andre , Setzer Nadine , Sühnel Sandra , Handwerker Jonas , Vassiliou Christopheros , van Heijster Frits , Knecht Stephan , Keim Michael , Schilling Franz , Schwartz Ilai
Published: November 2024

Motivation: Parahydrogen Induced Polarization (PHIP) is a potential alternative to d-DNP for the polarization of [1-13C]pyruvate, but has so far been limited to low polarizations, low concentrations, and high impurities. Goal(s): We present, for the first time at a conference, recent advances in the polarization of [1-13C]pyruvate using PHIP via Side-Arm-Hydrogenation. Approach: Demonstration of an automated production of hyperpolarized [1-13C]pyruvate using PHIP-SAH. The PHIP system was benchmarked against a d-DNP system and hyperpolarized [1-13C]pyruvate from both systems was injected in animals for comparative in vivo metabolic MRI. Results: PHIP and d-DNP based hyperpolarization achieve comparable results, but PHIP is much faster. Impact: PHIP is demonstrated as a fast, effective, and cost-efficient polarization method for [1-13C]pyruvate. With very short dose production times, researchers are enabled to administer multiple (4) injections into the same animal within reasonable anesthesia time (<1h), allowing averaging of metabolism.
Hyperpolarized 13C metabolic imaging of Alzheimer’s Disease: impact of sex, genotype and age in the hAPP-J20 mouse model
Authors: Radoul Marina , Le Page Lydia , Guglielmetti Caroline , Li Huihui , Nakamura Ken , Chaumeil Myriam
Published: November 2024

Motivation: The accelerating prevalence of Alzheimer's disease (AD) around the world urges the need not only for more effective treatment but also for improved non-invasive monitoring of onset and progression. Goal(s): Our goal is to investigate if the clinically expanding HP 13C MR method could improve diagnosis and monitoring of AD. Approach: hAPP-J20 AD mice and age-/sex-matched wild-type were imaged using HP 13C MR at 2-months-old (presymptomatic) and 14-months-old (amyloid plaques accumulation). The impact of sex, genotype, age, and their interactions, on the derived HP metrics was investigated. Results: HP13C metabolic imaging can provide crucial information on sexual dimorphism and metabolic aging in AD. Impact: Hyperpolarized 13C imaging provides unique metabolic information specific to sex and APP mutational status in an AD model. Upon clinical translation, such method could improve early diagnosis and patient-centric monitoring of AD progression, and potentially assessment of therapeutic response.
Assessing Pre-Treatment Metabolic Profiles in High-Risk DLBCL via Hyperpolarized 13C-Pyruvate MR Spectroscopy
Authors: Lai Ying-Chieh , Hsieh Ching-Yi , Lu Kuan-Ying , Lee Hsien-Ju , Chai Wen-Yen , Lin Gigin , Juan Yu-Hsiang
Published: November 2024

Motivation: The study addresses the need for early detection of treatment response in high-risk diffuse large B cell lymphoma, where traditional methods based on tumor size are inadequate. Goal(s): The study aims to validate 13C-Pyruvate DNP MR spectroscopy as a sensitive technique for early evaluation of treatment efficacy in lymphoma patients. Approach: Utilizing 13C MRS, the research monitors the metabolic conversion of 13C-labeled pyruvate to lactate, reflecting the treatment's impact on the tumor's metabolic activity. Results: Preliminary data from three patients show different metabolic rates, indicating the potential of this method to discern early treatment responses, leading to more timely and effective clinical decisions. Impact: These results could revolutionize protocols for lymphoma by enabling earlier assessment of therapy efficacy, thus informing more timely adjustments to treatment strategies. This advancement may spur further metabolic research and ultimately improving survival rates and quality of life for patients.
Hyperpolarized 13C Metabolic Imaging in Human Subjects with Advanced Coronary Artery Disease: Initial Experience and Thoughts
Authors: Sharma Gaurav , McNeil Sarah , Lin Sung-Han , Harrison Crystal , Park Jae Mo , Peltz Matthias , Malloy Craig , Jessen Michael
Published: November 2024

