bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of IDH Mutation Status of Gliomas Using Pre-operative MR Images: a Fully Automatic Convolutional Neural Networks Based Approach.
Authors: Chen Xiaohua , Chen Zhiqiang , Wang Zhuo , Zhang Shaoru , Zhou Yunshu , Liu Shili , Zhang Ruodi , Xiong Yuhui , Wang Aijun
Published: August 2024

Using an automated method of convolutional neural networks (CNNs), we aimed to predict the IDH mutation status of gliomas from conventional preoperative MRI in this study. We conclude that the Markov Random Field-U-Net network can accurately segment the tumor region. Using a modified 34-layer Resnet network, we were subsequently able to predict IDH mutation status effectively. Consequently, the model has the potential to be utilized more broadly as a practical tool with reproducibility, this model has the potential to be a practical tool for the non-invasive characterization of gliomas to help the individualized treatment planning.
Prediction of active Multiple Sclerosis lesions through use of logistic regression classifier and first-order features
Authors: Nguyen Vivian , Hasse Adam , Tao Emily , Jang Jihye , Javed Adil , Carroll Timothy , Kawaji Keigo
Published: August 2024

Multiple Sclerosis is a neuroinflammatory disease in which the immune system attacks nerve fibers and myelin sheaths, leading to the formation of lesions through white matter. Gadolinium-enhanced MRI is used to diagnose and track the progression of MS. Active MS lesions enhance with gadolinium, but there is an interest in prediction of lesion enhancement based on lesion features. In this study, we examined first-order features derived from T1w pre-contrast MS lesions acquired on multiple 3T imagers at a single center to train a logistic regression classifier to classify lesions as active or inactive.
Unsupervised Domain Adaptation for Automated Knee Osteoarthritis Phenotype Classification
Authors: Zhong Junru , Yao Yongcheng , Cahill Dόnal , Xiao Fan , Li Siyue , Lee Jack , Ho Kevin Ki-Wai , Ong Michael Tim-Yun , Griffith James , Chen Weitian
Published: August 2024

We propose a knee osteoarthritis phenotype classification system using unsupervised domain adaptation (UDA). A convolutional neural network was initially trained on a large source dataset (Osteoarthritis Initiative, n=3116), then adapted to a small target dataset (n=50). We observed a significant performance improvement compared to the classifiers trained solely on the target dataset. We demonstrated the feasibility of applying UDA for medical image analysis in a small label-free dataset.
RiskForm: A novel risk formulation to improve progressive disease outcome prediction
Authors: Rajamohan Haresh Rengaraj , Cho Kyunghyun , Kijowski Richard , Deniz Cem
Published: August 2024

We propose a novel risk constraint to improve the performance of deep learning models on progressive disorders. On the Osteoarthritis Initiative (OAI) dataset, the proposed approach outperforms a baseline model trained with the standard cross-entropy loss on predicting total knee replacement (TKR) within 3 different time horizons- 1 year, 2 years and 4 years of the MRI date. It further generalizes better to the external Multicenter Osteoarthritis Study dataset.
Free Breathing δUTE Sequence for T2* Mapping of Lung in Healthy and Post-COVID Adults
Authors: Malis Vadim , Kassai Yoshimori , Bae Won , Vucevic Diana , Ohno Yoshiharu , Miyazaki Mitsue
Published: August 2024

δUTE sequence collects multiple closely spaced short TE (<2ms) echoes resulting in a more accurate T2* mapping of anatomies with short T2 time. Application to lungs reveals inhomogeneities in T2* maps in post-COVID-19 adults.
Dysfunctional Respiratory Patterns in Symptomatic Post-Acute Covid-19 Patients on Dynamic High Temporal Resolution Free-Breathing Lung MRI
Authors: Azour Lea , Mikheev Artem , Rusinek Henry , Keerthivasan Mahesh Bharath , Bruno Mary , Moore William , Chandarana Hersh
Published: August 2024

Dynamic high temporal resolution free-breathing MRI allows for quantification of respiratory duration, depth and rate—parameters separate from those provided by pulmonary function tests. Post-acute Covid patients with persisting cardiopulmonary symptoms demonstrated larger tidal area, longer duration of inspiration, and larger variability in respirations.
Persistent Abnormalities in Lung Water Density Observed After COVID-19 Recovery
Authors: Keen Christopher , Grenier Justin , Šereš Peter , Stobbe Robert , White James , Beaulieu Christian , Paterson Ian , Thompson Richard
Published: August 2024

The long term effects of COVID-19, including those affecting the lung, represent a new global health burden. Lung water density (LWD) MRI is an emerging quantitative technique that can be used to measure relative LWD (rLWD) in 3D. 187 patients were imaged 5 months after COVID-19 recovery using LWD MRI and were compared to 91 healthy controls. The COVID-recovered group displayed significantly higher mean rLWD values as compared to healthy controls. Additionally, local and global patterns of abnormally increased and decreased rLWD were observed in the COVID-recovered group.
MRI for characterization of cardiac function in suspected myocarditis as post-acute sequelae of COVID-19
Authors: Ibrahim El-Sayed , Rubenstein Jason , Sosa Antonio , Koch Kevin , Stojanovska Jadranka , Benjamin Ivor
Published: August 2024

Among COVID-19 induced cardiac complications, myocarditis has clinical significance because it can result in permanent myocardial damage which leads to poor outcome. In this study, we studied 65 consecutive COVID-19 patients who underwent cardiac MRI post COVID-19 due to concerns of post-COVID myocarditis or other cardiomyopathies, where MRI was used to identify suspected versus excluded myocarditis based on LGE and T1/ECV/T2 mappings. The results demonstrated the value of MRI systolic strain and diastolic strain rate as sensitive markers for early detection of subclinical cardiac dysfunction and characterizing the heart contractility pattern in high-risk patients with suspected myocarditis versus excluded myocarditis.
Potential brain neural mechanisms underlying Long-COVID-19 syndrome
Authors: Pan Tingting , Wu Yaping , Yu Xuan , Bai Yan , Wang Meiyun
Published: August 2024

