bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Early-stage Primary Central Nervous System Lymphoma Manifesting Atypical Radiological Phenotype Using Multi-Task Neural Network
Authors: Deng Yujiao , zhao kaiyang , su xiaorui , Zhang Miaoqi , Zhou Huanyu , yin hongkun , Yue qiang
Published: November 2024

Motivation: In clinical practice, distinguishing atypical radiological features of primary central nervous system lymphoma (PCNSL) from certain glioma or demyelinating disease patients is challenging and often lead to delayed or incorrect treatment. Goal(s): To develop deep learning model to identify PCNSL with atypical radiological features. Approach: Developing a multi-task, multi-modal deep learning model capable of end-to-end identification of early-stage atypical PCNSL. Results: The multi-task, multi-modal deep learning model accurately discriminates early-stage atypical PCNSL from other radiologically similar diseases, significantly enhancing the diagnostic accuracy of radiologists in clinical practice. Impact: The practical clinical application of the model demonstrates its diagnostic value in identifying challenging cases suspected of early-stage atypical PCNSL. This research shifts academic attention towards distinguishing specific subtypes prone to misdiagnosis, rather than solely focusing on disease-level differentiations.
Predicting the IDH1 Mutation Status of Gliomas based on Multi-modality MRI Radiomics Combined with VASARI Features
Authors: Chen Xiaohua , Chen Zhiqiang , Liu Shili , Zhang Ruodi , Zhou Yunshu , Xiong Yuhui , Wang Aijun
Published: November 2024

Motivation: The IDH1 mutant state is an independent risk factor of affecting the treatment and prognosis of glioma. Predicting the IDH1 status accurately pre-operator is crucial for making personalized treatment decisions for glioma patients. Goal(s): This study aims to propose a non-invasive and convenient model based on MRI to predict the IDH1 status of gliomas before operation accurately. Approach: Building three machine learning models based on multi-sequence MRI radiomics features, VASARI features, and combined features to predict the IDH1 status. Results: These three models can predict the IDH1 status effectively and accurately, the combined model has the best diagnostic performance. Impact: Models based on conventional MRI sequences and VASARI features provide the clinical value for evaluation of molecular typing in gliomas. It is expected to become a practical tool for the non-invasive characterization of gliomas to help the individualized treatment planning.
Machine learning based characterisation of glioma shows best performance with post-contrast T1 and diffusion imaging
Authors: Oliveira-Stahl Gabriel , Inglese Marianna , Thust Steffi , Grech-Sollars Matthew
Published: November 2024

Motivation: Accurate glioma classification currently relies on tissue diagnosis, which has associated surgical risks. Machine learning based classification of MR images may enable non-invasive glioma characterisation. Goal(s): Our aim was to assess which imaging modalities provided optimal training data to increase accuracy of machine learning based glioma characterisation. Approach: A pyRadiomics based pipeline predicted tumour grade and IDH-mutation status with XGBoost on a glioblastoma-rich dataset. 10 structural and advanced MR acquisitions were used as model input and a systematic search for the most informative MR modalities was performed. Results: The classifier performed best when the model was trained on post-contrast T1 and diffusion imaging. Impact: We found post-contrast T1 and diffusion imaging to be the most informative MR modalities for machine learning based glioma characterisation. This result will benefit scientists in making well-informed choices on how to train their machine learning models for glioma classification.
A CMR-based multi-modality fusion machine learning approach for predicting left ventricular reverse remodeling in dilated cardiomyopathy
Authors: Kan AO , Dai Jiankun , Shi Jie , Gong Lianggeng
Published: November 2024

Motivation: Few multi-modality machine learning (ML) classifiers combine cardiac magnetic resonance (CMR) imaging with clinical data for predicting LVRR in DCM patients, limiting improvements in patient outcomes and management. Goal(s): To develop an ML classifier using multi-modality data, including CMR, to predict LVRR in initial DCM patients. Approach: 129 DCM patients with complete clinical and CMR data were collected. Feature selection identified relevant variables, and an LR-based nomogram was constructed and evaluated. Results: The nomogram achieved an AUC of 0.857 in the test cohort, incorporating late gadolinium enhancement pattern, global longitudinal peak strain, aldosterone antagonist, and severe mitral regurgitation. Impact: The CMR-based multi-modality nomogram has a superior ability in the prediction of LVRR in DCM patients.
The Clinical Utility of Radiomics Models Based on Non-Contrast T1 Mapping in CMR for Discriminating Acute and Chronic Myocardial Infarction
Authors: Li Shinuo , Hao Ruqian , Wu Yunzhu , Song Yang , Jiang Yueluan , Liu Ting
Published: November 2024

Motivation: The complexity of differentiation between acute and chronic myocardial infarctions(MI) not only complicates the choice of treatment plans but also poses challenges for post-treatment follow-up. Goal(s): This study aimed to determine whether radiomics model based on T1 mapping can be applied in differential diagnosis of acute and chronic MI. Approach: Images of 61 patients were included for feature extraction, and the statistically significant features were selected to establish the radiomics model. Results: This radiomics model demonstrates significant efficacy in distinguishing between acute and chronic myocardial infarction lesions in patients, providing valuable support for clinical diagnosis and follow-up treatment. Impact: The development of radiomics model to differentiate acute from chronic myocardial infarction lesions holds promise for facilitating prompt clinical decision-making. This advancement enables early medical intervention for MI patients, reducing the risk of adverse cardiovascular events and enhancing patient prognosis.
MRI Signal changes of meniscus in patients with knee osteoarthritis
Authors: Zhang Yuqian , Fan Zhuangzhuang , Bo Kaida , Wang Changqing
Published: November 2024

