bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-invasive characterization of response of breast cancer to paclitaxel chemotherapy using MR cell size imaging
Authors: jiang xiaoyu , Xie Jingping , Gore John , Xu Junzhong
Published: August 2024

Reliable and sensitive methods for assessing the response of breast cancer to treatment are critical for timely adjustments of therapies for individual patients, and development of novel therapies. Different from the conventional tumor-volume-based criteria, we hypothesize that more specific microstructural information on the cellular level in tumors, such as changes in cell size, may provide more accurate characterization of therapeutic response. Using both in vitro cell experiments and in vivo xenograft experiments, we demonstrated that temporal changes in MR-derived cell sizes in triple-negative MDA-MB-231 tumors treated with either drug vehicle or paclitaxel provide a new means to assess treatment response.
Non-invasive blood brain barrier integrity mapping in patients with high-grade glioma and metastasis by time-encoded arterial spin labelling
Authors: Hoffmann Gabriel , Preibisch Christine , Günther Matthias , Mahroo Amnah , van Osch Matthias , Václavů Lena , Schmitzer Lena , Zimmer Claus , Wiestler Benedikt , Kaczmarz Stephan
Published: August 2024

High-grade glioma are known to cause blood brain barrier (BBB) disruption, facilitating molecular leakage from inside the vessels into tissue. Current methods to probe BBB integrity are either not quantitative or, by using Gadolinium, insensitive to subtle changes. Here, we present first data of arterial spin labelling (ASL)-based BBB mapping of water exchange time (Texch) in brain tumour patients. Results show faster exchange (shorter Texch) in tumorous and even normal-appearing tissue compared to healthy subjects. This highlights the potential of ASL-based water exchange mapping as a proxy measure for BBB integrity, and its potential sensitivity to even subtle impairments.
Imaging metabolism of deuterated glucose in patients with primary brain tumors
Authors: Corbin Zachary , Liu Yanning , Fulbright Robert , Thaw-Poon Serena , Baehring Joachim , Blondin Nicholas , Kim Peter , Omuro Antonio , Chiang Veronica , Moliterno Jennifer , Omay Sacit , Piepmeier Joseph , Rothman Douglas , de Graaf Robin , De Feyter Henk
Published: August 2024

Deuterium metabolic imaging (DMI), a combination of 2H MRSI with administration of a deuterated substrate, was used to map regional metabolism of [6,6’-2H2]-glucose in 24 patients with multiple types of brain tumors. DMI data were acquired 70-90 minutes after oral intake of the deuterated glucose and revealed strong tumor-to-brain image contrast in high-grade tumors. Our metric, based on the labeling of specific glucose metabolites, reflects the canonical glucose metabolism in aggressive tumors – the Warburg Effect. The Warburg Effect appears higher in high-grade tumors and showed potential as a biomarker of treatment effect.
Probing Tumor Heterogeneity in Mouse Glioblastoma with Dynamic Glucose-Enhanced Deuterium Metabolic Imaging
Authors: Simoes Rui , Henriques Rafael , Olesen Jonas , Cardoso Beatriz , Fernandes Francisca , Carvalho Tania , Jespersen Sune , Shemesh Noam
Published: August 2024

Dynamic glucose-enhanced deuterium MRS (DGE 2H-MRS) coupled with Marchenko-Pastur PCA (MPPCA) denoising has been recently applied to immunocompetent mouse glioblastoma subtypes (GL261 and CT2A), demonstrating the ability to measure glucose metabolism through glycolysis and mitochondrial oxidation non-invasively, and its association with tumor proliferation. Here, we extend this approach to DGE Deuterium Metabolic Imaging (DGE-DMI) coupled with tensor MPPCA (tMPPCA) denoising, to map glucose fluxes in the same mouse models of glioblastoma. Our results demonstrate a strong association between glycolytic rates and MRI and histologic features of inter/intra-tumor heterogeneity.
MR image super-resolution via a variational diffusion model
Authors: Jiang Wei , Gao Yang , Sun Hongfu
Published: August 2024

