bluuebunny/crossref_metadata_2025 huggingface dataset:
A Versatile Setup for Measuring Complex Gradient-to-Acoustic-Noise or Gradient-to-Vibration Transfer Functions via the Scanner’s ADC
Authors: Müller Roland , Mildner Toralf , Wallstein Niklas , Möller Harald
Published: November 2024

Motivation: Knowledge of gradient transfer functions in situ would allow predictions about the auditory spectrum of arbitrary MRI sequences during execution, to achieve individualized assessments of potentially harmful sound levels or damaging vibrations of the gradient coil. Goal(s): Our goal was to enable the integration of appropriate sound or vibration measurements into the routine operation of a scanner. Approach: A modulator box was developed that emulates a receiver coil and permits the simultaneous digitization of variable sensor signals (e.g., microphones and accelerometers) by the scanner's ADC. Results: Realistic gradient-to-acoustic-noise and gradient-to-vibration transfer functions were determined without the need of synchronizing external devices. Impact: A versatile hardware concept has been developed that allows integration into a clinical scanner and prediction of the sound level inside the bore from the frequency spectrum of the input signal defined by the pulse sequence during scanning.
Concept 0.13 T bedside MRI for early brain imaging in the neonatal intensive care unit.
Authors: Purchase Aaron , Sliwiak Monika , Bates Sara , Stockmann Jason , Hurlimann Martin , Wald Lawrence , Cooley Clarissa
Published: November 2024

Motivation: Despite the high diagnostic value of MRI, safety concerns and logistical burdens often prohibit the transport of neonatal intensive care unit (NICU) patients to standard MRI scanners. Goal(s): In response, we aim to design a specialized NICU bedside MRI scanner that prioritizes minimal disruption to care and provides a higher field strength (and signal-to-noise) than currently available portable scanners. Approach: Using realistic finite element modeling and genetic algorithm optimization, we demonstrate a 131mT Halbach magnet design with a peak-to-peak homogeneity of 421ppm over a 14cm diameter spherical volume. Results: We present the computer-aided-design prototype of the full portable NICU MRI system. Impact: The bedside MRI scanner capable of diffusion contrast neuroimaging of neonates could bring a new early evaluation tool for brain conditions such as hypoxic ischemic encephalopathy (HIE).
Improved Hepatocellular Carcinoma Targeted Combination Immunotherapy Using a Nanocarrier: Monitoring Tumor Response via Functional MRI
Authors: Li Jiamin , Wei Ruili , Yang Ruimeng , Jiang Xinqing , Xu Yongzhou
Published: November 2024

Motivation: To enhance the efficacy of hepatocellular carcinoma immunotherapy using a nanocarrier and to explore IVIM-MRI for monitoring the tumor immune microenvironment. Goal(s): To synthesize iRGD-targeted liposomes to enhance the treatment efficacy of hepatocellular carcinoma and to develop effective biomarkers for the tumor microenvironment. Approach: We synthesized iRGD-modified liposomal co-encapsulating Lenvatinib and BMS-202. IVIM-MRI was performed before and at 6 and 12 days after treatments, followed by pathological examination after the final scan. Results: iRGD-lip@Len/BMS-202 promotes tumor vascular normalization and effectively activates an anti-tumor immune response. Importantly, the derived parameters D* and f are significantly correlated with tumor vascular normalization and immune activation. Impact: The iRGD-targeted dual-drug liposomal nanoparticles exhibited potent synergistic anti-tumor effects. Additionally, IVIM-MRI facilitated the monitoring of changes in the tumor microenvironment, with the D* and f parameters serving as valuable indicators for evaluating tumor vascular network and immune microenvironment modulation.
Intravoxel incoherent motion model for prediction of tertiary lymphoid structures in HCC.
Authors: Ma Lidi , Zhang Xiaolan , Zhou Fan , Geng Zhijun , Xie Chuanmiao
Published: November 2024

Motivation: Intra-tumoral tertiary lymphoid structures (TLSs) are associated with a favorable prognosis for patients with hepatocellular carcinoma (HCC). Intravoxel incoherent motion (IVIM) sequences describe heterogeneity of tumor components. Goal(s): We aimed to explore the value of intravoxel incoherent motion (IVIM) sequences in predicting TLSs. Approach: IVIM quantitative parameters and radiomics features were obtained. A fusion model based on the above and clinical characteristics was constructed. Receiver operating characteristic curve analysis was performed to assess the diagnostic performance of different models for TLSs prediction. Results: Radiomics features based on IVIM-DWI can be better conducive to preoperative prediction of TLSs in patients than IVIM parameter maps. Impact: TLSs exhibit considerable promise in prognostic prediction and the identification of appropriate candidates for immunotherapy. The fusion model based on the IVIM-DWI showed great performance in predicting TLSs, assisting the selection of clinical immunotherapy patients.
MR radiomics to predict microvascular invasion status and biological processes in combined hepatocellular carcinoma-cholangiocarcinoma
Authors: Xiao Yuyao
Published: November 2024

Motivation: Prognostic value of microvascular invasion (MVI) in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) was verified, and an effective prediction model is warranted to facilitate risk stratification and individual management. Goal(s): To establish an MRI-based radiomics model for predicting MVI status of cHCC-CCA, and to investigate biological processes underlying the radiomics model. Approach: Clinical data, conventional MR features, MR-based radiomics features and RNA sequencing data were collected and analyzed. Results: A robust MRI-based radiomics model was established for predicting MVI status in cHCC-CCA, in which potential prognostic value and underlying biological processes that regulate immune response were demonstrated. Impact: MVI is a significant manifestation of tumor invasiveness,and the MR-based radiomics model established in our study will facilitate risk stratification. Furthermore, underlying biological processes demonstrated in radiomics model will offer valuable insights for guiding immunotherapy strategies.
MRI-based prediction of microvascular invasion or high tumor grade and adjuvant therapy benefit for solitary HCC ≤5 cm
Authors: Jiang Hanyu , Li Binrong , Zheng Tianying , Qin Yun , Wu Zhenru , Ronot Maxime , Chernyak Victoria , Fowler Kathryn , Bashir Mustafa , Chen Weixia , Wang Yuan-Cheng , Ju Shenhong , Song Bin
Published: November 2024