Motivation: The pathogenesis of knee osteoarthritis is affected by many factors. Among them, meniscus of patients with different stages of disease in magnetic resonance imaging reveal different degrees of abnormal signals. Goal(s): In this work, abnormal meniscus signals in 400 MRI images of 40 cases were quantified. Approach: The quantitative indicators were evaluated according to the clinical manifestations of patients. Results: Results showed that the average area ratios of abnormal meniscal signals were different between the case group and the control group, and the different degrees of abnormal signals could be used as biomarkers of knee osteoarthritis. Impact: The average area ratios of abnormal signals of meniscus can be used as new biomarkers to provide some objective and accurate biomarkers for knee osteoarthritis.
Towards a Clinical Decision-Support System for Automating MRI Protocoling
Authors: Shokrollahi Peyman , Zambrano Juan , Li Allison , Raichandani Surbhi , Chaudhari Akshay , Loening Andreas
Published: November 2024

Motivation: We developed a system that performs radiology protocol selection for incoming MRI orders. Goal(s): To enhance MRI protocol selection accuracy and efficiency. We evaluated new models and expanded anatomic/subspeciality coverage compared to a prior body MRI protocol selection system. Approach: A machine learning-driven decision-support system was developed integrating kernel-based, tree-based, boosting, and deep-learning algorithms with an ensemble classifier in 22,524 patients. This system utilizes electronic medical records to predict the top-three likely MRI protocols and their probabilities. Results: A cumulative F1-score of 97.1% for the top-three predicted MRI protocols was obtained in a test set of 3,379 patients. Impact: The proposed system has the potential to improve radiologists’ protocol selection accuracy by notifying them of protocol-case discrepancies due to the individual patient’s conditions, and to enable a decision-support system for greater efficiency in selecting commonly utilized MR protocols.
T1 and T2 Mapping for Identifying Malignant Lymph Nodes in Head and Neck Squamous Cell Carcinoma
Authors: Chen Yu , Su Tong , Qu Jiangming , Xu Zhentan , Wang Tianjiao , Zhu Jinxia , Zhang Zhuhua , Feng Feng , Jin Zhengyu
Published: November 2024

Motivation: Find a novel Quantitative parameters of imaging to differentiate between metastatic lymph nodes and reactive lymph node hyperplasia in HNSCC. Goal(s): This study seeks to assess the ability of T1 and T2 mapping to differentiate between metastatic lymph nodes and reactive lymph node hyperplasia in HNSCC. Approach: Quantitative measurements derived from preoperative T1 and T2 mapping and DWI of metastatic and non-metastatic lymph nodes were compared using independent samples t-test or Mann–Whitney U test. Results: Metastatic lymph nodes exhibited significantly lower mean T2 values, higher apparent diffusion coefficient (ADC) and higher standard deviation of T1 values (T1SD) (p < 0.001). Impact: Our findings indicate that malignant cervical lymph nodes exhibit significantly lower T2 values and higher T1SD and ADC values compared to benign lymph nodes in HNSCC. This finding has important implications for achieving preoperative high-accuracy nodal staging in HNSCC.
An interleaved flip angle multi-slice acquisition method for 2D variable flip angle T1 mapping
Authors: Chen Yuting , Liu Huafeng , Ye Huihui
Published: November 2024

Motivation: Magnetization transfer (MT) effect has been demonstrated to be a significant factor that results in the estimation bias and reduced reproducibility of single pool T1 mapping by 3D variable flip angle (VFA) method. Goal(s): Reduce the estimation bias of 2D VFA T1 mapping method while improving its reproducibility using different protocols with a simple single-pool relaxometry model. Approach: Interleave the variable flip angles for multi-slice 2D acquisition to balance the MT effect between acquisitions without SAR increase. Results: Both simulations and in vivo experiments showed improved accuracy and reproducibility of 2D VFA T1 mapping with our proposed method. Impact: It has been reported that 2D VFA T1 mapping encounters biased estimation and low reproducibility issues. Improving estimation accuracy and reducing estimation variance can help promote the clinical application of 2D VFA T1 mapping.
Accelerated Low-rank MPnRAGE Denoising and T1 Reconstruction using Jointly Trained U-Net Regularizers
Authors: Thuwajit Punnawish , Chen Kuan-fu , Weaver Jayse , Alexander Andrew , Dean Douglas , Johnson Kevin , Kecskemeti Steven
Published: November 2024

Motivation: Quantitative T1 (qT1) using MPnRAGE is a promising brain biomarker. However, reliable qT1 measurements at 1 mm isotropic resolution across the brain may require long scan times (>8min). Goal(s): We aim to develop a low-rank denoising strategy providing reliable qT1 estimations from accelerated scans in about 2 minutes. Approach: We developed a novel strategy using two U-Net models, the denoiser and T1-estimator, trained together to jointly convert accelerated low-rank scans into accurate qT1 maps. Results: Our method exhibits good bias correction with low errors in both gray matter and white matter (<3%) with high image acceleration. Impact: Our method provides fast and accurate whole-brain high-resolution qT1 estimation from MPnRAGE scans in about 2 minutes.
Simultaneous multi-slice MR-STAT for robust high-resolution full-brain relaxometry
Authors: Versteeg Edwin , Liu Hongyan , van der Heide Oscar , Fuderer Miha , van den Berg Cornelis , Sbrizzi Alessandro
Published: November 2024