Motivation: Coronary Artery Disease (CAD) continues to be a significant health issue worldwide, necessitating enhanced diagnostic methods capable of imaging cardiac metabolism. Hyperpolarized Carbon-13 Magnetic Resonance Imaging (HP-13C MRI) offers a potential solution for the non-invasive evaluation of metabolism in the human heart. Goal(s): Our goal is to demonstrate the feasibility of HP-13C MRI in two human subjects with advanced CAD. Approach: By examining these subjects, we have successfully imaged metabolic abnormalities within the myocardium. Results: Our results indicate promising potential for using this technology to visualize dynamic changes in cardiac energetics associated with CAD. These findings can potentially influence the management of CAD. Impact: This study establishes HP 13C-MRI as a safe, non-invasive tool for visualizing metabolic abnormalities in CAD patients, paving the way for more precise management of ischemic heart disease and prompting further comparative research with traditional imaging methods.
Application of Automatic Subregion Segmentation in Perfusion Evaluation of Hippocampal Sclerosis based on Arterial Spin Labeling
Authors: Mengnan Yan , Ting Wang Yi , Jian Li , Ling Zhang Yan , Qin Li Jin , Bo Tian , Bing Chen , Hui Xiong Yu
Published: November 2024

Motivation: Evaluating the hippocampal volume and perfusion level is important in the diagnosis of hippocampal sclerosis (HS). However, further observation at the subregion level is difficult. Goal(s): To investigate the alterations in hippocampal subregion volume and blood flow in HS patients with an automatic segmentation procedure. Approach: T1-MPRAGE and 3D-pCASL images were automatically segmented to quantify the hippocampal subregion volume and blood flow. The diagnostic performance of these subregion quantitative metrics in HS were statistically analyzed. Results: The volume (VCA1) and blood flow (CBFCA1) of CA1 region are independent factors in diagnosing HS. The combination of VCA1 and CBFCA1 has the highest diagnostic performance. Impact: The combination of automatic segmentation and arterial spin labeling offers a quantitative imaging foundation for diagnosing hippocampal sclerosis at the subregion level. This scheme can also be applied to other MR techniques to improve the diagnostic effectiveness in hippocampal research.
Parallel transmit (pTx) 7T MRI for drug-resistant focal epilepsy
Authors: Klodowski Krzysztof , Zhang Minghao , Scoffings Daniel , Jen Jian , Cope Thomas , Rodgers Christopher
Published: November 2024

Motivation: In one third of patients diagnosed with drug-resistant focal epilepsy 3T MRI cannot identify the causative lesion. Single transmit (1Tx) 7T MRI is more sensitive, but signal dropouts obscure temporal lobes where lesions often occur. Goal(s): Show feasibility of parallel transmit (pTx) 7T MRI to identify epileptogenic lesions and compare with circularly polarized (CP) 7T MRI. Approach: 10 patients with drug-resistant focal epilepsy and normal 3T were scanned with pTx and CP 7T MRI. Results: : pTx images were more uniform than CP. In three cases epileptogenic lesions (focal cortical dysplasia and encephalocele) that had not been visible at 3T were revealed. Impact: Parallel transmit (pTx) 7T MRI improves lesion detection in drug-resistant focal epilepsy patients. With further validation, this could contribute to surgical decision making, potentially without requiring invasive depth electrodes tests. This would widen access to curative epilepsy surgery.
Impact of Vessel Removal on Classification of Chronic Liver Disease using Radiomics Features and Quantitative T2 Mapping
Authors: Karakay Deniz , Altbach Maria , Martin Diego , Bilgin Ali
Published: November 2024

