bluuebunny/crossref_metadata_2025 huggingface dataset:
Fumarate Metabolic Signature for Detecting Hereditary Leiomyomatosis and Renal Cell Carcinoma Syndrome-associated Renal Cell Carcinoma
Authors: Liu Guiqin , Wu Guangyu , Dai Yongming , Xue Ke
Published: August 2023

Non-invasive in vivo detection of abnormal fumarate accumulation is important for identify fumarate hydratase (FH) deficiency in hereditary leiomyomatosis and renal cell carcinoma (HLRCC). However, until now, no study has been reported to successfully identify fumarate accumulation in HLRCC-associated RCC. In our study, we achieved an 100% accuracy in primary HLRCC-associated RCC, as well as all of the HLRCC PDX models. For our best knowledge, it is the first time that, MRS can be successfully used to in vivo detected in FH-deficient renal lesions, which is a crucial innovation of conventional imaging diagnostic technology.
Reliability of the volumetric positional probability distribution of liver tumor using volumetric 4D-MRI: effect of temporal resolution
Authors: Wong Oi Lei , Yuan Jing , Poon Darren , Zhou Yi Hang , Yu Siu Ki , Cheung Kin Yin
Published: August 2023

This study aims to evaluate the impact of temporal resolution on the positional probability distribution. Based on our results, PPV was independent of the fps setting and was most reliable at the probability of occurrence >35 - 50%. Thus, PPV is potentially useful to minimize the registration error during daily positional verification.
Plain magnetic resonance imaging by black blood sequences to assess vascular invasion of complex retroperitoneal occupying
Authors: Cui Ying , Zhao Yufei , Peng Xingui
Published: August 2023

This study aimed to investigate the value of plain conventional and black-blood magnetic resonance imaging (MRI) for assessing the invasion of large and important vessels in patients with complex retroperitoneal tumors. The great advantages of vascular wall imaging are non-invasive and non-enhanced, as well as three-dementional, which provides a better presence and evaluation of wall structure, tumor contact of the vessel circumference, narrowing, and deformity. The researchers in the field of vascular imaging should be interested in this topic.
Comparison of Computed DWI with actual scanned DWI for nasopharyngeal carcinoma detection using DWI TSE MVXD
Authors: Wu Zhigang , Chen Rui , Liu Zaiyi , Zeng Fei , Wang Guangyi , Ye Huifeng
Published: August 2023

Diffusion MRI provides unique information on the structure, organization, and integrity of the nasopharyngeal carcinoma (NPC) non-invasively. Higher b-values diffusion-weighted imaging could improve the detection rate of malignancies. We use the combination of DWI TSE Multivane XD and computed DWI to generate the high b values diffusion for nasopharyngeal whithout distortion, with higher SNR and less scan time. A in vivo comparison between actual scanned DWI and cDWI study was also studied on both volunteer and patients with NPC. The image quality is comparable. It shows cDWI is a promising technique for the NPC diagnosis.
Gray Matter Atrophy and Neurological Deficits in Patients with Carbon Monoxide Poisoning
Authors: Zhang Yanli , Wang Tianhong , Wang Shuaiwen , Gao Yuling , Wang Shaoyu , Guo Shunlin , Lei Junqiang
Published: August 2023

White matter damage in patients with carbon monoxide (CO) poisoning have been extensively reported in previous studies, but neurological deficits-associated gray matter volume (GMV) changes are not well explored. Forty-one CO poisoning patients and 36 healthy controls were enrolled in this study. All subjects underwent 3D T1WI and cognition and motor function assessment. GMV change patterns of patients were explored using Voxel-based morphometry processing. This study would provide a simple neuroimaging biomarker to identify the brain anatomical signatures underlying neurological deficits in CO poisoning, and thus facilitate the ongoing effort of knowing of the neuropathologic mechanism happened in these patients.
Virtual Stiffness of Gray Matter in Normal Adult Brain Assessed by Virtual Magnetic Resonance Elastography
Authors: Liu Chenyue , Da Chunxu , Yang Jian , Li Xianjun
Published: August 2023

The mechanical properties of biological tissue provide information related to the strength and integrity of the cellular microstructure. Recently, mechanical properties of the brain have been visualized and measured non-invasively with magnetic resonance elastography (MRE). Virtual MRE (VMRE) is based on non-Gaussian distribution model, which can be regarded as an indicator to reflect the complexity and change of different brain microstructure. The purpose of this study is to explore the capability of diffusion–based VMRE in the characterization of the gray matter shear stiffness, discuss the cause of the differences of gray matter encephalic in normal human brains.
Pseudo-continuous arterial spin labeling reveal altered cerebral hemodynamics and blood-brain barrier dysfunction in CADASIL patients
Authors: Zhang Jinyuan , Zhang Zihao , Ling Chen , Shao Xingfeng , Li Zhixin , Liang Huilou , An Jing , Yang Qi , Xue Rong , Zhuo Yan , Wang Zhaoxia , Yuan Yun , Wang Danny
Published: August 2023

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited form of cerebral small vessel disease (cSVD). In this study, we investigated the changes of cerebral blood flow (CBF), arterial transit time (ATT) and water exchange rate (kw) measured by multi-delay pseudo-continuous arterial spin labeling (pCASL) and diffusion prepared pCASL. Increased ATT and decreased kw were found in CADASIL patients compared with healthy controls. The results indicated modified cerebral hemodynamics and dysfunction of blood-brain barrier in CADASIL patients. MD-pCASL and DP-pCASL are promising for evaluating hemodynamics and BBB function of cSVD.
The usefulness of 4D convolution in deep-learning-based noise reduction for low-SNR body DWI
Authors: Tachibana Yasuhiko , Tsuchiya Hiroki , Kishimoto Riwa , Omatsu Tokuhiko , Mori Shinichiro , Obata Takayuki , Higashi Tatsuya
Published: August 2023

