bluuebunny/crossref_metadata_2025 huggingface dataset:
Abnormalities of brain functional network in Parkinson’s disease at different stage
Authors: Wang Xinhui , Shen Yu , Ding Kaiyue , Zhou Yihang , Wei Wei , Bai Yan , Zhang Xianchang , Guo Zhiping , Wang Meiyun
Published: November 2024

Motivation: Currently there are no effective non-invasive neuroimaging biomarkers to evaluate the progression of Parkinson's disease (PD). Goal(s): To use graph theory analysis of resting-state functional MRI (rs-fMRI) to investigate the abnormalities of brain functional network in PD at different disease stages. Approach: We evaluated the global and nodal indicators changes between PD at different disease stages by comparison with healthy control. Results: Brain functional network topology was disrupted to a varying extent in patients with PD at different disease stages. Impact: The findings of this study may enhance our understanding of the mechanisms underlying the progression of Parkinson's disease and contribute to the development of non-invasive neuroimaging biomarkers for monitoring disease progression.
Abnormal dynamics function network during pain-free period: a resting-state co-activation pattern analysis in primary dysmenorrhea
Authors: Liu Huiping , Wang Wenyang , Su Xing , Shang Meiling , He Jiaxi , Ma Ling , Quan Lu , Zhang Ming , Dun Wanghuan
Published: November 2024

Motivation: Brain mechanisms for the pain of primary dysmenorrhea (PDM) patients pain remain unclear. Goal(s): To investigate dynamic brain functional networks in women with PDM during pain-free periods and explore the relationship between brain functional networks and the psycho-emotional states. Approach: Applied the CAP method to investigate the dynamic network connectivity characteristics of the brain in 59 PDM patients, as compared with 57 healthy controls. Results: The dynamic interaction of rs-fMRI brain networks in PDM patients were abnormal. The pain of PDM patients may related to the abnormal brain dynamic interaction of brain networks. Impact: This study provided new insights into the neural mechanisms underlying recurrent chronic pain. PDM patients exhibited atypical dynamic interactions within their brain networks during pain-free ovulation cycles, and these alterations corresponded to emotions related to pain.
Blood supply may affect the prognosis of meningiomas: a retrospective study based on Territorial Arterial Spin Labelling
Authors: Zhu Yuqi , Wang Dongdong , Li Xuanxuan , Zhao Yajing , Mei Nan , Lu Yiping , Yin Bo
Published: November 2024

Motivation: To explore the relationship between blood supply and prognosis of meningioma. Goal(s): Whether meningioma mainly supplied by the internal and external carotid artery (ICA and ECA) have different prognosis and symptoms, and the relationship between prognosis with blood supply and other clinical characteristics (including age, gender, tumor volume etc.). Approach: Territorial Arterial Spin Labelling was used to identify the feeding arteries of meningioma and divide patients into different blood supply groups. Results: Meningioma supplied by ICA had worse prognosis than ECA. Dizziness and headache were the most common symptoms in ICA and ECA groups, respectively. Age and pathological grading had effect on prognosis. Impact: Blood supply of meningioma was a prognosis-related factor, which was related to clinical symptoms and pathological results of patients, making it more crucial for neurosurgeons in planning surgery as well as evaluating prognosis.
3D high resolution, distortion-free, reduced field of view diffusion-prepared MRI at 3T
Authors: McElroy Sarah , Tomi-Tricot Raphael , Jeljeli Sami , Kinsella Shawna , Goh Vicky , Neji Radhouene
Published: November 2024

Motivation: High resolution distortion-free diffusion-prepared imaging (DiffPrep) is desirable for high-precision radiotherapy or surgical planning. Goal(s): To demonstrate 3D high resolution distortion-free DiffPrep using a reduced field of view (RFOV) approach and gradient echo (GRE) readout. Approach: A DiffPrep sequence was developed with magnitude stabilisers, RFOV excitation, fat suppression, 3D-GRE readout and 2D phase-correction navigator. The proposed approach using selective excitation of the tip-down pulse was compared against non-selective excitation at 3T in a phantom and in the spinal cord of a healthy volunteer. Results: Preliminary results presented in a phantom and in-vivo demonstrate successful outer volume signal suppression using the reduced FOV approach. Impact: The sequence introduced in this work enables 3D RFOV distortion-free DiffPrep with a GRE readout. This sequence could be advantageous for applications requiring accurate target delineation, such as radiotherapy planning or surgical planning.
Lorentzian fitting of Average Rotation of Saturation Effects (AROSE) CEST spectra for quantification in stroke
Authors: Chung Julius , Jin Tao
Published: November 2024

Motivation: Fitting of CEST spectra is obscured by MT, direct water saturation, and broad fast exchange peaks which result in contamination of quantified signals. Goal(s): Using AROSE spectra for fitting simplifies CEST quantification by reducing the need for isolation of CEST signals due to preemptive filtering. Approach: Fitting was first performed on simulated spectra at different exchange rates and then applied to in vivo data. Results: Our results in MCAO rodents showed that quantification of CEST signal from AROSERRex spectra resulted in low fitting residuals with robust peaks at 3.6, 2.6, and 2 ppm and minimal contamination from MT and fast exchanges. Impact: Fitting using AROSE-CEST spectra improves quantification of CEST exchange by minimizing contributions from broad fast exchanges and other contaminations such as MT which have been challenges for traditional fitting methods such as multiple -pool Lorentzian fitting.
Brain Temperature Mapping Based on Chemical Exchange Saturation Transfer of Creatine at 5.0T
Authors: Cai Siqi , Bie Chongxue , Zhou Yang , Zou Chao , Xu Xi , Jiang Chunxiang , Zhang Lijuan
Published: November 2024