The neural mechanisms underlying the neuropsychiatric disorders suffered by Long-Covid-19 patients remain unknown. Non-invasive [18F]-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) brain imaging is an effective way to study this issue. In the present study, based on 18F-FDG PET brain imaging and analysis of the brain metabolic network, we found significant reductions in metabolic levels in the frontal, temporal, and parietal lobes in patients with Long-Covid-19. A significant reduction in metabolic connectivity between temporal and frontal networks in patients with Long-Covid-19 may be the underlying neural mechanism underlying cognitive impairment.
Frontal-specific elevation of cerebral oxygen extraction fraction in COVID-19 ICU survivors: a pilot study
Authors: Jiang Dengrong , Rando Hannah , Khanduja Shivalika , Song Jie , Hazel Kaisha , Pottanat George , Jones Ebony , Xu Cuimei , Shi Wen , Hu Zhiyi , Lin Doris , Yasar Sevil , Cho Sung-Min , Lu Hanzhang
Published: August 2024

Compared to patients with mild COVID-19 disease, critically ill patients requiring intensive-care-unit (ICU) admission are at higher risk of developing post-acute COVID-19 syndrome (PCS). The mechanisms underlying PCS are under investigation and may involve neurovascular damage, which can disrupt oxygen delivery and utilization in the brain. Cerebral oxygen-extraction-fraction (OEF) is an important parameter for the brain’s oxygen utilization. In this work, we evaluated the post-acute changes of regional OEF in COVID-19 ICU-survivors, and found that ICU-survivors had significantly increased OEF in the frontal lobe compared to controls. This suggests that regional OEF may provide a sensitive biomarker in studying PCS.
End-of-life symptoms and imaging signs in COVID-19 patients with renal failure induced encephalopathy
Authors: Jiang Li , Ge Yulin
Published: August 2024

COVID-19 continues to be a threat to global public health. A large number of studies have reported various neurological symptoms in COVID-19 patients even after the respiratory symptoms have resolved. In severe cases, the neurological complications induced by SARS-CoV-2 can lead to extensive neuroimaging abnormality. Additionally, previous studies have shown that, among COVID-19 patients who went through dialysis, the short-term mortality rate is high. In this study, we reported three cases of deceased patients who had severe encephalopathy while going through dialysis, to better understand their fatal disease course and associated brain MRI and clinical symptoms complicated by COVID-19.
Identification of brain alterations specifically associated with Duchenne Muscular Dystrophy using multi-modal MRI and multivariate analysis
Authors: Peruzzo Denis , Ciceri Tommaso , Mascheretti Sara , Lampis Valentina , Arrigoni Filippo , Agarwal Nivedita , Giubergia Alice , Villa Filippo , Crippa Alessandro , Nobile Maria , Mani Elisa , Russo Annamaria , D'Angelo Maria
Published: August 2024

Duchenne Muscular Dystrophy (DMD) is a genetic disease caused by an abnormal dystrophin expression and it is often associated with other cognitive and behavioral impairments, which are an important confounding factor while investigating the effects of dystrophin abnormal expression in the central nervous system. We applied a Machine Learning based analysis to T1-weighted and Diffusion Tensor Imaging data of 36 subjects accounting also for their demographic, cognitive and behavioral profiles. DMD is specifically associated with a reduced microstructural integrity of long fiber bundles and a reduced cortical thickness of the motor cortex, cingulate cortex, hippocampus and insula.
Altered brain structure in a mouse model of ALS with mutation in Tardbp is observed from early adulthood
Authors: Bach Aurea Martins , Spring Shoshana , Ali Zeinab , Nieman Brian , Sled John , Nair Remya , Fisher Elizabeth , Corrochano Silvia , Cunningham Thomas , Lerch Jason , Miller Karla
Published: August 2024

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by aggregates of TDP-43 in the brain. The TDP-M323K mouse model of ALS has a mutation in Tardbp and presents progressive motor, neurological and behavioural phenotypes, in addition to widespread changes in brain volume at 12 months of age. Here, we assessed if these volumetric changes are progressive or if they are already present before other symptoms start to present. Post-mortem structural MRI in 3- and 12 months-old TDP-M323K mice revealed that brain volume is already altered in young adults despite the absence of major clinical and pathological phenotypes.
Hippocampal subfields atrophy based on automated volumetry analysis in end-stage-renal disease patients
Authors: Jiang Yuhan , Li Yuan , Song Qingwei , Miao Yanwei
Published: August 2024

Cognitive impairment is very common in patients with end-stage renal disease (ESRD). Hippocampal atrophy has been proven to be an effective marker for distinguishing the normal population from the cognitively impaired patients. However, there are almost no studies on changes in hippocampal structure, especially the volume of hippocampal subfields, in ESRD patients. In this study, automated volumetry of hippocampal subfields in ESRD patients was performed and compared with healthy controls, and found that ESRD patients have hippocampal subfield atrophy, especially in bilateral fimbria and right hippocampal tail.
Alterations of cortical and subcortical structures in mild cognitive impairment
Authors: Wang Junxia , Zhang Bing
Published: August 2024

