bluuebunny/crossref_metadata_2025 huggingface dataset:
The value of IVIM-DWI and IDEAL-IQ in evaluating pathological grading of Hepatocellular Carcinoma
Authors: Li Shaopeng , Deng Kexue , Wang Peng
Published: August 2023

During the evolution of hepatocellular carcinoma(HCC) from high differentiation to low differentiation, the number of tumor cells increased and arranged more closely, the limited diffusion of water molecules was more obvious. Meanwhile, the iron and fat content in the lesions decreased gradually. The ADC、D values derived from IVIM-DWI and FF、R2* values derived from IDEAL-IQ can accurately reflect the diffusion limitation and the changes of fat and iron content in HCC, so as to accurately evaluate the pathological grade of HCC.
Age-related changes in elasticity, fat degeneration, and morphology of the pancreas: evaluation using multiparametric MR imaging
Authors: Kanki Akihiko , Yasokawa Kazuya , Sotozono Hidemitsu , Maeba Kiyoka , Higaki Atsushi , Yamamoto Akira , Tamada Tsutomu
Published: August 2023

We evaluated relationships between age and shifted apparent diffusion coefficient, proton density fat fraction (PDFF), and pancreas size using 3-T MRI. PDFF increased with age, and anterior-posterior diameters decreased with age. Interestingly, elasticity of the pancreas decreased with age. Based on these results, decreases in the size of the pancreatic parenchyma with age appear attributable to not only fibrosis, but also fatty degeneration, resulting in decreased elasticity. Fat content should be evaluated at the same time as fibrosis of the pancreatic parenchyma.
Dynamic contrast-enhanced magnetic resonance imaging of endometrial cancer with/without squamous differentiation
Authors: Takeuchi Mayumi , Matsuzaki Kenji , Bando Yoshimi , Harada Masafumi
Published: August 2023

DCE-MRI of endometrial cancer including 41 low-grade type I cancers without squamous differentiation (LG) and 39 with squamous differentiation (LG_w/SD), and 20 high-grade type II cancers (HG) was retrospectively evaluated. Significant difference in the time-intensity curves was found between LG and HG, and LG and LG_w/SD, whereas no significant difference was seen between HG and LG_w/SD. Curve type 3 (initial signal rise which is steeper than that of the myometrium) was more frequent in HG (60%) and LG_w/SD (77%) than in LG (34%). It should be recognized as a pitfall that HG and LG_w/SD may show similar early strong enhancement.
The feasibility of ZTE MR lung imaging in the assessment of pulmonary nodules or masses: a prospective head-to-head comparison with CT
Authors: LIU Qianyun , Feng Zhichao , Zhou Wenming , LIU Weiyin
Published: August 2023

The feasibility of zero echo time MR lung imaging in the assessment of pulmonary nodules or masses: a prospective head-to-head comparison with CT.
Differentiating Cytokeratin 19 Expression of HCC by Using Multi-b-value Diffusion-Weighted MR Imaging
Authors: Chen Jiejun , Guo Yixian , Zhang Shujie , Sun Wei , Guo Yinglong , Zhang Yunfei , Dai Yongming , Wu Dongmei , Yao Xiuzhong
Published: August 2023

Diffusion-weighted imaging (DWI) is a powerful functional MRI technique. However, scarcely has the DWI been used to identify the expression of Cytokeratin 19 (CK19) in hepatocellular carcinoma (HCC). In this study, we aim to differentiate CK19 positive and negative HCC with diffusion parameters derived from different DWI techniques. Our results showed that diffusion parameters can be used as noninvasive quantitative imaging markers for preoperatively predicting the CK19 expression of HCCs. More importantly, the integration of different diffusion parameters could better describe the characteristics of tumor tissues，thus reaching better diagnostic performance.
The value of IVIM and enhanced T2star weighted angiography for preoperatively predicting Ki-67 status in hepatocellular carcinoma
Authors: Xu Qihao , Zhao Ying , Qi Wenjing , Ren Xue , Lin Tao , Song Qingwei , Liu Ailian
Published: August 2023

In hepatocellular carcinoma (HCC) patients, high Ki-67 was closely related with tumor size, vein invasion, histological grade and the metastasis. This worked aimed at investigating the value of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance (MR) imaging and enhanced T2star weighted angiography(ESWAN) for predicting tumor Ki-67 status in HCC. The results showed that Standard ADC, DDC, R2*, T2* and combine had promising performances in predicting Ki-67 status. This research suggested that the IVIM and ESWAN held great potential in predicting the Ki-67 status of HCC, which is valuable for noninvasively, preoperatively and accurately predicting the prognostic factors during clinical practice.
Texture analysis of R2* maps for evaluating the pathological grade of hepatocellular carcinoma
Authors: Xu Qihao , Zhao Ying , Cui Dahua , Song Qingwei , Ren Xue , Lin Tao , Li Xin , Guo Yan , Wu Tingfan , Liu Ailian
Published: August 2023

Hepatocellular carcinoma (HCC) is a common malignant tumor with a high mortality. The higher the pathological grade represents lower the differentiation degree of HCC. Patients with low differentiation have a higher postoperative recurrence rate and the worse prognosis. Texture analysis is a post-processing method that highlights the difference between the brightness of pixel features and the intensity of background signals by analyzing the distribution and spatial relationship of gray values, and quantify and evaluate the heterogeneity of tumors at the pixel level. This research suggested that R2* maps texture analysis held great potential in evaluating the pathological grade of HCC.
stratification of axillary lymph node metastasis burden with standard breast MRI in breast cancer
Authors: Chen Jieying , Su Xiaolian , Xu Tingting , Luo Qifeng , Zhang Jilei , Zhang Lin , Tang Guangyu
Published: August 2023