Motivation: High-resolution brain thermometry remains challenging. Goal(s): To estimate the feasibility of creatine chemical exchange saturation transfer (CrCEST) imaging for brain thermometry. Approach: The CrCEST imaging of creatine phantom and swine brain was conducted at various temperatures on a 5.0T MR scanner (UIH Jupiter). The relationship between the apparent offset of CrCEST and the temperature was estimated with regression analysis, based on which the temperature maps were generated. Results: Strong linear relationships between temperature and the apparent CrCEST offset were identified for both the creatine phantom (0.005ppm/oC) and the ex vivo swine brain (0.008ppm/oC) experiments. Impact: The linear relationship between the apparent CrCEST offset and temperature confirmed the feasibility of CrCEST for high-resolution brain thermometry.
Accelerated CEST MRI by reconstruction using low-rank plus sparse decomposition in both k-space and image domain
Authors: Liu Chuyu , Guo Rui , Li Zhongsen , Song Xiaolei
Published: November 2024

Motivation: Chemical Exchange Saturation Transfer (CEST) acceleration requires robust contrast recovery from under-sampled k-space data. Goal(s): To achieve accelerated CEST-MRI with well-preserved contrast among different tissue types. Approach: Herein we proposed a reconstruction method that iteratively decomposed both K-space and Image domains into Low-rank plus Sparse components, termed as KILS. Results: Retrospective experiments from the healthy adults and brain tumor patients indicated that KILS could achieve an 8X acceleration factor, with well-preserved contrast among different tissue types. Experiments conducted on human liver at 3T and rat brain at 9.4T demonstrated that KILS exhibited good general applicability, suggesting its potential clinical utility. Impact: We developed KILS, which utilizes an iterative low-rank plus sparse matrix decomposition in both k-space and image domains for robust CEST contrast recovery from under-sampled k-space data and holds significant potential.
An End-to-End deep learning compressed sensing reconstruction model with adaptive shrinkage threshold
Authors: Lian Yuan , Guo Hua
Published: November 2024

Motivation: Using deep learning methods to improve image quality and computation speed of compressed sensing reconstruction. Goal(s): Develop a model-based deep learning model with adaptive threshold selection module to improve the reconstruction quality. Approach: Introducing a new shrinkage function with adaptive threshold selection for Model-driven deep learning networks, and emploits End-to-End strategy for multicoil reconstruction. Results: Experiments demonstrate the efficacy of End-to-End reconstruction strategy with sensitivity reconstruction module, and show that proposed adaptive threshold selection method can effectively reduce reconstruction errors. Impact: We develop an End-to-End deep learning reconstruction network with adaptive threshold selection module. This network canenforce the performance of state-of-art model-based deep learning method for CS reconstruction, and achieve good reconstruction quality at R=8.
Generating 3D Volumetric Brain Images via Other Contrast Guidance from 2D Thick Slices
Authors: Wang Long , Xiang Lei , Chamberlain Ryan , Song Xinyu , Wei Xiao-Er , Li Yuehua
Published: November 2024

Motivation: The conventional multiple sclerosis(MS) protocol in the brain normally takes from 30 minutes to several hours. It often involves multiple 3D series for the quantitative metrics and reports. Goal(s): To reduce the scan time for the brain MS protocols with more than one 3D seriesApproach: We proposed a framework that utilized a 3D T1 and 2D FLAIR as inputs to generate a 3D T2 FLAIR. Results: The method generates comparable image resolution on all orientations as the acquired 3D FLAIR, and outperforms other methods. The lesion segmentation masks show high consistency. Furthermore, the method demonstrates robustness in the cases with motion. Impact: The method provides the solution of generating a volumetric FLAIR using the same time as a 2D series and achieving comparable resolutions and diagnosis accuracy as the 3D FLAIR.
A Computer-aided Diagnoses Method for Brainstem-and-cerebellar Hemangioblastoma
Authors: Zhao Botao , Zhang Xiao-Yong
Published: November 2024

Motivation: Brainstem and cerebellar hemangioblastoma is a rare tumor with a high risk of haemorrhage during the biopsy. However, it is still a challenging task to distinguish HB from other types of intracranial tumors solely based on neuroimaging techniques. Goal(s): To propose a computer-aided diagnosis method to classify hemangioblastoma. Approach: We propose a patient-level classification framework using multi-task supervised contrastive learning, named LaSCL-PLC, for hemangioblastoma classification. Results: We evaluated the proposed model on a local MRI dataset of brainstem-and-cerebellum tumors, consisting of 97(HB) and 143(others). The experimental results show that our model achieves competitive performance as neuroradiologists. Impact: It could improve the preoperative diagnosis hemangioblastoma, which is crucial for clinical treatments.
Meta-matching to translate phenotypic predictive models from big to small data on structural MRI
Authors: Wulan Naren , An Lijun , Zhang Chen , Kong Ru , Chen Pansheng , Bzdok Danilo , Eickhoff Simon , Holmes Avram , Thomas Yeo B. T.
Published: November 2024

Motivation: Small sample size on structural MRI is evitable in reality and significantly limits phenotypic prediction performance. Goal(s): Our goal was to improve prediction performance on small datasets for structural MRI brain imaging. Approach: We adapted the meta-matching framework from functional to structural MRI, and compared it with baseline methods (Elastic net and direct transfer learning). Results: Our meta-matching-based approaches can greatly boost behavioral prediction performance for different small-scale structural MRI datasets. Impact: Our meta-matching-based methods should be able to make good predictions for a variety of neurological and psychiatric disorders even if the availability of structural MRI brain imaging is quite small.
EPR imaging assessment of reduced tumor oxygenation induced by HIF-2a inhibitor Belzutifan in VHL-deficient renal cell carcinoma models
Authors: Horie Kazumasa , Kishimoto Shun , Yamashita Kota , Yamamoto Kazutoshi , Brender Jeffery , Devasahayam Nallanthamby , Merkle Hellmut , Krishna Murali , Linehan W
Published: November 2024