Motivation: MR-STAT is a framework that enables simultaneous T1, T2 and proton-density mapping. Currently, MR-STAT acquires slices sequentially which is relatively inefficient in terms of SNR and time. Goal(s): Increase the scan-efficiency of MR-STAT while limiting motion-sensitivity Approach: We use a simultaneous multi-slice (SMS) acquisition to increase the scan efficiency of MR-STAT and use a two-step approach for the reconstruction: an SMS-SENSE reconstruction followed by a conventional slice-by-slice MR-STAT reconstruction. Results: Phantom and in-vivo results showed that a four-fold increase in encoded slices from 28 to 112 was possible achieving full-brain high-resolution T1, T2 and proton density maps in 5 minutes scan time. Impact: MR-STAT combined with a simultaneous multislice acquisition enables a 4-fold increase in scan efficiency. This can be used to increase the resolution in the slice-direction and allow the detection of smaller brain structures while not increasing scan time.
Spectral Localization by Imaging based T2 Relaxation Under Spin Tagging to measure the distribution of oxygen extraction fraction in human brain
Authors: Lee Phil , Choi In-Young , Adany Peter , O'Brien Caitlin , Jezzard Peter
Published: November 2024

Motivation: Reliable quantification and region/tissue specific mapping of cerebral oxygen extraction fraction (OEF) are critical for studying cerebral oxygen metabolism in health and disease. Goal(s): To develop Spectral Localization by Imaging (SLIM) based TRUST techniques to overcome limitations of current TRUST techniques with limited spatial resolution or prolonged scan time for clinical applications at 3T. Approach: SLIM-TRUST was developed with spatial-encoding and multi-echo for efficient sampling of venous blood transit time. SLIM approach was applied to quantify tissue-type/region-specific OEF. Results: SLIM-TRUST provided reliable quantification of blood T2 values originated from GM and WM, and lateral and medial regions. Impact: SLIM‐TRUST allows noninvasive measurement of spatial distribution of OEF, including GM/WM and various brain regions, suitable for clinical applications. The combination of SLIM and multi-echo TRUST approaches also promises reliable assessment of cerebral oxygen metabolism in clinically feasible scan time.
Value of whole-lesion histogram analysis based on ADC and ASL in predicting the response to chemotherapy and prognosis of PCNSL
Authors: Zhang Nan , Liu Guoli , Wang Mingxiao , Ma Lin
Published: November 2024

Motivation: Primary central nervous system lymphoma (PCNSL) is a rare malignant non-Hodgkin's lymphoma with a poor prognosis, the combination chemotherapy regimen based on methotrexate is the main therapeutic regimen. There are no reliable indicators to predict the treatment response and survival outcome of PCNSL patients. Goal(s): To predict the response to methotrexate (MTX) chemotherapy and prognosis in primary central nervous system lymphoma (PCNSL) patients by the histogram parameters based on apparent diffusion coefficient (ADC) and arterial spin labeling (ASL). Approach: Use the univariate and multivariate logistic regressions to identify the independent predictors for the response of MTX chemotherapy. The predictive performance was assessed by the receiver operating characteristic. The Kaplan-Meier analysis and Cox regression were used to analyze the OS. Results: Number of lesions (NL), the maximum of ADC values and the 95th percentile of CBF values were independent predictive factors of chemotherapy response. Impact: ADC and CBF values are promising predictive factors of chemotherapy response and outcome in PCNSL patients.
Comparing DSC-CBV, DSC-CBF and ASL for Detecting Residual and Recurrent Glioblastoma with Deep Learning and multishell Diffusion MRI
Authors: Gagnon Louis , Gupta Diviya , Mastorakos George , White Nathan , Goodwill Vanessa , McDonald Carrie , Beaumont Thomas , Siebert Tyler , Hattangadi-Gluth Jona , Kesari Santosh , Schulte Jessica , Piccioni David , Bolar Divya , Farid Nikdokht , Dale Anders , Rudie Jeffrey
Published: November 2024

Motivation: Differentiating recurrent tumor from post-treatment changes is challenging in post-operative glioblastoma MRI. Goal(s): To compare the performance of DSC-CBV, DSC-CBF, and ASL perfusion MRI to differentiate recurrent tumor from treatment-related changes using a Deep Learning segmentation model together with multishell Diffusion MRI. Approach: 138 post-operative scans were manually segmented for enhancing and non-enhancing cellular tumor volume. A Deep Learning segmentation was trained to segment cellular tumor and then tested to differentiate recurring disease from post-treatment changes from the segmentations. Results: DSC-CBV and DSC-CBF improved the detection of residual/recurrent cellular tumor with Deep Learning while ASL perfusion did not. Impact: Our work re-demonstrates the importance of including a DSC perfusion method in clinical brain tumor MRI protocols.
Mapping cellular proliferation activity of glioma by water exchange DCE-MRI at high spatial resolution
Authors: jia yinhang , han guangxu , wang zejun , Hsu Yi-Cheng , wang bao , liu yingchao , bai ruiliang
Published: November 2024

Motivation: Cell proliferation abnormalities (e.g., Ki67 status) are key features of glioma. Conventional biopsy is used to characterize Ki67 expression levels in vivo, but it lacks spatial and temporal information because of intratumorally heterogeneity. Goal(s): To identify MRI parameters representing the intracellular water-efflux rate regulated by aquaporin-4, a noninvasive biomarker sensitive to Ki67 quantitative expression, in glioma. Approach: Human tumors, animal models, and cell lines were investigated by water-exchange DCE-MRI and immunohistochemistry. Results: Ki67 and transmembrane water-efflux rate showed a strong linear relationship. The underlying mechanism was the close symbiotic expression pattern between aquaporin-4 and Ki67. Impact: Transmembrane water-efflux rate is a sensitive biomarker of Ki67 because rapidly growing cells upregulate aquaporin-4 expression for enhanced transmembrane transport.
Quantification of BBB Permeability in glioma using ASL with tissue specific T2 values
Authors: Cetin Ayse Irem , Turhan Gulce , Padrela Beatriz , Mahroo Amnah , Konstandin Simon , Hoinkiss Daniel , Breutigam Nora-Josefin , Keil Vera , Ersan-Danyeli Ayca , Özduman Koray , Eickel Klaus , Mutsaerts Henk-Jan , Petr Jan , Günther Matthias , Dincer Alp , Ozturk-Isik Esin
Published: November 2024