In this study, we investigated alterations of cortical morphology, subcortical nuclei volume and morphology in MCI using multiple morphological analysis methods. Moreover, we explored these imaging features relationship with cognitive performances and their efficiency in classification of MCI using support vector machine (SVM). We speculate that combining volumetric and morphological analysis methods will outperform than single analysis method in MCI identification.
Comparison of DWI-ASL Mismatch and Collaterals for Predicting Clinical Outcome in Patients with Subacute Ischemic Stroke
Authors: Li Yi , Wu Di , Liang Xiaoyun , Li Zihan , Cai Pinjia , Huang Feng , Zhu Wenzhen
Published: August 2024

As a contrast agent-free MR imaging, ASL will not cause contrast agent-associated nephrotoxicity and allergic reaction. However, low image resolution makes it time-consuming and difficult for clinicians to quantify hypoperfusion volumes using ASL. We developed an automatic and robust algorithm to quantify core-penumbra mismatch based on DWI-ASL. Furthermore, models were built with clinical and/or imaging features and their performances in predicting prognosis of subacute stroke patients were evaluated. When combining infarct location and collaterals with NIHSS, but not mismatch ratio, the model can predict prognosis of subacute stroke patients the best. Therefore, this may add benefits to delayed intervention.
Prediction for clinical outcome using prominent vessel sign in patients with subacute cerebral infarction
Authors: Chang Peipei , Xie Lizhi , Miao Yanwei
Published: August 2024

This study was to investigate the effect of prominent vessel sign (PVS) in patients with unilateral subacute infarction on hemorrhagic transformation (HT) and short-term prognosis by using susceptibility-weighted imaging (SWI). It was found that there were no significant differences in the incidence of prominent cortical veins (PCV), prominent medullary veins (PMV), PCV+PMV, SWI-ASPECT score and SWI-DWI mismatch score between two groups. Although higher than the HC group, there was no difference in venous MSV between HT and NHT groups. NIHSS score was negatively correlated with SWI-ASPECT score and DWI-ASPECT score and NIHSS score at discharge was negatively correlated with the proportion of PCV, PCV + PMV and MSV of CV. This study suggesting that PVS had little effect on HT in patients with unilateral subacute infarction, but related to worse short-term clinical status.
Prediction of brain invasion in meningioma by preoperative MRI based on U-NET and DenseNet convolutional neural network
Authors: Yu Juan , Liu Yujian , Deng kan , Lin Fan , Yue Guanghui , Du Jie , Luo Liangping
Published: August 2024

The new guidelines suggest that brain invasion is not a unique feature of malignant meningiomas, but may be a pathologic condition of benign meningiomas with a potential risk of recurrence. However, maximum preservation of normal brain tissue is essential for surgery. Accurate preoperative MRI evaluation of meningioma brain invasion is expected to solve the dilemma faced by neurosurgeons.
Deep Learning-based noise reduction for advanced brain MR imaging: Application to quantitative biomarkers in brain tumors
Authors: Debacker Clement , Pouliquen Geoffroy , Charron Sylvain , Fayolle Anna , Prevost Valentin , de Graaf Wolter , Roux Alexandre , Pallud Johan , Oppenheim Catherine
Published: August 2024

Our work is the clinical validation of a deep-learning algorithm (DLR) used to denoise MR images on quantitative MR biomarkers. Since it has been trained on including T1- and T2-weighted conventional images, in healthy volunteers, its effects on multiparametric quantitative MRI in patients, are uncertain. It could potentially improve brain tumors characterization by providing quantitative biomarkers under clinical time-constraints.
Histogram analysis based on T2 mapping can predict the molecular markers in meningiomas
Authors: Li Zongye , Yang Yijie , Zhang Yue , Lin Yanhong , Wang Xiao , Zhuang Yuchuan , Yang Qinqin , Gao Eryuan , Ren Yanan , Zhang Yong , Cai Shuhui , Chen Zhong , Cai Congbo , Cheng Jingliang , Bao Jianfeng
Published: August 2024

There is an immediate need for neurosurgeons to be able to identify certain molecular markers’ status of meningioma preoperatively, such as progesterone receptors and S100. In this study, we explored the use of histogram analysis of T2 maps and ADC maps in predicting such molecular markers. T2 maps and ADC maps could serve as useful tools for predicting PR and S100 status of meningiomas. Similar studies may be extended to investigate other pathological markers.
Multi-Parametric MRI-based radiomics for noninvasively predicting Tert genotype in Oligodendroglomas
Authors: Zhao Jun , Gan Tiejun , Ke Xiaoai , Hu Wanjun , Zhou Qing , Zhang Jing , Zhou Junlin
Published: August 2024

In this study, radiomic based predictive models using MRI can non-invasively assess Tert genotype of Oligodendrogliomas(ODs). Compared With histopathological assessment,radiomic based predictive models has its unique advantages in assessing Tert genotype of ODs. such as noninvasive, more comprehensive information about tumor heterogeneity and repeatable. Furthermore,radiomic based predictive models can clearly and directly show Tert genotype of ODs. Therefore, it is a potential alternative to invasive biopsy.
A clini-radiomics model based magnetic resonance imaging for differentiating fibroblastic from non-fibroblastic meningioma
Authors: Han Tao , Liu Xianwang , Zhou Junlin
Published: August 2024

This study evaluated the feasibility of noninvasive preoperative differentiation fibroblastic meningioma (FM) from non-fibroblastic meningiomas (nFM) based a clini-radiomics model. A total of thirteen radiomics features were included after Selectpercentile and Lasso feature screening. Our results showed that Random forest is the most efficient among the six radiomics models in differentiating FM from nFM, and the diagnostic efficacy of clini-radiomics models in training and validation group is further improved. Therefore, we believe that the clini-radiomics model is of great value in noninvasive preoperative differentiation of FM and nFM and contributes to the selection of individualized treatment options for meningioma patients.
Novel non-invasive cardiac MR oximetry and 4-dimensional flow in single ventricle hearts
Authors: Desai Lajja , Weiss Elizabeth , Varghese Juliet , Ahmad Rizwan , Simonetti Orlando , Rigsby Cynthia , Markl Michael
Published: August 2024