Assessment of axillary lymph node metastasis burden before surgery in breast cancer patients is warranted for axillary management. This study developed a simple model based on the standard breast MRI features of breast tumor and axillary lymph node to differentiate patients with no, low or heavy axillary metastasis burden. With the help of this model, patients and clinicians would make more rational decision when to choose omitting surgery, sentinel lymph node biopsy or axillary lymph node dissection for axilla management.
Classification of Benign and Malignant Breast Lesions Using high b-value Diffusion MRI with a Continuous-time Random-walk (CTRW) Model
Authors: Jiang Yuan , Xue Ke , Dai Yongming , Wu Dongmei , Yang Junzhe , Qin Naishan , Qiu Jianxing
Published: August 2023

The high b-value DWI with a CTRW Model is useful in classification of benign and malignant proliferative breast lesions. The identification model using the combinations of CTRW parameters, Dm and β, has a moderate efficiency.
Potential of a Nomogram Based on DCE MRI and Clinical Features to Reduce Unnecessary Biopsies of Breast Lesions: Comparison with BI-RADS
Authors: Zhao Youfan , Chen Zhongwei , Zhou Jiejie , Miao Haiwei , Ye Shuxin , Liu Huiru , Wang Meihao , Su Min-Ying
Published: August 2023

318 patients (331 breast lesions) with DCE-MRI and clinical features were analyzed to establish a nomogram for diagnosis of breast cancer. The dataset was split to 233 (145 malignant 88 benign) for training, and 98 (61 malignant 37 benign) for testing. Radiomics features were extracted from DCE-MRI and selected to calculate the radiomics score. The clinical features were analyzed by univariate and multivariate analyses. Then a nomogram was established based on clinical features and rad-score. When applying cut-off values with ≥95% sensitivity, the nomogram can reduce 59.5% to 65.9% unnecessary biopsies, which was higher than that of BI-RADS.
Intravoxel incoherent motion imaging for the differentiating early breast adenosis from sclerosing adenosis
Authors: Wu Qi , zhang lina , song qingwei , liu ailian , lin liangjie , zhang xiaoxiao , xu xiaofang
Published: August 2023

Sclerosing adenosis (SA) of the breast is the late development stage of breast adenosis which is difficult to diagnose. Because its imaging manifestations are similar to malignant lesions of the breast, which often needs pathological diagnosis. Intravoxel incoherent motion(IVIM ) imaging is an MR method to separate diffusion and perfusion effects by fitting a double exponential model of signal attenuation and can accurately display the diffusion movement of water molecules. This study confirmed that some parameters of IVIM can be used in the identification of early breast adenosis and SA. Therefore, IVIM is of great value in the diagnosis of breast adenosis.
Developing CEST-detectable liposomal hydrogel for monitoring local brain tumor treatment
Authors: Park Se Weon , Lai Joseph H.C , Han Xiongqi , Huang Jianpan , Xiao Peng , Chan Kannie W.Y.
Published: August 2023

Glioblastoma is a malignant form of brain tumors, which has a high recurrence even with combined treatments. Here, we developed anti-cancer drugs loaded liposomal hydrogels for sustainable drug release to treat brain tumors locally under MRI guidance. These anti-cancer drugs are CEST-detectable. We observed a continuous decrease in tumor size and CEST contrast at 3.5 and -3.5 ppm compared to control group, where drug-free liposomal hydrogel was injected. The therapeutic efficacy of local drug delivery using liposomal hydrogel was evidenced and can be monitored using CEST multiple-contrast approach. This could serve a robust theranostic application for local brain tumor treatment.
Correlation between changes of pelvic bone marrow fat content and hematological toxicity in concurrent chemoradiotherapy for cervical cancer
Authors: QIN XIAOHANG , WANG CONG , YIN YONG
Published: August 2023

Bone marrow is a heterogeneous mixed tissue, which can be divided into red bone marrow with hematopoietic activity and yellow bone marrow with high fat content. Concurrent chemoradiotherapy can induce red bone marrow transfer into yellow bone marrow, increasing the bone marrow fat content and inhibiting hematopoietic function. The study used the MRI IDEAL IQ sequence to quantify the changes of pelvic bone marrow fat content receiving different doses of concurrent chemoradiotherapy for cervical cancer, and to determine associations with peripheral blood cell counts.
MRI-based radiomics model for preoperative prediction of extramural venous invasion of rectal adenocarcinoma
Authors: Jiang Huijie , Lin Xue , Zhao Sheng , Hu Hongbo
Published: August 2023

Radiomics features were extracted through MRI images and different prediction models (clinical model, logistic regression [LR], random forest [RF], support vector machine [SVM], clinical-LR model, clinical-RF model, and clinical-SVM model) for extramural venous invasion (EMVI) were constructed on the basis of radiomics features and clinical factors, respectively. The optimal model, which had the best predictive efficiency, was screened out for predicting the EMVI status of rectal adenocarcinoma patients.
Diagnostic evaluation of the Kaiser scoring combined with breast vascular assessment for the characterization of breast lesions
Authors: Zhou Xin-zhu , Lai Hua , Liu Lian-hua , He Shuang , Yao Hui-fang , Chen Li-ping , Deng Chen , Li Shuang-Ling , Zhang Xiao-yong
Published: August 2023

Kaiser scoring (KS) system for breast magnetic resonance imaging (bMRI) is a new clinical decision-making tool for the diagnosis of breast lesions. This study proposed and investigated the feasibility of Kaiser score combined with breast vascular assessment, defined as KS* , for its diagnostic performance in breast magnetic resonance imaging (bMRI). The results showed that the additional used ipsilateral breast vascularity and positive adjacent vessel sign (AVS) ﻿can accurately evaluate breast lesions, and KS* has higher diagnostic efficiency for breast lesions than conventional KS, especially for non-mass lesions.
New Diagnosis Criteria for Hepatocellular Carcinoma: Gadoxetic Acid-enhanced MRI Integrating CT-Vascular Features May Facilitate Evaluation
Authors: Yao Shan , Wei Yi , Tang Hehan , Nie Lisha , Wei Xiaocheng , Song Bin
Published: August 2023