Motivation: Blood brain barrier arterial spin labeling (BBB-ASL) could assess BBB integrity. However, the assumption of homogeneous T2 in data fitting might be broken in gliomas. Goal(s): To evaluate the BBB integrity in gliomas with regional tissue-specific T2. Approach: A mono-exponential T2 fitting was used to obtain tissue-specific T2 values to estimate time of water exchange (Tex) and perfusion (CBF) in the tumor, normal-appearing white (NAWM), and gray matter (NAGM) using ExploreASL. Results: Higher Tex in NAWM, and lower Tex in the tumor and NAGM were observed and the tumor heterogeneity was better depicted when tissue-specific T2 values were used. Impact: Water exchange and perfusion maps are highly affected by the tissue T2 value used in BBB-ASL data processing. Applying tissue-specific T2 correction has resulted in a more reliable evaluation of BBB integrity in gliomas.
Sex- and age-related changes in cerebral microvasculature can be detected with vascular architecture mapping
Authors: Hohmann Anja , Zhang Ke , Mooshage Christoph , Jende Johann , Schlemmer Heinz-Peter , Vollmuth Philipp , Bendszus Martin , Wick Wolfgang , Kurz Felix
Published: November 2024

Motivation: While vessel architecture mapping (VAM) is an emerging quantitative MR imaging technique that can characterize cerebral blood vessel microstructure in vivo based on dynamic changes in gradient-echo and spin-echo relaxation rates during contrast agent administration, no study has examined how age-related morphological changes affect VAM parameters. Goal(s): Our goal was to assess region-specific age- and sex-related changes in cerebral microvasculature with VAM. Approach: We applied high-resolution VAM on the healthy contralateral hemisphere of 72 age-matched women and men with stable low-grade brain tumors. Results: We could show that microvascular morphology and aging-related remodeling differ between sexes, particularly in thalamus, insular cortex, and putamen. Impact: This is the first study to characterize age- and sex-specific changes in cerebral microvascular architecture across different anatomical regions using vascular architecture mapping. Results may be of particular importance for future studies on sex-specific diagnostics and prevention of cerebrovascular disease.
Quantification of Tau in the Piriform Cortex in AD using MR-PET
Authors: Taghavi Hossein Moein , Karimpoor Mahta , van Staalduinen Eric , Leventis Samantha , Young Christina , Carlson Mackenzie , Vossler Hillary , Davidzon Guido , Romero America , Trelle Alexandra , Rosenberg Jarrett , Henderson Victor , Zaharchuk Greg , Poston Kathleen , Georgiadis Marios , Mormino Elizabeth , Zeineh Michael
Published: November 2024

Motivation: Olfactory dysfunction can be an early sign of Alzheimer’s disease (AD), but involvement of primary olfactory piriform cortex in AD pathology is unknown. Goal(s): We use Tau MR-PET to compare piriform cortex uptake to the adjacent medial temporal lobe across the progression of AD pathology. Approach: Using PI-2620 Tau MR-PET, we manually segmented and computed piriform tau compared to automatically segmented medial temporal uptake in amyloid negative/positive healthy controls, mild cognitive impairment, and AD subjects. Results: Piriform tau uptake increases ordinally with disease severity and is significantly different higher in amyloid positive compared to negative controls. Impact: We show early increases in piriform cortex tau uptake that closely track adjacent medial temporal regions. This not only explains deficits in olfaction early in AD but opens the door to more sensitive testing and comprehensive detection of neurodegeneration.
A Longitudinal Study of Functional Brain Complexity in Progressive Alzheimer's Diseases
Authors: Zhang Ru , Aksman Leon , Wijesinghe Dilmini , Ringman John , Wang Danny , Jann Kay
Published: November 2024

Motivation: Complexity is generally reduced in mild cognitive impairment (MCI) and Alzheimer's disease (AD) than cognitive normal (CN) in cross-sectional cohorts. However, the trajectory of complexity in AD progression remains unknown. Goal(s): To investigate longitudinal changes in resting-state fMRI (rsfMRI)-complexity in AD progression. Approach: A linear mixed-effects model was implemented to investigate the main effects of Group and Group-by-time interactions. Results: rsfMRI-complexity was reduced in the MCItoAD group (those converted from MCI to AD) relative to the CN group. The CNtoMCI group (those converted from CN to MCI) showed the most pronounced rsfMRI-complexity decline over time. Impact: fMRI-complexity as a novel marker for Alzheimer's disease (AD) progression remains poorly understood although cross-sectional studies indicated reduced complexity relative to healthy aging. Our study demonstrates longitudinal changes in AD-related fMRI-complexity, indicating its potential as an early AD biomarker.
Potential MRI and PET imaging patterns of decreased Alzheimer's-disease pathological protein clearance in patients with cognitive impairment
Authors: Yin HaoLin , LU ZIHAO , ZUO CHAO , XU HAORAN , TIAN XIAOHE , GONG QIYONG
Published: November 2024