Motivation: Noninvasive assessment of high-risk histopathology (microvascular invasion or Edmondson-Steiner G3/4) for early HCC is critical but challenging. Goal(s): To develop an MRI-based diagnostic model for high-risk histopathology. Approach: This dual-center retrospective study included consecutive patients who underwent contrast-enhanced MRI and subsequent curative resection or RFA for solitary BCLC 0/A HCC≤5 cm. A diagnostic model was developed against pathology based on resection-treated patients. Results: 554 patients were included. Serum α-fetoprotein, non-simple nodular growth subtype, and the VICT2 trait constituted the model (testing center AUC, 0.828). Adjuvant therapies were associated with improved RFS (resection, P=.009; RFA, P=.009) for the model-positive patients. Impact: This dual-center study developed and externally validated a diagnostic model which could effectively predict high-risk histopathology and adjuvant therapy benefit for patients receiving curative resection or radiofrequency ablation for solitary BCLC 0 or A HCCs ≤5 cm.
39K/23Na-MRI at 7T for assessment of ionic balance combined with fat quantification at 3T in myofibrillar myopathies
Authors: Mathy Claudius , Gast Lena , Holtzhausen Christian , Gerhalter Teresa , Türk Matthias , Heiß Rafael , Dörfler Arnd , Uder Michael , Nagel Armin , Schröder Rolf
Published: November 2024

Motivation: Recent advances have enabled the application of 39K-MRI in skeletal muscle in vivo. Moreover, information on disease progression/pathogenesis from non-invasive 1H-MRI is still limited. Goal(s): Determination of apparent tissue potassium and tissue sodium concentrations (aTPC/aTSC) in myofibrillar myopathies. Approach: Less severe effected lower legs of 10 patients with filaminopathy-, desminopathy- and zaspopathy-causing mutations measured by 39K/23Na-MRI at 7T and Dixon-type-sequence at 3T. Results: Fat-corrected ion concentrations were significantly altered in calf muscles of all patients with myofibrillar myopathies in comparison to healthy control subjects. Despite incoherencies with respect to disease progression and etiology fat-corrected aTSC were in- and aTPC were decreased. Impact: Combined 39K/23Na-MRI detects changes in ionic balance beyond fatty replacement of muscle in a diverse cohort of myofibrillar myopathies. Further studies are needed to investigate whether different genotypes or whether disease progression can be detected in early stages by 39K/23Na-MRI.
A new handle on extracellular diffusion and exchange? Single and double diffusion encoded MRS in humans after MSM ingestion
Authors: Lundell Henrik , Bouyagoub Samira , Döring André , Dowell Nick , Kreis Roland , Ronen Itamar
Published: November 2024

Motivation: The investigation of extracellular spaces with diffusion weighted MRI andMRS is limited by the ubiquitous distribution and fast exchange of water, while endogenous metabolites are mostly intracellular. Goal(s): Investigate the diffusion characteristics of ingested MSM compared to water and endogenous metabolites. Approach: Multi b-valued single and double diffusion encoded MRS in humans at 3T. Results: MSM diffuses anisotropically, but considerably faster than intracellular metabolites, and exhibits a substantially different behavior compared to both water and metabolites. Impact: MSM provides a novel probe of extracellular spaces similar to water but with differences that could be rotted in different transmembrane exchange properties.
Characterization of neurite and soma organization in the in vivo spinal cord with diffusion MRI
Authors: Schilling* Kurt , Palombo* Marco , O'Grady Kristin , Pizzolato Marco , Landman Bennett , Smith Seth
Published: November 2024

Motivation: Multicompartment models of diffusion MRI have proven valuable in the brain. Goal(s): However, application of these models in the spinal cord (SC) remains relatively understudied. Approach: Here, we address challenges related to acquisition and image processing in order to apply the Soma and Neurite Density Imaging (SANDI) model in the human SC in 11 healthy subjects. Results: We show that SANDI captures differences between white and gray matter tissue types and across the functionally relevant white matter pathways and gray matter architectures and has the potential to act as a biomarker for biomedical applications. Impact: We show that the Soma and Neurite Density Imaging (SANDI) diffusion model is a feasible method to characterize both white and gray matter tissue microstructure of the in vivo human spinal cord on clinical scanners.
Safe Spirals for Your Scanner
Authors: McCready Matthew , Liao Congyu , Pauly John , Kerr Adam
Published: November 2024

Motivation: Vibration of gradient coils is a source of loud acoustics, signal dropout, field distortion, and potential system damage particularly at mechanical resonant frequencies. Goal(s): To design safe spiral gradient waveforms which avoid mechanical resonant frequencies and their resulting severe vibrations. Approach: Instantaneous gradient frequency during spiral readout is estimated as the rotational frequency of a circle at the current k-space radius and gradient amplitude. Amplitude is limited to drop through resonant bands quickly. A convex problem for spiral rewinders is formed minimizing the DFT at resonant frequencies. Results: Coil vibration was significantly reduced using safe spirals, and gradient field oscillations were minimized. Impact: Frequency constrained “safe” spiral waveforms were shown to avoid specified frequency bands, reducing gradient vibrations and k-space oscillations without degrading image quality. Such waveforms could potentially prolong gradient coil lifetime, reduce acoustic discomfort, and remove artefacts from persisting k-space oscillations.
Open-Source, Cross-Platform Workflow for MRI Data Acquisition and Image Reconstruction Based on the Pulseq Framework
Authors: Chen Qingping , Zijlstra Frank , Hucker Patrick , Littin Sebastian , Zaitsev Maxim
Published: November 2024

