bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmentation and quantification of hand synovitis in rheumatoid arthritis on DCE-MRI-based clustering
Authors: Fang Wanxuan , Mao Yijun , An Yujie , Sugimori Hiroyuki , Kiuch Shinji , Kamishima Tamotsu
Published: August 2024

Volumetry of enhancing pannus can be used as a marker for disease activity in synovial proliferative disorders such as RA. Enhancing pannus quantified by manual outlining as well as semiquantitative visual assessment of synovitis is too time-consuming to be justified in busy clinical practice. Our study showed great potential for automated quantitative segmentation and quantification of enhancing pannus, which would allow for accurate estimation of disease aggressiveness and thus prompt early therapeutic intervention for patients and assessment of treatment efficacy without increasing the burden on physicians.
Multiexponential UTE Relaxation in Achilles Tendon of Ballet Dancers Reveals Matrix Proton Pool Associated with Tendon Shear Stiffness
Authors: Horner Anna , Gonzalez Felix , Gleason Courtney , Blackmon Amanda , Faulkner Emma , Reiter David
Published: August 2024

Multi-echo ultrashort echo time (UTE) MRI provides quantitative structural information on both tendon matrix constituents and water distribution, which influence the mechanical function of tendons. UTE images of professional ballet dancers' Achilles tendons (AT) were combined with Shear Wave Elastography (SWE) Ultrasound (US) measurements of their AT to provide insight on the structure-function. The signal fraction corresponding to the off-resonance relaxation tendon components were found to positively correlate with the long-axis SWE velocity in this dancer cohort.
Do adult patients with moyamoya disease have glymphatic system dysfunction? - evaluation using diffusion along perivascular space
Authors: Hara Shoko , Kikuta Junko , Takabayashi Kaito , Kamagata Koji , Hayashi Shihori , Inaji Motoki , Tanaka Yoji , Hori Masaaki , Ishii Kenji , Nariai Tadashi , Taoka Toshiaki , Naganawa Shinji , Aoki Shigeki , Maehara Takeoshi
Published: August 2024

We aimed to evaluate the glymphatic system of adult moyamoya disease (MMD) by measuring diffusion along the perivascular space (DTI-ALPS index). We evaluated 46 patients using diffusion MRI, perfusion parameters of 15O-gas PET, and cognitive tests, and 34 age-sex-matched normal controls. Compared to normal controls, patients with MMD showed significantly lower DTI-ALPS index. DTI-ALPS index in MMD revealed the correlation between perfusion and freewater parameters, and executive dysfunction, and suggested that dysfunction of the glymphatic system may exist, correlate with the degree of hemodynamic disturbance, lead to increased parenchymal free water, and relate to cognitive dysfunction in adult MMD.
Multimodal MR imaging approach to evaluate the interaction between cardiac pulsation and perivascular CSF motion
Authors: Wright Adam , Tong Yunjie , Wu Yu-Chien , Wen Qiuting
Published: August 2024

We designed a non-invasive multimodal MRI approach to evaluate the relationship between cardiac pulsation and perivascular cerebrospinal fluid (pCSF) dynamics in humans. We utilized cardiac-aligned resting-state functional MRI and dynamic diffusion-weighted imaging to describe cerebral vascular events and pCSF motion, respectively. This approach revealed that changes in cerebral blood volume preceded an increase in pCSF motion, demonstrating the cardiac cycle’s effect on pCSF dynamics. Our results parallel preclinical two-photon imaging findings of perivascular CSF dynamics in mice. Our in-vivo assessment of cardiac pulsations influencing pCSF motion provides a non-invasive look into a crucial part of the human brain’s glymphatic system.
DWI with dynamic b-value cycling reveals evidence of reduced suprasellar cistern neurofluid motion in Parkinson’s disease
Authors: Mays Gabriela Pierobon , Hett Kilian , Eisma Jarrod , McKnight Colin , Elenberger Jason , Song Alexander , Considine Ciaran , Han Caleb , Claassen Daniel , Donahue Manus
Published: August 2024

The goal of this study was to use a novel diffusion weighted imaging (DWI) protocol with dynamic cycling of low b-values to test fundamental hypotheses regarding neurofluid movement along inflow and egress pathways of the suprasellar cisterns in older adults with and without Parkinson’s disease (PD). Contrast consistent with reduced neurofluid motion was observed in PD relative to healthy participants, with reduced fluid movement corresponding to choroid plexus hyperemia. Modeling of DWI signal decay as a function of b-value provides quantitative neurofluid kinetics and may present a candidate non-tracer technology for quantifying neurofluid flow non-invasively in vivo in humans.
Physical exercise activates intrinsic CSF outflow metrics in healthy humans
Authors: Miyazaki Mitsue , Malis Vadim , Yamamoto Asako , Kungsamutr Jirach , McDonald Marin , McEvoy Linda , Bae Won
Published: August 2024

Possible two intrinsic CSF egress pathways of dura mater and the lower parasagittal dura (PSD) are observed using non-contrast spin-labeling MRI. Intrinsic CSF outflow metrics increase in the adults with an active lifestyle than adults with sedentary lifestyle. However, after 3 weeks of increased physical activity, the sedentary group showed improved CSF outflow metrics. This improvement was notable at the lower PSD, where outflow metrics were highest among the active group. These quantitative CSF results indicate a new pathway of CSF flow from the lower PSD to the superior sagittal sinus that is most evident in physically active individuals.
Quantification of CSF T1 and T2 in the Subarachnoid Space: Implication for Brain-CSF Exchange
Authors: Jiang Dengrong , Gou Yifan , Wei Zhiliang , Hou Xirui , Yedavalli Vivek , Lu Hanzhang
Published: August 2024