Gadoxetic acid-enhanced magnetic resonance imaging (MRI) has been widely used in detection and diagnosis for hepatocellular carcinoma (HCC), while transient severe motion artifact that affects the arterial phase (AP) images quality and reduces diagnosis performance remains a concern. A new diagnosis criterion for HCC integrating CTAP and MRAP images was introduced in this study and achieved a high sensitivity and comparable specificity when compared with the gadoxetic acid-enhanced MRI only. It may be able to improve the diagnostic performance of gadoxetic acid-enhanced MRI in patients with HCCs and further affect the clinical treatment plan.
Value of Amide Proton Transfer Combined with Dynamic Contrast-Enhanced MRI in Predicting Pathological Features of cervical cancer
Authors: Song Qingling , Liu Ailian , Ma Changjun , Song Qingwei
Published: August 2023

The proper evaluation of pathological features including differentiation degree, deep stromal invasion (DSI) and vascular space invasion (VSI) is vital for patients with cervical cancer. Amide Proton Transfer (APTW) and Dynamic Contrast-Enhanced MRI (DCE-MRI) were used to predict tumor differentiation, DSI and VSI. Results showed that combined APTW and DCE-MRI predicted VSI with good performance. Therefore, combination of APTW and DCE-MRI is potentially a promising and valuable non-invasive method in detection for predicting VSI.
Improved Nuisance Signal removal for 1H-MRSI Using a Low-Rank Plus Sparse Model with Learned Subspaces
Authors: Ye Xinyu , Wang Zepeng , Lam Fan
Published: August 2023

Removing nuisance signals is an essential step for MRSI. A union-of-subspaces model that uses spatiospectral priors has achieved excellent water/lipid removal performance for 1H-MRSI, but may not be sufficient when the initial water/lipids are too strong and/or when field inhomogeneity is severe. We propose a low-rank plus sparse method for improved nuisance removal. The sparsity term is used to capture residual nuisance failed to be captured by the union-of-subspace model and the low-rank term with learned subspaces protects metabolite signals. Results from in vivo 1H-MRSI data show that the proposed method led to improved nuisance signal removal.
A comparison study of novel and conventional diffusion weighted imaging techniques in subjective and objective evaluation of the pancreas
Authors: Pei Yigang , Bai Yu , Li Wenzheng , Liu Wenguang , Liu Weiyin , Hu Zhangxuan , Peng Lingling
Published: August 2023

Based on field-of-view optimized and constrained undistorted single shot (FOCUS) combined with multiplexed sensitivity-encoding (MUSE) techinique, a new diffusion-weighted imaging (DWI) sequence was developed in our study (named FOCUS MUSE-DWI). Our aim is to assess FOCUS MUSE-DWI’ reliability with comparison to single-shot DWI (ss-DWI), FOCUS-DWI and MUSE-DWI with the evaluation of apparent diffusion coefficient (ADC) repeatability, surrogate signal-to-noise ratio (sSNR) and image quality. FOCUS MUSE-DWI can provide sufficient sSNR and excellent image quality, best ADC repeatability in above four DWIs. It suggests that FOCUS MUSE-DWI is a reliability technique and should be recommended for the clinical application of pancrentic DWI.
Dynamic quantitative T1 mapping (dyQT1) series for quantitative DCE imaging using variable flip angle method
Authors: Li Qing , Song Xinyu , Wang Jienan , Fu Caixia , Sun Yi , Li Yuehua
Published: August 2023

In this work, a new acquisition scheme is proposed for directly measuring the continuous quantitative T1 changes during the contrast enhancement. By alternatively changing the flip angles from phase to phase, the temporal resolution of T1 mapping could be the same as conventional DCE (conv-DCE) imaging, i.e., 4.36 s in our experiments. The dynamic quantitative T1 mapping (dyQT1) DCE method were validated on animal study (rabbit with VX2 tumor), and compared with conv-DCE. The preliminary results showed dyQT1-DCE was more time efficient without native T1 scans and higher sensitivity in the detection of tumor than conv-DCE.
Axial T2-weighted MR imaging of the cervical spine using PROPELLER with deep learning reconstruction to improve image quality
Authors: Song You Seon , Lee In Sook , Hwang Moon jung , Jang Kyungeun , Fung Maggie , Wang Xinzeng
Published: August 2023

We evaluated the utility of PROPELLER T2 FSE with deep-learning (DL) reconstruction in the cervical spine MRI, with the goal of overcoming respiratory and swallowing motion, improving image sharpness, and achieving high-resolution imaging within a comparable scan time to the conventional T2 FSE sequences. With utilization of DL reconstruction, the axial PROPELLER T2 was able to obtain images with high resolution and reduced noise.
Residual Non-local Attention Graph Learning (PNAGL) Neural Networks for Accelerating 4D-MRI
Authors: Liu Bei , She Huajun , Zhang Yufei , Wang Zhijun , Du Yiping
Published: August 2023

Residual non-local attention graph learning neural networks are proposed for accelerating 4D-MRI. Stack-of-star GRE radial sequence with self-navigator is used to acquire the data. We explore non-local self-similarity features in 4d-MR images by using residual non-local attention methods, and we use a graph convolutional network with an adaptive number of neighbor nodes to explore graph edge features. A global residual connection of graph learning model is used to further improve the performance. Through exploring non-local prior, the proposed method has the potential to be used in clinical applications such as MRI-guided real-time surgery.
A Microstructural Estimation Transformer with Sparse Coding for NODDI (METSCN)
Authors: Zheng Tianshu , Hsu Yi-Cheng , Sun Yi , Zhang Yi , Ye Chuyang , Wu Dan
Published: August 2023