Motivation: Impaired Alzheimer's disease (AD) pathological protein clearance plays a critical role in the progression of cognitive impairment. Goal(s): To explore whether microscale abnormalities in clearance pathways exhibit macroscopic imaging patterns. Approach: Data collection was performed, and quantitative features were calculated for intergroup differences and correlation analysis. Results: The specific imaging patterns represented by choroid plexus and its associated alterations are associated with increased brain AD pathological protein burden and decreased clearance capacity of the glymphatic system. Impact: This study provides a novel perspective on the decreased clearance capacity of amyloid-beta and tau proteins in cognitively impaired patients' brains. The discovery of distinct imaging patterns aids in accurate diagnosis, treatment, and deepens our understanding of Alzheimer's disease mechanisms.
Transcriptional level and neurotransmitter systems associate with brain abnormalities across Alzheimer's disease spectrum: a meta-analysis
Authors: Tang Xinyue , Wang Ying , Cui Wei
Published: November 2024

Motivation: Numerous neuroimaging studies have reported that Alzheimer's disease and preclinical AD have been linked to alterations in the amplitude of low-frequency fluctuation /fractional ALFF and cortical thickness of some brain areas. Goal(s): However, the findings have been inconsistent and the correlation with the transcriptional profile and neurotransmitter systems remain largely unknown. Approach: We conducted a meta-analysis to identify multimodal differences in ALFF/fALFF and CT in patients with AD and preclinical AD, using the Seed-based d Mapping with Permutation of Subject Images software. Results: Overlapping meta analysis showed that patients with AD displayed decreased ALFF/fALFF and CT in the left PCC. Impact: These findings may provide different insights into the pathophysiology of AD spectrum.
MR fingerprinting for quantification of brain amyloid burden: from development to prospective multi-site external validation
Authors: Fujita Shohei , Fushimi Yasutaka , Otsuka Yujiro , Murata Katsutoshi , Buonincontri Guido , Koerzdoerfer Gregor , Nittka Mathias , Fukunaga Issei , Takabayashi Kaito , Motoi Yumiko , Nakajima Madoka , Murakami Koji , Shima Atsushi , Kubota Manabu , Bilgic Berkin , Kamagata Koji , Sawamoto Nobukatsu , Abe Osamu , Nakamoto Yuji , Aoki Shigeki
Published: November 2024

Motivation: A non-invasive amyloid beta (Aβ) imaging technique is needed for objective diagnosis and treatment monitoring of Alzheimer’s disease. Goal(s): To develop and validate an MRF-based method quantifying brain Aβ. Approach: A framework with efficient MRF data acquisition, neural network decoding, and atlas-based segmentation was implemented. A prospective analysis was conducted on external dataset to evaluate its generalizability, repeatability, and correlation with Aβ-PET measurements and clinical cognitive function tests. Results: The method showed high repeatability (CV<2%), significant correlation with Aβ-PET measurements and Montreal Cognitive Assessment test (p=0.015 and 0.020, respectively), and discriminated subject-level Aβ positivity with an AUC of 0.84 on external test set. Impact: The proposed framework is compatible with clinical 3T MRI and offers ‘one-stop’ examination in 10 minutes for patients with cognitive decline by providing structural MRI and Aβ-quantification. Its non-invasive nature facilitates longitudinal evaluation and correlates with Aβ-PET and cognitive function.
Evaluation of the relation between tau protein and white matter structural changes in Alzheimer's disease using fixel-based analysis
Authors: Kitagawa Takafumi , Kamagata Koji , Uchida Wataru , Yamazaki Keigo , Takabayashi Kaito , Saito Yuya , Andica Christina , Hagiwara Akifumi , Akashi Toshiaki , Sano Katsuhiro , Wada Akihiko , Aoki Shigeki
Published: November 2024

Motivation: Studies have suggested that tau deposition-induced neurotoxicity causes progressive white matter (WM) degeneration in Alzheimer's disease (AD) and its prodromal phase; however, this is not yet fully elucidated. Goal(s): To employ fixel-based analysis (FBA) to assess tau-related WM degeneration and its effect to cognitive function. Approach: The WM integrity and cortical tau load were compared across AD, mild cognitive impairment, and cognitive normal subjects using FBA and tau PET. Results: FBA metrics in WM under highly tau-deposited cortex were downward with higher effect sizes in patients. An association between entorhinal tau and cognitive function was mediated by FBA metrics in the parahippocampal cingulum. Impact: Our findings suggest the possibility that neurons were degenerated through prion-like tau propagation along axons and may shed light on future research on mechanisms of cognitive decline in Alzheimer's disease.
Simultaneous Multi B0 Shim-Coil Calibration
Authors: Arango Nicolas , White Jacob , Adalsteinsson Elfar
Published: November 2024

Motivation: Multicoil B0 shimming improves signal quality in many MRI applications but either requires pre-calibrated ridged shim coils or lengthy coil re-calibration scans. This has precluded the use of flexible arrays and limited body applications. Goal(s): Accelerate B0 shim coil re-calibration to enable body-conforming flexible shim coil arrays. Approach: Field calibration is accelerated using physics-based reconstruction, interleaving few measured slices, and de-tangling contributions of simultaneously active shim coils. Results: Measured data is used to demonstrate the effectiveness of shim field recovery from few-slice measurements, and simulation is used to demonstrate simultaneous multi shim coil calibration, resulting in a 6.7x total acceleration. Impact: Physics-based reconstruction of coil fields from few interleaved slices, and detangling fields from simultaneous B0 shim coil activation, achieves rapid calibration. Fast subject-specific calibration will enable the use of body-conforming, flexible B0 shim arrays.
Biomechanical properties and multiparametric MRI to identify microstructural dynamics in a non-alcoholic steatohepatitis mouse model
Authors: Safraou Yasmine , Brüggemann Kristin , Huang Biru , Bayerl Christian , Krehl Karolina , Kühl Anja , Meyer Tom , Shahryari Mehrgan , de Moraes Pedro , Jordan Jakob , Jaitner Noah , Tzschätzsch Heiko , Sack Ingolf , Asbach Patrick , Guo Jing , Braun Jürgen
Published: November 2024