High-resolution MR images are advantageous for medical diagnosis. However, they may require longer scan time and more powerful hardware. Significant effort has been made to carry out super-resolution methods to synthesize higher-resolution MR images from lower-resolution acquisitions using deep learning approaches. However, most current methods are biased. In this work, we propose a new super-resolution method based on the state-of-the-art generative model (i.e., variational diffusion model), using the lower-resolution K-space measurements as a condition for guiding the super-resolution process. This unsupervised approach achieved high performance for reconstructing MR images from arbitrary lower resolutions without retraining the model.
Federated Learning for Utilizing Multi-Institutional Prostate MRI with Diverse Histopathology
Authors: Rajagopal Abhejit , Redekop Katya , Kemisetti Anil , Kulkarni Rishi , Raman Steven , Sarma Karthik , Magudia Kirti , Arnold Corey , Larson Peder
Published: August 2024

Prostate cancer screening and diagnosis from MRI is extremely challenging, and current machine learning algorithms suffer in cross-institutional generalizability. Federated learning is a way to alleviate these issues by combining multi-center data without aggregating or homogenizing data. To enable this for prototype-stage algorithms, we introduce FLtools, a lightweight python library with re-usable federated learning components available freely at https://federated.ucsf.edu. We use this federated learning system to train a 3D UCNet on bi-parametric MRI and paired prostate biopsy data from two University of California hospitals, demonstrating dramatic improvements in cross-site generalization accuracy in clinically-significant lesion classification.
A Machine Learning-Based Prediction of RF Transfer Function of Active Implantable Medical Devices in Homogeneous and Heterogeneous Tissue
Authors: Ma Mingjuan , Shi Hexuan , Yao Aiping
Published: August 2024

Both the Tier-3 and Tier-4 methods proposed in ISO/TS 10974 for assessing the radiofrequency safety of active implantable medical devices have limitations in practice. The transfer function proposed in the Tier-3 method can only be measured individually for each implant and only for homogeneous tissue environments, while Tier-4 requires significant high-speed computing resources. In this study, machine learning algorithms are proposed to predict the transfer function both in homogeneous and heterogeneous tissue environment. The results show that this approach is feasible and performs well in the prediction task.
Cardiac adipose tissue proton-density fat fraction quantification by free-running cardiac Dixon at 3T
Authors: Daudé Pierre , Troalen Thomas , Mackowiak Adèle , Royer Emilien , Piccini Davide , Yerly Jérôme , Pfeuffer Josef , Kober Frank , Gouny Sylviane Confort , Bernard Monique , Stuber Matthias , Bastiaansen Jessica , Rapacchi Stanislas
Published: August 2024

Free-running cardiac Dixon-MRI has the potential for motion-resolved R2* and PDFF quantification to explore cardiac fat accumulation and alteration in metabolic diseases. This study combines a self-navigated 3D radial sequence with 13 echoes using fast bipolar signal-readouts, a k-space trajectory correction, a compressed sensing reconstruction, and IDEAL fat-water separation to obtain precise ( limits of agreement: ±1.2 % and 5.0 s-1) and highly spatially and motion-resolved quantitative PDFF and R2* maps of the whole heart. We report here the first in vivo characterization of metabolically-active epicardial fat (PDFF: 81.6±9.6 %), distinct from adjacent paracardial fat.
Myocardial oxygen extraction fraction moderately correlates with fibrosis burden in patients after heart transplant: a MR metabolism study
Authors: Wang Jing , Li Ran , Fu Xiaona , Yang Yang , Sun Xiaojie , Shu Shenglei , Zhao Jie , Kong Xiangchuang , Zheng Jie
Published: August 2024

Microvascular dysfunction and excessive fibrous burden are independent prognostic factors after heart transplantation. A new novel cardiovascular MR technique for the measurement of myocardial oxygen extraction fraction was evaluated for a feasibility study in 10 patients after heart transplantation. It was observed that oxygen extraction fraction was significantly correlated with myocardial extracellular volume (diffuse fibrosis indicator). Further research with more patients is warranted to explore this new CMR metabolism index for early diagnosis of cardiac dysfunction in these patient cohorts.
Respiratory navigated free-breathing myocardial arterial spin labeling (ASL) with phase sensitive reconstruction
Authors: Bozic-Iven Masa , Rapacchi Stanislas , Tao Qian , Schad Lothar , Weingärtner Sebastian
Published: August 2024