Cardiac magnetic resonance imaging can provide novel non-invasive estimation of blood oxygen saturation and quantification of blood flow streaming in pediatric and adult patients with complex single ventricle physiology. Non-uniform distribution of inferior and superior caval blood flow and oxygenation to the left and right lungs may cause complications in patients with Fontan circulation. An individualized, comprehensive approach may identify patients at risk.
Comparison of 3D Ultra-short Echo Time (UTE) Phase-Resolved Functional Lung (PREFUL) with Hyperpolarized 129Xe MRI in Pediatric Cystic Fibrosis
Authors: Munidasa Samal , Zanette Brandon , Dumas Marie-Pier , Wee Wallace , Au Jacky , Braganza Sharon , Li Daniel , Ratjen Felix , Santyr Giles
Published: August 2024

2D phase-resolved functional lung (PREFUL) MRI has been shown to correlate with hyperpolarized Xenon MRI (Xe-MRI) in pediatric Cystic Fibrosis (CF) lung disease but ventilation defects may be missed using the 2D approach. In this study we develop a 3D ultra-short echo time (UTE) PREFUL MRI method and compare to 2D PREFUL MRI and Xe-MRI in CF. 3D UTE PREFUL MRI showed a lower bias between Xe-MRI as compared to 2D PREFUL and was able to detect ventilation defects missed by the 2D approach, suggesting that the 3D approach may be a more comprehensive measure of ventilation in pediatric CF.
Fetal Cardiovascular Magnetic Resonance: A Comparison of Doppler Ultrasound and Self-Gating Techniques
Authors: Polak Paul , von Kleist Henrik , Hott Marcus , Englund Erin , Barker Alex , Cuneo Bettina , Friesen Richard , Browne Lorna , Moghari Mehdi
Published: August 2024

Fetal cardiovascular magnetic resonance requires an accurate measure of the fetal heart rate for cine image acquisitions. In this work, we compared the use of Doppler ultrasound with a self-gating technique in 8 subjects. Images were acquired in the axial and short-axis orientations of the fetal heart, and the images were compared with qualitative scoring, heart rate analysis, and ventricular volumes. It was found that the techniques had only minor differences demonstrating the potential use of retrospective self-gating in the clinic, as it reduces workflow complexity and may lead to shorter exam times for pregnant women.
Optical position tracking fiducial marker for rigid body motion parameter estimation with high performance
Authors: Silic Marina , Jegatheesan Aravinthan , Tam Fred , Graham Simon
Published: August 2024

Optical position tracking (OPT) using fiducial markers is advantageous for data acquisition of rigid body head motion parameters and motion correction in magnetic resonance imaging (MRI). Many opportunities still remain to improve OPT through the development of new devices. A promising prototype OPT marker and analysis pathway are described. The marker through-plane degree of freedom (DOF) precision was enhanced via moiré patterns and stereovision. Precision was assessed using positional and rotational stages in all 6DOF. Initial results strongly suggest that with minimal additional work, the OPT marker will provide excellent performance in a 3 T MRI system.
Phase-Constrained Reconstruction for Enhancing PROPELLER SNR
Authors: Chang Yuchou , Saju Gulfam , Yu Jasina , Abiri Reza , Liu Tianming , Li Zhiqiang
Published: August 2024

PROPELLER blade acquisition has been accelerated by undersampling blade k-space data. Missing data on each blade can be reconstructed by parallel MRI reconstruction methods. However, noise deteriorates the blade and the overall image quality. To enhance the signal-to-noise ratio (SNR), phase-constrained reconstruction is studied for improving the SNR of PROPELLER imaging. Phase-constrained reconstruction can improve PROPELLER imaging SNR when the acceleration of data acquisition is used. Optimal selection of the ACS lines and the outer reduction factors is expected to achieve a better SNR and accelerate the PROPELLER imaging speed simultaneously.
In-plane B0 inhomogeneity effects in T2* mapping
Authors: Morrell Glen
Published: August 2024

Main field B0 inhomogeneity may adversely affect the accuracy of T2* mapping in the abdomen even at locations spatially distant from the B0 variation. We show this effect in both simulation and phantom studies, and show that it can be ameliorated with the use of two-dimensional spatially selective excitation. These findings have important ramifications for applications of BOLD imaging in the abdomen such as renal BOLD or liver T2* mapping, where large B0 inhomogeneity is often present in areas of the image volume spatially remote from the organ of interest.
Pilot Tone respiratory signal processing with RF interference suppression and validation against image navigator
Authors: Huang Yantu , Tan Huixin , Zhang Qiuyi , Speier Peter
Published: August 2024

Pilot Tone (PT) has been demonstrated to extract respiratory signal successfully. However, RF interferences are not considered. We propose a method to create a high-quality PT respiratory signal, while suppressing RF interference. At beginning of a measurement, initial RF suppression matrix and respiratory combination vector are learned. Then a PT respiratory signal can be generated to trigger measurement. Afterwards, RF suppression matrix is updated during each RF train. We validate our method in a moving phantom and in 39 volunteers against image navigator. Results show that our method can suppress RF interference effectively- highly correlated with image navigator.
Consolidation of expert ratings of motion artifacts using hierarchical label fusion
Authors: Balbastre Yael , Frost Robert , Morparia Khushi , Carrington Richard , Chang Yuh-Shin , Applewhite Brooks , Rockenbach Marcio , Fischl Bruce
Published: August 2024