Motivation: To enhance efficiency, transparency, and reproducibility of data acquisition and reconstruction in large-scale MRI studies. Goal(s): To establish an open-source, cross-platform, easy-to-learn data acquisition and reconstruction workflow. Approach: The Pulseq framework is extended to integrate Siemens’ “Image Calculation Environment” (ICE) and Gadgetron. To validate the workflow, MPRAGE and EPI sequences were developed using the extended Pulseq and executed on three Siemens scanners with comparison to the corresponding product sequences. Results: The preliminary results show that Gadgetron had comparable reconstruction performance to ICE, and Pulseq sequences generally produced image quality comparable to product sequences. Online Gadgetron and ICE produce images within seconds/minutes after measurements. Impact: An open-source, cross-platform MRI data acquisition and reconstruction workflow is established by extending the Pulseq framework to link to reconstruction tools. The preliminary results indicate that this workflow has the potential to enable efficient, transparent, reproducible data acquisition and reconstruction.
Fast volumetric Cartesian MRI with auto-calibrated local B0 coil array – a reproducing kernel Hilbert space perspective
Authors: Tian Rui , Uecker Martin , Holder Oliver , Steffen Theodor , Scheffler Klaus
Published: November 2024

Motivation: The local B0 coil array has been shown to speed up 2D Cartesian MRI and provides a platform for investigating the most efficient B0 encoding fields. Nevertheless, optimizing the rapid modulations for accelerating volumetric scans without introducing additional artifacts becomes more challenging. Goal(s): We explore distinct nonlinear modulation B0 fields and reconstruct artifact-free accelerated images. Approach: With a recent RKHS framework, the k-space efficiency maps for various modulation fields are analyzed, and a novel auto-calibration reconstruction method is introduced. Results: Our k-space analysis provides insights validating optimal modulation fields, and the ex-vivo and in-vivo scans demonstrate the robustness of the proposed reconstruction technique. Impact: We demonstrate the RKHS formalism as a valuable tool for understanding 3D MRI scans encoded with nonlinear modulation fields. Our auto-calibration reconstruction, analogous to GRAPPA in parallel imaging, offers a promising approach for image acceleration with rapid B0 modulation.
Pushing contrast at low field with very high B1
Authors: Leitão David , Ipek Ozlem , Prathapan Avanya , West Daniel , Hajnal Jo , Wood Tobias , Malik Shaihan
Published: November 2024

Motivation: Inherently reduced SAR at low B0 fields opens the possibility for sequences employing high B1 to generate contrasts inaccessible on common systems. Goal(s): Explore generation of magnetization transfer (MT) and inhomogeneous MT (ihMT) contrast using high B1 sequences on low-field MRI system. Approach: A tuned resonator was used to enhance B1 fields locally within a 0.55T scanner. Rapid gradient-echo based MT/ihMT sequences were tested on ex-vivo lamb brain sample. Results: Achieved ~9-fold increase in B1, boosting observed MTR/ihMTR. Unexpectedly, RF pulses failed to function at high B1 due to Bloch-Siegert and spin-locking; new pulse designs for this regime will form future work. Impact: Using high B1 fields at low B0 enables contrasts that were previously off-limits due to safety constraints at high B0. To exploit these with clinical hardware we demonstrate a passive resonator that increases the B1 by a factor of 9.
Topological network analysis and virtual brain modelling combined to portray subject-specific profiles of dementia stages.
Authors: Monteverdi Anita , Palesi Fulvia , Manzon Sofia , Conca Francesca , Mazzocchi Laura , Ramusino Matteo Cotta , Lupi Eleonora , De Grazia Marialaura , Lorenzi Roberta , Gaviraghi Marta , Farina Lisa , Costa Alfredo , Pichiecchio Anna , Cappa Stefano , Wheeler-Kingshott Claudia Gandini , D'Angelo Egidio
Published: November 2024

Motivation: The high level of heterogeneity typical of mild cognitive impairment (MCI) condition currently hinders the selection of a personalized effective therapy. Goal(s): Our goal is to obtain a personalized profile exploring not only structural and functional topology but also diving in subject-specific physiological parameters. Approach: Starting from structural and functional connectomes, we combined graph theoretical analysis with virtual brain models in the default mode network of healthy subjects, MCI and Alzheimer's disease patients. Results: Our results offer a detailed description of alterations at single-subject level, illustrating differences between dementia stages based on topology and subject-specific physiological parameters. Impact: The personalized profile obtained combining graph theory and virtual brain models portray dementia stages at single-subject level, capturing the wide heterogeneity of mild cognitive impairment and opening new perspectives for personalized effective interventions.
A Multi-Modal Biomechanical Imaging and Analysis Framework for Co-Correlation of 7T MR Elastography, 7T DTI, and Amyloid Deposition
Authors: Triolo Em , Langan Mackenzie , Khegai Oleksandr , Binder Sarah , Hedden Trey , Balchandani Priti , Kurt Mehmet
Published: November 2024