It has been suggested that the brain’s waste clearance system involves water exchange between brain tissue and CSF in perivascular spaces, which are part of the subarachnoid space (SAS). In this work, we found CSF T1 and T2 in SAS were shorter than corresponding values in the frontal-horns of lateral ventricle, which have minimal exchange. Numerical simulations showed that a higher brain-CSF water exchange rate was associated with lower apparent relaxation time in SAS, providing a potential means to estimate brain-CSF water exchange rate in vivo.
Measurement of CSF pulsation in Parkinson’s disease patients using EPI-based fMRI data
Authors: Kim Jun-Hee , Kim Suhong , Im Jae-Geun , Chung Seok Jong , Lee Phil Hyu , Jeong Yong , Park Sung-Hong
Published: August 2024

The fMRI dataset for Parkinson’s disease with mild cognitive impairment (PD-MCI) was studied using a recently-proposed method of simultaneous CSF pulsation and BOLD activity imaging. The PD group was classified to dementia (PDD) high-risk and low-risk groups. The CSF pulsation of both PDD high-risk and low-risk groups was higher than that of healthy control. Opposite to the tendency of CSF pulsation, coefficient of variation of CSF pulsation was reduced in PD group compared to healthy control. These results indicate association of CSF pulsation with brain waste clearance in these patients, which requires further investigations for elucidation.
A Deep Learning-Based Tool for Analyzing the Female Reproductive System in MR images
Authors: Khaghani Javad , Basar Saqib , Chodakiewitz Yosef , London Sean , Attariwal Rajpaul , Hashemi Sam
Published: August 2024

MRI is a powerful imaging technique for examining the anatomy of the female reproductive system. However, due to cost-related concerns, ease of access, acquisition time, and necessity of expert reviewers for MR images, ultrasound is the primary modality of choice. To mitigate some of these concerns, we developed an AI-driven tool comprising seven neural networks that segments the regions of interest for the whole uterus, uterine zones, ovaries, and further identifies common benign gynecological conditions. We evaluated our package on a large representative population of 2955 sagittal T2-weighted pelvic scans to obtain normative aging-curves for various regions of interest.
Deep Learning Reconstruction to Pelvis Multi-Shot DWI Improved Image Quality with Less Image Distortion: A Preliminary Study
Authors: Lee Elaine Yuen Phin , Li Chia-Wei , Lan Patricia , Wang Xinzeng , Guidon Arnaud , Lin Chien-Yuan
Published: August 2024

This study introduced the deep learning reconstruction (DLRecon) to multi-shot DWI (MUSE-DWI) in the pelvis and aimed to investigate the changes in SNR and image quality with MUSE-DWI DLRecon. Compared with the MUSE-DWI non-DLRecon, the MUSE-DWI DLRecon showed higher SNR with stable ADC quantification. With that, DLRecon could reduce image distortion using higher shots MUSE-DWI with comparable SNR and scan time to clinically used 2-shot MUSE-DWI. This preliminary result showed the potential power of DLRecon in the pelvis allowing higher shots MUSE-DWI to be integrated in clinical practice to reduce image distortion.
Improved differentiation of BI-RADS 4 breast lesions based on ultrafast dynamic contrast-enhanced MRI radiomics and artificial neural network
Authors: Meng Lingsong , Zhao Xin , Guo Jinxia , Lu Lin , Cheng Meiying , Xing Qingna , Shang Honglei , Chen Yan , Zhang Penghua , Zhang Xiaoan
Published: August 2024

Improving the assessment of Breast Imaging Reporting and Data System (BI-RADS) 4 lesions can avoid unnecessary biopsies. As an emerging field, radiomics has been successfully explored as a means to aid decision-making for the diagnosis and risk stratification of several kinds of cancers1-4. In this study, we combined radiomics features extracted from ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) (using the Differential sub-sampling with cartesian ordering (DISCO) technique) with an artificial neural network (ANN) to improve diagnostic performance in assessing BI-RADS 4 lesions and evaluate the potential to avoid unnecessary biopsies.
Multiparametric MRI–based Radiomics Analysis of Endometrial Carcinoma for Preoperative Risk stratification
Authors: min Bai
Published: August 2024

Preoperative risk stratification of endometrial cancer (EC) is one of the important prognostic factors and is crucial for clinical treatment planning. We aimed to evaluate the predictive value of radiomics features based on multiparameter magnetic resonance imaging (MP-MRI) for preoperative risk stratification in patients with EC. The clinical and radiomic combined predictive models has a better performance than the model based on clinical characteristics. In the training set and the test set, the IDI and he reclassification improvement index of combined predictive models is higher than that of clinical model.
Automated Segmentation of Multi-Vendor Kidney Images using an Iteratively Trained Convolutional Neural Network
Authors: Daniel Alexander , Cox Eleanor , Evans Rachael , Wain Louise , Brightling Christopher , Tunnicliffe Elizabeth , Neubauer Stefan , Raman Betty , Francis Susan
Published: August 2024

Measures of total kidney volume (TKV) help to evaluate disease progression, and masks to define the kidney are important for the automatic assessment of multiparametric images collected in the same data space. For accurate measures in multicentre studies an automated method which is vendor agnostic and robust against image artefacts is needed. Here a single-vendor convolutional neural network is retrained and shown to be accurate on two vendors of scanner and robust against image artefacts associated with wrapping in the phase-encode direction.
Influential factors in deep learning classification of clear cell renal carcinoma cancer
Authors: Guo Junyu , Hulsey Keith , Xi Yin , Pedrosa Ivan
Published: August 2024