Diffusion MRI (dMRI) models play an important role in characterizing tissue microstructures, commonly in the form of multi-compartmental biophysical models that are mathematically complex and highly non-linear. Fitting of these models with conventional optimization techniques is prone to estimation errors and requires dense sampling of q-space. Here we present a learning-based framework for estimating microstructural parameters in the NODDI model, termed Microstructure Estimation Transformer with Sparse Coding for NODDI (METSCN). We tested its performance with reduced q-space samples. Compared with the existing learning-based NODDI estimation algorithms, METSCN achieved the best accuracy, precision, and robustness.
Better Inter-observer agreement for Stroke Segmentation on DWI in Deep Learning Models than Human Experts
Authors: Lin Shao Chieh , Juan Chun-Jung , Li Ya-Hui , Tsai Ming-Ting , Liu Chang-Hsien , Peng Hsu-Hsia , Huang Teng-Yi , Liu Yi-Jui , Chang Chia-Ching
Published: August 2023

Inter-observer agreement is commonly used to evaluate the consistency of clinical diagnosis for two or more doctors. However, it is seldom to use to evaluate the consistency of clinical diagnosis for two or more deep learning models. In this study, four deep learning models for segmentation of stroke lesion were trained using GTs defined by two neuroradiologists with two ADC thresholds. We found the addition of an ADC threshold (0.6 × 10-3 mm2/s) helps eliminate inter-observer variation and achieve best segmentation performance. The inter-observer in two deep learning models shows the more consistent degree compared with inter-observer in two neuroradiologists.
Accelerate MR imaging by anatomy-driven deep learning image reconstruction
Authors: Lau Vick , Man Christopher , Liu Yilong , Leong Alex T. L. , Wu Ed X.
Published: August 2023

Supervised deep learning (DL) methods for MRI reconstruction is promising due to their improved reconstruction quality compared with traditional approaches. However, all current DL methods do not utilise anatomical features, a potentially useful prior, for regularising the network. This preliminary work presents a 3D CNN-based training framework that attempts to incorporate learning of anatomy prior to enhance model’s generalisation and its stability to perturbation. Preliminary results on single-channel HCP, unseen pathological HCP and IXI volumetric data (effective R=16) suggest its potential capability for achieving high acceleration while being robust against unseen anomalous data and data acquired from different MRI systems.
phase correction of magnetic resonance spectra based on convolutional neural network
Authors: Bao Qingjia , Li Piqiang , Li Zhao , Liu Kewen , Bai Chongxin , Sun Peng , Wang Jiazheng , Wang Jie , Pan Feng , Xie Weida , Yang Lian , Liu Chaoyang
Published: August 2023

We proposed a spectrum-to-spectrum/spectrum-to-phase phase correction method based on a neural network for magnetic resonance spectra. The former network obtains phase-corrected spectra by the end-to-end training the mapping between the manually corrected spectra and uncorrected spectra. And the latter can achieve more accurate phase correction by predicting the zero- and first-order phases for correction. The result shows that the proposed network can effectively obtain high-quality phase correction spectra even under noisy and baseline distortion conditions.
Development of measurement method of metabolite concentration in 1H MRS under B1 inhomogeneity at high magnetic field
Authors: Watanabe Hidehiro
Published: August 2023

The method for measurement of metabolite concentrations in 1H MRS in a human brain at high B0 field was proposed. A water phantom as a reference and a human brain area measured separately. The ratio of the reception sensitivities between uniform areas in the phantom and in the human brain can be computed from measured B1+s. The ratio between the VOI and the uniform area in the human brain can be computed by our previously reported ratio map method. Then, metabolite concentrations in the VOI can be calculated. Our method was demonstrated in the phantom experiments using metabolite mixtures.
Baseline Correction of 1H MRS for Cerebral Glucose Quantification via Detecting H1-α-Glucose Peak at 7 T
Authors: Kuribayashi Hideto , Urushibata Yuta , Dinh Thuy , Imai Hirohiko , Ahn Sinyeob , Seethamraju Ravi , Isa Tadashi , Okada Tomohisa
Published: August 2023

Glucose concentrations at posterior cingulate cortex in 20 young healthy subjects were quantitated via detecting H1-α-glucose peak at 5.23 ppm in 1H MRS at 7T. The spectra were analyzed using LCModel with data excluding a range of the residual water peak using PPMGAP parameter, which simply corrected baselines around the H1-α-glucose peak distorted from the tail of the residual water peak. The mean glucose concentration was estimated to be 1.0 mM via both sequences. Cramer-Rao lower bounds of fitting H1-α-glucose peak were significantly smaller in the semi-LASER (mean: 33.1 %) than those in the short-TE STEAM (49.8 %).
Role of insulin resistance in the optic nerve glymphatic system
Authors: Faiq Muneeb , Sainulabdeen Anoop , Adi Vishnu , Sajitha Thajunnisa , Khoja Sophia , Parra Carlos , Lee Choong , Zhang Jiangyang , Chan Kevin
Published: August 2023

Recent evidence suggests the existence of a functional glymphatic system in the optic nerve. Insulin resistance in the central nervous system (CNS-IR) has been implicated in neurodegenerative conditions. Its mechanism remains unclear though one candidate involves dysregulation of the cerebrospinal fluid (CSF). Here, we investigated if CNS-IR affects CSF flow in the visual pathway by measuring the spatiotemporal profiles of CSF dynamics using gadolinium-enhanced MRI following intrathecal administration of the specific insulin receptor blocker, S961. Our results suggested that central insulin function may play an imperative role in CSF dynamics for the homeostasis of the visual system.
Myelin Water Imaging in an HIV Population at Risk of Cerebral Small Vessel Disease
Authors: Uddin Md Nasir , Faiyaz Abrar , Finkelstein Alan , Schifitto Giovanni
Published: August 2023