Motivation: There is currently a profound need for non-invasive early detection of mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Goal(s): The purpose of this study is to determine the relationships between imaging and cognitive testing metrics. Approach: Subjects underwent multimodal imaging, including 7T DTI, 7T MRE, and amyloid PET, and a PACC test. These metrics were used in Shapley Regressions to determine which metrics were the best predictors of MRE or SUVR. Results: We determined that SUVR was the best predictors of MRE metrics, and that MRE was one of the best predictors of SUVR in subjects with amyloidosis. Impact: Using multimodal imaging at ultrahigh field (7T) we have observed preliminary relationships between amyloid deposition and biomechanical and microstructural metrics as determined by 7T MR Elastography and DTI in the human brain.
Increased Extra-neurite Conductivity of Brain in Patients with Alzheimer’s Disease
Authors: Jahng Geon-Ho , Hong Seowon , Choi Yunjeong , Lee Mun Bae , Rhee Hak Young , Park Soonchan , Ryu Chang-Woo , Jin Wook , Kwon Oh In
Published: November 2024

Motivation: The decomposed high-frequency conductivity (HFC) into extra-neurite and intra-neurite components to calculate compartmental conductivities has not been applied to any neurological conditions. Goal(s): To investigate how the separated extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer’s disease (AD) patients and to evaluate the association between compartmental conductivities and cognitive declineApproach: A total 66 patients included in 20 AD patients, 25 amnestic MCI patients, and 21 controls were scanned with a multi-echo turbo spin-echo and multi-shell diffusion tensor EPI sequences. Results: The EC value was higher in patients with AD than others and decreased with increasing K-MMSE scores. Impact: The EC value might be used as an imaging biomarker for helping to monitor cognitive function.
Volumetric MR, Blockface Imaging, and Histology Deliver High Fidelity Coregistered MR-Histology
Authors: Wang Yixin , Ho William , Huszar Istvan , Taghavi Hossein Moein , Nirschl Jeff , Leventis Samantha , Schlömer Philip , Axer Markus , Shao Wei , Rusu Mirabela , DiGiacomo Phillip , Georgiadis Marios , Zeineh Michael
Published: November 2024

Motivation: Validating pathological findings from ultra-high-resolution ex-vivo MRI through histology is significant but challenging due to nonlinear 3D deformations between MRI and histological samples. Goal(s): Addressing the challenge of accurately quantifying complex neurodegenerative diseases by improving the alignment of post-mortem MRI data with histological images. Approach: We built a novel pipeline integrating advanced imaging techniques with innovative registration algorithms, linking high-resolution MRI with blockface imaging and histological sections. Results: Our methodology successfully generated blockface volumes with minimal distortion and artifacts, accomplished precise alignment between MRI and blockface volumes, and achieved an accurate 2D correspondence between MRI and histology slides. Impact: This study introduces an advanced correlative MRI-histology pipeline with robust 2D and 3D coregistration methods, promising to enhance our understanding of neurodegenerative diseases and contribute to the evolution of MRI-based biomarkers for the disease.
Quantitative chemical exchange saturation transfer MR imaging of the substantia nigra and red nucleus in Parkinson’s disease
Authors: Li Xinyang , Tian Yaotian , Zheng Dandan , Li Chunmei , Chen Min
Published: November 2024

Motivation: Achieving precise quantification of target molecules has been a prominent focus of chemical exchange saturation transfer (CEST) . Goal(s): To investigate the alteration of CEST-MRI in the bilateral substantia nigra (SN) and red nucleus (RN) in Parkinson’s disease (PD) and to explore its value of clinical application. Approach: The signal change of CEST imaging was separated using the 4-pool Lorentz fitting model. The amide, nuclear overhauser enhancement (NOE), direct water saturation (DS), and magnetization transfer (MT) value were compared between the PD and NC group. Results: The results indicated that CEST-MR can reveal the signal alterations the SN and RN in PD patients. Impact: CEST-MRI, utilizing the 4-pool Lorentz fitting model, was employed to accurately delineate the amide signal alterations within the SN and RN of patients with PD. This approach demonstrates significant promise for enhancing the clinical diagnosis of PD.
Brain Region Mapping and Quantification of White Matter Hyperintensity: Estimating the Direct and Indirect impact of WMH Load on Cognition
Authors: Gupta Niraj , Yadav Neha , Tiwari Vivek
Published: November 2024

Motivation: Understanding the magnitude and threshold of PVWMH and DWMH that disrupt cognitive abilities in MCI and AD, compared to healthy aging. Goal(s): To investigate white matter hyperintensity distribution & its impact on cognitive functions. Approach: Neuroanatomic segmentation & quantification of Periventricular WMH and DeepWMH, with mediation analysis assessing their impact on cognitive functionsResults: WMH load accrues vascular insult to brain structures, which in-turn mediates impaired cognitive functions, specifically motor and executive functions. WMH load in periventricular region abrogates the information processing and processing speed indirectly mediated through paracentral gyrus thickness, rostral middle frontal volume and lingual gyrus thickness. Impact: Periventricular white matter hyperintensity progresses faster compared to DeepWMH with Aging. We establish that the Regional Distribution of DeepWMH load is distinct for CN, MCI and AD. High WMH load impairs Executive memory and Motor Memory via specific structural atrophy.
RAFF4, magnetization transfer and diffusion tensor MRI in a mouse model of demyelination and remyelination
Authors: Dvořáková Lenka , Salo Raimo , Laakso Hanne , Kyyriäinen Jenni , Zehnder Thamara , Mueggler Thomas , Künnecke Basil , Sierra Alejandra , Gröhn Olli
Published: November 2024