Deep learning has been successful in predicting tumor malignancy. Clear cell renal carcinoma (ccRCC) diagnosis may help in decision making between active surveillance and definitive intervention. In this study, we investigate the effects of different factors on the performance of deep learning classification of ccRCC using T2w images. We demonstrate that the performance of 15 different CNN models varied substantially. The choice of CNN models, the cropped image size, and the type of inputs greatly altered the performance of ccRCC classification. We achieved the best AUC value of 0.81, which is close to the reported performance of radiologists.
Using D2O-Induced 2H labeling, Deuterium MRI at 1.5T Enables In Vivo Visualization of Body Tissues and Early Assessment of Anticancer Therapies
Authors: Elhelaly Abdelazim , Hyodo Fuminori , Noda Yoshifumi , Kato Hiroki , Ichihashi Koki , Tomita Hiroyuki , Matsuo Masayuki
Published: August 2024

DMI emerged as a promising alternative in cancer metabolic imaging. We D2O-induced 2H-labeling followed by DMI to study deuterium kinetics and track tumor response to treatment at 1.5T. We succeeded to use dMRI to monitor 2H kinetics in tissues of a pancreatic carcinoma model. Higher 2H build-up was observed in tumor. Treated mice showed a significant decrease in 2H in tumor during 7 days of treatment and before anatomical changes were detectable. Tumor homogenates of treated mice also showed a significant reduction in 13C lactate production. DMI of tumors is a potential imaging method for assessment of early treatment responses
Early monitoring of radiation treatment based on tumor redox status using in vivo dynamic nuclear polarization MRI
Authors: Hyodo Fuminori , Koyasu Norikazu , Iwasaki Ryota , Eto Hinako , Elhelaly Abdelazim , Tomita Hiroyuki , Mori Takashi , Murata Masaharu , Noda Yoshifumi , Kato Hiroki , Matsuo Masayuki
Published: August 2024

In vivo dynamic nuclear polarization-MRI (DNP-MRI, also called OMRI, PEDRI) using carbamoyl-PROXYL(CmP) as a redox sensitive DNP probe enables the accurate monitoring of the tissue redox status. We found that the redox status decreases 1 day after radiation treatment, and the decay of redox status occurs before any micro- or macroscopic changes in tumor morphology and pyruvate metabolism based on the Warburg effect. This decay of redox status can also be associated with the decreased production of intratumor reducing redox molecules such as GSH and AsA.
The impact of intracranial atherosclerotic on the load and progress of cerebral small vessel disease
Authors: yuerong Lizhu
Published: August 2024

This study hypothesized that the load and the progression of cSVD in the unilateral hemisphere is correlated with the features of ipsilateral intracranial large arterial vessel wall lesions. Using the fluctuations of WHMs at baseline and follow-up to reflect the severity of cSVD. VW-HRMRI, the most sensitive non-invasive ways to evaluate the lesions of intracranial vascular, was used to assessment the morphological and enhancement characteristic of the culprit plaque. The result suggested that mild stenosis and positive remodeling of MCA may associated with WHM progression.
Contrast-to-noise ratio of carotid artery perivascular adipose tissue on MRI: A potential indicator for carotid vulnerable plaque
Authors: Yu Shuwan , Huo Ran , Qiao Huiyu , Ning Zihan , Shen Rui , Xu Ning , Zhao Xihai
Published: August 2024

Inflammation of carotid artery perivascular adipose tissue (PVAT) is associated with atherosclerotic disease. This study investigated the association between carotid artery PVAT and atherosclerotic plaques using multi-contrast MR vessel wall imaging. The contrast-to-noise ratio (CNR) of PVAT was measured on TOF MRA images. We found that the CNR of carotid artery PVAT measured by TOF MRA is independently associated with carotid vulnerable plaque features, suggesting that the CNR of PVAT might be a potential indicator for vulnerable atherosclerotic plaques.
Multifunctional Nanoparticles for Detection and Treatment of Atherosclerotic Vulnerable Plaques
Authors: Ye Man
Published: August 2024

The instability of atherosclerotic plaque is seriously harmful to human health. The nanoparticle molecular probe we prepared can simultaneously achieve magnetic resonance and ultrasound imaging, which is expected to reflect the pathophysiological characteristics of plaque at the molecular level. The phase change induced by low intensity focused ultrasound (LIFU) can cause the apoptosis of macrophages in plaque，which has the potential for phase change ablation of plaque.1 It provides a simple, effective, safe and non-invasive new method for early diagnosis, treatment and efficacy monitoring of vulnerable plaque.
In vivo MR vessel size imaging of brain vascular plasticity after experimental spinal cord injury
Authors: qian junchao , zhou ke , Zhou Chen , tian yu , Zhang Yanan , Song Tianwei , Qian Junchao
Published: August 2024

Spinal cord injury (SCI) leads to neuronal cell death, axonal damage and demyelination. Brain undergo anatomical changes following SCI. Recently MR vessel size imaging has shown promising application in visualizing neovascularization. In this study we explored the possibility to vascular morphology changes and angiogenesis in the regions along the cranial corticospinal tract (CST) in SCI using vessel size imaging. The results showed increased microvascular density (Density), mean vessel diameter (mVD) and vessel size index (VSI) values in contralateral pyramids four weeks post-injury compared to pre-injury levels. Thus, vessel size imaging could provide valuable information of neovascularization in brain after SCI.
Reliability of spinal cord measures based on Synthetic T1-weighted MRI derived from multi-parametric mapping (MPM)
Authors: Schading Simon , Seif Maryam , Leutritz Tobias , Hupp Markus , Curt Armin , Weiskopf Nikolaus , Freund Patrick
Published: August 2024