Motivation: In the previous study, EPR oximetry unveiled physiological responses to a VEGF inhibitor, but the potential of EPR oximetry in upstream inhibition of the HIF pathway remained unclear. Goal(s): To determine if Belzutifan, a HIF-2α inhibitor, affects tumor oxygenation as measured by EPR oximetry and to offer a non-invasive biomarker of its therapeutic efficacy. Approach: Three xenograft models of clear cell carcinoma were treated with Belzutifan and changes in tumor oxygen levels were assessed using EPR oximetry. Results: We observed significant alterations in tumor oxygenation exclusively in responding tumors, which we attributed to diminished VEGF expression. Impact: This research underlines the significance of EPR oximetry as a non-invasive tool to detect early responses to HIF-2α inhibitors like Belzutifan, which could profoundly affect the management and therapeutic approach for cancer treatment, guiding personalized medicine.
Influence of temporal resolution in determining pharmacokinetic parameters from CAIPIRINHA-Dixon-TWIST-VIBE DCE-MRI for breast lesions
Authors: Xie Tianwen , Huang Yan , Fu Caixia , Robert Grimm , Nickel Marcel Dominik , Peng Weijun , Gu Yajia
Published: November 2024

Motivation: The quantitative parameters from dynamic contrast-enhanced (DCE) MRI can improve the diagnosis in characterizing breast cancer. Goal(s): However, the influence of temporal resolution in determining pharmacokinetic parameters is still unclear. Approach: In this study, we aimed to evaluate influence of scan temporal resolution on pharmacokinetic parameters and performance in diagnosing breast cancer. Results: The results demonstrated that as temporal resolution decreases, Ktrans, kep, and ve increase, and there were no significant differences in AUCs in diagnosing breast cancer for any of the parameters. Impact: This study transforms breast cancer diagnosis by validating the influence of temporal resolution in determining pharmacokinetic parameters. It encourages exploration into broader adaptations, aiming to provide the accurate pharmacokinetic quantitative parameters in the diagnosing cancer and assessing prognosis across multi-institutions.
Highly efficient simultaneous joint T1-T2 mapping for isotropic resolution 3D knee imaging at 0.55 T
Authors: Garrido Nicolás , Castillo-Passi Carlos , Araya Nicole , Phair Andrew , Prieto Claudia , Botnar René
Published: November 2024

Motivation: Low-field 0.55T knee imaging promises to provide more accessible assessment of injuries. Anatomic imaging has been evaluated, however quantitative knee imaging at 0.55T has not been demonstrated. Goal(s): To investigate the feasibility of 3D joint T1-T2 mapping for evaluation of the articular cartilage at 0.55T. Approach: A free-running, 3D-radial sequence with golden-angle and spoiled gradient echo readout and 1mm3 isotropic resolution was implemented using Pulseq for T1-T2 mapping. Bloch simulations were used for dictionary matching. Results: The sequence was tested with a standardized phantom, showing good agreement with reference values, and promising results for in-vivo images in healthy subjects in a ~4min scan. Impact: 3D joint T1-T2 mapping of knee articular cartilage with low-field MRI could provide a fast, more accessible and comprehensive test to assess knee injuries and chronic knee disease.
Comparative Analysis of Cardiac T1 Mapping Reliability: Free-Breathing Versus Breath-Hold Techniques
Authors: Velikina Julia , Unal Orhan , Samsonov Alexey
Published: November 2024

Motivation: Quantitative myocardial T1 mapping is an invaluable tool for detection and characterization of myocardial fibrosis and infarction. Recent emergence of free-breathing non-ECG-gated techniques requires evaluation of their reliability in controlled experiments. Goal(s): We evaluated repeatability of free-breathing non-ECG-gated Multitasking and breath-held MOLLI T1 mapping techniques and studied factors influencing them. Approach: Test-retest study was performed in 15 healthy adult volunteers. Bland-Altman plots and Spearman rank correlation were used for statistical analysis. Results: Our analysis reveals that while free-breathing technique has low bias, controlling data sampling patterns is needed to prevent high variability of test-retest measurements. Impact: Reliability of myocardial T1 mapping with free-breathing techniques may benefit from designing controlled data sampling patterns utilizing either external or self-calibrated cardiac/respiratory triggers.
Quantitative multi-dimensional assessment of cardiovascular system (qMACS)
Authors: Kong Qingle , Chen Yang , Chen Junzhou , Xiao Jiayu , Christodoulou Anthony G , Li Debiao , Fan Zhaoyang
Published: November 2024

Motivation: A recently developed MACS technique provides exquisite delineation of the structure and motion of the whole heart and aorta. However, it lacks T1, T2 information and is limited in assessing complex vascular and myocardial pathologies. Goal(s): To develop a quantitative MACS (qMACS) technique by incorporating T1 and T2 mapping into original MACS imaging pipeline. Approach: The qMACS sequence builds on a multi-tasking imaging framework and stack-of-stars acquisition. Respiratory-resolved T1,T2 maps were generated using dictionary-matching approach. Results: Free‐breathing and ECG-free 3D quantitative imaging of cardiovascular system in 10 minutes is feasible by proposed qMACS. qMACS measured slightly higher myocardial T1/T2 values than reference methods. Impact: qMACS is a time-efficient and patient-friendly technique for both quantitative and qualitative imaging of the whole cardioaortic system and may be used as a gatekeeper approach to the diagnosis of a variety of cardiovascular diseases.
An UTE-Stack-Of-Spirals Sequence For Biexponential-T1ρ Mapping of Knee Joint
Authors: de Moura Hector Lise , Keerthivasan Mahesh , Benkert Thomas , Regatte Ravinder
Published: November 2024