HIV-infected individuals are at increased risk of developing cerebral small vessel disease (CSVD). Myelin damage is a feature in CSVD, and can be quantified using myelin water imaging. In this work, we investigated if MWI can be used to quantify myelin related changes in white matter in an HIV cohort at risk of CSVD. Our results lend support to the use of MHI to track myelin related abnormalities in the white matter.
Saturated Multi-delay Arterial Spin Labeling (SAMURAI) Technique for Simultaneous Perfusion and T1 Quantification of Kidneys
Authors: Ning Zihan , Chen Shuo , Chen Zhensen , Han Hualu , Qiao Huiyu , Shen Rui , Wu Peng , Zhao Xihai
Published: August 2023

We proposed a Saturated Multi-delay Arterial Spin Labeling (SAMURAI) technique with a correspondingly modified kinetic model to achieve simultaneous acquisitions of RBF, aBAT, tBAT and T1 map in kidney with a single scan. SAMURAI provided T1 map with excellent correlation (R2=0.976) compared with IR-SE. Compared with multi-TI FAIR, SAMURAI provided equally reliable ASL and T1 quantification results (ICC: 0.875-0.958) with excellent scan-rescan repeatability (ICC: 0.905-0.992) and significantly reduced scan time (45’ vs 4’6’’ for 9 TIs).
Ultrafast B1 Mapping with RF-Prepared 3D FLASH Acquisition: Correcting the Bias due to T1-Induced k-Space Filtering Effect
Authors: Zhu Dan , Qin Qin
Published: August 2023

The traditional RF-prepared B1 mapping technique consists of one scan with an RF preparation module for FA-encoding and a second scan without this module for normalizing. To reduce the T1-induced k-space filtering effect, this method is limited to 2D FLASH acquisition with a two-parameter method. Based on the point spread function analysis of FLASH readout, a novel 3D RF-prepared three-parameter method for B1-mapping is proposed to correct the T1-induced quantification bias. The proposed technique was compared with existing methods in the brain, breast, and abdomen and demonstrated with high accuracy for ultrafast B1 mapping.
Single-shot simultaneous T2* mapping and QSM using overlapping-echo acquisition for quantitative structural and functional MRI
Authors: Yang Qinqin , Ma Lingceng , Cai Shuhui , He Hongjian , Chen Zhong , Zhong Jianhui , Cai Congbo
Published: August 2023

A quantitative magnetic resonance imaging (MRI) sequence GRE-MOLED based on overlapping-echo detachment is implemented to simultaneously achieve distortion-free T2* mapping and quantitative susceptibility mapping (QSM) in a single shot. The accuracy of quantitative structural MRI results is verified by comparison with the results from multi-shot method in in-vivo experiments. We also evaluate the technique through a statistical analysis of fMRI experiments with vision and motion tasks and demonstrate that it achieves higher BOLD sensitivity than conventional method.
MRI Based Automated Deep-Learning System in the Assessment of Prostate Cancer: Comparison of Advanced Zoomed DWI and Conventional Technique
Authors: Hu Lei , Fu Caixia , Grimm Robert , von Busch Heinrich , Benkert Thomas , Zhao Jun-gong
Published: August 2023

Prostate cancer (PCa) detection by an automated deep-learning computer-aided diagnosis (DL-CAD) system using advanced zoomed diffusion-weighted imaging (z-DWI) and full-field-of-view DWI (f-DWI) were compared. The DL-CAD system using z-DWI performed significantly better for PCa detection accuracy per patient (AUC: 0.937 vs. 0.871; P=0.002) and had significantly higher PCa lesion detection accuracy per lesion compared to f-DWI (AUC: 0.912 vs. 0.833; P=0.003). Given this, use of z-DWI can improve the performance of the DL-CAD system for PCa detection.
Accelerated MR Parameter Mapping with Scan-specific Unsupervised Networks
Authors: Kim Tae Hyung , Cho Jaejin , Zhao Bo , Bilgic Berkin
Published: August 2023

We introduce a novel framework that jointly performs advanced image reconstruction and model-based MR parameter mapping, where various traditional and modern reconstruction techniques and signal relaxation models (T1, T2, T2*, etc) can be integrated as a plug-and-play manner. Using the proposed framework, we also incorporated model-based parameter mapping with scan-specific deep learning reconstruction (a method named LORAKI). The experiment results with T2, T2* and T1 indicate that this synergistic combination is advantageous, providing improved quantitative imaging over existing methods, e.g. with up to 3.6-fold, 1.7-fold, 2.3-fold NRMSE gain in T2, T2* and T1 estimation, respectively.
Comprehensive 3D quantitative transient response MRI
Authors: Kotek Gyula , van Valenberg Willem , Nunez-Gonzalez Laura , Poot Dirk , Vogel Mika , Hernandez-Tamames Juan
Published: August 2023

Unlike multi-parametric methods as MR Fingerprinting and quantitative transient imaging we present a quantitative MRI method based on the transient response without variation of experimental parameters (FA…). Our method is based on the exact solution of the recursive equation for the magnetization along an acquisition train. Based on this analytical approach we determine the requirements for the features and parameters of a repeated acquisition block to allow simultaneous estimation of experimental (B0, B1) and intrinsic (PD, T1, T2) parameters. The feasibility of the technique on clinical scanners is demonstrated by acquiring a comprehensive set of 3D in vivo parametric maps.
Quantification of Electrostatic Molecular Binding Model Using the Water Proton Signal
Authors: Bie Chongxue , Zhou Yang , van Zijl Peter , Xu Jiadi , Zou Chao , Yadav Nirbhay
Published: August 2023