Deep-learning-based slice-by-slice noise reduction may not be suitable for low-SNR body DWI that contains insufficient information in the original single slice. Moreover, averaging multiple acquisitions after denoising to avoid this problem is insufficient because it causes blurring owing to a mismatch between acquisitions. Herein, we designed a neural network that utilises 4D convolution to incorporate adjacent slices and multiple acquisitions simultaneously for a slice to achieve adequate denoising. The results support the utility of the proposed method in comparison with the usual slice-by-slice method and averaging.
Brain T1ρ quantification at the first 5T whole-body MR system: a pilot study
Authors: Liu Yuanyuan , Gao Lanlan , Zhang Shuheng , Cui Zhuoxu , Zhu Qingyong , Wang Haifeng , Liang Dong , Zhu Yanjie
Published: August 2023

MR quantitative T1ρ mapping has gained increasing attention due to its capability in studying low-frequency motional processes and chemical exchange in biological tissues. At ultra-high fields, the chemical exchange and proton diffusion in biological tissues should be more prominent. In this study, for the first time, we aim to test the feasibility of T1ρ mapping of brain at 5T and evaluate the T1ρ values estimated from datasets using both 3T and 5T scanners.
Acceleration of Relaxation Time Mapping by Joint K-space and Image-space Parallel Imaging (KIPI)
Authors: Zu Tao , Hsu Yi-Cheng , Sun Yi , Wu Dan , Zhang Yi
Published: August 2023

The relaxation time mapping has proven to be an important diagnostic tool, but it is limited by the prolonged scan time due to the measurements of multiple frames at the same location. In this study, the recently proposed auto-calibrated reconstruction method by joint k-space and image-space parallel imaging (KIPI) is utilized for the acceleration of relaxation time mapping. Combined with the ESPIRiT method, KIPI generates improved coil sensitivity maps and allows an acceleration factor of up to 4-fold for acquiring source images, yielding the accurate parameter map without obvious errors or artifacts.
BUDA-SAGE with Slider encoding and self-supervised denoising enables fast, distortion-free, high-resolution T2 and T2* mapping
Authors: Zhang Zijing , Ye Huihui , Wang Long , Setsompop Kawin , Liu Huafeng , Bilgic Berkin
Published: August 2023

BUDA-SAGE is an efficient multi-shot echo‐planar imaging (EPI) sequence that provides multiple distortion-free T2*-, T2’- and T2-weighted contrasts for quantitative mapping. In this work, we employ Slider encoding to reach 1 mm isotropic resolution by performing super-resolution reconstruction on volumes acquired with 2 mm slice thickness. A self-supervised neural network MR-Self2Self (MR-S2S) was utilized to perform denoising to boost SNR. Estimated quantitative maps showed consistent values with conventional mapping methods in phantom and in-vivo measurements. We demonstrate that BUDA-SAGE acquisition with self-supervised denoising and Slider encoding enables rapid, distortion-free, whole-brain T2/T2* mapping at 1 mm isotropic resolution under 90 seconds.
Enhancing Analysis Algorithm for T2-based water suppressed diffusion MRI (T2wsup-dMRI) by adding least-square fitting
Authors: Kimura Tokunori
Published: August 2023

A T2-based water suppressed diffusion MRI (T2wsup-dMRI) was proposed to solve the CSF partial volume effects (CSF-PVE) in quantifying several parameters in tissue. There a simple closed form (CF) algorithm was used but errors were increased when tissue T2, T2t is long (> 100ms). In this study, to reduce those errors, several algorithms using least-squares (LSQ) fitting method were assessed by simulation and in vivo data. Through this study, the combined algorithm of single and bi-exponential LSQ applied in 2D (TE, b) space is the best in keeping those accuracies especially when applied in random data pattern.
Compressed sensing chemical exchange saturation transfer for simultaneous APT, ssMT, and rNOE imaging
Authors: Chu Ying-Hua , Liebig Patrick , Yuan Yifan , Wang He , Hsu Yi-Cheng
Published: August 2023

We proposed a fast 3D CEST imaging method using compressed sensing SPACE and demonstrated its routine clinical application for simultaneous APT, ssMT, and rNOE imaging. The total scan time of CEST images with 58 z-spectra and an off-resonance map was 6 minutes and 49 seconds. We used low refocusing flip angle and high bandwidth to achieve a narrow point spread function, and the images could be reproduced between different scans. This method could be used for tumor grading and treatment response assessment at 3T.
Which CEST technique provides most insight into tumors – 3T APTw, 3T CEST-MRF or 7T multi-pool CEST?
Authors: Sedykh Maria , Fabian Moritz , Herz Kai , Perlman Or , Farrar Christian , Mennecke Angelika , Schmidt Manuel , Dörfler Arnd , Zaiss Moritz
Published: August 2023

We report on only one glioblastoma patient, but who could be measured with several different CEST MRI methods: 3T APTw, 3T CEST fingerprinting, and 7T multi-pool CEST in order to reveal their relative performance and correlations. Coarse features can be observed in all methods, with MRF and 7T CEST being more versatile in non-active tumor parts. Isolation, separation and smarter combination of different CEST contrast is still needed to improve the diagnostic performance of CEST.
Free-breathing abdominal CEST sequence using water presaturation and precise respiratory synchronization
Authors: Chen Zhensen , Liu Chuyu , Wang Yishi , Chen Weibo , Guo Rui , Wang He , Song Xiaolei
Published: August 2023