Motivation: The relationship between the microstructural changes and the imaging-based biophysical properties of the liver as NASH progresses are not fully established. Goal(s): We aim to identify quantitative imaging markers that can provide valuable insights into the microstructural progression of NASH. Approach: We established non-alcoholic steatohepatitis in mice with a defined amino-acid high-fat diet. We performed MRI, MR elastography and histological scoring with automated fat segmentation at different times during the course of NASH. Results: Our results shed light on liver viscosity and water diffusivity as potential quantitative markers of steatohepatitis progression in mice. Impact: This study highlights the role of multiparametric-MRI, MR elastography and histopathology to reveal the dynamics of microstructural changes of non-alcoholic steatohepatitis in a mouse model using a clinical scanner. We identify liver viscosity and water diffusivity as reliable quantitative markers.
Distribution of MRI-derived T2 values as a biomarker for in vivo rapid screening of phenotype severity in MDX mice
Authors: Waters Emily , Haney Chad , Spann Alisha , Vaught Lauren , McNally Elizabeth , Demonbreun Alexis
Published: November 2024

Motivation: The frequently-used mdx model of Duchenne muscular dystrophy exhibits wide variation in disease severity, confounding detection of treatment effects. Goal(s): We sought to design a rapid, noninvasive imaging/analysis pipeline to prescreen animals and balance disease severity across treatment groups. Approach: Axial MR images and T2 maps were obtained in the hindlimbs of mdx and wildtype mice. A neural network was trained to speed segmentation. The distribution of muscle T2 values was analyzed. Results: Semiautomated segmentation reduced image processing time ~tenfold. Pearson Skew and interdecile range of muscle T2 distributions were repeatable indicators of muscle disease severity and correlated with Evans Blue dye uptake. Impact: Use of this rapid, non-invasive, semi-automated MRI/analysis pipeline has the potential to improve the sensitivity of preclinical treatment studies by enabling screening of dystrophic mice prior to study enrollment to increase uniformity of muscle pathology across treatment groups.
A Preclinical Co-Registration Pipeline for MRI and PET/CT: Enabling Multi-tracer Multiparametric PET-CT/MRI in Solid Tumors
Authors: Mansur Ameer , Gallegos Carlos , Lee Seth , Song Patrick , Burns Andrew , Sorace Anna
Published: November 2024

Motivation: Robust preclinical multimodal image registration must be developed to provide rich multiparametric data to noninvasively reveal biological treatment-induced tumor alterations. Goal(s): Establish a pipeline to enable multimodal registration of semi-rigid, subcutaneous tumors in preclinical models to evaluate multi-tracer multiparametric PET/CT-MR metric alterations. Approach: Utilizing a breast cancer murine model, a custom-designed mouse couch, augmented with an injectable liquid fiducial marker, was assessed for MR-CT co-registration, facilitating the development of a registration pipeline. Results: Post-registration tumor segmentation performed independently across modalities yielded high Dice Similarity Coefficient scores (0.92-0.95), indicating accurate tumor alignment, and enabling preliminary multiparametric voxel-wise comparisons of multimodal imaging metrics. Impact: Preclinical imaging with our registration pipeline enables for biological treatment-induced characterization of subcutaneous tumors through sequential multi-tracer multiparametric PET/CT-MR.
Pioneering High-Throughput Micro-NMR in Reproductive Biology: Unveiling Metabolic Profiles in Early Bovine Embryos and Oocytes
Authors: Sivelli Giulia , Marable Kathryn , Gruet Guillaume , Conley Gaurasundar , Grisi Marco
Published: November 2024

Motivation: Traditional methods for early embryos assessment are often invasive or lack detail, underscoring the necessity for non-invasive, high-resolution techniques. Goal(s): The primary goal was to test MRS as a predictive tool for embryo viability. By leveraging microchip-based probes, we analyzed the metabolic profile of early-stage bovine embryos and oocytes. This aimed at predicting developmental outcomes with high precision and accuracy. Approach: In total, we conducted multi-channel high-throughput spectroscopy to perform a minimally invasive analysis of 1 hour on 61 single 8-cell embryos and 84 single oocytes. Results: We found strong correlation between spectra at the 8-cell stage and subsequent development to blastocyst. Impact: This work offers new data for MRS and embryology, laying a foundation to improve fertility treatments by selecting viable embryos. By revealing previously inaccessible data it opens to new embryonic research, potentially revolutionizing our understanding of early developmental biology.
Biomechanical phase angle as proxy to quantify the presence of microvascular invasion in hepatocellular carcinoma
Authors: Mangin Gabrielle , Bacquet Raphaël , Beaufrère Aurélie , Garteiser Philippe , Pagé Gwenaël , Paradis Valérie , Vilgrain Valérie , Sinkus Ralph
Published: November 2024