Intra-scan motion costs tens of thousands of dollars per scanner annually due to the need to repeat non-diagnostic scans1. When assessing the scale of the problem and potential solutions, radiologists’ ratings of artifacts are considered the gold standard. However, inconsistent and conflicting ratings must be consolidated into a single gold-standard. We introduce a hierarchical label fusion algorithm that infers each rater's performance and promotes consistency across slices from a volume. This algorithm reduces label noise compared to majority votes, and allows non-expert ratings to be calibrated and included as additional silver-standards.
Validation of respiratory correlated 4D-MRI for radiotherapy planning, using a motion phantom and comparing to 4D-CT.
Authors: Chick Joan , Kousi Evanthia , Wetscherek Andreas , Hughes Julie , Hopkinson Georgina , Gough Jessica , Westley Rosalyne , Neji Radhouene , Dunlop Alex , Nill Simeon , Mandeville Henry , Aitken Katharine , Koh Dow-Mu , Oelfke Uwe
Published: August 2024

Respiratory correlated 4D-MRI has the potential to be a valuable tool in radiotherapy. This work aims to optimise and validate a 4D-MRI golden angle stack of stars radial sequence for measuring respiratory motion of abdominal organs. A 4D motion phantom is used to compare 4D-MRI against 4D-CT. For craniocaudal movement, motion is underestimated in 4D-MRI but motion estimation improves for non-axial acquisitions. This could be due to the alignment of the motion direction with the cartesian phase encoding direction for axial stack of stars acquisitions.
Initial observations and potential pitfalls when validating respiratory correlated MRI for radiotherapy planning.
Authors: Kousi Evanthia , Chick Joan , Wetscherek Andreas , Hughes Julie , Hopkinson Georgina , Gough Jessica , Westley Rosalyne , Neji Radhouene , Nill Simeon , Koh Dow-Mu , Oelfke Uwe
Published: August 2024

In this abstract we present our initial results from the validation of a respiratory correlated 4D MRI golden angle stack of stars radial sequence prior to its clinical implementation and highlight potential experimental pitfalls to avoid that may impact motion range estimations. Correct phantom set up reduced motion underestimations by 3%-18% for the simulated respiratory waveforms considered. Larger motion discrepancies observed for the low amplitude motion which improved by increasing the number of bins.
A robust method for estimating CVR dynamics from breath-hold BOLD data without end-tidal carbon dioxide recordings
Authors: Nanayakkara Nuwan , Meusel Liesel-Ann , Anderson Nicole , Chen J. Jean
Published: August 2024

Cerebrovascular reactivity (CVR) can be estimated from the BOLD response to a vasoactive stimulus such as a breath-holding (BH) approximated by a sinusoidal regressor. We proposed a robust approach for estimating CVR using the frequency spectrum of BOLD data itself, without regressions or correlations with external recordings. We also estimated regional CVR time delay patterns using the BOLD signal phase relative to a non-brain reference. We demonstrate our pipeline in 18 healthy adults.
Assessing the robustness of the correlation between intra-axonal T2 and axon diameter across participants
Authors: Dell'Acqua Veronica , Tax Chantal , Molendowska Malwina , Parker Greg , Jones Derek , Barakovic Muhamed , Canales-Rodriguez Erick Jorge
Published: August 2024

In-vivo quantification of axon diameter is an attractive and debated topic in the MRI community. The possibility to resolve submicrometric axon diameters non-invasively yields the potential to push further the boundaries in research and clinics but yet, further work is needed to better explore and validate the existing approaches to estimate the inner axon diameter. Recently, the feasibility of estimating the axon diameter from the intra-axonal transverse relaxation time has been investigated combining a diffusion-relaxation protocol and histological data. In the present study, we apply this approach in a larger in vivo population to assess variability across participants.
Model-based image reconstruction for highly accelerated point spread function encoded echo planar imaging
Authors: Meyer Nolan , In Myung-Ho , Halverson Maria , Huston John , Bernstein Matt , Trzasko Joshua
Published: August 2024

A model-based image reconstruction (MBIR) framework is developed for highly accelerated point spread function (PSF) encoded echo planar imaging (EPI). The reconstruction accounts for known physics, and utilizes a subspace representation with local low-rank (LLR) regularization along with a variable splitting solution. Comparisons with images obtained through standard methods demonstrate considerable artifact reduction and sharpness preservation through MBIR. MBIR accommodates arbitrary sampling trajectories along the PSF-encoding dimension, enabling reconstruction of quality images from less than one minute of scan time; and we demonstrate performance boosts with nonstandard trajectories precluded by conventional reconstruction methods.
An investigation of the performance of T2-weighted MR imaging with AI-assisted compressed sensing in routine clinical settings
Authors: Karthik Adiraju , Devappa Apoorwa , Kapoor Aakaar , Singh Dharmesh , Kumar Dileep
Published: August 2024

T2-weighted imaging (T2WI) is an essential diagnostic tool for several diseases. However, one of the challenges faced by patients and radiology departments is the longer scanning time of MR examinations. Recent advancements in artificial intelligence (AI) and deep learning techniques have made it able to acquire images quickly while preserving high-quality image resolution. In this study, the efficacy of a deep learning-based reconstruction technique termed AI-Assisted Compressed Sensing (ACS) was evaluated qualitatively and quantitatively using T2WI in routine clinical settings for brain, spine, knee, kidney and liver.
Practical Correction of Gradient Nonlinearities in Diffusion-Weighted Imaging
Authors: Kanakaraj Praitayini , Cai Leon , Rheault Francois , Rogers Baxter , Anderson Adam , Schilling Kurt , Landman Bennett
Published: August 2024