MRI acquisition time is a main factor for patient's comfort and motion artifacts. To avoid additional time consuming T1-w MPRAGE imaging for measuring spinal cord atrophy, when quantitative multi-parameter maps (MPM) are available, we reconstructed and validated a synthetic T1-w (synT1-w) based on MPMs. Test-retest repeatability was assessed and synT1-w images were compared with T1-w MPRAGE in a longitudinal study following spinal cord injury. Measures derived from synT1-w demonstrated high intra- and inter-site repeatability with only small difference when compared to MPRAGE. The estimated effects of spinal cord atrophy agreed with those obtained from MPRAGE.
Quantitative Analysis of Posterior Decompression in Chiari Malformation by Cine-PC MRI and 3D-T2w Scanning
Authors: Wang Xinyu , Li Fengtan , Wang Xinli , Zhang Chen , Qu Jianxun
Published: August 2024

In this study, the cine-phase contrast (cine-PC) sequence was used to compare the flow rate of cerebrospinal fluid in the midbrain aqueduct of patients with Chiari type I before and after posterior decompression and to analyze the difference in the ratio of cerebellar volume to posterior fossa volume between patients with Chiari type I and normal controls. Cine-PC magnetic resonance imaging and 3D-T2 scanning are shown to be effective for surgically evaluating patients undergoing posterior decompression surgery.
Histogram analysis of Intravoxel incoherent motion (IVIM) in differentiating high-grade glioma and solitary brain metastasis
Authors: Su Yifei , Guo Jinxia , Wang Junhao , Cheng Rui , Wang Chunhong , Hao Liangliang , Ji Hongming , He Yexin , Xu Cheng
Published: August 2024

We aim to explore the value of intravoxel incoherent motion (IVIM) in differentiating high-grade glioma (HGG) and solitary brain metastasis (SBM) by using histogram and first-order texture analysis in combination with the structural lesion feature. Results showed there were significant higher skewness (Dfast, f) and kurtosis (Dslow, f), and significant lower entropy (Dslow, f) and mean (f) in HGG solid tumor region as well as significant lower mean (f) in HGG peritumoral edema zone. Clear tumor margin in T2-weighted imaging help improve the differentiation when integrated with the IVIM parametric values.
The Value of Diffusion Weighted Imaging in Predicting the Growth Pattern of Meningioma: A Retrospective Study
Authors: Zheng Hui , Wang Zongmeng , Zheng Lingmin , Zhang Rufei , Song Yang , Lin Lin
Published: August 2024

The natural history of meningioma remains unclear and a simple, practical method is needed to identify fast growth tumors. This study evaluated correlations between clinical parameters, tumor growth rate (TGR), tumor volume doubling time (VDT), Ki-67 and relative apparent diffusion coefficient (rADC) derived from diffusion weighted imaging (DWI). The results showed that rADC was an independent predictive parameter of meningioma growth and baseline rADC had a good predictive ability for differentiating slow growth from fast growth meningioma. This suggests that in asymptomatic meningiomas, DWI might be a valuable predictive imaging method.
The value of an apparent diffusion coefficient histogram model in predicting meningioma recurrence
Authors: Han Tao , Zhou Junlin , Liu Xianwang
Published: August 2024

This study evaluated the feasibility of the model combining conventional MRI features and apparent diffusion coefficient (ADC) histogram parameters for predicting recurrent meningioma. The results showed that tumor shape and ADCp1 were independent risk factors for predicting meningioma recurrence after removing confounding factors by single and multiple logistic regression analysis. The logistic regression model nomogram constructed based on the above two risk factors for predicting meningioma recurrence, which had a higher predictive effect than a single risk factor. In conclusion, logistic regression model nomogram have important value in predicting meningioma recurrence and helping patients achieve the greatest survival benefit.
7T metabolic MRI in three types of diffuse glioma
Authors: Jacobs Sarah , Wiegers Evita , Shams Zahra , Wijnen Jannie , Willems Peter , Robe Pierre , Mühlebner Angelika , Van Hecke Wim , Zijlmans Maeike , Klomp Dennis , van der Kolk Anja
Published: August 2024

We combined metabolic magnetic resonance imaging (MRI) sequences at 7 Tesla (7T) to characterize glioma tissue and discover metabolic MRI profiles that could help delineate the extent of disease spread and determine molecular tumor subtypes preoperatively. Here we show the first preliminary results of three different diffuse glioma subtypes imaged with 1H MR spectroscopy (MRS), 31P 3D chemical shift imaging (CSI), glutamate chemical exchange saturation transfer (GluCEST) and quantitative susceptibility mapping (QSM).
Detecting microstructural features in gliomas with differences in malignancy and IDH-1 mutation status with a three-component diffusion model
Authors: Cao Mengqiu , Wang Xiaoqing , Liu Fang , Xue Ke , Dai Yongming
Published: August 2024

Evaluation of the degree of malignancy of gliomas, including the histopathological and molecular features, is of great importance for neurosurgeons in making individualized operation plans before surgery. In our study, the clinical value of a three-component diffusion model in characterizing gliomas malignancy and IDH-1 mutation status was evaluated. Our results showed that the three-component diffusion model exhibited great potential in evaluating the phenotype and genotype of gliomas by providing more complex microstructural information and showed significantly optimal diagnostic performance than the mono-exponential, bi-exponential and DKI models.
Determination of Meningiomas Consistency by Histogram Analysis of Different Models of Diffusion-Weighted MR Imaging
Authors: Zheng Lingmin , Wang Zongmeng , Lin Danjie , Song Yang , Lin Lin , Xue Yunjing
Published: August 2024