Saturation transfer MRI has previously been used to probe molecular binding interactions with signal enhancement via the water signal (IMMOBILISE approach). Here, we detailed the relayed nuclear Overhauser effect (rNOE) based mechanisms of this signal enhancement by a four-pool magnetization transfer model, verified the model both using simulations and experimentally (using small charged molecules: arginine, choline, and acetyl-choline). The analytical model can be used to quantify molecular binding affinity, i.e., the dissociation constant (KD). The characterization of the transient binding of small natural substrates paves a pathway towards the detection of receptor-substrate binding in vivo using MRI.
Investigation of neurovascular coupling to cannabinoid 1 receptor occupancy: a simultaneous PET/fMRI study on non-human primates
Authors: Yoo Chi-Hyeon , Rani Nisha , Bagdasarian Frederick , Reid Sarah , Wang Changning , Wey Hsiao-Ying
Published: August 2023

The goal of this study was to investigate relationship between hemodynamic responses and underlying neurochemistry targeting cannabinoid receptor 1 (CB1R) in response to the injection of rimonabant in non-human primates using simultaneous positron emission tomography (PET) and function magnetic resonance imaging (fMRI). Following the rimonabant injection, fast and slow hemodynamic responses were identified throughout the brain. The CB1R occupancy estimates suggested that the radiotracer binding to CB1R was blocked by rimonabant highly in cerebellum and several brain regions. Future PET/fMRI studies with other CB1R-agonists/antagonists and more accurate occupancy estimates will provide further understanding about neurovascular coupling to CB1R.
Statistical Shape Models of Bone and Cartilage for Predicting Demographics: Data from the Osteoarthritis Initiative
Authors: Gatti Anthony , Wang Kuan-Chieh , Gold Garry , Delp Scott , Chaudhari Akshay
Published: August 2023

Three-dimensional statistical shape models built from MRI data can predict future disease and distinguish between groups. However, these models do not leverage the major advantage of MRI – the ability to visualize and quantify soft tissues such as cartilage. This study built three MRI-based statistical shape models, 1) bone shape, 2) cartilage thickness, 3) both bone shape and cartilage thickness. We showed that bone shape and bone shape + cartilage thickness models predicted sex with an R2 of ~0.9, significantly outperforming cartilage thickness alone (0.8). However, cartilage thickness alone was significantly better at predicting radiographic knee osteoarthritis.
Stochastic Fibrosis Signatures from 3D LGE: Novel Threshold-Free Quantification of Left Atrial Fibrosis
Authors: Mehrnia Mehri , Kholmovski Eugene , Passman Rod , Katsaggelos Aggelos , Nazarian Saman , Kim Daniel , Elbaz Mohammed
Published: August 2023

Assessment of left atrial (LA) fibrosis in atrial fibrillation (AF) patients from 3D LGE MRI have shown promise in evaluating atrial myopathy for selecting patients for catheter ablation and to predict AF recurrence post intervention. Nevertheless, current methods for fibrosis quantification suffer from lack of standardization and reproducibility as they rely on different thresholds for defining fibrosis. Hence, limiting the clinical translation of 3D LA LGE MRI. Here, we propose the first threshold-free technique to quantify LA fibrosis burden using novel stochastic fibrosis signature technique. We demonstrated feasibility and correlations to four of the previously published methods for fibrosis quantification.
Free-breathing Fully Ungated 3D Cardiac T2* MR Mapping using a Low-Rank Tensor Framework
Authors: Guan Xingmin , Yang Hsin-Jung , Hu Zhehao , Wang Nan , Christodoulou Anthony , Sharif Behzad , Li Debiao , Dharmakumar Rohan
Published: August 2023

A 3D fully ungated, free breathing cardiac T2* technique was developed using a low-rank tensor framework. An animal model with iron-oxide contrast-enhanced studies was used to test and validate the proposed technique. T2* images reconstructed from the proposed approach showed better image quality than those from conventional 2D T2* imaging approach. Excellent agreement of septal T2* was found between the proposed approach and conventional 2D approach. Our findings show that the proposed approach can accurately characterize T2* of myocardium under baseline and during iron overload conditions.
Simultaneous T1, T2, and T1ρ Mapping of the Myocardium with Multi-Parametric SASHA
Authors: Chow Kelvin , Xue Hui , Kellman Peter
Published: August 2023

Parametric T1 and T2 mapping can provide valuable insight into myocardial tissue microstructure. T1ρ is a complimentary technique that is sensitive to macromolecular content and may potentially enable non-contrast scar visualization. Characterization with all parameters is desirable as they may have different sensitivities to pathology but is time consuming with separate acquisitions for each. We propose a novel mSASHA sequence with T1, T2, and T1ρ maps in a single 13 HB breath-hold or free-breathing acquisition. mSASHA had superior T1 and T2 accuracy and similar precision to conventional MOLLI and T2p-bSSFP in phantoms and data is presented from 3 volunteers.
R1rho Dispersion in Spinal Cord and Nerve
Authors: Rivera-Garcia Alan , Uribe Juan , Turner Jay , Gore John , Wang Ping
Published: August 2023

Previous studies have demonstrated that at high fields (3T and beyond), dispersion of R1rho with different locking fields may reflect chemical exchange processes in biological tissues. This study aimed to investigate if R1rho dispersion is measurable in the spinal cord and nerve bundles. The results show that the dispersion is significant and measurable in both tissues, suggesting that R1rho dispersion has potential to characterize changes in composition or other physicochemical properties in nerve injuries and/or neurological disorders.
A study on structural changes of limbic systems in cerebral small vascular disease patients with mild to moderate depression
Authors: Li Kun , Liu Dongtao , Jia Xiuqin , Bu Qiao , Jia Rui , Jiang Tao , Jiang Yueluan , Shi Qinglei , Pan Zhenyu , Zhou Lichun
Published: August 2023