Motivation: MRI radiomics with T2-mapping has been proposed to detect changes of chronic liver disease (CLD) but may be hampered by liver vasculature. Goal(s): Our goal is to evaluate radiomics features of T2 maps and the impact of vessel removal on CLD classification. Approach: T2 liver maps from a clinical cohort were analyzed using radiomics features and a T2 thresholding-based feature, followed by feature selection and random forest classification. Experiments were conducted on both full liver T2 maps and T2 maps with vessel removal using the Frangi filter. Results: Vessel removal significantly enhanced CLD classification performance as measured by mean AUC. Impact: Our findings have the potential for clinical translation to help establish MRI radiomics with T2-mapping for CLD diagnosis and treatment monitoring.
Radiomics Model for Prognosis of Brainstem Stroke Based on Lesion and Surrounding Features
Authors: Fu Kuang , Wu Yun , Xu Tianquan , Wang Jia , Guan Haonan , Mi Shaonan , Yan Xin
Published: November 2024

Motivation: Stroke is a major global health issue, necessitating early outcome prediction for optimal treatment. Brainstem stroke, often overlooked, requires dedicated predictive models due to its unique challenges. Goal(s): Develop radiomics models to predict brainstem stroke outcomes, considering infarct edge and surrounding regions, improving prognosis, and simplifying clinical evaluation. Approach: 474 patients were studied, and radiomics features were extracted from diffusion-weighted images. Machine learning models were trained using SVM, RF, KNN and AdaBoost algorithms. Results: The RF model, based on the circle2 region, exhibited the highest performance (AUC=0.84). Models in the circle region outperformed core. Impact: Our specialized radiomics models offer a valuable tool for personalized brainstem stroke treatment planning, potentially enhancing patient outcomes.
Optimal selection of candidate datasets for deep learning model retraining using radiomics: application to pancreas segmentation in MRI
Authors: Bagur Alexandre Triay , Jain Vishal , Aljabar Paul
Published: November 2024

Motivation: Machine learning (ML) models need to be periodically evaluated to combat ‘data drift’, where the target population changes over timeGoal(s): The goal is to present a framework for optimally selecting new datasets and updating ML modelsApproach: We retrained a pancreas segmentation model in MRI scans. We selected 50 new cases to annotate using radiomics features, i.e., those unlabelled cases with most differing segmentations from those in the previous training setResults: The system identified a diversity of failure cases, which flagged challenges in real-world data. The mean performance of the model improved after retraining with the additional casesImpact: The proposed system yields a helpful guide for researchers and technicians for retraining machine learning models, particularly deep learning models for organ segmentation in MRI. Selecting an optimal new set of data to annotate produces time and cost savings
Radiomics-optimized MRI: Evaluation of keyhole technique to prostate cancer DWI
Authors: Chu Rui , Jambor Ivan , Pesola Marko , Taimen Pekka , Ettala Otto , Saunavaara Jani , Boström Peter , Aronen Hannu , Merisaari Harri
Published: November 2024

Motivation: Radiomic feature extraction techniques may be combined with reduced k-space data acquisition, if their repeatability and clinical performance would stay in the same levels as with full data acquisition. Goal(s): We evaluate radiomics for their potential to be used in keyhole imaging acquiring k-space only partially. Approach: We utilized 78 patients with prostate cancer who underwent short-term test-retest prostate MRI examination. We calculated ADC parameter map with different portions of k-space, simulating keyhole acquisitions. We extracted radiomics, evaluating intra-class correlation coefficient ICC(3,1) changes and area under ROC curve (AUC). Results: Repeatability and classification performance stayed in acceptable limits for some of the radiomics. Impact: The technique is relative easy to implement, and thus may benefit clinical MR examinations in the near future.
External Validation of IDH Mutation Detection Using Radiomics Extracted from T2-weighted MRI with Machine Learning
Authors: Arpak Esra Sümer , Danyeli Ayca Ersen , Pamir M Necmettin , Özduman Koray , Dinçer Alp , Ozturk-Isik Esin
Published: November 2024