To date, chemical exchange saturation transfer (CEST) is rarely used in abdominal imaging of human body due to its high sensitivity to motion. In this study, we developed a free-breathing abdominal CEST sequence that uses a precise respiratory synchronization strategy and includes a water presaturation module. Preliminary in-vivo experiments showed that the proposed sequence outperformed non-triggered and breath-holding abdominal CEST in reducing the slice position inconsistency between the frequency offsets and motion-induced noise.
Using 3D Amide Proton Transfer weighted imaging at 3T to investigate lesions and normal-appearing white matter in Multiple Sclerosis
Authors: Khormi Ibrahim , Al-iedani Oun , Paton Bryan , Lechner-Scott Jeannette , Alshehri Abdulaziz , Fazlollahi Amir , Casagranda Stefano , Papageorgakis Christos , Arango-Lievano Margarita , Ponsonby Anne-Louise , Liebig Patrick , Ramadan Saadallah
Published: August 2023

This novel study explores amide proton transfer weighted (APTw) imaging in people with relapsing-remitting multiple sclerosis (pw-RRMS). We evaluated the APTw signal intensity in selected MS lesions and normal-appearing white matter (NAMW) regions in 9 pw-RRMS. Compared to NAWM regions, a statistically significant increase in APTw signal intensity was observed in the MS lesions. Elevated APTw signal intensity could mark increased mobile myelin proteins decomposition and accumulation from the demyelination process.
A new approach for in-vivo liver CEST imaging
Authors: Wang Zhichao , Zhang Jilei , Zhao Yu , Hua Ting , Tang Guangyu , Li Jianqi , Zhang Yu
Published: August 2023

Chemical exchange saturation transfer (CEST) imaging shows great potentials in the diagnosis of brain diseases. However, there are still many challenges in the hepatic disease due to the fat suppression and large B0 inhomogeneity. In this study, we achieved CEST imaging with simultaneous B0 correction in one sequence, and conducted a pixel-by-pixel prediction on the background reference Z-spectra representing the magnetization transfer and direct saturation effects. Our approach also effectively separated the amide proton transfer (APT) effects from the mixing effect of fat and nuclear Overhauser enhancement (NOE), by subtracting the background reference Z-spectra from the predicted Z-spectra.
Amide proton transfer weighted MR imaging in predicting the stiffness of meningiomas: a feasibility study
Authors: Yu Hao , Wang Yanting , Sun Zhanguo , Wang Weiwei , Zhou Zhe , Dou Weiqiang , Wen Zhibo , Chen Yueqin
Published: August 2023

Stiffness of meningioma is an important factor affecting the surgical resection. In this study we aimed to explore if amide proton transfer-weighted MR imaging has clinical potential of predicting meningioma stiffness
Amide Proton Transfer Imaging of Bladder Cancer at 3 T: A Preliminary Study
Authors: Wang Fang , Xu Yun , Xiang Yong-Sheng , Wu Peng , Shen Ai-Jun , Wang Pei-Jun
Published: August 2023

Amide proton transfer (APT) imaging is an emerging chemical exchange saturation transfer (CEST)-based MRI technique that is sensitive to mobile proteins and peptides in tissue and has drawn considerable attention in the field of cellular and molecular imaging. In the present work, our result demonstrates that it is feasible to use APT imaging for Bladder Cancer (BCa) and it has shown great potential for bladder cancer imaging, thus opening new research avenues in this field.
A Nitroreductase Responsive Fluorescent/ 19F MRI Dual-Imaging Probe for Hypoxia Tumor Detection In Vivo
Authors: Xiao Long , Li Yu , Li Sha , Yuan Yaping , Zhang Lei , Chen Shizhen , Zhou Xin
Published: August 2023

We designed and synthesized a molecular probe-based on fluorescence imaging and 19F MRI bimodal imaging to identify overexpressed nitroreductase in hypoxic tumor. The two imaging modes complement each other in sensitivity and imaging depth, providing more abundant information. More importantly, the bimodal molecular probe is enriched in the tumor region depending on the passive targeting ability and has been well verified by fluorescence imaging and 19F MRI in the metastatic tumor model. And we successfully identified the cancerous left lung and healthy right lung in lung cancer model mouse.
Deep Learning Driven EMI Prediction and Elimination for RF Shielding-Free MRI at 0.055T and 1.5T
Authors: Zhao Yujiao , Xiao Linfang , Liu Yilong , Leong Alex T. L. , Wu Ed
Published: August 2023

All clinical MRI scanners require bulky and enclosed RF shielding rooms to prevent external electromagnetic interference (EMI) signals during data acquisition, and quality electronics inside shielding room (i.e., with minimal EMI emission). A deep learning EMI cancellation strategy is presented to model, predict and remove EMI signals from acquired MRI signals, eliminating the need for RF shielding. We demonstrated that this method worked robustly for various EMI sources from both external environments and internal scanner electronics, producing final image SNRs highly comparable to those obtained using a fully enclosed RF shielding cage in 0.055T and 1.5T experiments.
Design of a Metamaterial-inspired Flexible Structure for MRI Field Enhancement at 3T: a Numerical Approach
Authors: Teymoori Morteza , Yalçınkaya Arda
Published: August 2023

MR imaging has a significant role in medical diagnostics. Imaging quality depends on SNR levels. Higher B0 field and consequently higher RF-field intensity increase SNR but it also elevates the total body SAR. This can be alleviated by local magnetic field enhancement. Metamaterial based structures have shown promising applications in this regard. Here we report a new metamaterial inspired resonant structure for local field enhancement in 3T MRI machine. We show field enhancement capabilities of our design in planar and cylindrical forms, each of which can be used based on the anatomical site under investigation.
Wireless power transfer on non-main eigenmodes within birdcage coil
Authors: Burmistrov Oleg , Kretov Egor , Dashkevich Dmitrii , Seregin Pavel
Published: August 2023