Major depressive disorder severity is associated with limbic systems grey matter volumetric reductions, while for cerebral small vascular disease (CSVD) patients with mild to moderate depression the pathological mechanism needs to be future investigated. Diffusion kurtosis imaging (DKI) is an advanced diffusion model that characterizes water diffusion process as non-Gaussian distribution. DKI parameters are highly sensitive to the micro-environment of tissues, especially for the anisotropic structure. This study aimed to investigate the structure changes of limbic systems in patients with cerebral small vascular disease (CSVD) induced mild to moderate depression by applying diffusion kurtosis imaging.
Diagnostic Performance of PDFF and Multi-Frequency 3D-MRE in the Detection of NASH and NASH-Required Therapy in a Large Cohort of 380 Patients
Authors: Kalutkiewicz Kyle , Li Jiahui , Zhu Zheng , Chen Jun , Mounajjed Taofic , Glaser Kevin , Hoodeshenas Safa , Venkatesh Sudhakar , Manduca Armando , Sirlin Claude , Shah Vijay , Allen Alina , Ehman Richard , Yin Meng
Published: August 2023

Liver biopsy and multi-parametric MRI/MRE were performed on 380 patients at risk of NASH. Histopathological diagnoses of NASH were collected along with proton density fat fraction (PDFF), and 3D-MRE measured liver stiffness (LS) and loss modulus (LM). While PDFF alone showed good ability to predict NASH (AUC: 0.80 [0.76, 0.85]), the addition of MRE measurements increased the diagnostic performance with strong statistical significance (AUC: 0.85 [0.81, 0.89], p<0.0004). LS alone was also found to be the strongest predictor of NASH-required treatment (AUC: 0.89 [0.84, 0.93], p<0.05), further establishing the critical role of MRE for clinical management of liver disease.
Optimizing Prostate DWI Acquisitions for non-Gaussian models using an Activity MRI [aMRI] library
Authors: Li Xin , Kopp Ryan , Baker Eric , Moloney Brendan , Springer Charles , Gartotto Mark , Coakley Fergus
Published: August 2023

Characterizing the non-Gaussian signature of the prostate DWI b-space decay often employs the kurtosis-, stretched-, and bi-exponential models. However, the optimal acquisition strategy in terms of maximum b value sampled and the number of b-values needed remains a research topic. Using the best-matched curves from a DWI library created with Monte Carlo random walk simulations of contracted Voronoi-cell ensembles, this work shows that, for prostate DWI, a maximum b-value near 2000 s/mm2 is optimal and the number of b-values is not as crucial as long as it is larger than the number of model parameters.
Incorporating data heterogeneity for improved regression models: application to stroke
Authors: Sharma Anuja , DiBella Edward
Published: August 2023

Symbolic data regression provides a systematic way to bring together heterogenous data from imaging and non-imaging sources in the form of histograms, intervals and scalar-valued observations. Classic multiple linear regression is adapted to mixed symbolic features and applied to data from diffusion spectrum images and clinical measurements for stroke recovery prediction. By utilizing the implicit variability within observations and natural grouping within features, the amount of information available to the modelling process is increased. This provides increased stability for model parameters over traditional regression and is especially beneficial with low sample sizes.
Magnetic Resonance Spectroscopy Frequency and Phase Correction Using Convolutional Neural Networks
Authors: Ma David , Le Hortense , Ye Yuming , Laine Andrew , Lieberman Jeffrey , Rothman Douglas , Small Scott , Guo Jia
Published: August 2023

Frequency and Phase Correction (FPC) is an essential technique to resolve frequency and phase shifts that arise in Magnetic Resonance Spectroscopy (MRS). As of today, a deep learning method using multilayer perceptrons has been developed to correct these shifts. However, a more robust network such as convolutional neural networks (CNN) can be considered as this approach more accurately obtains spatial information and extract key features of the given data. In this study, we aim to investigate the feasibility and utility of CNNs for FPC of single voxel MEGA-PRESS MRS simulated and in vivo data.
Investigation of Magnetic Wall Decoupling for planar Quadrature RF Array coils using Common-Mode Differential-mode Resonators
Authors: Payne Komlan , Khan Salik Inayat , Zhang Xiaoliang
Published: August 2023

Parallel imaging using quadrature coil arrays can help to reach their ultimate intrinsic signal-to-noise ratio (uiSNR) and higher spatial resolution at ultra-high fields, because quadrature RF coils provide higher sensitivity and reduced excitation power over the commonly used linear polarized RF transceivers. However, due to the complicated structure and difficulties in achieving sufficient electromagnetic decoupling, it is technically challenging in designing multichannel quadrature RF coil arrays, particularly at ultrahigh fields. In this work, we design and investigate the magnetic wall decoupled common-mode differential mode quadrature RF arrays for ultrahigh field 7T MR imaging applications.
Determination of the dielectric constant for RF passive shimming at 4T MRI
Authors: Jayatilake Mohan , Sica Christopher , Elyan Rommy , Pang Rang , Karunanayaka Dhevin , Ekanayaka Anupa , Karunanayaka Prasanna
Published: August 2023

Optimal image quality for Magnetic Resonance Imaging (MRI) at high fields requires a homogeneous RF (B1) field; however, the dielectric properties of the human brain results in B1 field inhomogeneities, and signal loss at the periphery of the head. Selecting the appropriate permittivity and quantity of material for the shim is essential. Here, we introduce a theoretical framework for determining the requisite dielectric constant of the passive shim material directly.
Monitoring mild cognitive impairment of workers exposed to occupational aluminum based on quantitative susceptibility mapping
Authors: Zhang Zhiyi , Jiang Haoru , Sun Xiangru , Wang Xiaochun , Wang Bin , Niu Qiao , Meng Huaxing , Du Jiangfeng , Yang Guoqiang , Liu Bo , Zhang Hui , Tan Yan
Published: August 2023