Gradient nonlinearity correction is well-established but not straightforward to implement in existing diffusion software packages due to it producing gradient tables that vary by voxel. We propose a simple, practical approach that approximates full correction by: (1) scaling the diffusion signal and (2) resampling the gradient orientations. Our approach results in uniform gradients across the corrected image and provides the key advantage of seamless integration into current diffusion pipelines. The proposed method resulted in negligible differences in multi- compartment indices from the standard voxel-wise empirical correction.
Evaluating liver fibrosis in chronic hepatitis B patients using multi-compartment restriction spectrum imaging
Authors: Zhang Jing , Yang Kaifan , Zhu Yiyuan , Zheng Liyun , Dai Yongming , Xu Yikai
Published: August 2024

This study evaluated the feasibility of the restriction spectrum imaging (RSI) model in the characterization and staging of liver fibrosis. The results demonstrated that the four-compartment model emerged as the best option and the C4 derived from the four-compartment model outperformed conventional apparent diffusion coefficient (ADC) values. Therefore, the four-compartment RSI model could be a noninvasive and in vivo diagnostic technique in the evaluation of chronic hepatitis, which is conducive to treatment decisions and patient management.
In vivo investigation of a Healthy Liver Lipid composition by 2D L-COSY Using 3T
Authors: Nagarajan Rajakumar , Saucedo Andres , Thomas M
Published: August 2024

In vivo magnetic resonance spectroscopy has the potential to provide information about both the quantity and composition of fat within the liver. We have demonstrated the feasibility of detecting cross peaks using the 2D L-COSY technique at 3T in a healthy liver. This can be used to study fatty liver to derive quantitative indexes.
Simulation of Short Breath-hold Steady State MultiParameter MRS in Liver.
Authors: Hamilton Gavin , Henderson Walter , Batakis Danielle , Ceriani Lael , Louie Ashley , Covarrubias Yesenia , Gonzalez Celene , Middleton Michael , Reeder Scott , Fowler Kathryn , Sirlin Claude
Published: August 2024

To permit simultaneous T1w, T1f, T2w, T2f and proton density fat fraction (PDFF) estimation, we developed a single-average, 21 s, single-breath-hold, Steady-state, Multi-Parameter MRS (SMP MRS) sequence. However, a 21 s breath-hold may be challenging especially children, such as pediatric subjects, so we simulated a shorter 12 s breath-hold sequence by removing the longer TR and TE values. We found good agreement for T1w, T2w and PDFF between the full 21 s SMP and simulated 21 s sequences, suggesting the shorter 12 s SMP MRS can be run instead of the full 21 s sequence.
Performing Quality Control of your MRI Liver Fat/Iron Quantification Studies: A Critical Requirement
Authors: Hajibonabi Farid , Nandwana Sadhna , Sharma Puneet , Balthazar Patricia , Davarpanah Amir Hossein , Moreno Courtney , Pectasides Melina
Published: August 2024

Liver fat/iron quantification with MRI is essential for detection of iron/fat overload that can lead to NAFLD and cirrhosis. The two widely used tools for this purpose are chemical shift-encoded MR sequences and HISTO. Both methods can fail due to various preventable technical factors. We analyzed various quality factors of technical acceptability for these studies and determined that >25% of all quantification studies performed over six months at our institution were technically unacceptable or had data handling errors. We then developed a checklist for MR technologists to confirm acceptability of the study and decrease potential errors before sending for interpretation.
Kaplan-Meier survival analysis of the DCE-MRI-based radiomics in the prognosis of prostate cancer
Authors: Huang Ting , Chen Zhiqiang , Zhang Shaoru , Wang Zhuo , Chen Xiaohua , Zhou Yunshu , Wei Xiaocheng , Wang Aijun
Published: August 2024

In this study, we aim to investigate whether DCE-MRI-based radiomics can be used in the prognosis of prostate cancer. Rad-score in which DEC-MRI-based radiomics labels were established by screening radiomics features GLCM_Correlation and shape_Flatness through Lasso regression was significantly different between the death group and the censor group. It was concluded that DCE-MRI-based radiomics can be used as prognostic factors for prostate cancer.
Effect of Echo Times on Prostate Cancer Detection on Diffusion Weighted Images at high b-value and Apparent Diffusion Coefficient maps
Authors: Chatterjee Aritrick , Kim Audrey , Gundogdu Batuhan , Medved Milica , Antic Tatjana , Karczmar Gregory , Oto Aytekin
Published: August 2024

This study compared the effect of echo times on the detection of prostate cancer on DWI at high b-value and ADC maps. Contrast between benign tissue and cancer increased significantly with higher TE on ADC maps. However, due to increased noise at higher TEs, CNR (study endpoint) was highest at TE 57 ms; higher by 23, 26, 33% than that at TE 70, 150 and 200 ms on ADC maps. CNR, contrast ratio AND auc are higher at lower TE on DWI high-b image. Therefore, the use of lower echo times for DWI and ADC mapping may improve prostate cancer.
Radiomics of MRI Based on Zoomit DWI in Predicting Clinically Significant Prostate Cancer: A Towards Step of a Non-invasive Auxiliary Tool
Authors: Qiao Xiaomeng , Bao Jie , Song Yang , Wu Yunzhu , Wang Ximing
Published: August 2024

Radiomics models based on ZOOMit DWI had better accuracy in the diagnosis of PCa and csPCa compared with those based on RESOLVE DWI technology, and was promising as a powerful non-invasive auxiliary tool to improve the diagnostic performance of PI-RADS of radiologists with different clinical experience.
Using Multi-parametric MRI Quantitative Metrics as Image Biomarkers to Predict the Tumor Malignant degree of Prostate Cancer
Authors: Liu Shili , Chen Zhiqiang , Zhang Shaoru , Chen Xiaohua , Wang Zhuo , Xiong Yuhui , Wang Aijun
Published: August 2024