The consistency of Intracranial tumors is crucial to determine the required surgical instruments as well as affecting the outcome of surgery, but no specific feature of conventional MRI is reliable in predicting the consistency of tumors. Histogram analysis of diffusion parameters has been successfully used in predicting the grade, subtype, and proliferative activity of meningiomas. This study prospectively evaluated and compared the potential of various diffusion metrics obtained from the mono-exponential model (MEM), bi-exponential model (BEM), and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in predicting consistency of meningiomas. It was found that different models of DWI (MEM, BEM, and SEM) are useful in the differentiation between soft and hard meningiomas. However, Alpha obtained from SEM and fast-ADC from BEM are more promising diffusion parameters for predicting the consistency of meningiomas.
Balanced steady-state free precession imaging and associated rapid relaxation time mapping on a point-of-care 46 mT Halbach MRI scanner
Authors: Najac Chloé , Birk Florian , O’Reilly Tom , Scheffler Klaus , Webb Andrew , Heule Rahel
Published: August 2024

Point-of-care imaging with low-field MRI (<0.1T) is a potential game changer for low-income countries and the intensive care unit. The main challenge is the low SNR. Balanced steady-state free precession (bSSFP) sequences are fast and SNR-efficient. However, bSSFP is very sensitive to B0 inhomogeneities resulting in banding artifacts. We evaluated the feasibility of using bSSFP on our 46 mT MRI scanner. By acquiring 17 bSSFP datasets with linearly increasing frequency offsets (from 0 to 1/TR), we could reconstruct banding-free maximum-intensity images as well as F0 and F-1 SSFP configurations, which we employed for rapid relaxation time mapping.
Bringing MRI to Low- and Middle- Income Countries: Directions, Challenges and Potential Solutions
Authors: Adeleke Sola , Murali Sanjana , Ding Hao , Adedeji Fope , Qin Cathy , Obungoloch Johnes , Sirkis Tamir , Asllani Iris , Ntusi Ntobeko , Mammen Regina , Anazodo Udunna , Niendorf Thoralf
Published: August 2024

While innovations in MRI technology continue to advance healthcare in the global north, there is a persistent disparity in MRI access and research opportunities in low- and middle-income countries (LMICs). Reasons for this longstanding disparity include technological, economic, geopolitical, and social factors. As awareness of the situation expands, concerted efforts are underway to address it by developing sustainable approaches designed with and for local communities. Here, we provide a framework of such approaches by tackling different aspects of MRI development and access in LMICs.
Optimized MR Fingerprinting OPTIMUM in vivo in the vicinity of a metallic implant at low field
Authors: Zihlmann Gabriel , Sarracanie Mathieu , Salameh Najat
Published: August 2024

Magnetic susceptibility changes at interfaces induce artefacts, and hence compromises MRI diagnostic value. Low-Field (LF) MRI is inherently less sensitive to susceptibility artifacts making it suitable for imaging near metallic implants. In addition, the dispersion in T1-contrast is enhanced at LF. To evaluate the potential for new contrast mechanisms, quantitative imaging would be key if acquisition times are compatible with clinical constraints. In that context, model-based multi-parametric OPTIMUM was performed in a healthy volunteer’s forearm carrying a titanium plate from plate-osteosynthesis surgery. Performance of two signal models, one oblivious to intravoxel dephasing and the other accounting for it was compared.
Self-supervised Learning Based Liver Multi-parametric Mapping in a Single Breath-hold
Authors: Huang Chaoxing , Qian Yurui , Hou Jian , Jiang Baiyan , Chan Queenie , Wong Vincent , Chu Winnie , Chen Weitian
Published: August 2024

A self-supervised learning based multiparametric mapping method is proposed to map T1ρ and T2 simultaneously, by utilising the relaxation constraint in the learning process. The method was examined on a dataset of 52 patients with non-alcoholic fatter liver disease. Results showed that the proposed method can produce comparable parametric maps to the traditional fitting method, with reduced number of images, and reduced scan time.
T2 mapping with ZOOM-OLED on the kidney
Authors: Wu Jian , Kang Taishan , Li Simin , Chen Weikun , Wu Zhigang , Cai Congbo , Cai Shuhui
Published: August 2024

The overlapping-echo detachment (OLED) imaging can capture a T2 map within about 150 ms. However, when the region of interest (ROI) is smaller than the object, it is inefficient to acquire the whole object because many unnecessary phase-encoding steps should be acquired. The zonal oblique multislice (ZOOM) is a method to reduce the field of view (FOV) by using two pulses to excite two slabs that have a specific angle between them. This study combined ZOOM with OLED to capture the T2 map with reduced FOV. The ZOOM-OLED can reduce geometric distortion and improve image resolution.
Establishment of SPGR-based MOLLI T1 mapping for the calculation of extracellular volume fraction (ECV) in Gd-EOB-DTPA-enhanced MRI
Authors: Jingu Ryotaro , Sato Keisuke , Nozaki Atsushi , Wakayama Tetsuya , Nakamuta Ryuji , Yoshimitsu Kengo
Published: August 2024

In phantom study, SPGR-MOLLI acquisition scheme was optimized for abdominal T1 mapping in EOB-MRI, which was applied to clinical patients to measure ECV of the spleen and paraspinal muscle obtained 4 min and 25 min after the contrast administration. ECV obtained from contrast-enhanced CT within 3 months from EOB-MRI was used as reference standard. ECVs calculated from EOB-MRI showed significant agreements with those obtained from CT with ICCs of 0.9 and 0.74 for 4 min and 25 min, respectively (p<0.0001), which suggested that our T1 mapping protocol is appropriate and applicable to ECV measurement in EOB-MRI similarly with contrast-enhanced CT.
Over-estimation of T2 with radial sampling: Identification, understanding and strategies to mitigate the bias.
Authors: Corbin Nadège , Trotier Aurélien , Miraux Sylvain , Ribot Emeline
Published: August 2024