Motivation: Quantitative mapping of the whole knee joint could potentially improve the understanding of how OA initiates and progresses. Goal(s): To develop an UTE-based spiral sequence capable of quantifying biexponential T1ρ in knee cartilage, ligaments, tendons, and menisci. Approach: An UTE stack-of-spirals sequence with a magnetization-preparation module was developed and tested on healthy volunteers at 3T. Results: The developed UTE-based spiral sequence presented an increased signal-to-noise ratio in T1ρ- weighted images and a smaller standard deviation in quantitative maps. Impact: The feasibility of the UTE-based spiral sequence was demonstrated and showed potential for quantifying T1ρ on short T2 components in the whole knee joint.
Correlation analysis between quantitative-T2 and diffusion-MRI measurements in human white matter: a study across different field strengths.
Authors: Marchetto Elisa , Flassback Sebastian , Johnson Patricia , Assländer Jakob , Veraart Jelle
Published: November 2024

Motivation: Quantitative MRI is increasingly translated to low (<=0.55T) and high (>=7T) field strengths. Yet, differences in the underlying biophysics across field strengths remain poorly understood. Goal(s): To identify and understand deviations in the correlation of T2 and diffusion metrics at extreme field strengths. Approach: Quantitative T2 and diffusion MRI maps were computed from a comprehensive MRI protocol at 0.55T, 1.5T, 3T, and 7T. Results: We observe decreased correlation between T2 relaxation and diffusivity at high field strengths, while the results at 0.55T align well with clinical field strengths, which shows the ground for optimization of experimental design at low- and ultra-low fields. Impact: T2 and diffusion-MRI commonly complement each other in clinical imaging. Our results show a similar correlation of related metrics, suggesting shared information on tissue properties, which can be used to optimize experimental design at low- and ultra-low fields.
Multi-contrast Multi-resolution UTE for Myelin Fraction Mapping
Authors: Yin Nan , Liu Shuai , Reisert Marco , Ilbey Serhat , Rau Alexander , Emir Uzay , Bock Michael , Özen Ali
Published: November 2024

Motivation: The direct detection of myelin is not possible due to extremely short T2 of the myelin bilayer. Ultra-short T2* component can be calculated with ultra-short echo-time (UTE) sequences. Goal(s): To evaluate the performance of the multi-contrast multi-resolution 3D-UTE sequence (mcUTE) in myelin fraction estimation. Approach: Combining 1-1 binomial water-excitation pulses and zero-moment encoding in between, mcUTE enables simultaneous acquisition of quantitative and high-resolution water-excited structural images. Myelin fraction from mcUTE is compared to myelin water fraction method. Results: Myelin fraction values were comparable with literature, and consistent within the subjects. Impact: mcUTE can potentially be used as a single imaging modality for myelin fraction estimation since it produces both quantitative and a high resolution water-excited anatomical image data in 18mins with TE=20μs. Our results show the acquisition can be further accelerated.
Machine Learning with Multiparametric MRI for preoperative prediction of intraductal component in invasive breast cancer
Authors: Meng Lingsong , Zhao Xin , Guo Jinxia , Lu Lin , Cheng Meiying , Xing Qingna , Shang Honglei , Zhang Penghua , Shen Yanyong , Zhang Xiaoan
Published: November 2024

Motivation: To predict the presence of an intraductal component (ductal carcinoma in situ, DCIS) in invasive breast cancer (IBC-IC). Goal(s): To improve the preoperative prediction of IBC-IC. Approach: This study was to develop and validate a machine-learning algorithm to preoperatively predict IBC-IC using the multiparametric MRI features. Results: The machine learning model with multiparametric MRI features could provide the individualized probability of IBC-IC and might help to optimize surgical planning for patients with breast cancer before BCS. Impact: This study developed a prediction model combining a machine-learning algorithm with multiparametric MRI features to preoperatively predict intraductal component in invasive breast cancer, which may be beneficial to the preoperative planning of breast-conserving surgery for early-stage invasive breast cancer.
Multi b-value Reverse Polarity Gradient Distortion Correction for Breast Diffusion-Weighted MRI
Authors: Loubrie Stephane , Conlin Christopher , Batasin Summer Joyce , Lundström Elin , Rodriguez-Soto Ana , Kuperman Joshua , Seibert Tyler , Dale Anders , Rakow-Penner Rebecca
Published: November 2024

Motivation: DW-MRI holds great potential in improving specificity in breast cancer screening (BCS). This technique uses Echo-Planar imaging (EPI) and is sensitive to distortion due to spatial magnetic inhomogeneity. Correcting such distortion is key, especially when evaluating quantitative biomarkers. Goal(s): To study multi b-value Reverse Polarity Gradient (mRPG), originally developed for prostate DWI (abstract #4789), in comparison to standard RPG and FSL topup. Approach: A breast phantom scan and a BCS patient dataset were distortion corrected with the three methods. Results: mRPG showed better performance than RPG and topup, especially in ADC maps where they yield a misleading improvement of EPI distortions. Impact: mRPG demonstrated improved performance compared to RPG and topup in correcting distortions. Normalizing DWI volumes across b-values eliminates intensity changes resulting from distortions and solves overfitting issue where Jacobian intensity correction (JIC) makes up for underestimation of tissue displacement.
Lipid composition mapping of the breast in BRCA1/2 genetic mutation carriers using chemical shift-encoded imaging
Authors: Cheung Sai Man , Chan Kwok-Shing , Masannat Yazan , Ragupathy Senthil , Miedzybrodzka Zosia , He Jiabao
Published: November 2024