Myocardial arterial spin labeling (myoASL) holds promise for needle-free myocardial blood flow (MBF) quantification but requires tedious averaging over multiple breath-holds. Here, free-breathing myoASL was implemented with dual-navigator gating, both with bSSFP and spoiled GRE readout. Images were processed using individual blood T1 and inversion time correction as well as a phase-sensitive (PS) image reconstruction. Phantom results showed PS reconstruction to reduce MBF variations for short RR and T1 values. Perfusion values were comparable with breath-held myoASL and on par with the literature. Ultimately, this can enable faster myoASL acquisitions with improved patient comfort.
High spatial resolution quantitative susceptibility mapping using in-phase echoes enables the depiction of breast microcalcifications
Authors: Boehm Christof , Komenda Alexander , Weiss Kilian , Stelter Jonathan , Borde Tabea , Meineke Jakob , Makowski Marcus , Fallenberg Eva , Karampinos Dimitrios
Published: August 2024

Breast microcalcifications (MCs) can be the only sign of carcinoma and other precursor lesions of breast cancer in x-ray mammography. Mammography is routinely used for population-based breast cancer screening. However, due to the ionizing nature of x-ray radiation, the use of an MR-based technique would be desirable for repeated examinations especially in screening targeted sub-cohorts at high-risk or younger women. In this work, we present initial results on the visualization of MCs using MR with an optimized high-resolution GRE-scan and quantitative susceptibility mapping. The proposed methodology allows for the robust visualization of MC clusters in MR for the first time.
Automated breast tumor segmentation in DWI using multi-modality image registration: a feasibility study using multi-center data
Authors: Le Nu , Newitt David , Li Wen , Hathi Deep , Liang Jiachao , Wilmes Lisa , Gibbs Jessica , Onishi Natsuko , Joe Bonnie , Kornak John , Bolan Patrick , Partridge Savannah , Hylton Nola
Published: August 2024

Diffusion-weighted imaging (DWI) in MRI plays an important role in diagnostic applications. Automated tumor segmentation is an important yet challenging step for quantitative breast imaging analysis. While methods have been developed for dynamic contrast enhanced (DCE) MRI, automatic segmentation in breast DWI-MRI is still underdeveloped. The purpose of this study is to develop methods to transfer functional tumor volume (FTV) analysis ROI from DCE-MRI image space to DWI-MRI image space using image registration and extract ADC statistics in regions corresponding to those of DCE segmentations for prediction of pathologic treatment response (pCR).
Multisite Intravoxel Incoherent Motion Repeatability and Reproducibility in a Breast Diffusion Phantom at 3T
Authors: Basukala Dibash , Mikheev Artem , Gilani Nima , Benkert Thomas , Moy Linda , Pinker-Domenig Katja , Thakur Sunitha , Sigmund Eric
Published: August 2024

Monoexponential apparent diffusion coefficient (ADC) and biexponential intravoxel incoherent motion (IVIM) analysis of diffusion-weighted imaging (DWI) is helpful in the characterization of breast tumors. Toward this goal, a novel breast phantom containing tubes of different polyvinylpyrrolidone (PVP) concentrations, water, fat, and sponge flow chambers was utilized. This work tests this breast phantom at two sites employing different vendor MRI scanners to estimate the ADC and IVIM parameters. The results are reproducible within sites, and show progress towards reproducibility across sites and vendors, and can be used in the future in multicenter clinical trials for breast cancer characterization, prediction and prognosis.
Intravoxel incoherent motion improves diffusion-weighted imaging in the detection of response to neoadjuvant chemotherapy in breast cancer
Authors: Cheung Sai Man , Wu Wing Shan , Senn Nicholas , Sharma Ravi , McGoldrick Trevor , Gagliardi Tanja , Husain Ehab , Masannat Yazan , He Jiabao
Published: August 2024

Breast cancer is a major and expanding health challenge, and neoadjuvant chemotherapy (NACT) is increasingly prescribed to facilitate breast surgery. However, response to NACT is highly inconsistent, imposing an ongoing demand for improved imaging methods for early response identification. Tissue perfusion, a sensitive marker of cancer metabolism, can be derived from intravoxel incoherent motion (IVIM) model, and recent Bayesian algorithm yields increased sensitivity and precision in pancreatic cancer. We therefore hypothesise that IVIM model powered by Bayesian algorithm is able to detect early treatment-induced changes in tumour perfusion and diffusion, with the potential to impact patient care pathway.
Hybrid-PUSH pulses for controlled MT bias in T1 mapping at 7T
Authors: Leitão David , Tomi-Tricot Raphael , Bridgen Pip , Liebig Patrick , Gumbrecht Rene , Ritter Dieter , Hajnal Jo , Malik Shaihan
Published: August 2024