Quantitative MRI protocols can benefit from radial trajectory sampling to reduce the acquisition time. However we identified a bias in T2 relaxometry studies conducted with radial imaging. After in-depth analysis aiming at further our understanding of the underlying mechanisms, we propose some guidelines to mitigate this bias. The error depends on the range of T2 present in the object of interest and its geometry, the number of spokes and the trajectory of the sequence. Parallel imaging and compressed sensing help reducing the bias.
T1 Spectrum Analysis with Reduced Number of Datapoints Using Neural Networks
Authors: Parasram Tristhal , Xiao Dan
Published: August 2024

Quantitative analysis of T1 spectra could reveal microscopic properties and have been used to study biological tissues such as the heart, brain and related disease. It is challenging to determine the relaxation times from magnetic resonance signals particularly with multicomponent continuous spectra as it is an inherently ill-posed exponential analysis problem even with a large number of input data points. Artificial neural networks have been trained to determine T1 spectra with 8 to 4 logarithmically spaced data points. Improved performance over a larger range of T1 values and faster processing time compared to traditional methods have been achieved.
Exploration of an optimal ROI measurement for predicting tumor and node stage in rectal adenocarcinoma using 3D CEST-MRI
Authors: Pei Yigang , Wang Xiao , Liu Wenguang , Li Wenzheng , Liu Weiyin
Published: August 2024

Three dimensional chemical exchange saturation transfer (3D-CEST) can provide some quantitative values, such as amide proton transfer weighted-signal intensity (APTw-SI) and magnetization transfer (MT). Different ROI approaches (ss-ROI: single slice ROI; ts-ROI: three-slice ROI; wt-ROI: whole-tumor ROI ) affected the clinic feasibility of APTw-SI and MT in predicting tumor and node (TN) staging. We found MT assisted TN staging of RA patients with a good AUC for all three ROI approaches. Furthermore, MT with ss-ROI is easier to perform in clinical work than ts-ROI and wt-ROI and can be used for clinical diagnosis in the future.
Highly efficient simultaneous joint T1-T2 mapping for isotropic resolution 3D knee imaging
Authors: Barrera Dabne , Garrido Nicolás , Phair Andrew , Coronado Ronal , Qi Haikun , Botnar René , Prieto Claudia
Published: August 2024

Recently, a free-running T1-T2 3D radial imaging sequence was proposed to enable simultaneous acquisition of T1 and T2 maps of the hearth with isotropic spatial resolution. Here, we sought to investigate the feasibility of this sequence with 1 mm3 isotropic spatial resolution for the characterization of articular cartilage in scan time of ~4 min. The proposed approach was evaluated on a standardized phantom and in-vivo in healthy subjects, showing good agreement with reference values.
CMAPSS-NET: Deep-Learning Based Reconstruction of 3D Magnetization-Prepared GRE with Complementary Phase-Cycling Acquisition
Authors: Jafari Ramin , Wu Can , Zhao Yansong , Murray Victor , Peng Qi
Published: August 2024

Deep learning enables efficient reconstruction of 3D Magnetization-Prepared GRE with Complementary Phase-Cycling to remove both undersampling artifacts as well as T1 contamination associated with this type of acquisition only requiring half the acquisition time compared to current standard technique.
A Simulation Study of the Effect of Sampling Strategy on Computation of T2 Maps
Authors: Galiana Gigi , Elsaid Nahla , Tagare Hemant
Published: August 2024

This work presents a simulation study on the differences between data from accelerated T2 mapping experiments vs T2w imaging studies. Subspace constrained and model-based reconstruction were tested on trajectories that exhibited narrow k-space sampling at each window, energy differences across echoes related to the k-space collected by each echo, and small total data size. Energy differences had the largest impact on T2 map reconstruction, and both methods were unsuitable for reconstructing T2w data that combined all features. This highlights the need for tailored reconstruction approaches, such as e-CAMP, to reconstruct T2 maps from T2w data.
mcLARO: Multi-Contrast Learned Acquisition and Reconstruction Optimization for simultaneous multi-contrast and multi-parametric mapping
Authors: Zhang Jinwei , Nguyen Thanh , Spincemaille Pascal , Solomon Eddy , Li Chao , Li Jiahao , Wang Yi
Published: August 2024

We propose a unified framework for highly accelerated multi-contrast and multi-parametric imaging in a single scan. Our framework, named mcLARO, includes designing a novel multi-contrast pulse sequence, optimizing k-space sampling pattern and image reconstruction with a learning-based approach, and fitting T1, T2 T2* and QSM maps using the reconstructed multi-contrast images. mcLARO is compared with reference T1w, T2w, GRE, T1, T2, T2* and QSM mapping sequences and achieves comparable results.
Deep Learning Segmentation of Lung Parenchyma For UTE Proton MRI
Authors: Keen Christopher , Šereš Peter , Grenier Justin , Stobbe Robert , Paterson Ian , Punithakumar Kumar , Jaremko Jacob , Thompson Richard
Published: August 2024

Accurate segmentation is required to perform quantitative analysis on lung parenchyma in ultrashort echo time (UTE) proton MRI. Deep learning methods offer a solution to this problem, however, previous application to UTE lung MRI is limited. A deep learning model was trained to segment lung parenchyma using fine tuned region growing masks as a reference. To test the generalizability of the model the performance of three different 3D UTE k-space trajectories were compared. Overall, the model produced high quality segmentation for the different acquisition approaches with improvements over training data in areas of high vessel density and high signal intensity.
Development and validation of combined Ki67 status prediction model for intrahepatic cholangiocarcinoma based on MRI radiomics
Authors: Qian Xianling , Zhou Changwu , Zhang Yunfei , Dai Yongming , Zeng Mengsu
Published: August 2024