In this work, we investigate a concept of a wireless power transfer system for 1.5T MRI scanner. Our system exploits additional eigenmodes of a birdcage body coil that are not used during the scanning process. Such a solution could be implemented in existing hardware with a minor change in MRI components and at the same time minimize the interference between the power transfer system and imaging functions of the scanner.
Intravoxel incoherent motion imaging of a small-vessel MRI phantom: Preliminary study.
Authors: Tamura Hajime , Ota Hideki , Nagasaka Tatsuo , Mori Ryuichi , Ichinoseki Yuki , Funamoto Kenichi
Published: August 2023

IVIM signal intensities could be compared with the ‘ground truth’ by use of a micro-vessel phantom in this study. In IVIM imaging, images with b = 0 are often included in the analysis, but this study indicated that images with b = 0 should be excluded. In this study, IVIM analysis showed a tendency to overestimate D* and underestimate f.
High-Resolution 3D-TOF MR Angiography in intracranial arteries and branches: A Initial Experience on Comparison between 3.0-T and 5.0-T
Authors: Shi Zhang , Lin Jiang , Zhang Yunfei , Dai Yongming , Zeng Mengsu
Published: August 2023

3D-Time-of-Flight MR Angiography (3D TOF-MRA) of the intracranial vessels is a first-line and noninvasive tool for the evaluation of patients with cerebrovascular disease. However, it is still challenged at 3.0-T MR imaging because peripheral segments of the main arteries can often not be sufﬁciently visualized. The expected remarkable increase in visualizations of intracranial arteries segments and vessel brancher provided by ultra-high field 5.0-T MRI may be valuable for addressing above issues. Our prospective analysis demonstrated that the 5.0-T TOF-MRA provides higher improvement in visualization of distal large arteries and small vessel branches than that at 3.0-T.
Model-free mapping of neural activation in brain white matter based on local fiber architecture
Authors: Zhao Yu , Gao Yurui , Zu Zhongliang , Li Muwei , Schilling Kurt , Anderson Adam , Ding Zhaohua , Gore John
Published: August 2023

We propose a model-free method to detect BOLD signal changes in brain white matter (WM) without an assumption of a hemodynamic response function or a linear shift-invariant response as assumed in conventional general linear models. Instead, neural activations are measured by the synchrony of BOLD signals under constraints of the anisotropic architecture of WM fibers. A 60 subject sub-group sourced from the Human Connectome Project database was used to validate the proposed method at a group level. Our results demonstrate that the proposed method can probe neural activations in WM with high sensitivities and high specificities.
Can Proximal Nerve Morphometrics Predict Disease Severity in Polyneuropathies?
Authors: Chen Yongsheng , Bezanovski Alexandar , Saba Sadaf , Marceau Vince , Xuan Yang , Tariq Mariam , Yang Xue , Li Jun
Published: August 2023

Human sciatic nerve morphometrics were measured for nerve volume, fascicle volume, and fascicle density using a 3D gradient echo sequence with an in-plane resolution of 0.15 x 0.15 mm2. Metrics from healthy controls showed a moderate correlation of nerve and fascicle volumes with body mass index but not with age. There was a strong correlation between nerve volume and the clinical score of disease severity in patients with hereditary neuropathy with liability to pressure palsies.
Reduced white matter venous density is associated with neurodegeneration and cognitive impairment: a susceptibility weighted imaging study
Authors: Li Chenyang , Rusinek Henry , Chen Jingyun , Bokacheva Louisa , Vedvyas Alok , Masurkar Arjun , Wisniewski Thomas , Haacke E.Mark , Ge Yulin
Published: August 2023

High resolution SWI images provide unique contrast to small venous vasculature. The conspicuity of small veins on SWI venography, such as deep medullary vein in white matter (WM), is susceptible to venous blood oxygenation level changes. This study demonstrates a significant association between WM venous density and neurodegenerative feature characterized by brain atrophy in the elderly, but no significant association of WM venous density to white matter hyperintensities (WMHs) load. Further clinical correlative analysis revealed a significant correlation of WM venous density to semantic fluency and different stages of cognitive status.
Genetic susceptibility to myelin and axonal injury as measured by myelin water imaging and multi-shell diffusion in multiple sclerosis
Authors: Rahmanzadeh Reza , Herms Stefan , Burger Bettina , Lu Po-Jui , Barakovic Muhamed , Weigel Matthias , Nguyen Thanh , Wang Yi , La Rosa Francesco , Cuadra Meritxell Bach , Radue Ernst-Wilhelm , Kuhle Jens , Kappos Ludwig , Cichon Sven , Granziera Cristina
Published: August 2023

Despite several large-scale genome-wide association studies (GWAS) have been performed in MS, to date no study explored the relationship between genetic risk factors for MS and the extent of myelin and axon damage in the brain of MS patients, as measured by advanced MRI techniques. Our results identify novel genetic loci that might be associated with myelin and axonal pathology in MS Patients.
3D MRI versus conventional ultrasound tumour measurements for treatment planning of eye tumours
Authors: Klaassen L. , Jaarsma-Coes M.G. , Ferreira T.A. , Vu T.H.K. , Marinkovic M. , Luyten G.P.M. , Rasch C.R.N. , Beenakker J.W.M.
Published: August 2023