Motivation: In vivo assessment of myelin status is important for diagnostic and therapeutic purposes in multiple sclerosis. Goal(s): The goal of this study was to explore the capability of RAFF4, MT, and DTI metrics to detect changes in the myelin content and integrity during both demyelination and remyelination. Approach: A genetic mouse model of widespread demyelination and remyelination was imaged with RAFF4, MT, and DTI and the MRI metrics were compared with histological analyses. Results: Both RAFF4 and MT detected differences between the disease model and control animals in both demyelination and remyelination. DTI differed only in the demyelination phase. Impact: RAFF4 showed the ability to detect both demyelination and remyelination in the mouse brain. This suggests that RAFF4 has great potential in serving as a translational biomarker in the development of new therapeutic agents for myelin repair.
CSF Outflow and Egress in Optic Nerve: Non-contrast MRI Revelations
Authors: Vucevic Diana , Malis Vadim , McDonald Marin , Miyazaki Mitsue
Published: November 2024

Motivation: The rose of cerebrospinal fluid (CSF) in neural health is recognized, yet its outflow and egress within the optic nerve, especially amidst new findings about the glymphatic system, remains less explored. Goal(s): Investigate CSF interactions within the optic nerve using advanced MRI techniques, highlighting implications for conditions like glaucoma. Approach: Utilized advanced Time-Slip sequences on a 3-T MR imager, targeting specific brain regions to study CSF outflow and egress. Results: Clear CSF egress pathways through the optic nerve were found, with distinct outflow influenced by participants’ optical attributes. Impact: Enhances understanding of CSF outflow and egress, providing pivotal insights for addressing neuro-ophthalmological disorders like glaucoma.
Localized convolutional function regression: A computational method for measuring interstitial fluid flow and perfusion in DCE-MRI
Authors: Woodall Ryan , Esparza Cora , Gutova Margarita , Wang Maosen , Cunningham Jessica , Brummer Alexander , Stine Caleb , Brown Christine , Munson Jennifer , Munson Jennifer , Rockne Russell
Published: November 2024

Motivation: Aggressive gliomas are known to migrate in the direction of interstitial fluid flow (IFF), though it is difficult to measure interstitial fluid flow using MRI. Goal(s): Our goal is to develop a computational method for measuring IFF using DCE-MRI. Approach: We developed localized convolutional function regression (LCFR), validated in silico, in porous hydrogel, and apply it to in vivo tumors. Results: LCFR accurately measures fluid flow and perfusion to less than 10% error in silico, and measures IFF in a mouse model of glioma to be 1.63E-3 mm/s. In a case study, the method tentatively predicts invasion across the corpus collosum. Impact: This method will allow physicians and researchers to investigate how highly aggressive gliomas invade healthy tissue, and can be further used to predict how therapeutic agents or cells will disperse throughout the tumor, predicting disease progression and response.
Deep Learning techniques to predict treatment outcomes in newly diagnosed epilepsy
Authors: Mishra Debabrata , Chang Richard Shek-kwan , Ngyuen Shani , Thom Daniel , Nazem-Zadeh Mohamad , Chen Zhibin , Law Meng , Kwan Patrick , Sinclair Benjamin
Published: November 2024

Motivation: Epilepsy is a complex neurological disorder with a high degree of heterogeneity. Selecting the appropriate antiseizure medication(ASM) is a time-consuming trial-and-error process that requires expert knowledge from neurologists. Goal(s): Our goal was to utilise Deep Learning(DL) techniques with neuroimaging information to predict the treatment outcome of ASM. Approach: We developed a DL model that utilises multi-modal information (MRI scans and clinical characteristics) to predict seizure outcomes of initial ASM for patients with newly diagnosed epilepsy. Results: Our model achieved AUROC/AUPRC of 0.72/0.71 respectively in predicting treatment outcomes, demonstrating the potential of brain MRI scans as a biomarker for treatment response. Impact: The model showed promise for development of decision-support systems that could help neurologists select the best ASM, potentially improving treatment outcomes. Clinical translation will require larger datasets and external validation, but this work implies that MRI contains additional prognostic information.
4D Dynamic Brain PET Prediction Using Anatomical and Statistical Models
Authors: Yousefi Hamed , Yousefi Hamed , Ying Chunwei , Wang Yujie , Wang Biwen , An Hongyu
Published: November 2024

Motivation: The reduction in PET scan duration not only improves the efficiency of the scanning process but also contributes to a more comfortable experience for patients. Goal(s): Leveraging the temporal models in conjunction with previously predicted weights of PCs, we aim to reconstruct entire 4D dynamic PET frames using an inverse PCA method. Approach: A novel technique has been developed to generate pseudo-T1 images from noisy 4D PET data, as well as the reverse process, obtaining the initial components of 4D dynamic PET images from MRI data. Results: The results endorsed that only 5 minutes observation is enough to predict whole 70 minute data. Impact: We predicted later PET frames from noisy initial frames using a novel approach combining anatomical and statistical temporal PCs from MRI data. This method has clinical potential for insights into dynamic processes, radiation reduction, and identifying abnormalities in medical imaging.
A Multi-Parametric MRI Deep Learning Fusion Model for Grading Arterial Transit Artifacts
Authors: Tian Yuchi , Li Yi , Liang Xiaoyun
Published: November 2024

Motivation: ATAs are essential indicators of collateral pathways in cerebral perfusion anomalies. However, the conventional grading systems for ATA suffer from subjectivity, which may subjectively leads to variabilityGoal(s): We aim to standardize ATA grading by a deep learning fusion model that combines information from ASL and DWIApproach: A deep learning fusion model was developed, which applies two 3D CNNs to extract respective feature map of each modality; this model combines the high-level feature maps to fuse the multi-sequence MRI informationResults: The fusion model shows significant improvements over a single modality model, achieving an AUC value of 0.895Impact: The good ATA evaluation performance of the deep learning fusion model shows its clinical potential in assisting neuroradiologists in conducting the treatment and prognosis analysis for patients with ischemic stroke
MR-Transformer: Vision Transformers for Total Knee Replacement Prediction using Magnetic Resonance Imaging
Authors: Zhang Chaojie , Chen Shengjia , Rajamohan Haresh Rengaraj , Cho Kyunghyun , Kijowski Richard , Deniz Cem
Published: November 2024