Motivation: In hepatocellular carcinoma (HCC), microvascular invasion (MVI), an indicator for tumor aggressiveness, is identified typically through post-resection pathology examination. Currently, non-invasive methods for assessing tumor aggressiveness are lacking. Goal(s): Our objective is to discover a non-invasive imaging biomarker for evaluating the presence/absence of MVI. Approach: The alterations induced by the tumor, such as MVI, can modify the tissue architecture and, consequently, its mechanical properties. Magnetic resonance elastography at 40Hz was performed in 44 HCC patients who had liver resection. Results: Peritumoral tissue phase angle accurately distinguish patients with/without MVI, indicative for aggressiveness. These results correlate with higher tumor differentiation in patients without MVI. Impact: This clinical study introduces the phase angle as a new biomarker for gauging HCC aggressiveness whereby enabling patient stratification.
The prognostic value of amide proton transfer-weighted and intravoxel incoherent motion imaging for rectal adenocarcinoma.
Authors: Kan Shiji , Gao Bo , Chen Pengyu , Cheng Yongjun , AI Kai
Published: November 2024

Motivation: To improve the accuracy of rectal cancer staging via imaging techniques. Goal(s): To explore the correlation between amide proton transfer (APT) imaging, intravoxel incoherent motion imaging (IVIM) quantitative parameters, and the pathological traits and prognostic markers of rectal adenocarcinoma. Approach: Standard Magnetic resonance imaging (MRI), APT, and IVIM scans were performed on patients with suspected rectal cancer. Following this, APT and IVIM quantitative parameters were derived. Results: Significant differences in D and D* values were observed across various T stages. However, no substantial variations in APT signal intensity (APTSI), D, D*, f were noted in different N stages, perineural invasion, and vascular invasion. Impact: The research conducted has significant implications for the clinical staging of rectal cancer. By providing a more detailed and nuanced understanding of the disease's progression, it can aid in developing more precise and individualized treatment plans.
Detection Limits and Assessment of the Hepatocellular Content of Lipids using Deuterium Metabolic Imaging: a Pilot Study.
Authors: Pfleger Lorenz , Baumgartner Clemens , Wolf Peter , Scherer Thomas , Bogner Wolfgang , Niess Fabian , Trattnig Siegfried , Krššák Martin
Published: November 2024

Motivation: While HCL can be assessed in vivo using 1H-MRS it may be of interest to determine it with DMI, as this offers the possibility for dynamic studies with incorporation of deuterated substances. Goal(s): Our goal was to explore the detection limits and estimate HCL based on DMI. Approach: 10 healthy subjects were measured in a 7T-MR-system with liver adjusted RF surface coil applying a single-voxel 1H-MRS-GUSTEAU sequence and a 2H-MRSI sequence. HCL was assessed by comparison with the water signal from both measurements. Results: The HCL values were underestimated when applying DMI compared to the well-established 1H-MRS ultra-short echo time GUSTEAU sequence. Impact: Besides the use of 1H-MRS, HCL can also be assessed with DMI. Due to the much lower natural abundance of 2H compared to 1H, the detection limit for 2H-HCL was estimated to be ≥1%.
Differentiation of hepatocellular adenoma and well-differentiated hepatocellular carcinoma using MRI and clinical-based nomogram model
Authors: Zhu Zheng , Hou Lina , Zhao Yanfeng , Zhao Xinming
Published: November 2024

Motivation: Hepatic hyperintense lesions, has been shown to be difficult for differential diagnosis in clinical. Goal(s): Multiple parameters MRI can potentially provide whole insights into hepatic lesion diagnosis. Approach: 144 patients based on hepatic hyperintense lesions (HCA and WDHCC) with presurgical MRI to investigate the differential diagnosis. Results: Results demonstrated that MRI signal model can provide more effective information for the differential diagnosis of hepatic hyperintense lesions especially for HCA and WDHCC. Impact: Differentiating Hepatocellular adenomas (HCA) and well-differentiated hepatocellular carcinoma (WDHCC) via MRI signal-based model could offer a more comprehensive diagnostic approach than clinical factors-based model and combined MRI signal plus clinical factors-based model.
Characterization of small liver lesions using a partial volume corrected T2 mapping technique
Authors: Toner Brian , Keerthivasan Mahesh , Galons Jean-Philippe , Johnson Kevin , Martin Diego , Bilgin Ali , Altbach Maria
Published: November 2024

Motivation: T2 mapping is an effective way to classify benign and malignant lesions within the liver, but existing methods that do not account for partial volume systematically underestimate lesion T2, leading to false positives. Goal(s): To develop a signal model that accounts for partial volume effects to more accurately quantify T2 of liver lesions. Approach: Use a two-compartment signal model tailored for turbo spin-echo acquisitions taking into account the varying lesion fraction across the imaging slice. Results: The proposed method leads to more accurate T2 estimation in the presence of partial volume as demonstrated in simulations, physical phantoms, and subjects with focal liver lesions. Impact: This work presents a turbo spin-echo signal model that accounts for partial volume effects to estimate T2 values of focal liver lesions more accurately. The proposed method improves the accuracy of classifying benign and malignant liver lesions.
Deep-learning-based phase correction during reconstruction of high-resolution, multi-shot reduced-FOV pancreatic DWI.
Authors: Brunsing Ryan , Besser Alexandra , Guidon Arnaud , Wang Xinzeng , Lan Patricia
Published: November 2024

Motivation: Diffusion weighted imaging (DWI) is valuable in pancreatic imaging but suffers from artifacts and low SNR. The combination of reduced FOV imaging with a multishot data sampling strategy (rFOV-msDWI) improves artifacts from susceptibility and allows higher achievable resolution but still suffers from low SNR. Goal(s): Here we report early findings from an ongoing pilot study Approach: Evaluate a DL-based phase correction algorithm for improved SNR in patients undergoing rFOV-msDWI of the pancreas. Results: DL-based phase correction subjectively improves image quality. Impact: DL-based phase correction may improve rFOV-msDWI of the pancreas. Further evaluation is warranted.
Investigating The Effects of The Menstrual Cycle on Glycogen Utilisation and Metabolic Activity During Exercise: A 13C MRS Study
Authors: Bawden Stephen , Dexter Louise , Kaviani Mehri , Wolfe Sarah , Grove Jane , Gowland Penny , Aithal Guruprasad , Matsuda Tomoka
Published: November 2024