In this work, we presented a study which investigated the diagnostic value of quantitative susceptibility mapping (QSM) in mild cognitive impairment (MCI) of occupational aluminum (Al) workers, we found that QSM might be a reliable neuroimaging marker for the diagnosis of MCI.
Predicting conversion from normal aging to mild cognitive impairment using 1H-MRS of posterior cingulate cortex
Authors: Kiryanova Anna , Manzhurtsev Andrei , Bozhko Olga , Fedorova Yana , Semenova Natalia
Published: August 2023

This study aims to identify possible biomarkers of minimal cognitive impairment (MCI) in the posterior cingulate cortex using MR spectroscopy. Absolute concentrations of metabolites such as Cr, NAA, Cho, Glx, Ins were determined in subjects with MCI and in subjects from the normal group. Our study revealed a statistically significant increase in the absolute concentration of choline-containing compounds, as well as the Cho/Cr value in PCC in the MCI group, what may indicate the destruction of cell membranes. The results expand our knowledge in understanding the causes of MCI and are promising for the study of Cho as biomarkers.
Rapid High-resolution Quantitative MR Neurography in the Lumbosacral Plexus using Accelerated Quantitative Double Echo Steady-State (qDESS)
Authors: Ogawa Takumi , Abe Kayoko , Hamatani Yutaka , Goto Yasuhiro , Yoneyama Masami , Lu Quin , Shiina Isao , Kodaira Kazuo , Kato Mana , Nagao Michinobu , Sakai Shuji
Published: August 2023

Double Echo Steady-State (DESS) with water-selective excitation is a useful sequence to depict small nerves such as intracranial nerves, it would also be promising for visualizing lumbar nerves. Recently, accelerated qDESS sequence combined with compressed sensing sensitivity encoding (Compressed SENSE) has been proposed for further rapid knee morphological and quantitative imaging. In this study, we evaluate the feasibility of the accelerated qDESS sequence for visualization and quantification of the lumbosacral plexus within a short scan time.
Improved visualization of MR Neurography in the lumbosacral and sciatic nerves using double-diffusion sensitized driven-equilibrium (D2SDE)
Authors: Murayama Daichi , Yoneyama Masami , Sakai Takayuki , Yokota Hajime , Ochi Shigehiro , Watanabe Atsuya
Published: August 2023

We developed a new prepulse scheme, D2SDE, inspired by filter-probe double diffusion scheme for improved visualization of MR Neurography in the lumbosacral and sciatic nerves. This technique may be useful for arriving at an accurate diagnosis of lumbosacral plexus pathology.
Acceleration Motion Compensation Diffusion-weighted Imaging for Large Vessel Vasculitis: Phantom Model and Initial Clinical Experience
Authors: Hyodo Tomoko , Morimoto-Ishikawa Daisuke , Kaida Hayato , Ueda Yu , Tomita Daisuke , Yamamoto Atsuhiro , Itoh Makoto , Yasuda Nao , Fukushima Hiroyuki , Nozaki Yuji , Matsumura Itaru , Ishii Kazunari
Published: August 2023

The ascending aorta is poorly delineated on DWI due to the heartbeat, making it difficult to assess the activity of large vessel vasculitis using MRI. We investigated the utility of acceleration motion compensation diffusion-weighted imaging (aMC-DWI) compared with conventional DWI (cDWI) to detect active inflammation of the accenting aorta. The phantom experiment revealed that aMC-DWI showed a significantly higher median visual score than cDWI in both experimenters (P =.048 for both). The clinical study on 11 patients showed that aMC-DWI had higher sensitivity, specificity, and positive predictive value (with FDG-PET/CT as the reference method) than cDWI.
Association of Aortic Wall Characteristics and Cardiac Function in Fontan Patient
Authors: Lin Yu-Cheng , Wu Ming-Ting , Weng Ken-Pen , Peng Hsu-Hsia
Published: August 2023

The interaction of aortic wall characteristics and cardiac function in Fontan patients is unclear. 4D flow MRI was employed to quantify the wall shear stress (WSS) and oscillatory shear index (OSI) in the aorta. Fontan patients exhibited increased axial WSS, decreased axial OSI and non-roundness of WSS in descending aorta (DAo). We also found that the increased axial WSS in DAo correlated with decreased ejection fraction and increased indexed end-systolic volume. The cardiac dysfunction presented adverse interaction with aortic wall characteristics in patients with Fontan, especially in DAo, and might lead to higher risk of atherosclerosis and stenosis.
Left Ventricular Strain is associated with Outcomes of Pulmonary Valve Replacement in Patients with Repaired Tetralogy of Fallot
Authors: Zhuang Baiyan , Lu Minjie , Zhao Shihua
Published: August 2023

Given the fact that patients who have underwent repair of tetralogy of fallot (rTOF) further need pulmonary valve replacement (PVR) due to pulmonary regurgitation, but the effect of PVR is mixed. We prospectively enrolled 45 asymptomatic rTOF patients who required PVR due to moderate or severe pulmonary regurgitation and measured their pre-operative strain and strain rate. After follow-up and analysis, we found that the radial strain (RS), circumferential strain (CS), longitudinal strain (LS), systolic radial strain rate (RSRs), early diastolic radial strain rate (RSRe) and early diastolic longitudinal strain rate (LSRe) before PVR are important prognostic factors for adverse events.
The predictive value of intravoxel incoherent motion in the assessment of adverse cardiovascular events of athletes heart
Authors: Deng Yujiao , Chen Jing
Published: August 2023

Regular exercise can have a beneficial effect on the cardiovascular system, but more and more reports of sudden cardiac deaths in athletes and general people during exercise had made people gradually pay attention to the damage effect of exercise on the heart.There is currently lack of imaging examination methods for early and accurate judgment of athletes’ myocardial injury.This study intended to use intravoxel incoherent motion diffusion-weighted imaging to evaluate the myocardial microcirculation of athletes to early predict the incidence of adverse cardiac events such as cardiac remodeling and delayed enhancement of the myocardium.