While standard pulse design methods control the rotation of magnetization (i.e. flip angle), the recently proposed PUSH method aims to control the root-mean-squared B1, to control magnetization transfer (MT) effects. General RF pulses create both effects simultaneously: this is important in T1 mapping, where incidental MT effects introduce bias. We show that using standard pulse design methods to improve flip angle uniformity can actually worsen the bias in T1 measurement by producing uncontrolled spatially variable MT effects. We propose a ‘hybrid-PUSH’ method optimizing both flip angle and B1rms, and demonstrate this improves quality of T1 estimation in-vivo at 7T.
Eliminating Banding Artifacts in bSSFP using Parallel Transmission
Authors: Wu Chia-Yin , Jin Jin , Barth Markus , Cloos Martijn
Published: August 2024

In this work, we demonstrate a parallel transmit implementation of the bSSFP sequence at 7 Tesla. The bSSFP sequence is one of the most efficient acquisition strategies however highly sensitive to B0 inhomogeneity which creates undesirable banding artefacts. A tailored pair of pTx pulses can be used to induce the desired steady-state magnetisation behaviour at all spatial locations regardless of the off-resonance frequency due to B0 inhomogeneity. Shown through simulation and experimental validation, we were able to capture signal in one acquisition with significant mitigation of banding artifacts and improvement in signal uniformity without SNR loss and time penalty.
Experimental Assessment of the Effects of Subject Motion on Local SAR and pTx Pulse Performance at 7T
Authors: Williams Sydney , McElhinney Paul , Ding Belinda , Allwood-Spiers Sarah , Porter David , Gunamony Shajan , Brink Wyger
Published: August 2024

Previous simulation studies of motion in parallel transmission (pTx) have identified large increases in specific absorption rate (SAR) and pulse performance error. This abstract extends this by evaluating the effects of motion on RF shimming and dynamic pTx in vivo at 7T. The T1w image of a healthy volunteer was segmented to create a body model for electromagnetic simulation in a custom pTx coil. The model was simulated at six head positions matched to experimental measurements. Motion had a detrimental effect on pTx pulse performance and also caused local SAR changes, though not as severe as seen previously in simulation.
An Improved Intraoral Transverse Loop Coil Design for High Resolution Dental MRI
Authors: Özen Ali , Ilbey Serhat , Jia Feng , Bock Michael
Published: August 2024

MRI can simultaneously image soft and hard tissues such as glands, teeth, gum, nerves and bone, thus could be valuable for diagnosis of dental pathologies and implant planning. Intraoral coils have been proved essential to dental MRI due to superior sensitivity compared to external coils. In this study, we introduce a modified transverse loop coil design, which provides improved sensitivity, homogeneity, comfort and safety. We also introduce a bio-compatible, artefact-free and MR-silent coating for intraoral coils. Phantom and in vivo dental MR images demonstrate the advantages of the new intraoral coil design.
A self-decoupled 16-channel transmit, 80-channel receive array for 10.5 Tesla human head imaging
Authors: Waks Matt , Lagore Russell , Auerbach Edward , Grant Andrea , DelaBarre Lance , Jungst Steve , Tavaf Nader , Radder Jerahmie , Van de Moortele Pierre-Francois , Sadeghi-Tarakameh Alireza , Eryaman Yigitcan , Adriany Gregor , Ugurbil Kamil
Published: August 2024

We present a splittable 16-channel self-decoupled (SD)1 transmit/receive (Tx/Rx) loop array combined with a 64-channel receive-only (Rx) loop array to generate a 80Rx/16Tx array for human head imaging at 10.5 Tesla. Compared to the previously presented SD transmitter, we designed, miniaturized, and integrated the MR system interface, including custom transmit/receive switches and preamplifiers, into the coil housing. We also implemented our new custom 128 receiver system, which supported this combined 80 channel receive configuration. Experimental MR results demonstrate advantages over our previous 16-channel transmit-only SD array and substantially increased central SNR with the 80-channel compared to the 64-Rx only configuration.
Dynamic dipole receive coils for improved 3D parallel imaging at ultra-high magnetic field
Authors: Glang Felix , Nikulin Anton , Avdievich Nikolai , Bosch Dario , Steffen Theodor , Scheffler Klaus
Published: August 2024