Motivation: Deregulation of lipid composition in the breast of BRCA1/2 carriers has been observed using single voxel spectral edited MRS, however the spatial distribution may further distinguish the disease state. Goal(s): We aimed to determine the power and repeatability of CSEI in detection of lipid deregulation in BRCA1/2. Approach: Lipid composition maps were acquired from 20 BRCA1/2 and 20 patients, to derive monounsaturated, polyunsaturated and saturated fatty acids in the peri-tumoural region in patients and the whole breast in all subjects. Results: Lipid composition in BRCA1/2 showed similarity to positive control. CSEI has excellent repeatability in lipid composition mapping of the breast. Impact: Deregulation of lipid composition in the breast of BRCA1/2 genetic mutation carriers resembles the diseased group, serving as potential precursor of breast cancer. CSEI yields highly repeatable quantitative maps of lipid composition critical for effective disease monitoring.
Identification of Early-stage Renal Abnormalities by Magnetic Resonance Imaging in Chronic Heart Failure Patients: A Preliminary Study
Authors: Xue Kaiming , Liu Lin , Jiang Yueluan , Bernd Kühn , Zhang Mengchao
Published: November 2024

Motivation: The prevalence of impaired renal function is high in chronic heart failure (HF). However, renal abnormalities are faced with difficulties in early diagnosis. Goal(s): Identification of preclinical pathophysiological changes of kidney by multiparametric MRI in chronic HF patients. Approach: Chronic HF with eGFR>60 ml/min/1.73 m2 and healthy volunteers underwent multiparametric MRI. RBF, T1 relaxation time, T2 relaxation time, R2*, and ADC values of renal cortex were measured and compared between the patients and controls. Results: Chronic HF group demonstrated higher R2* values (p=0.043) and lower RBF values (p<0.01) than control group. The other three parameter values showed no statistically significant difference between groups. Impact: In this preliminary study, we revealed that even with preserved estimated glomerular filtration rate (eGFR), patients with chronic heart failure demonstrated subclinical pathophysiological, including decreased perfusion and hypoxia. The association could be a potential target for diagnosis and protective treatment.
Multiparametric MRI based assessment of kidney injury in a mouse model of ischemia reperfusion injury
Authors: Bhaduri* Sourav , Mukherjee* Soham , Harwood Rachel , Murray Patricia , Wilm Bettina , Bearon Rachel , Poptani Harish
Published: November 2024

Motivation: Assessment of kidney health is paramount for early diagnosis of impairment and subsequent methods of intervention. Goal(s): This study enhances our understanding of kidney pathophysiology using multiparametric MRI analysisApproach: Parsimonious pharmacokinetic modelling of the DCE-MRI data along with ASL and DWI was used to assess longitudinal changes in glomerular filtration rate (GFR) and kidney function in a mouse model of ischemia reperfusion injury. Results: Findings suggest that Renal Blood Flow (RBF), parsimonious filtration quotient (Ft), GFR, kidney volume, and Apparent Diffusion Coefficient (ADC) are important in comprehending the renal effects induced by ischemia reperfusion injury. Impact: This study provides an improved understanding of renal pathophysiology and underscores the value of multi-parametric MR imaging for assessing early changes in kidney function due to IRI, which may aid in early diagnosis of kidney injury and monitoring treatment response.
Diffusion-weighted MRI-based Virtual Elastography for the Assessment of Liver Fibrosis
Authors: Fan Fengxian , Jiang YanLi , Yang Pin , Zou Jie , Wang Shaoyu , Zhang Jing
Published: November 2024

Motivation: Liver biopsy is considered the reference standard for liver fibrosis quantification, however, noninvasive techniques are the emerging focus in this field. Elasticity values based on Diffusion-weighted (DW) MRI–based virtual elastography has been confirmed of a highly correlation with MR elastography. Goal(s): Assess the usefulness of DW MRI-based virtual MR elastography in the evaluation of fibrosis. Approach: We compared the diagnostic performance of elasticity values based on virtual MR elastography(μDiff), US elastography (Fibroscan) and serum markers for identifying significant liver fibrosis. Results: μDiff were significantly different between non-significant and significant fibrosis, and slightly accurate than Fibroscan for depiction of significant fibrosis. Impact: Diffusion-weighted MRI–based virtual elastography was confirmed with good agreement with shear modulus measured at MR elastography. Our study found that virtual modulus were significantly different between non-significant and significant liver fibrosis and appeared to preoperative prediction of liver fibrosis.
Robust inter-blade and inter-slice motion correction reconstruction for PROPELLER MRI
Authors: Zhu Xucheng , Chang Shaorong , Wei Moran , Ersoz Ali , Gaddipati Ajeet , Ghedin Piero
Published: November 2024

Motivation: PROPELLER MRI has been widely used to mitigate patient motion; however, conventional approach is not very robust, and does not address inter-slice misalignment that tends to occur on few moving patients. Goal(s): Develop new robust inter-blade and inter-slice motion correction technique. Approach: We propose a novel inter-blade and inter-slice motion correction reconstruction technique for PROPELLER MRI using volumetric calibration scan as reference. Results: The results show large improvement brought by the proposed method compared to convention Motion Correction on both in-plane motion artifact mitigation and inter-slice alignment. Impact: Reducing repeat scans due to patient motion, hence, increase patient throughput. Enable scanning patient who cannot keep still in the scanner, such as pediatric patients.
Prospective motion correction with 3D Orbital Navigators for robust and rapid susceptibility weighted imaging
Authors: Serger Matthias , Ehses Philipp , Ulrich Thomas , Riedel Malte , Stirnberg Ruediger , Boulant Nicolas , Pruessmann Klaas , Stoecker Tony
Published: November 2024