The aim of this study was to compare ultrasound and MRI dimension measurements for eye tumours and to determine the most suitable measurement modality. MRI and ultrasound yield similar prominence measurements (median absolute difference 0.3 mm) when tumour extent is visible on both modalities. However, in anteriorly located tumours, MRI measurements are more accurate, and using US for these tumours might lead to an underestimation of tumour diameter. MRI provided insight in 3D tumour geometry, even when tumour extent was difficult to visualize on US, enabling more accurate therapy planning and selection for uveal melanoma patients.
Inter-site reliability of diffusion microstructure measurements: A 3-tissue constrained spherical deconvolution study
Authors: Huang Richard , Newman Benjamin , Druzgal T
Published: August 2023

As large multi-site neuroimaging and diffusion MRI (dMRI) microstructure studies become more common, it is necessary to understand factors affecting reliability of outcome measurements collected across different sites. In this study, we analyze dMRI collected from 3 subjects traveling to 10 different sites with identical MRI scanners, sequence protocols, and software. We perform a detailed microstructural analysis in 212 grey matter and white matter brain regions and find that measurements are generally reliable across sites. However, there remains variation in specific locations that may suggest caution when interpreting small effects in small or hard to measure brain regions.
The Performance of Image Quality Metrics Depends on the Diagnostic Task: A Case Study in Stroke MRI
Authors: Pryde Michelle , Reeve Sarah , Bouchie Taylor , Cora Elena Adela , Volders David , Schmidt Matthias , Abdolell Mohamed , Bowen Chris , Rioux James , Beyea Steven
Published: August 2023

Image Quality Metrics (IQMs) have allowed for objective analysis of MR images in order to optimize protocols or reconstruction algorithms, for example. However, the performance of IQMs depends on the diagnostic task. Therefore, the aim of this study was to explore how well leading IQMs correlate with, or predict, neuroradiologists’ diagnostic confidence in acute and chronic stroke diagnostic tasks. We observed that, although the IQMs in question calculated for T2 FLAIR images could be used to predict neuroradiologists’ diagnostic confidence scores for the chronic stroke diagnostic task, they did not correlate with diagnostic confidence scores for acute stroke.
Spatial alignment of structural images on common and RESOLVE diffusion images in the optic nerve
Authors: Janko Markus , Rose Patrick , Schoeffling Vanessa , Korczynski Oliver , Ponto Katharina , Hoffmann Esther , Brockmann Marc , Kleinekofort Wolfgang , Kronfeld Andrea
Published: August 2023

A successful use of anatomical templates in the evaluation of functional neuroimaging-studies is only possible, if anatomical and functional intra-individual data can be registered with sufficient accuracy. We wanted to investigate the possibility to register structural on common and RESOLVE diffusion-images of the optic nerve. Three volunteers were examined and the structural images were registered to the two diffusion-datasets. Two observers defined seeds for tractography of the optic nerve on the structural and on the diffusion images. Tractography worked with seeds defined on the structural images registered to RESOLVE. Therefore RESOLVE is suitable for the use in template-based studies.
A U-Net based Approach to the Prediction of Regions-of-Interest for Metabolic Sodium Imaging
Authors: Worthoff Wieland , Sommer Yannic , Abbas Zaheer , Shah N. Jon
Published: August 2023

Sodium MRI yields metabolic information about the brain and might indicate existing or emerging pathologies. Often this information is to be determined in a certain region-of-interest (ROI). These ROIs can be, for example, all grey or white matter regions, or more specific sub-regions thereof and it is important to predict these ROIs without bias. Here, an approach to obtain well segmented ROIs is presented based on a deep neural network architecture.
Real-time survey base estimation of gestational age to guide a fetal MRI scan
Authors: Singh Maneesha , Silva Sara , Uus Alena , Grigorescu Irina , Rutherford Mary , Hajnal Jo , Hutter Jana
Published: August 2023

Fetal MRI is an excellent tool for estimating the fetal gestational age using the head circumference measurements. This study measures the biometry information using fast 30 sec survey scans for the measurement of fetal head circumference using 3D UNet, Bi-parietal diameter, Frontal-occipital diameter for the estimation of the fetal gestational age in the second half of gestation. The results show high accuracy in gestational age measurements which correlates well with the clinical data.
T2 Mapping of the Prostate with a Convolutional Neural Network
Authors: Saunders Sara , Gross Mitchell , Metzger Gregory , Bolan Patrick
Published: August 2023

This work compares T2 maps calculated from multi-echo spin-echo MR images using a conventional non-linear least squares (NLLS) fitting method to those constructed with a U-Net, a type of convolutional neural network. The performance of the U-Net and NLLS methods was compared in two retrospectively simulated experiments with a) reduced echo train lengths and b) decreased SNR to emulate accelerated acquisitions. The U-Net generally gave higher accuracy than NLLS fitting, with the trade-off of a modest increase of blurring of the resultant T2 maps.
Brain Growth and Folding Processes Using Deep Neural Networks
Authors: Guo Yanchen , Chavoshnejad Poorya , Razavi Mir , Dai Weiying
Published: August 2023

Finite Element (FE)-based mechanical models can simulate the brain growth and folding process. But they are time consuming due to the large number of nodes in a real human brain and the reverse process to the initial smooth brain surfaces is difficult because it is not invertible problem. Here, we demonstrate a proof-of-concept that deep-learning neural networks (DNN) can learn the growth and folding process of human brain in forward and reverse directions and can predict/retrieve the developed/primary folding patterns in a very fast speed.
Improving Motion-Robust Structural Imaging at 7T with Deep Learning-Based PROPELLER Reconstruction
Authors: Litwiller Daniel , Wang Xinzeng , Lebel R , Yang Baolian , McGovern Jeffrey , Burns Brian , Banerjee Suchandrima
Published: August 2023