Motivation: Current deep learning methods for assessing knee osteoarthritis have limitations in learning long-range spatial information from magnetic resonance imaging (MRI). Goal(s): This study aims to develop a new deep learning model for total knee replacement (TKR) prediction using MRI. Approach: We proposed a novel transformer-based model, MR-Transformer, adapted from the ImageNet pre-trained vision transformer DeiT-Ti. The model can capture long-range spatial information from MR images with transformer architecture. We evaluated our model on TKR prediction using MR images with different tissue contrasts. Results: The experimental results demonstrated an improved performance of MR-Transformer compared to conventional deep learning models. Impact: Our proposed MR-Transformer enhances computer-aided diagnosis accuracy in total knee replacement prediction using MRI. It has the potential to provide rapid and quality diagnostic outcomes, assisting physicians in making timely and informed treatment decisions.
Fully automated analysis of contrast agent-free T1-rho mapping for enhanced myocardial tissue characterization
Authors: de Villedon de Naide Victor , Narceau Kalvin , Villegas-Martinez Manuel , Ozenne Valéry , Nogues Victor , Brillet Nina , Zhang Jana Huiyue , Ben lala Ilyes , Stuber Matthias , Cochet Hubert , Bustin Aurélien
Published: November 2024

Motivation: Contrast agent-free myocardial T1-rho (T1ρ) mapping has shown promise in myocardial injury quantification. However, the lack of analysis tools hinders its clinical use and induces increased workload and operator variability. Goal(s): To explore the feasibility and benefits of clinically-integrated artificial intelligence-driven analysis of myocardial T1ρ mapping. Approach: The automated process combines left ventricular wall segmentation, right ventricular insertion point detection and the creation of a 16-segment American Heart Association model for segmental T1ρ values analysis. Results: Automated T1ρ mapping showcased strong agreement with manual processing, enhanced with time efficiency. Impact: Artificial intelligence-driven analysis of myocardial T1-rho mapping exhibits strong agreement with manual processing, bolstered by time efficiency. This approach shows promise for the rapid and non-invasive assessment of heart disease without the need for contrast agents.
Accelerated multi-shell diffusion MRI with Gaussian processes estimated reconstruction of multi-band imaging
Authors: Ye Xinyu , Miller Karla , Wu Wenchuan
Published: November 2024

Motivation: Advanced diffusion MRI models that utilize multi-shell data provide higher specificity about tissue microstructure but require longer scan time, hindering wider application. Goal(s): To increase the acquisition speed of multi-shell diffusion MRI for rapid tissue microstructure mapping. Approach: We integrated multi-band imaging with the extended multi-shell Diffusion Acceleration with Gaussian process Estimated Reconstruction (ems-DAGER), including eddy-current corrected joint k-q reconstruction. The method was evaluated with in vivo data. Results: Simulated and in-vivo results demonstrate that ems-DAGER method can significantly improve the image quality of reconstructed dMRI data with both in-plane and slice-wise acceleration to enable advanced multi-shell diffusion analysis. Impact: Highly accelerated dMRI with the proposed method can shorten the scan time of multi-shell dMRI without sacrificing quality compared to conventional practice. This may facilitate a wider application of advanced dMRI models in basic and clinical neuroscience.
0.9mm isotropic 1min MPRAGE using highly-accelerated Deep learning Reconstruction for Brain Structural Analysis
Authors: Watanabe Keita , Kasai Sera , Umemura Yoshihito , Tatsuo Soichiro , Oyu Kazuhiko , Nozaki Atsushi , Zhu Xucheng , Wakayama Tetsuya , Kakeda Shingo
Published: November 2024

Motivation: The project was driven by the need to reduce 3D T1-weighted MRI acquisition times, which are often prolonged, leading to motion artifacts and compromised image quality in structural nuroimaging analysis. Goal(s): To evaluate whether deep learning reconstruction can shorten MRI scan times without significantly compromising image quality, facilitating efficient clinical and research neuroimaging. Approach: We employed a deep learning technique, DL-speed, to reconstruct undersampled data from accelerated MRI scans, assessing image quality against conventional methods using a standardized rating system. Results: Images with DL-speed maintained image quality, despite a slight quality trade-off, suggesting its viability for rapid, motion-artifact-reduced neuroimaging in various patient populations. Impact: Our results impact clinicians and patients by enabling faster, high-quality MRIs, reducing patient discomfort and motion-related artifacts. This advance opens avenues for more efficient neuroimaging protocols, enhancing patient care and research productivity.
Non-invasive magnetic resonance imaging agent for in-vivo detection of cardiac fibrosis.
Authors: Vollett Kyle , Hong Anlan , Cheng Hai-Ling
Published: November 2024

Motivation: Fibrosis is a progressive pathological process that contributes to 45% of deaths worldwide and is associated with the accumulation of collagen and the destruction of tissue architecture. While progression of fibrosis is often slow, early detection is difficult, leading to intervention at late stage when transplant may be the only option. Goal(s): Establish a targeted MRI contrast agent for detecting early fibrosis. Approach: Validation of agent sensitivity in-vivo with isoproterenol-induced heart fibrosis in a mouse model. Results: Our novel fibrosis agent surpassed the sensitivity and specificity of Gd contrast enhanced T1 mapping for detecting mild cardiac fibrosis. Impact: This project sets out to create a new, hitherto inaccessible window on fibrogenesis, providing a new paradigm for diagnosing patients with fibrosis and the study of anti-fibrosis intervention before fibrosis becomes extensive and irreversible.
Nanodiamonds as a novel T1-contrast agent for MRI
Authors: Lazovic Jelena , Sitti Metin
Published: November 2024