Motivation: Isocitrate dehydrogenase (IDH) mutation plays a key role in the prognosis of gliomas. Several studies have detected the IDH mutation using radiomics. However, few studies focused on the generalizability of radiomics-based machine learning models. Goal(s): To externally validate the ability of radiomics for noninvasive detection of IDH mutation using multi-site data. Approach: Radiomics of T2w MRI of UCSF-PDGM dataset (Cohort 1) was used for training machine learning models, then externally validated at the local dataset (Cohort 2). Results: T2w MRI-radiomics could identify the IDH mutation with an accuracy of 0.89 on Cohort 1, which was externally validated with an accuracy of 0.73. Impact: External validation studies are important for investigating the generalizability of machine learning models. The models based on T2w MRI-radiomics resulted in 0.89 accuracy in the training dataset, with a slightly lower accuracy on external validation dataset for identifying IDH mutation.
MRI-Based Radiomics Analysis to Assess Treatment Response after Neoadjuvant Therapy in Nasopharyngeal Carcinoma
Authors: Wang Zhuo , Zhang Jing , Jia Fei , Jiang Jingqi
Published: November 2024

Motivation: Radiomics, as a non-invasive way for analysis of tumor heterogeneity, has been applied to the detection of therapeutic sensibility with satisfactory outcomes. Goal(s): This study aimed to explore the predictive value of nomogram combing MRI-based radiomics and clinical factors in detecting tumor response to neoadjuvant therapy in nasopharyngeal carcinoma patients. Approach: LASSO-logistic regression analysis was applied to select radiomics features. The “rms” package was used to construct nomogram and calibration curves. The ROC curves, calibration, and decision curves were performed to assess the performance of the models. Results: The nomograms integrated radiomics scores with clinical factors outperformed the clinical-only or radiomics-only models. Impact: The nomogram developed from MRI-based radiomics combined with clinical factors could serve as a reliable tool for non-invasively discriminating neoadjuvant chemotherapy responders from non-responders and provide a basis for personalized therapeutic regimens for LA-NPC patients.
The evaluation of white matter lesion with 3D-T1 weighted imaging for predicting dementia
Authors: Iseki Rinako , Kamagata Koji , Saito Yuya , Yoshida Seina , Anidica Christina , Uchida Wataru , Takabayashi Kaito , Zou Rui , Kitagawa Takafumi , Ozawa Takuya , Hagiwara Akifumi , Akashi Toshiaki , Wada Akihiko , Aoki Shigeki
Published: November 2024

Motivation: Evaluating cognitive function-related white matter lesions (WML) conventionally requires 3D fluid attenuated inversion recovery (3D-FLAIR), which isn't always available. We aimed to explore the suitability of routinely acquired 3D-T1 weighted images (3D-T1WI) for WML assessment. Goal(s): This study investigated whether 3D-T1WI could replace 3D-FLAIR in WML assessment. Approach: We compared the correlation coefficient, ICC, and DSC of WML volume between 3D-FLAIR and 3D-T1WI, as well as its correlation with cognitive scores. Results: WML based on 3D-T1WI strongly correlated with WML based on 3D-FLAIR, with high ICC, DSC, and cognitive score associations, indicating the potential of 3D-T1WI for WML assessment alternative to 3D-FLAIR. Impact: White matter lesions (WML) based on 3D-T1 weighted images (3D-T1WI) closely matched 3D-fluid attenuated inversion recovery (3D-FLAIR) in WML area, volume, and cognitive function associations. It is suggested 3D-T1WI is valuable alternative to 3D-FLAIR for WML volume assessment.
Multi-parametric imaging in muscle based on chemical shift encoded multi-echo variable flip angle sequence: initial experience at 5T system
Authors: Peng Hao , Cheng Chuanli , Wan Qian , Guan Ziyun , Zhang Zhen , Liu Xin , Zheng Hairong , Zou Chao
Published: November 2024