This study aims to investigate whether the quantitative metrics derived from diffusion weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI can be used to predict the tumor malignancy of prostate cancer. The results showed that the apparent diffusion coefficient (ADC) value, Tmax (s), SImax%, Rmax% were correlated with Ki-67 to a certain extent, DWI and DCE-MRI parameters are expected to be a non-invasive examination method to measure the ability of prostatic malignant tumor cells to expand, and provide an important theoretical basis for evaluating the efficacy of prostate cancer and monitoring the prognosis.
Comparison of 3D amide proton transfer imaging and intravoxel incoherent motion imaging in the diagnosis of prostate cancer
Authors: Hou Guorui , Ai Kai
Published: August 2024

Prostate cancer (PCA), which seriously hazard the life and health, is one of the most common malignant tumors in middle-aged and elderly men, and the incidence population tends to be younger. Amide proton transfer imaging (APT) and intravoxel incoherent motion imaging (IVIM) are two technologies that can be used for prostate cancer diagnostic. This study aims to compare and analyze the diagnostic performance of APT and IVIM in prostate diseases. Besides, we also test the relationship between APT and IVIM derived parameters and Gleason score (GS).
Application of Synthetic MRI in the Diagnosis and Invasion Assessment of Peripheral Zone Prostate Cancer
Authors: Zhou Yunshu , Chen Zhiqiang , Song Na , Wang Zhuo , Zhang Shaoru , Chen Xiaohua , Wei Xiaocheng , Wang Aijun
Published: August 2024

This retrospective study aims to investigate the application value of the quantitative relaxation maps derived from synthetic MRI in the diagnosis and invasion assessment of peripheral zone (PZ) prostate cancer (PCa). 88 patients (45 experimental & 43 control) were scanned using the magnetic resonance image compilation (MAGiC) sequence and the quantitative relaxation metrics were calculated and compared. The results demonstrate that quantitative T1 and T2 values are significant indicators for distinguishing PZ PCa from non-cancerous PZ. T2 value has a similar diagnostic performance to apparent diffusion coefficient value and has potential clinical value in evaluating the invasiveness of PCa.
A Machine Learning Approach for Identifying the Severity and Regional Anatomical Location of HIV Infection in the Brain
Authors: Salan Teddy , Sheriff Sulaiman , Vyas Sameer , Aggarwal Deepika , Singh Paramjeet , Govind Varan
Published: August 2024

Identifying and monitoring viral habitats of HIV in the brain is crucial to the advancement of treatment strategies for containing the infection. However, no in-vivo methods currently exist for this purpose. In this study, we demonstrate the use of a machine learning model that integrates brain measurements from MRSI, DTI, and DKI for identifying the severity and anatomical location of microstructural and metabolic abnormalities in the brain. This information may provide important clinical and diagnostic value for the treatment of people living with HIV.
Effect of a flow-diverter stent on flow in the vessel and aneurysm measured with MRI.
Authors: Bautz Lana , Oni Oluwabusayo , Toraman Hivnu , Jansen Olav , Hövener Jan-Bernd , Larsen Naomi , Pravdivtseva Mariya
Published: August 2024

Flow diverter stents are effective for the treatment of intracranial aneurysms at a high risk of rupture. Still, complications may occur after stent implantation, so evaluation of aneurysm treatment is required. Treatment follow-up can be performed with 4D phase-contrast MRI. In this work, flow within the aneurysm and adjacent vessels with and without stent was measured with 4D flow. Strong metal artifacts were observed at the parent vessel which resulted in MRI signal voids and a 30 % reduction of measured flow. No artifacts were seen within an aneurysm sac, here flow was reduced up to 83 %.
Voxel-Based Brain Morphometry: an Optimized Image Analysis Pipeline and Proof-of-Concept in a Non-human Primate Model of Ebola Virus Infection
Authors: Lee Byeong-Yeul , Lee Ji Hyun , Solomon Jeffrey , Castro Marcelo , Mani Venkatesh , Laux Joseph , Chu Winston , Lackemeyer Matthew , Bohannon Jordan , Honko Anna , Crozier Ian , Kuhn Jens , Calcagno Claudia
Published: August 2024

We present an optimized voxel-based morphometry magnetic resonance imaging (MRI) analysis pipeline for non-human primate brain images, and its preliminary application in Ebola virus (EBOV)-exposed rhesus monkeys. Results suggest the optimized pipeline can detect brain morphometric changes after EBOV exposure in this model. Further analyses will be required to confirm and build upon these findings, including their implications for acute and post-acute neurological findings in human survivors. Future studies may make use of this and other optimized, voxel-based pipelines to shed further light on the role of central nervous system involvement in EBOV and other infectious diseases.
T2 Mapping in Hemorrhagic and Ischemic Stroke using Standard Clinical Images
Authors: De Ashmita , Snyder Jeff , Kate Mahesh , Emery Derek J. , Wilman Alan H.
Published: August 2024

T2 mapping can provide a route to monitor both iron changes in hemorrhage and water changes in ischemic stroke. Our aim is to investigate the value of T2 mapping from standard proton density and T2-weighted fast spin echo images for hemorrhagic and ischemic stroke. Rapid T2 maps using sequence modeling were reconstructed and compared with susceptibility and apparent diffusion coefficient for 13 hemorrhages and 14 ischemic stroke lesions respectively. Quantitative T2 is highly correlated with susceptibility for hemorrhage and diffusion for ischemic stroke, providing complementary measurements of water and iron changes.
Quantitative Parameters of Diffusion Spectrum Imaging: Prediction of Severe Neurologic Deficits at Discharge in Acute Ischemic Stroke Patients
Authors: Jiang Peirong , Xu Xiuzhu , Zheng Yanping , Chen Jialin , Wu Peng , Xue Yunjing
Published: August 2024