The high sensitivity of MRI at 7T enables brain imaging with unprecedented spatial resolution, which can be important to the assessment of a variety of neurological disorders, such as multiple sclerosis, epilepsy, and neurodegenerative disease. With sub-millimeter voxel dimensions, and prolonged acquisition times, however, sensitivity to motion and pulsatility is increased dramatically. This increased sensitivity to motion can be managed with techniques like PROPELLER. Here, we present an initial assessment of a deep learning-based image reconstruction for high-resolution, 7T PROPELLER, and evaluate its ability to improve signal-to-noise ratio, and anatomical conspicuity, without increasing scan time.
Exploration of vision transformer models in medical images synthesis
Authors: Chen Weijie , Estakhraji Seyed Iman Zare , McMillan Alan
Published: August 2023

Applications such as PET/MR and MR-only Radiotherapy Planning need the capability to derive a CT-like image from MRI inputs to enable accurate attenuation correction and dose estimation. More recently, transformer models have been proposed for computer vision applications. Models in the transformer family discard traditional convolution-based network structures and emphasize the importance of non-local information yielding potentially more realistic outputs. To evaluate the performance of SwinIR, TransUet, and Unet. After comparing results visually and quantitatively, the SwinIR models and TransUnet models appear to provide higher-quality synthetic CT scans compared to the conventional Unet.
Synthetic MRI aids in glioblastoma survival prediction
Authors: Navarro-González Rafael , Moya-Sáez Elisa , de Luis-García Rodrigo , Aja-Fernández Santiago , Alberola-López Carlos
Published: August 2023

Radiomics systems for survival prediction in glioblastoma multiforme could enhance patient management, personalizing its treatment and obtaining better outcomes. However, these systems are data-demanding multimodality images. Thus, synthetic MRI could improve radiomics systems by retrospectively completing databases or replacing artifacted images. In this work we analyze the replacement of an acquired modality by a synthesized counterversion for predicting survival with an independent radiomic system. Results prove that a model fed with the synthesized modality achieves similar performance compared to using the acquired modality, and better performance than using a corrupted modality or a model trained from scratch without this modality.
Brain Tumour Studies using Low-Dose Gadolinium-Based Contrast Agent Dynamic Contrast Enhancement MRI
Authors: Zhu Xiaoping , Lewis Daniel , Li Ka-Loh , Jackson Alan
Published: August 2023

Using one-fifth of standard GBCA dose, high spatial resolution (LDHS) whole brain pharmacokinetic maps was calculated and compared with those from dual temporal resolution (DTR) DCE, which combines high temporal resolution (LDHT) and full dose spatial resolution DCE. Results from Monte Carlo simulation suggested the measurement uncertainty and bias reduced to negligible whilst CNR of tumour concentration curves is greater than 3.1. The in-vivo LDHS maps have compatible accuracy with those from HT DCE, moreover revealing tumor heterogeneity to the quality DTR have achieved. Largely reduced dose enabled safer exams for patients undergoing repeated administration of GBCA.
19-hour stability of T2* mapping of brain regions
Authors: Dietrich Olaf , Levin Johannes , Remi Jan
Published: August 2023

The purpose of this study was to assess the temporal stability of T2* mapping results in the human brain of healthy volunteers. Three healthy male participants (36-45y) were each scanned 6 times over a period of 19 hours. Median T2* values were determined within the 9 regions of the MNI structural atlas. For each region, mean values, standard deviations (SD), and the coefficients of variation were calculated over the six acquisition time points. The results demonstrate very good intra-individual stability of T2* in different brain regions with coefficients of variations lower than 3 % in all evaluated regions and volunteers.
Abdominal Water-Only T2 Estimation at 0.55T using a 3D Stack-of-Stars TSE-DIXON Technique
Authors: Keerthivasan Mahesh , Bruno Mary , Solomon Eddy , Grodzki David , Bhat Himanshu , Block Kai Tobias , Chandarana Hersh
Published: August 2023

We explore the use of a stack-of-stars 3D TSE sequence along with multi-echo DIXON readouts for SNR-efficient, free-breathing water-only T2 estimation at 0.55T. A subspace constrained reconstruction is combined with a multi-step fat/ water separation algorithm to generate water-only T2-weighted images and T2 maps.
Rapid Low SAR T2 Relaxometry near Metallic Implants
Authors: Keerthivasan Mahesh , Fritz Jan , Schwarzkopf Ran , Khodarahmi Iman
Published: August 2023

Quantitative T2 mapping in the presence of metal implants is affected by susceptibility-related artifacts. We propose a low flip angle view angle tilting-enabled turbo-spin echo sequence along with spatiotemporal undersampling for low SAR scan efficient T2 mapping. The proposed technique would allow 2.5min T2 mapping with high temporal sampling of the T2 relaxation curve. Performance of the proposed technique is evaluated using retrospective under-sampling simulations and phantom experiments using a cobalt-chromium hip arthroplasty implant.
Characterization and Correction of Diffusion Gradient-Induced Eddy Currents in Echo-Planar and Spiral Cardiac Diffusion Tensor Imaging
Authors: van Gorkum Robbert , Guenthner Christian , Koethe Andreas , Stoeck Christian , Kozerke Sebastian
Published: August 2023

Second-order motion-compensated diffusion encoding gradient waveforms cause substantial eddy currents (ECs), which can violate the linear-system assumption of a gradient impulse response function and thus require a dedicated measurement and reconstruction approach. Using a 3-dimensional spectroscopic imaging method, diffusion encoding gradient-induced ECs were characterized and non-linear effects were identified. When accounting for zeroth- and first-order diffusion encoding gradient-induced ECs besides off-resonance and trajectory-induced concomitant fields and ECs, image distortions could be adequately mitigated in echo-planar and spiral in vivo second-order motion-compensated cardiac diffusion tensor imaging sequences.
Quantitative T2* and T1 mapping of post-mortem MS tissue at 7T for discrimination of normal-appearing and dirty-appearing white matter pathology
Authors: Thevakumaran Risavarshni , Groh Adam , Stratton Jo , Rudko David
Published: August 2023