Motivation: The quality of susceptibility weighted images may deteriorate under subject motion, especially at high fields, impairing further data analysis. Goal(s): To mitigate motion artifacts through prospective motion correction(PMC) by employing 3D orbital navigators and real-time processing of a linear perturbation model. Approach: Orbital navigators were integrated into a high-resolution 3D EPI sequence for rapid susceptibility-weighted imaging at 7T, and a real-time motion estimation pipeline was established. The impact of prospective correction for large instructed motion on the resulting images was investigated. Results: Prospective motion correction successfully preserved the image quality of susceptibility weighted images, yielding results comparable to a scan without instructed motion. Impact: The improvements in image quality of the susceptibility weighted images underline the high potential of a linear perturbation model with Orbital Navigators for precise and rapid prospective motion correction in ultra-high field gradient echo imaging and potentially many more applications.
AI-Integrated MRS Scan Identifies and Updates Scan Parameters in the Presence of OOV Artifacts
Authors: Gudmundson Aaron , Hupfeld Kathleen , Simegn Gizeaddis , Song Yulu , Zöllner Helge , Davies-Jenkins Christopher , Özdemir İpek , Schär Michael , Oeltzschner Georg , Ganji Sandeep , Edden Richard
Published: November 2024

Motivation: Deep learning is a promising new tool for post-processing MRS data. Neural network-based MRS acquisition methods do not yet exist, but should lead to higher-quality data. Goal(s): The goal of this work was to create an “intelligent MRS scan” by integrating a Convolutional Neural Network (CNN) directly into a MRS acquisition protocol. Approach: Here, a CNN-powered pre-scan collects a single-transient from 48 different gradient geometries, and updates future scans, without human intervention, to avoid out-of-voxel (OOV) artifacts. Results: The AI-informed scan produced high-quality data for all participants while the control parameters failed half of the time in the artifact-rich mPFC region. Impact: The work demonstrates the first AI-integrated MRS scan protocol in which an intelligent pre-scan modifies scan parameters to improve data quality, here reducing out-of-voxel artifacts.
mtrk – A flexible open-source framework for developing MRI pulse sequences based on common web standards
Authors: Artiges Anais , Saimbhi Amanpreet Singh , Wiggins Roy , Lattanzi Riccardo , Block Kai Tobias
Published: November 2024

Motivation: Pulse-sequence development has been challenging due to high software complexity and limited documentation. Moreover, proprietary licenses make sharing developments difficult. Goal(s): To provide an open-source solution based on modern software engineering principles that simplifies the design, implementation, and dissemination of sequences. Approach: Our vendor-agnostic “mtrk” framework is based on a compact, human-readable descriptive language (SDL) in JSON format. SDL files can be generated with any programming language and can be played on MRI scanners or tested with simulators. Results: Python libraries for SDL generation and tools for interactive sequence design and visualization are presented. mtrk sequences were equivalent to vendor sequences in experiments. Impact: mtrk will lower the burden for students and researchers to develop and disseminate sequences. It will aid reproducible research, as developments can be publicly shared. Moreover, it will allow exploring innovative concepts such as remote calculation and cloud-driven “sequence-as-a-service” models.
AI-based reconstruction of diffusion weighted images to improve image quality and shorten acquisition time in prostate MRI
Authors: Iordanishvili Elene , Lemainque Teresa , Kuhl Christiane , Zhang Shuo , Peeters Johannes , Barabasch Alexandra
Published: November 2024

Motivation: While DWI is crucial for prostate MRI, it suffers from low SNR and CNR. Goal(s): To use AI-based image reconstruction for DWI and compare image quality, TA and diagnostic certainty with the standard DWI. Approach: Patients underwent standard prostate MRI protocol and received an extra DWI sequence with less averages and AI-based reconstruction. Image quality and PI-RADS were assessed by two blinded radiologists. ROI-based SNR, CNR and ADC values in lesions were calculated. Results: TA of AI-DWI was reduced by 57 %, while image quality improved. Lesion ADC values and PIRADS assessment remained the same regardless of reconstruction. AI-DWI outperforms the standard DWI. Impact: AI-based reconstruction of DWI shows promising results for further improving the accessibility and quality of prostate MRI while reducing scan time.
Playing with k-space lines: downsampling through deep learning to improve clinical sensitivity of diffusion imaging
Authors: Gaviraghi Marta , Kanber Baris , Ricciardi Antonio , Palesi Fulvia , Grussu Francesco , Tur Carmen , Calvi Alberto , Collorone Sara , Samson Rebecca S. , Wheeler-Kingshott Claudia Gandini
Published: November 2024

Motivation: The long acquisition time of diffusion-weighted (DW) imaging hinders its adoption in the clinic for studying pathological microstructural changes in vivo. Goal(s): The goal of this study was to reduce these long acquisition times by performing downsampling in k-space while maintaining clinical sensitivity. Approach: Deep learning was used to transform k-space data to DW images. Experiments were performed eliminating 30% of k-space lines using different methods. Results: DW images obtained with k-space down-sampling showed a reduction in artefacts, while fractional anisotropy images fitted from the network output appeared to have increased clinical sensitivity. Impact: This work paves the way for the design of acquisition strategies for fast diffusion-imaging. Through deep learning, it was possible to downsample k-space data in several ways, while obtaining a reduction in artefacts, with a potential increase in clinical sensitivity.
Intraoperative Precision Sampling of Tumor Microenvironments based on 7T MRSI: A pipeline development
Authors: Acharya Sagar , Cadrien Cornelius , Huskic Sara , Lazen Philipp , Brenner Christina , Azgin Ahmet , Furtner Julia , Kiesel Barbara , Wadiura Lisa , Preusser Matthias , Roetzer-Pejrimovsky Thomas , Köllensperger Gunda , Trattnig Siegfried , Bogner Wolfgang , Widhalm Georg , Rössler Karl , Hangel Gilbert
Published: November 2024