This study explores the value of quantitative parameters derived from diffusion spectrum imaging (DSI) in distinguishing between mild (NIHSS score ≤ 5) and severe (NIHSS score > 5) neurologic deficits at discharge in DWI positive acute ischemic stroke (AIS) patients. The method is to compare conventional diffusion and DSI parameters of acute infarction between the two groups. Our research shows DKI_AK, DKI_MKT, DKI_RK, MAP_RTPP and NODDI_ICVF can predict poor neural function outcome at discharge, with NODDI_ICVF demonstrates the highest diagnostic performance. DSI is a promising approach in detecting microstructural brain tissue changes in acute infarction lesion.
Assessing cerebral oxygen metabolism changes in preeclampsia using voxel-based morphometry of oxygen extraction fraction (OEF) maps in MRI
Authors: Sui Chaofan , Zhang Qihao , Cho Junghun , Yang Linfeng , Chen Tao , Guo Bin , Gillen Kelly , Li Jing , Guo Lingfei , Wang Yi
Published: August 2024

The objective of this study was to analyze the different brain oxygen metabolism statuses in preeclampsia. Furthermore, we also investigated the influencing factors that affect cerebral oxygen metabolism in preeclampsia. Forty-nine preeclampsia patients, forty nonpregnant healthy controls (NPHCs) and twenty-two pregnant healthy controls (PHCs) were included in this study. Brain OEF values were computed using quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level‐dependent magnitude-based OEF mapping (QSM+qBOLD, or QQ). Voxel-based morphometry (VBM) was applied to investigate the differences of OEF values in brain regions among groups.
Neural correlates of bi-cephalic transcranial direct current stimulation in upper limb hand function post stroke
Authors: Bhasin Ashu , Sharma Rahul , Srivastava MV Padma , Kumaran S Senthil
Published: August 2024

Non invasive brain stimulation holds great promise in post stroke recovery in upper limb hand function and inducing neural plasticity. Transcranial direct current stimulation (tDCS) enables the alteration of cortical excitability by passing direct currents causing hypo or hyperpolarization of neuronal resting membrane potentials. Bi-cephalic tDCS with anode applied on the affected cortex especially M1 and cathode over the non-affected cortex has been used to normalize excitatory and inhibitory corticospinal networks.
Evaluation of Pediatric Musculoskeletal Disease using CT-like MR of Pointwise Encoding Time Reduction with radial Acquisition sequence
Authors: Zhuang Xiamei , Jin Ke , Yin Yan , Li Junwei , Zhang Huiting
Published: August 2024

Cortical bone can be clearly displayed by CT-like MRI using ultrashort TE sequence. This study aimed to investigate the value of CT-like MRI using PETRA (ct-PETRA) sequence in the pediatric musculoskeletal diseases. Our results showed that ct-PETRA had no significant difference in measuring the C-E index and acetabulum index of children's hip joint compared with X-ray, and had no significant difference in visualization of lesions compared with X-ray and CT. Moreover, ct-PETRA has more advantages than X-ray in displaying trabecular fracture of fine bone. CT-like PETRA can be used as conventional complementary sequence for some assessments of pediatric musculoskeletal diseases.
Fast free-breathing pediatric MRI using accelerated radial acquisition and deep learning motion-resolved reconstruction
Authors: Murray Victor , Siddiq Syed , Behr Gerald , Otazo Ricardo
Published: August 2024

Motion remains a significant challenge in pediatric MRI. Motion-resolved 4D MRI, such as XD-GRASP, is a promising alternative to motion correction. However, long scan times and particularly reconstruction times restricted routine clinical use. This work presents a deep learning approach called MRI-movienet for 4D reconstruction of radial data, which enables acceleration of both acquisition and reconstruction for free-breathing pediatric MRI with only 1 minute scan time and less than 2 seconds reconstruction time. The deep learning approach is demonstrated for free-breathing abdominal pediatric MRI without anesthesia using XD-GRASP as a reference for comparison.
Heterogeneous distribution of hepatic and pancreatic fat fraction in overweight or obese children and adolescents
Authors: Cao Yang , Lin Dingyi , Zhou Yufan , Hsu Yi-Cheng , Mi Gaoyang , Zhang Hongxi , Wang Min
Published: August 2024

The ectopic fat is not evenly distributed in organs and can be a time dependent process that starts at early age. In this work, we focused on obese or overweight children and adolescents and calculated the voxel-wised liver and pancreas fat fraction. With our recently proposed deep learning method, we separately quantified the fat depositions in different compartments of liver and pancreas with high precisions. Our analysis revealed an unevenly distributed ectopic fat in both liver and pancreas at young age and suggested that hepatic and pancreatic fat depositions are weakly coupled but have different underlying mechanisms.
Association of physical activity and screen time with DXA- and MRI-based body composition in adolescents, a population-based study
Authors: Wu Tong , Yang-Huang Junwen , Vernooij Meike , Rodriguez‑Ayllon María , Jaddoe Vincent , Raat Hein , Klein Stefan , Oei Edwin
Published: August 2024

This study is embedded in the Generation R Study, a population-based prospective cohort study in the Netherlands. At 13 years, whole-body Dixon MRI was performed. A previously presented Competitive Dense Fully Convolutional Network (CDFNet) was retrained and used to quantify the abdominal subcutaneous and visceral fat. We found a higher physical activity and lower screen time are associated with lower levels of MRI-based abdominal visceral obesity in adolescents. Therefore, promoting physical activity and reducing screen time should be one of the goals of lifestyle intervention programs for tackling the childhood obesity.