Motivation: Water T1 (wT1) has been shown to be a sensitive biomarker for muscle disease in the 3T system. Goal(s): The aim of this work was to investigate the feasibility of simultaneous wT1/PDFF/R2* imaging in the 5T system. Approach: Simultaneous multi-parametric imaging was achieved using chemical shift encoded multi-echo variable flip angle (CSE-VFA) sequences combined with B1 measurement techniques. Results: Corrected by the preTFL approach, homogeneous wT1 maps are obtained even under B1 varying from 0.37 to 1.12. Impact: In this work we have tested the feasibility of simultaneous quantification of wT1/PDFF/R2* in the 5T imaging system. This work has laid the foundation for subsequent research into the clinical significance of extracellular volume fraction.
Evaluation of venous oxygen saturation using k-space energy spectrum analysis
Authors: Wu Pei-Hsin , Chuang Tzu-Chao
Published: November 2024

Motivation: OEF as a biomarker requires SvO2 quantities which can be estimated via susceptometry-based oximetry (SBO). The fundamental is based on the presence of deoxyhemoglobin which induces local field inhomogeneity. The conventional approach for SvO2 estimation via SBO utilizes the phase difference accrued over time between intra- and extravascular compartments. Goal(s): Our goal was to demonstrate an alternative for SvO2 estimation with a single-echo GRE image. Approach: In this study, the k-space energy spectrum analysis was performed to quantify k-energy displacement for field inhomogeneity mapping. Results: The preliminary result shows a comparable SvO2 value as that from the conventional approach. Impact: Susceptometry-based oximetry, based on field inhomogeneity, has become a metric for SvO2 estimation. The KESA algorithm was applied to a single-echo GRE image to map field inhomogeneity. The comparable SvO2 indicated the potential of KESA in SvO2 estimation.
Principal Deformation Analysis of Cleft Palate Speech Using Atlas-Driven Dynamic Vocal Tract MRI
Authors: Xing Fangxu , Jin Riwei , Gilbert Imani , Kim Jiyoon , Perry Jamie , Sutton Bradley , Woo Jonghye
Published: November 2024

Motivation: Characterizing velopharyngeal motion patterns in children with cleft palate is an important research topic. Goal(s): Utilizing recently improved dynamic MRI techniques, we aim to uncover distinctive deformation patterns in cleft palate speech from a statistical perspective. Approach: We propose a post-processing pipeline based on spatiotemporal atlases, manually segmented velopharyngeal labels, deformable registration, and principal component analysis. The speech dataset consisting of 17 normal controls and 4 patients was analyzed. Results: The proposed method effectively captures and separates patient-specific deformation patterns within principal component’s feature spaces. Furthermore, it reveals the impact from different anatomical regions in cleft palate speech. Impact: In practice, cleft palate patterns in speech MRI are too subtle for visual examination or conventional post-processing methods to reveal. Providing a solution to uncover such patterns is essential to help understand the anatomical and functional changes in this disorder.
Layer-fMRI in lower brain structures: why is it so hard and what can we do about it?
Authors: Huber Renzo , Stirnberg Rüdiger , Kan Chung , Ehses Philipp , Koiso Kenshu , Wardle Susan , Gephart Isabel , Graedel Nadine , Audrain Sam , Persichetti Andrew , Morgan A , Bandettini Peter
Published: November 2024

Motivation: Layer-fMRI can address questions of directional information flow, but it’s difficult in lower brain areas. Goal(s): We want to make layer-fMRI work in low brain structures, despite commonly low tSNR, EPI distortions, and EPI phase errors. Approach: We tested the efficacy of four advanced acquisition approaches to mitigate these challenges: pTx, dual-polarity readouts, multi-shot segmentation, and aggressive GRAPPA. Results: We found that pTx and high GRAPPA had limited impact for improved image quality. Though, multi-shot segmentation and dual-polarity readouts allowed layer-fMRI applications in low brain areas. Impact: This work helps to fulfill the promise of layer-fMRI beyond the top 50% of the cortex.