Motivation: Molecular and pathological diagnosis requires fresh tissues. It is important to achieve precise sampling and preservation of the tumor is for maintaining the tumor integrity. MRSI can accurately identify tumor hotspots and can be used for obtaining high quality samples. Goal(s): Develop MRSI pipeline for precise intraoperative tumor sampling. Approach: We processed 7T MRSI metabolic ratio maps and identified the tumor hotspots. We then correlated them with their quantitatively analyzed metabolic profiles. Results: We were able to achieve high quality tumor samples based on our 7T MRSI maps. Impact: Due to high resolution 7T metabolic ratio maps we could identify and define tumor hotspots which resulted in precise tumor sampling. We were also able to preserve the tissue specimens and obtain high quality results.
Tissue water referencing for 7T MRSI: Integrating proton density maps into quantitative metabolic mapping
Authors: Azgın Ahmet , Dymerska Barbara , Callaghan Martina , Lazen Philipp , Hingerl Lukas , Strasser Bernhard , Bogner Wolfgang , Rössler Karl , Trattnig Siegfried , Hangel Gilbert
Published: November 2024

Motivation: In magnetic resonance spectroscopic imaging, generating concentration estimates is desirable. So far, our approach has been limited by the need for WM/GM separation and literature values, limiting it to healthy subjects. To solve this, it can be replaced by PD map-based references. Goal(s): To test an approach of calculating concentration estimates within volunteers without relying on literature assumptions for reference. Approach: Use quantitative proton density maps to calculate water concentration maps for metabolic imaging at 7T. Results: We successfully used ME-GRE imaging to calculate water concentration maps. In healthy volunteers, these maps correspond well to the previous method. Impact: Using tissue water maps for MRSI concentration estimation allows to not only apply the method to healthy brains, but also to pathologies like gliomas. This will make 7T MRSI a better tool for studies.
Prediction of Lifetime Acute Ischemic Stroke Risk using Multimodal Models and SHAP-based Interpretability Methods
Authors: Mao Wenyue , Dai Yuxiang , Shi Zhang , Zheng Rencheng , Chu Yinghua , Wang Chengyan , Wang He
Published: November 2024

Motivation: Accurately predicting the lifetime risk of acute ischemic stroke (AIS) remains a significant challenge, and there is a notable scarcity of multimodal models that effectively integrate medical imaging with clinical factors. Goal(s): To propose an effective multi-modality deep learning model based on both MR images and clinical factors for improved prediction of AIS occurrence. Approach: The model leveraged a clinical-factor-agnostic module to extract clinical features from clinical factors and employed Shapley methods to scrutinize the significance of features. Results: The proposed method achieved higher performance than conventional models for the prediction of lifetime AIS occurrence. Impact: Our model's predictive outcomes could pinpoint individuals at high risk for AIS, allowing clinicians to advise them on self-health vigilance.
Investigating the Predictive Power of Oxygen-Enhanced MRI to Assess Radio-sensitivity in a Murine Model of Oral Carcinoma
Authors: Roy Upasana , Boult Jessica , Box Carol , Robinson Simon
Published: November 2024

Motivation: Tumour hypoxia is associated with radioresistance and is a negative factor in the prognosis of oral cavity squamous cell carcinoma. Non-invasive methods to rapidly quantify the extent and heterogeneity of tumour hypoxia would offer clinical benefit in treatment planning. Goal(s): To assess the utility of oxygen-enhanced (OE-) MRI to image hypoxia and provide predictive imaging biomarkers of radiation response. Approach: OE-MRI was performed in murine oral carcinoma allografts prior to 8Gy irradiation, and relationships with subsequent overall tumour response sought. Results: Tumours exhibiting voxels with a marked hyperoxia-induced reduction in R2* yet negligible ΔR1 were more radiosensitive. Impact: OE-MRI revealed extensive hypoxia in murine oral carcinoma allografts, and have the potential to predict tumour radiosensitivity based on the combined degree of hypoxia and haemodynamic vasculature.
Unveiling Metabolite Alterations in Photon-Irradiated Tramp C1 Cells via Hyperpolarized 13C NMR
Authors: Hsieh Ching-Yi , Lai Ying-Chieh , Lu Kuan-Ying , Lee Hsien-Ju , Lin Gigin
Published: November 2024

Motivation: Investigating metabolic changes in glycolysis within Tramp C1 cells due to photon irradiation, focusing on the role of HP 13C pyruvate. Goal(s): To determine how photon irradiation affects pyruvate-to-lactate flux in vitro, indicating metabolic reprogramming. Approach: Utilizing benchtop NMR to monitor HP 13C dynamics in irradiated versus control cells, targeting lactate production. Results: Photon irradiation elevated 13C lactate production by two-fold on Day 0, with persistently higher levels observed on Day 3, signifying altered metabolic flux post-irradiation. Impact: This study's findings reveal photon irradiation's potent effect on cellular metabolism, potentially influencing radiation therapy strategies. It opens avenues for targeted metabolic interventions and underscores the metabolic resilience in Tramp C1 cells, crucial for cancer treatment optimization.
High-resolution full pancreas water T1 mapping
Authors: Moquillaza Elizabeth Huaroc , Steinhelfer Lisa , Weiss Kilian , Lee Yoo Jin , Stelter Jonathan , Amthor Thomas , Koken Peter , Makowski Marcus , Braren Rickmer , Doneva Mariya , Karampinos Dimitrios
Published: November 2024