Motivation: The structural defects in diamond particles, are known for their paramagnetic properties. Here we aim to determine if the presence of paramagnetic centers in detonation nanodiamonds particles can be exploited to enhance longitudinal relaxation time (T1). Goal(s): Introduce nanodiamonds as a novel T1-contrast agent and contrast differences with gadolinium chelates. Approach: Using high-field, 7 T MRI, longitudinal and transverse relaxation rates were measured and compared between detonation and air-oxidized detonation nanodiamonds. In-vivo demonstration was carried out using chicken embryos. Results: Air-oxidized detonation nanodiamonds have superior longitudinal and transverse relaxivity compared to detonation nanodiamonds. We demonstrate their potential as an alternative, gadolinium-free T1-contrast agent. Impact: Nanodiamonds hold great promise for biomedical applications mostly due to their biocompatibility, non-toxicity and versatile functionalization. A possibility for direct visualization by means of T1-weighted MRI is opening new venues for tracking over time without a concern for Gd3+-toxicity.
Validating DCE-MRI estimates of leakage volumes associated with subtle blood-brain barrier dysfunction using two-photon microscopy.
Authors: Kozár Martin , Al-Bachari Sarah , Parkes Laura , Boutin Hervé , Schiessl Ingo , Dickie Ben
Published: November 2024

Motivation: DCE-MRI can be used to quantify subtle blood-brain barrier disruption. In this setting, it is generally assumed that contrast agent has access to the entire interstitial space. Prior work from our group indicates that contrast agent has access to a leakage volume much smaller than the interstitial space. Goal(s): To provide independent validation of DCE-MRI leakage-to-vessel volume ratios (ve/vb) in the case of subtle BBB impairment. Approach: The ve/vb ratio of Sulphorhodamine-101 (MW = 606.7g/mol) was measured in mouse brain using two-photon microscopy and compared to DCE-MRI estimates. Results: The ve/vb ratio of sulphorhodamine-101 agrees well with DCE-MRI estimates. Impact: Our results indicate that DCE-MRI kinetic models that assume infinite leakage volume (e.g. Patlak model) do not accurately reflect how Gd-DOTA distributes within the brain when BBB impairment is subtle.
Association of Iron Deposition in Early-Stage Multiple Sclerosis Lesion with Remyelination Capacity: chi-separation imaging study
Authors: Shin Hyeong-Geol , Kim Woojun , Lee Hyun-soo , Kim Jiwoong , Nam Yoonho , Li Xu , van Zijl Peter , Lee Jongho , Jang Jinhee
Published: November 2024

Motivation: In multiple sclerosis (MS) lesion, factors influencing myelin dynamics and future remyelination are under active investigation. Goal(s): To assess dynamic changes of MS lesions from their early stage and explore the factors related to their future remyelination outcomes. Approach: Longitudinal changes of MRI phenotypes in MS lesions were assessed from their early stage, particularly focusing on longitudinal alternations in diamagnetic myelin and paramagnetic iron signals using susceptibility source-separation (chi[𝜒]-separation). . Results: 26 lesions show remyelination and 36 did not. The hyperintensity in paramagnetic iron signal (hyper-paramagnetic sign, HPS) at early stage of lesion development was significantly associated to future remyelination. Impact: Iron deposition sign in early-stage MS lesion, which detected by added sensitivity of 𝜒-separation to iron and myelin, can offer potential imaging marker for the impaired remyelination capability in MS pathology.
Multiparametric Quantitative MRI Shows Enhanced Degeneration in Paramagnetic Rim Lesions and Their Perilesional Tissue in Multiple Sclerosis
Authors: Cagol Alessandro , Ocampo-Pineda Mario , Ayci Batuhan , Benkert Pascal , Lu Po-Jui , Weigel Matthias , Melie-Garcia Lester , Chen Xinjie , Lutti Antoine , Nguyen Thanh , Wang Yi , Lee Jongho , Kuhle Jens , Kappos Ludwig , Sormani Maria Pia , Granziera Cristina
Published: November 2024

Motivation: Paramagnetic rim lesions (PRLs), a subset of chronic active lesions identifiable through susceptibility-based imaging, are linked to insidious disease progression in multiple sclerosis (MS). However, data on local microstructural changes in PRLs remain limited. Goal(s): To comprehensively characterize pathological alterations within PRLs and the surrounding perilesional tissue. Approach: Employing multiparametric quantitative 3T MRI on 175 people with MS, we obtained contrasts sensitive to tissue microstructural damage. Results: PRLs exhibited more pronounced pathological alterations compared to other white matter lesions, displaying enhanced demyelination, neuro-axonal loss, and iron accumulation. Remarkably, these alterations extended into the perilesional tissue appearing normal on conventional MRI. Impact: In people with multiple sclerosis, paramagnetic rim lesions (PRLs) exhibit pronounced microstructural quantitative MRI alterations. This strengthens PRLs as reliable biomarkers for lesions with smoldering degenerative activity, and offers potential insights into their association with a more severe disease course.
The changes of oxygen extraction fraction in different types of lesions in multiple sclerosis: A cross-sectional and follow-up study
Authors: Xie Yan , Zhu Wenzhen
Published: November 2024