Quantitative T2* and T1 relaxometry metrics calculated at 7T have high sensitivity to myelin and can be jointly used to identify dirty-appearing white matter (DAWM) and normal-appearing white matter (NAWM) pathology in post-mortem, multiple sclerosis (MS) brain tissue. Relaxometry mapping was performed on fixed, cerebral brain samples from MS patients and healthy donors. T2* and T1 distributions in WM from MS tissue exhibited bimodality and were shifted to higher relaxation time values compared to healthy tissue. Using k-means clustering applied to 2D T2* and T1 MS tissue data, regions of DAWM were detected in periventricular WM for MS tissue samples.
In vivo mapping of hippocampal venous vasculature and oxygen saturation using dual-echo SWI/QSM on 7T: a potential marker for neurodegeneration
Authors: Li Chenyang , Jiang Li , Muccio Marco , Buch Sagar , Lu Hanzhang , Haacke E.Mark , Ge Yulin
Published: August 2023

In this study, we reconstructed the venous drainage course of Basal vein of Rosenthal (BVR) and its tributaries using dual-echo SWI/QSM. Consistent with existing knowledge of venous anatomy, our results show that BVR drains blood from multiple tissue structures such as insula, amygdala and hippocampus. Inferior ventricular vein (IVV) and medial atrial vein (MAV), two tributaries of BVR, are anatomically relevant to the venous drainage in hippocampus. With the proposed technique, we extracted the venous blood susceptibility value in BVR and IVV/MAV to examine its feasibility in characterizing changes of venous oxygenation level related to hippocampal neurodegeneration.
High-resolution Diffusion Tensor Imaging at 7T with Multi-band Multi-shot EPI acquisition and Deep Learning Reconstruction
Authors: Wang Xinzeng , Yang Baolian , Label Marc , Moeller Steen , Banerjee Suchandrima
Published: August 2023

Diffusion tensor imaging (DTI) is a well-established tool for providing insights into brain network connectivity and detecting brain microstructure but suffers from artifacts, low SNR, low spatial resolution, and long scan times. High-resolution DTI at 7T with multiband MUSE (MB-MUSE) and noise reduction methods have shown many potentials for mitigating these challenges. In this study, we combine a deep learning reconstruction method with MB-MUSE to overcome the image quality challenges and demonstrate improved quantification of high-resolution DTI at 7T compared with MB-MUSE and MB-MUSE with low-rank denoising.
Visual Cortex Bioenergetic Abnormalities in Schizophrenia
Authors: Bashir Adil , Lahti Adrienne , Kraguljac Nina , Denney Thomas
Published: August 2023

This study measured high energy metabolite ratios and CK and ATP metabolic reaction rate in visual cortex of SZ patients and HCs. The forward rate constant hence ATP production flux through CK enzyme was significantly lower in SZ patients when compared to age/sex matched controls. We did not observe abnormalities in metabolite concentration. Impaired CK reaction may underlie abnormal neuro function and information processing in SZ.
Is curvature a biomarker for major depressive disorder? A morphological study using 7T MRI
Authors: Lago Tara , Reynoso Mariella , Jacob Yael , Alper Judy , Delman Bradley , Murrough James , Balchandani Priti , Verma Gaurav
Published: August 2023

Numerous studies have analyzed morphological measurements to better understand how depression alters the brain, but few studies have explored curvature as a potential biomarker. By analyzing data from 7T MRI scans, we aimed to determine whether curvature measurements can differentiate between MDD patients and controls. We performed generalized linear models to analyze the relationship between participants’ status and measurements for intrinsic curvature index, Gaussian curvature, mean curvature, and folding index in thirty-four brain regions. Six regions showed significantly higher measures of curvature in MDD patients: the inferior temporal, pars triangularis, supramarginal, lateral orbitofrontal, isthmus cingulate, and entorhinal.
Feasibility of $$$R_2^*$$$ /QSM susceptibility source separation for application in multiple sclerosis
Authors: Dimov Alexey , Nguyen Thanh , Gillen Kelly , Marcille Melanie , Spincemaille Pascal , David Pitt , Gauthier Susan , Wang Yi
Published: August 2023

For determination of dia- and paramagnetic sources, quantitative susceptibility mapping (QSM) of phase is combined with a R2* model of magnitude of multiecho gradient echo data, which is advantageous over R2’ model that requires additional T2 mapping, Magnetic source separation was performed in in vivo (17 multiple sclerosis (MS) patients) and ex vivo (a whole brain and 3 MS brain tissue blocks). Both R2* and R2’ methods were found to be well correlated in vivo data. R2* based positive and negative susceptibility sources estimation in ex vivo MS lesions correlated with optical density of lesion histology.
Association Between Common MRI Metrics of Disease Activity in MS and Spinal Cord Atrophy
Authors: Zeydan Burcu , Neyal Nur , Son Jiye , Morrison Holly , Atkinson Elizabeth , Port John , Kantarci Kejal , Kantarci Orhun
Published: August 2023

Cervical spinal cord atrophy is an important MRI measure that correlates with progressive MS. We have previously shown that the cranio-caudal loss of cervical cord area correlates with the evolution in MS disease continuum. In this prospective study, in addition to age, we showed that thalamic volumes may correlate with cervical cord area measurements, possibly through a Wallerian degeneration mechanism, while total brain lesion volumes do not. Our findings suggest that spinal cord area measurements in MS is potentially an independent metric from lesion load measurements but can be complemented by thalamic volume measurements as imaging outcomes in clinical trials.
Brain Oxygen Extraction Fraction in Patients with Normal Pressure Hydrocephalus
Authors: Zhuang Hangwei , Cho Junghun , Chiang Gloria , Kovanlikaya Ilhami , Heier Linda , Wang Yi
Published: August 2023