Motivation: T1 mapping provides valuable insights for the assessment of pancreatic diseases which might be challenging to evaluate if only based on qualitative MRI. Goal(s): Not only a high-resolution, fast T1 mapping method of the entire pancreas remains a challenge, but also a technique for water T1 mapping since the T1 is biased in the presence of fat. Approach: This work proposes a high-resolution, rapid, continuous inversion-recovery Look-Locker method combining a spiral read out with Dixon and a dictionary-based processing for water T1 mapping. Results: The entire pancreas is scanned within 24 slices, distributed in 3 breath-holds of 12s each. Impact: The present work proposes a high-resolution water T1 mapping methodology of the whole pancreas: 24 slices (2x2x5mm3) in 3 short breath-holds of 12s. The proposed method aims to support the fast assessment of diseases in the entire pancreas.
Assessment of Patients with Non-Alcoholic Fatty Liver Disease In Vivo Using Ultrashort Echo Time Magnetization Transfer (UTE-MT)
Authors: Liu Jin , Liang Xiaoling , Li Wei , Feng Jiaxin , Liao Jianwei , Zhang Jianbang , Ma Yajun , Li Shaolin
Published: November 2024

Motivation: UTE-MT is suggested to indirectly assess macromolecular contents in both short and long T2 tissues, which may have the potential to assess non-alcoholic fatty liver disease (NAFLD). Goal(s): To utilize the UTE-MT technique to assess the patients with NAFLD. Approach: A total of 40 subjects were recruited (20 with NAFLD and 20 without NAFLD) and underwent UTE-MT scans on a 3T MRI scanner. Results: The liver UTE-MTR value of NAFLD patients was significantly lower than that of normal ones (P<0.001). The ROC analysis between NAFLD patients and normal controls showed a high AUC value of 0.953. Impact: The UTE-MT technique can be utilized for the assessment of macromolecular content changes in NAFLD livers. The UTE-MTR may serve as a promising biomarker for screening patients with NAFLD.
Comparison of dissolved xenon imaging methods: 2D CSI vs 4-echo flyback radial spectroscopic imaging.
Authors: Collier Guilhem , Stewart Neil , Norquay Graham , Smith Laurie , Wild Jim
Published: November 2024

Motivation: Several dissolved xenon imaging methods have been proposed to detect impaired gas transfer in the lung. However, none have been validated against a gold standard CSI sequence. Goal(s): To validate quantitative xenon gas exchange metrics from a 4-echo radial EPSI implementation against those from CSI. Approach: 4-echo radial EPSI results were compared to CSI in 2 healthy volunteers. Results: We found good correlations between xenon gas exchange metrics from CSI and radial EPSI and minimal biases (0.4 to 5.8%) between the two methods for the main outcome parameter RBC:M, the ratio of dissolved xenon signals from the blood and in the membrane. Impact: Our implementation of dissolved xenon imaging using a 4-echo radial EPSI is validated against the reference standard CSI sequence, providing confidence in the quantitative nature of the xenon gas exchange metrics from this method to assess lung diseases.
Regional quantification of 129Xe Gaussian broadening in the lungs with time-domain Voigt fitting of 3D CSI
Authors: Norquay Graham , Collier Guilhem , Wild Jim
Published: November 2024

Motivation: Frequency-domain dissolved 129Xe CSI suffers from low spectral resolution, which can result in inaccuracies in the fitted spectral parameters. Time-domain Voigt fitting of CSI can improve accuracy and enable regional quantification of Gaussian broadening of 129Xe lung spectra. Goal(s): To quantify regional Gaussian broadening of 129Xe resonances in the lung airspaces and adjacent lung parenchyma. Approach: Time-domain Voigt fitting was performed on 129Xe 3D CSI data from the lungs of healthy volunteers. Results: Gaussian broadening contributed to 75-80% and 45% of the total linewidth for the gas and membrane 129Xe resonances, respectively, over all healthy volunteers. Corresponding Voigt T2 values were also quantified. Impact: We have demonstrated regional quantification of 129Xe Gaussian broadening in the lungs. Knowledge of this should enhance accuracy of spectral parameters computed for lung disease metrics while offering potential utility as a metric itself.
Impact of Wall Shear Stress and Flow Displacement on Aortic Root Dilation in Bicuspid Aortic Valve Patients with Varied Regurgitation Severity
Authors: Aliabadi Shirin , Garcia Julio
Published: November 2024

Motivation: Congenital bicuspid aortic valve (BAV) effects and its associated lesions on hemodynamic alterations, leading to aortic root dilation as the most severe form of aortopathy, remains unexplored. Goal(s): We aimed to examine the relationship between BAV phenotypes, considering various regurgitation severities, and aortic root dilation by analyzing abnormal wall shear stress (WSS) and normalized flow displacement (NFD) related to retrograde and anterograde flow jets. Approach: We utilized time-resolved three-dimensional phase contrast MRI to measure these velocity-derived flow biomarkers in healthy and BAV cohorts. Results: WSS proved a more sensitive and reliable metric than NFD in distinguishing BAV from healthy controls. Impact: Validating and quantifying advanced flow biomarkers in the aortic root due to its different biomechanical properties could enhance risk assessment, prognosis, and prevention of clinical complications in BAV patients with secondary valvular insufficiency.