Motivation: Multiple sclerosis (MS) lesions with different pathologic conditions could be distinguished by MRI. There may be differences in oxygen metabolism in different types of lesions. Goal(s): To explore the oxygen metabolism of different types of lesions in MS patients by oxygen extraction fraction (OEF) both cross-sectionally and longitudinally. Approach: The OEF map was reconstructed from a 3D multi-echo gradient echo scan. White matter lesions were classified into four types based on contrast-enhanced T1WI and quantitative susceptibility mapping. Results: There were differences in OEF among different types of MS lesions. The OEF in the lesion and the lesion type may change as time progresses. Impact: This study revealed tissue damage and oxygen metabolism level in different types of MS lesions. The OEF may contribute to further understanding of the pathological mechanisms in MS lesion evolution.
High-resolution mapping of hand innervation: novel approaches at 7T MRI
Authors: Guillemin Pauline , Branco David Ferreira , M'Rad Yacine , Mattera Loan , Lorton Orane , Poletti Pierre-Alexandre , Piredda Gian-Franco , Klausser Antoine , Martuzzi Roberto , Salomir Rares , Boudabbous Sana
Published: November 2024

Motivation: Exploit the high resolution provided by the 7T MRI technology to detect fine structures in the hand. Goal(s): To create an atlas of hand structures, with a specific focus on nerves and Pacinian corpuscles. This atlas is intended to serve both diagnostic purposes and to support reconstructive surgical procedures. Approach: An ethics committee was obtained to scan volunteers using 7T MRI. Post-processing was carried out to delineate the nerve fiber network and mechanoreceptors. Results: We successfully reconstruct and describe the anatomy of all nerve fibers from the carpus to the digital nerve division, as well as the Pacinian corpuscles, for three healthy volunteers. Impact: A visual interactive “Hand Nerves Atlas” matching morphology and fiber tracking of hand nerves on high-field will be delivered to the scientific community for fundamental research, to clinicians for microscopic surgery of nerves, and for educational purposes in medical schools.
ABRICOTINE MRI: Enhancing Sparsity Across the Three Dimensions of the Fourier Domain in Cartesian Sampling
Authors: Klauser Antoine , Piredda Gian Franco , Yu Thomas , Liebig Patrick , Martuzzi Roberto , Kober Tobias , Hilbert Tom
Published: November 2024

Motivation: With the increasing demand for high-resolution and short MRI exams, especially at high and ultra-high field, there is a need for fast acquisition techniques. Goal(s): To improve highly accelerated compressed-sensing by introducing a novel sampling named Alternating Basis Readout Imaging with COmpressed$$$\,$$$sensing with Three-dImensioNal Encoding (ABRICOTINE). Approach: ABRICOTINE incorporates sparse phase-encoding in three orthogonal directions, achieving true three-dimensional undersampling of the Fourier domain. This differs from conventional compressed$$$\,$$$sensing, which only undersamples within two phase-encoding dimensions. Results: We demonstrate significant enhancements in brain image quality through both simulations and true ABRICOTINE-accelerated acquisitions. It surpasses conventional compressed$$$\,$$$sensing methods and enables 0.5mm isotropic imaging in 4min. Impact: ABRICOTINE allows for a substantial improvement in compressed-sensing acceleration compared to traditional sparse sampling techniques, especially when high acceleration factors are required. It thus shows great potential for further accelerating high resolution MRI acquisitions.
Efficient Constrained Reconstruction of Non-Cartesian Time-Segmented Data with Implicit GROG and Polynomial Preconditioning
Authors: Nishimura Mark , Abraham Daniel , Cao Xiaozhi , Liao Congyu , Pauly John , Setsompop Kawin
Published: November 2024

Motivation: Fast, regularized subspace reconstruction would enable the acquisition and synthesis of a standard clinical brain protocol in mere minutes. Goal(s): Our goal is to make high-resolution, image reconstruction faster and more robust to $$$B_0$$$ inhomogeneities. Approach: Our reconstruction alternates between data consistency (DC) and spatio-temporal low rank regularization. We leverage coil sensitivities to "snap" non-Cartesian trajectories to the kspace grid, speeding up DC steps and enabling $$$B_0$$$-robust reconstructions with fewer time segments. Polynomial preconditioning enables convergence in up to 2x fewer iterations, reducing expensive proximal updates. Results: Our method reduces the reconstruction time by an order of magnitude while retaining quality. Impact: The ability to reconstruct MRF quickly should make integration of MRF into clinical workflows not just possible, but convenient. Additionally, the efficiency gains from this framework can make even the most sophisticated and expensive regularizers computationally feasible.
Navigator-free multi-shot EPI with shift-invariant kernel extraction in subspace
Authors: Tian Rui , Uecker Martin , Scheffler Klaus
Published: November 2024

Motivation: In functional and diffusion MRI, multi-shot EPI enhances spatial resolution and minimizes distortion compared to single-shot scans. However, its vulnerability to shot-to-shot phase variations presents a significant challenge, with various proposed methods having drawbacks. Goal(s): We propose a robust, navigator-free, computational efficient multi-shot method without SNR penalty. Approach: In readout-segmented multi-shot EPI, we exploit the k-space overlapped regions between adjacent segments to extract relative phase fluctuations. This method, inspired by ESPIRiT and nonlinear gradient calibration, efficiently extracts shot-dependent phase variations in subspace. Results: Our ex-vivo and in-vivo scans, including diffusion-weighted imaging, successfully achieves a high in-plane resolution of about 0.6mm without ghost artifacts. Impact: Our proposed multi-shot technique eliminates the needs for time-consuming navigators, provides robust high-resolution diffusion and potentially functional imaging, and could be easily adapted for interleaved Cartesian and spiral EPI allowing robust phase error estimation from merely small k-space regions.