In the past decades, the incidence and mortality of intrahepatic cholangiocarcinoma (ICC) have been on the rise. A nuclear antigen named Ki67 is a poor prognostic predictor and an attractive therapeutic target in patients with ICC. Therefore, accurate prediction of Ki67 status in ICC patients is a predictor for treatment efficacy evaluation and outcome prediction. In this study, we established a multiparametric model for predicting Ki67 status in ICC patients preoperatively.
An 18F-FDG PET/3D-UTE MRI-based radiomics model facilitates the preoperative assessment of lymph node status in non-small cell lung cancer
Authors: Meng Nan , Feng Pengyang , Yu Xuan , Wu Yaping , Fu Fangfang , Li Ziqiang , Luo Yu , Tan Hongna , Yuan Jianmin , Yang Yang , Wang Zhe , Wang* Meiyun
Published: August 2024

18F-FDG PET/MRI is one of the most advanced means for the noninvasive diagnosis and evaluation of tumors. Three-dimensional ultrashort echo time (3D-UTE) is a novel MRI technique, which not only does not have ionizing radiation but also yields similar diagnostic results as conventional pulmonary CT. Our results showed that the 18F-FDG PET/MRI model based on clinical factors, 3D-UTE, and PET radiomics features could noninvasively assess the lymph node status in non-small cell lung cancer(NSCLC). Compared with the PET/CT model, it has similar diagnostic efficiency but less radiation, which is expected to provide new ideas for related research.
Multi-modal fusion with joint conditional transformer for grading hepatocellular carcinoma
Authors: Li Shangxuan , Fang Yanshu , Wang Guangyi , Zhang Lijuan , Zhou Wu
Published: August 2024

Multimodal medical imaging plays an important role in the diagnosis and characterization of lesions. Transformer pays more attention to global relationship modeling in data, which has obtained promising performance in lesion characterization. We propose a multi-modal fusion network with jointly conditional transformer to realize adaptive fusion of multimodality information and mono-modality feature learning constrained by other modal conditions. The experimental results of the clinical hepatocellular carcinoma (HCC) dataset show that the proposed method is superior to the previously reported multimodal fusion methods for HCC grading.
Identifying multimodal imaging biomarkers: a framework exploring association of β-Amyloid Accumulation and Microstructural integrity at 7T
Authors: Langan Mackenzie , Triolo Em , Khegai Oleksandr , Ferreira-Atuesta Carolina , Sutkowski Johnathan , Hedden Trey , Kurt Mehmet , Balchandani Priti
Published: August 2024

Here we outline a preliminary method using a novel method which leverages UHF neuroimaging to measure detectable correlations in two measures: microstructural (mean diffusivity and fractional anisotropy) acquired at 7T and amyloid beta (β-amyloid) accumulation, acquired using 3T PET-MR. The combination of these methods aids in the ability to map tissue structure and achieve unprecedented visualization of the consequences of β-amyloid accumulation as it relates to neurodegenerative disorders. We show the feasibility of leveraging high resolution diffusion to advance out understand of the relationship between fractional anisotropy and mean diffusivity within brain regions that may be affected by β-amyloid deposition.
Free Water Imaging in deep gray matter nucleus of Wilson’s Disease
Authors: Jing Xiao-Zhong , Li Gai-Ying , Wu Yu-Peng , Yuan Xiang-Zhen , Chen Jia-Lin , Taximaimaiti Reyisha , Li Jian-Qi , Wang Xiao-Ping
Published: August 2024

This is the first study to use a bi-tensor free water imaging to evaluate microstructural changes in deep gray matter (DGM) nuclei of Wilson’s disease (WD). Despite the shortcomings our study manifested that free water imaging detects microstructural alterations in both normal and abnormal appearing DGM nuclei of WD patients. Correlations between free water imaging indices and neurological impairment in WD patients were also noticed. Therefore, as a promising tool, free water imaging deserves further investigation in longitudinal studies to evaluate its role in monitoring disease onset, progression, and treatment efficacy in WD patients.
Abnormal effective connectivity of reward network in first-episode schizophrenia with auditory verbal hallucinations
Authors: Chen Jingli , Wei Yarui , Xue Kangkang , Cheng Jingliang
Published: August 2024

Our study employs the dynamic causal modeling (DCM) approach to perform effective connectivity (EC) analysis of the reward network to investigate the mechanisms underlying schizophrenia patients with auditory verbal hallucinations (AVHs). This study enrolled 86 first-episode drug-naïve schizophrenia patients with AVHs (AVH), 93 patients without AVHs (NAVH), and 88 normal controls (NC), undergoing resting-state functional magnetic resonance. Our findings suggest that there are some common and different EC abnormalities in the reward network of AVH and NAVH. Particularly, the abnormalities of mesolimbic and mesocortex pathways in AVH may provide guidance for understanding the neurobiological mechanisms of AVHs and treatment.
The application of high-resolution isotropic EPI DWI by CS with different acceleration factor in brain tumor
Authors: Duan Mengting , Zhu Yi , Wang Qi , Liu Hui
Published: August 2024

It has been shown before that C-SENSE can improved the ss-EPI DWI image quality in higher spatial resolution. The aim of this paper is to achieve a high-resolution isotropic EPI DWI by CS and to investigate the impact of different acceleration factor(AF) on the diagnostic quality of brain metastases in comparison with SENSE EPI DWI.
Time-Dependent OGSE Diffusion MRI with MAGNUS Ultra-High-Performance Gradient Coil for Microstructure Imaging in Glioma Brain Tumor Patients
Authors: Shih Robert , Zhu Ante , Huang Raymond , DeMarco J , Morris H , Hood Maureen , Abad Nastaren , Bhushan Chitresh , Foo Thomas , Ho Vincent
Published: August 2024