Motivation: The menstrual cycle (MC) has been shown to effect muscle glycogen utilisation during exercise but little is known about the full metabolic or glycogenic effects at varying phases. Goal(s): To explore MC effects on exercise-induced changes in metabolites and glycogen stores. Approach: 13C MRS and bloods were acquired from the liver and leg before and after 45 minutes of moderate exercise in healthy females. Test day was repeated 4 times 1 week apart throughout the MC. Results: Previous findings of hormonal effects on muscle glycogen utilization were confirmed. Also, liver glycogen stores appear reduced in later MC days and correlated negatively with progesterone. Impact: This study provides pilot data for future research. 13C MRS allows for the repeated monitoring of glycogen storage and turnover in an ethically viable way. This work has implications in understanding metabolic disorders, medical research and sports science.
Functional and structural connectivity changes in neocortical regions of the brain in a mouse model of Alzheimer’s disease
Authors: Wang Ziyi , Li Hui , Shi Bowen , Qin Qikai , Ye Qiong , Thompson Garth
Published: November 2024

Motivation: The early diagosis of Alzheimer's disease clinically using non-invasive techniques is important, find the relationship of brain structural and functional connectivity will helpful to diagnosing. Goal(s): We used multimodal MRI technique to elucidate the differences between different ages of AD and WT mice and analyze the relationship between brain structure and brain function. Approach: We used rs-fMRI to measure the functional connectivity, used DTI to measure the microstructure and structural connectivity of the brain. Results: Our results showed higher structural connectivity causes higher functional connectivity, but in gustatory region, the functional connectivity had a negative correlation with structure. Impact: Early diagnose is the important part to delay the progression of AD, the relationship of structural and functional connectivity is helpful to drug discovery. Our results suggest several potential early biomarkers for study in young versus old, humans and mice.
Examining the changes of default-mode network in the developmental brain of transgenic monkeys with Huntington’s disease using rsfMRI
Authors: Li Chun-Xia , Zhang Xiaodong
Published: November 2024

Motivation: The dysfunction of the default-mode network (DMN) in Huntington Disease (HD) patients has been reported in previous studies, but the results remain inconclusive. Goal(s): This study aimed to investigate the dysfunction of the DMN during the evolution of the disease using a transgenic monkey model. Approach: Four HD and 4 age-matched wild-type monkeys were utilized and functional connectivity (FC) data at 3, 4 and 5 years of age were analyzed. Results: Decreased FC in posterior cingulate cortex (PCC) - PCC and increased FC in anterior cingulate cortex (ACC) - PCC in HD monkeys were observed. Impact: The findings suggest divergent FC alteration patterns in different DMN area exist concurrently with the evolution of the disease, and the monkey models could provide a unique platform for preclinical studies of dysfunctionality and cognitive decline in HD.
Correlations of Blood and Brain NMR Metabolomics with Mouse Models of Alzheimer’s Disease
Authors: Knörnschild Franz , Zhang Ella , Kobus Marta , Chen Jiashang , Zhou Jonathan , Sun Joseph , Wang Xiaoyu , Li Wei , Muti Isabella , Habbel Piet , Nowak Johannes , Xie Zhongcong , Zhang Yiying , Cheng Leo
Published: November 2024

Motivation: Alzheimer’s disease (AD) diagnosis currently relies on clinical evaluation, and definitive disease characterization can only be accomplished from tissue pathology during autopsy. Goal(s): Evaluations of AD metabolomics using nuclear magnetic resonance (NMR) spectroscopy to identify potential biomarkers that can differentiate AD from non-AD conditions. Approach: We collected cortex, hippocampus, and blood samples from mice with and without AD, followed by NMR analysis. Results: NMR could differentiate between AD and wild-type (WT) conditions for all tissue types, and metabolomic differences in several spectral regions were observed across disease conditions, leading to the identification of potential contributing metabolites and metabolic pathways. Impact: HRMAS NMR-based metabolomic evaluations can differentiate mice with and without Alzheimer’s disease (AD), characterize metabolic states within brain and blood samples, and identify possible AD biomarkers. It has potential for in vivo implementation and may improve AD diagnosis in clinic.
Longitudinal changes of in vivo Quantitative Susceptibility Mapping (QSM) in the 3xTg-AD mouse model of Alzheimer's disease
Authors: Ye Qiong , Wang Ziyi , Li Hui , Shi Bowen , Thompson Garth
Published: November 2024

Motivation: To investigate the longitudinal change of in vivo QSM of 3xTg-AD mice, age matched wile-type (WT) mice were used as a reference group. Goal(s): The regional variation of in vivo QSM in 3xTg-AD mice, and how they change with ageing. To investigate the sensitivity of in vivo QSM to the pathophysiological changes in 3xTg-AD mice. Approach: The 3xTg-AD and WT mice with 22 and 40 weeks old were scanned. A 3D multi-echo gradient echo sequence (mGRE) was acquired for the quantification of QSM. Results: Notable differences in QSM values were observed between various brain regions across ages and genotypes. Impact: The in vivo QSM of the mouse brain can be obtained within approximately 21 minutes of scanning time. Significant variations were observed between different age groups and genotypes in various brain regions closely associated with the pathophysiology of Alzheimer's disease.