Oxygen extraction fraction (OEF) maps were obtained from multi-echo gradient echo (mGRE) using a novel MRI biophysics model called QSM+qBOLD (QQ) in Normal Pressure Hydrocephalus (NPH) patients. OEF of the whole brain, cortical gray matter, caudate, and pallidum were significantly negatively correlated with ventricular volume. The finding demonstrates the feasibility of OEF mapping using MRI in NPH patients and suggests global and local neurodegeneration.
Longitudinal changes in brain oxygen extraction fraction (OEF) in older adults: relationship to vascular and Alzheimer’s pathology
Authors: Lin Zixuan , Lim Chantelle , Jiang Dengrong , Soldan Anja , Pettigrew Corinne , Oishi Kumiko , Liu Peiying , Albert Marilyn , Lu Hanzhang
Published: August 2023

Oxygen extraction fraction (OEF) has been suggested to be differentially affected by Alzheimer’s and vascular pathology in older adults. We aimed to investigate age-related OEF change with a longitudinal study design. 138 elderly participants were recruited with a 2-year follow-up. Individuals with higher vascular risks showed significant elevation in OEF but not those with lower vascular risks. Higher OEF was also associated with a faster growth in white matter hyperintensities, but not with any Alzheimer’s pathology or APOE gene. The results suggested a prominent effect of vascular pathology on OEF in aging.
Brain Ultrashort-T2* component measurements in patients with multiple sclerosis
Authors: Deveshwar Nikhil , Caverzasi Eduardo , Yao Jingwen , Green Ari , Henry Roland , Larson Peder
Published: August 2023

This work presents a study measuring and characterizing the brain ultrashort-T2* component in patients suffering from MS. Our results show that the measured T2* relaxation time of the ultrashort-T2* component is significantly lower in almost all white matter ROIs measured. Fitted signal curves for the fractional component suggest the fractional component fits well in certain patients but not as well in others suggesting a more robust fitting model may be necessary for using this UTE relaxometry technique in patients with MS.
Tracking motor and cognitive network connectivity in MS over 2 years using SFCI, a pathway-combined connectivity metric
Authors: Bhattacharyya Pallab , Fox Robert , Lin Jian , Sakaie Ken , Lowe Mark
Published: August 2023

Motor and cognitive network integrity in multiple sclerosis over 2 years in patients receiving the same therapy was tracked using structural and functional connectivity index (SFCI), a metric that combines functional and structural connectivity along function-specific pathways and then forms a pathway-combined composite metric. Changes of the individual measures, functional connectivity and transverse diffusivity along transcallosal motor and frontoparietal cognitive pathways, were also tracked over 2 years. Pathway-combined SFCI was more efficient in tracking network integrity than the individual imaging measures or pathway-specific composite metric.
Association of Fibroglandular Tissue ADC features on Diffusion-weighted MRI with Breast Cancer Risk
Authors: Surento Wesley , Kazerouni Anum , Yee Janis , Biswas Debosmita , Hippe Daniel , Rahbar Habib , Partridge Savannah
Published: August 2023

In this study, we investigated the association of fibroglandular tissue (FGT) apparent diffusion coefficient (ADC) measures with risk of breast cancer. Whole breast FGT regions were segmented on diffusion-weighted MRI (DWI) using a semi-automated fuzzy c-means-based algorithm. In high-risk screening cohort, ADC measures of FGT were compared in subjects with subsequent cancer diagnosis versus matched negative controls. Our findings indicate a modest negative association between FGT ADC and subsequent cancer diagnosis, with greater predictive value than mammographic density in the same cohort, pointing to the possible utility of DWI in the assessment of breast cancer risk.
A Data-Driven Sequential Backward Selection Framework to Accelerate Diffusion-Relaxation Prostate Microstructure Mapping
Authors: Zhang Zhaohuan , Mirak Sohrab Afshari , Hosseiny Melina , Azadikhah Afshin , Bajgiran Amir , Priester Alan , Sung Kyunghyun , Sisk Anthony , Reiter Robert , Raman Steven , Enzmann Dieter , Wu Holden
Published: August 2023

Diffusion-Relaxation Correlation Spectrum Imaging (DR-CSI) can provide unique microstructural information for prostate cancer characterization, but requires longer scan times for two-dimensional encoding of TE and b-values. This study developed a data-driven sequential backward selection framework that determined subsampled encoding schemes for DR-CSI, achieving 70% reduction of scan time to 6min while maintaining accurate ex vivo prostate microstructure mapping.
Bilateral asymmetry of early parenchymal kinetics predicts response of breast cancer to neoadjuvant therapy
Authors: Ren Zhen , Pineda Federico , Howard Frederick , Hill Elle , Szasz Teodora , Safi Rabia , Medved Milica , Nanda Rita , Yankeelov Thomas , Abe Hiroyuki , Karczmar Gregory
Published: August 2023

We retrospectively reviewed data from 23 patients who received neoadjuvant therapy (NAT) and were scanned with a protocol that included ultrafast DCE-MRI (temporal resolution = 3-7 seconds) for the first minute after contrast injection prior to NAT. We measured parenchymal kinetics from ipsi- and contra-lateral normal parenchyma separately, so that new parameters related to bilateral parenchymal enhancement asymmetry could be calculated. The results showed that patients with similar pre-NAT parenchymal enhancement kinetics in ipsi- and contralateral normal parenchyma were more likely to achieve pCR post NAT ($$$p < 0.02$$$).