The MAGNUS ultra-high-performance gradient coil delivers simultaneous 200 mT/m and 500 T/m/s performance on each axis, with higher peripheral nerve stimulation thresholds than whole-body gradient coils, which is particularly useful for diffusion MRI-based microstructure imaging. We used MAGNUS-enabled OGSE to assess shorter diffusion times and length scales <10 µm in four brain tumor patients with gliomas. We measured differences in time-dependent diffusivity between high-grade glioma and low-grade glioma, as well as between recurrent glioblastoma and treatment effects. The malignant lesions demonstrated greater time-dependence of diffusivity. Further investigation with additional subjects and histopathologic correlation may lead to future clinical applications.
Abdominal MRI at 0.55 T: Initial evaluation and optimization in healthy subjects
Authors: Ramachandran Anupama , Hussain Hero , Lala Mishal , Richardson Jacob , Dudek Nancy , Morehouse Joel , Wright Katherine , Gulani Vikas , Seiberlich Nicole
Published: August 2024

Abdominal MRI including MRCP was performed in 15 healthy subjects on both a 0.55T and a 1.5T MR system. Image quality (IQ) was rated by two radiologists (22 and 17 yrs experience). All sequences were rated acceptable at 0.55T. In comparison to 1.5T, IQ scores at 0.55T were higher for DWI and 3D MRCP, and lower for the other sequences. Acquisition times were longer at 0.55T for all sequences except 3D MRCP. Thus, acceptable quality abdominal images can be obtained on a commercial 0.55T system with slightly lower IQ ratings of some of the sequences compared to 1.5T.
Optimization of the magnetization-prepared rapid gradient echo (MP-RAGE) sequence for 0.55 T
Authors: Schäper Jessica , Bieri Oliver
Published: August 2024

The MP-RAGE is the most commonly used sequence for structural brain imaging in clinical routine. Consequently, the optimization of imaging parameters for maximum contrast and signal is an important task. In this work, we implemented a previously developed computation and calculated optimal parameters for 0.55T. Additionally, the obtained images were compared with a gray-white matter contrast-optimized FLASH. Computing the contrast-to-noise ratio revealed a clear benefit for MP-RAGE over FLASH at mid to low resolutions, while a trend towards similar or even higher contrast-to-noise ratios for FLASH as compared to MP-RAGE at high resolutions was observed.
Optimization and Construction of a Low-Field MRI System Using Permanent Magnets
Authors: Mellors Mikah , Feldman Rebecca
Published: August 2024

A low-field tabletop spoke-and-hub permanent magnet array was constructed and assessed for homogeneity as a B0 field. Spatial encoding in the x and y directions was achieved by tilting the hubs relative to one other to generate a linearly increasing field in the tilt direction. A non-array RF coil was designed and optimized for low field strengths, where the signal-to-noise ratio is limited by the weak signal from the sample. The optimized coil design was tuned and matched to the resonant frequency of the spoke-and-hub magnet.
Low Volume, Pneumatic Flow Phantom for Validation of Flowing T2* Estimation Using Projection Acquisition with Flow-Encoded Subtraction
Authors: Margain Corina , Sandino Christopher , Vasanawala Shreyas , Bush Adam
Published: August 2024

Blood-oxygen level is a known biomarker for cardiovascular diseases which can be quantified by T2*-weighted MRI. Challenges with validation and motion have limited the clinical use of T2* oximetry methods. We present a PALMS sequence to measure flowing T2* which was validated using a pneumatically powered, low-volume, continuous flow phantom. Our results suggest that the presence of readout gradients influence T2* during flowing conditions while obliquity influences T2* in all settings conditions.
Solving fat-water separation with arbitrary echo combination by phase unwrapping
Authors: Peng Hao , Cheng Chuanli , Liu Xin , Zheng Hairong , Zou Chao
Published: August 2024

The phase unwrapping technique is only applicable to the fat-water separation problems with IP/OP acquisition. This work developed a transition approach that enabled phase unwrapping technique applicable to fat-water separation with arbitrary TE combination. By establishing intermediate variables, the proposed method provided an effective way to diminish the traditional “ambiguity” problem. To validate the concept, datasets acquired with various field strength, anatomical areas and acquisition types (two-point and six-point acquisition) were applied, and no fat-water swaps were observed.
Pilot Tone-navigated motion estimation for liver DW-MRI
Authors: Ariyurek Cemre , Vasylechko Serge , Zhong Xiaodong , Deshpande Vibhas , Bush Michael , Voss Stephan , Afacan Onur , Kurugol Sila
Published: August 2024

Diffusion-weighted MRI (DW-MRI) is capable of detecting and characterizing liver tumors and following-up treatments. Unfortunately, respiratory motion during DW-MRI scan causes misalignments between slices and reduces image quality. 3D slice-to-volume registration (SVR) can be employed to correct for motion. However, motion estimates may be inaccurate for high b-value images where SNR decreases. In this work, we propose to use PT estimated motion correction, which is calibrated on 3D SVR motion parameters obtained from low b-value images. We showed misalignments between slices are reduced by the proposed PT-based motion correction compared to SVR-based motion correction and no correction.
Highly Accelerated 3D MPRAGE using Robust SAMER Motion Mitigation
Authors: Splitthoff Daniel , Cauley Stephen , Kober Tobias , Hossbach Julian , Clifford Bryan , Lo Wei-Ching , Huang Yan Tu , Huang Susie , Conklin John , Wald Lawrence , Polak Daniel
Published: August 2024

Long clinical acquisitions can face the challenge of motion during the scan. One approach to address this problem is the recently introduced SAMER retrospective motion correction technique for 3D MPRAGE. As an alternative, it has been suggested to shorten the scan time by acceleration techniques, e.g., using Compressed Sensing, and thus reduce the likelihood of patient discomfort and severe motion. We here combine SAMER with Compressed Sensing for high acceleration factors (R=6).