Parallel imaging with electronically modulated time-varying receive sensitivities is a novel concept for improved reconstruction quality and reduced noise amplification. Previously, it was demonstrated for 2D imaging using reconfigurable surface loop receive elements. In the present work, we extend the approach to 3D imaging and for that introduce a reconfigurable single-row dipole receive array. By using PIN diodes to switch between capacitive and inductive impedance in the dipole arms, spatially distinct sensitivity profiles are formed that can be rapidly modulated. This is shown to enable parallel imaging acceleration along the dipole’s axis and improve reconstruction quality compared to static sensitivities.
Design of a 64-Channel ex vivo Brain Rx Array Coil with field monitoring and temperature control for DWI at 3T
Authors: Scholz Alina , Mahmutovic Mirsad , Alem Mona , Müller Roland , Schlumm Torsten , Möller Harald , Yendiki Anastasia , Ramos-Llorden Gabriel , Wald Lawrence , Huang Susie , Keil Boris
Published: August 2024

Long-durational diffusion weighted MRI scans with high gradient strength and high slew rate experiences in addition to the generally low signal-to-noise-ratio several problems, such as image artifacts due to eddy currents and the gradual increase of the sample temperature. Combining a high-density anatomically shaped receive coil with field monitoring and temperature control can overcome these limitations. Therefore, we designed and constructed a 64-channel whole human ex vivo brain Rx coil with integrated field monitoring and temperature control system. First SNR measurements confirm the receive capability with high SNR.
A head and neck array add-on to the two-channel Nova coil using six SCC elements and Nova 32 channel receive array at 7T-MRI
Authors: Güler Sadri , Zhurbenko Vitaliy , Zivkovic Irena , Christensen Hanne , Rosenbaum Sverre , Havsteen Inger , Petersen Esben
Published: August 2024

The advantage of low coupling ratios of shielded-coaxial-cable coils (SCCs) are used to obtain an eight-channel head-neck transmit array for 7T-MRI. The six SCCs are combined with the two-channel Nova coil by taking the advantage of low coupling between SCCs and the Nova coil. Low inter element coupling along with the independent radiation regions of the SCCs and the Nova coil made it possible to do a straightforward B1-shimming resulting in a relatively homogeneous magnetic field in both head and neck region. Structural images are acquired with large coverage down to the bifurcation while high SNR is preserved.
Hippocampal-cortical connections with high-resolution ex vivo and in vivo diffusion MRI of human brain at 7T
Authors: Cao Zuozhen , Zhao Zhiyong , Zhu Qinfeng , Zhu Keqing , Zhang Jing , Wu Dan
Published: August 2024

Hippocampus is a critical brain structure associated with many brain functions. The connectivity between hippocampal sub-regions and cerebral cortex hasn’t been fully characterized, and spatial resolution is the key to resolve such connectivity. We utilized 3D high-resolution ex vivo diffusion MRI (dMRI) at 7T to investigate the structure connectivity between hippocampal sub-regions and cortex and compared the results with in vivo data. We found that different sub-regions demonstrated unique fiber projections to cortex, and the high-resolution ex-vivo dMRI resulted in more connections with temporal-occipital lobe and less connections to central gyrus and frontal lobe, compared to lower-resolution in vivo dMRI.
The Influence of b value and Resolution on MR Tractography and Connectome Construction in Adult Mouse Brain at 16.4 Tesla
Authors: Alkhalily Majd , Currey Laura , Piper Michael , Kurniawan Nyoman
Published: August 2024

Several pipelines are available to quantify mouse brain connectome using diffusion-tractography. However, data acquisition and processing methods used a wide range of parameters. In this study, ex-vivo adult mouse brains were scanned using a range of b values, and spatial and angular resolutions at 16.4 T. iFOD2 were used for fibertracking to generate the connectomes. Network analysis revealed increased nodal degree and reduced connectivity at 75 μm and this change increases at higher b value. Comparison with Allen mouse brain atlas showed consistent connectome profiles were achieved by acquiring diffusion with b=5000 s/mm2 at 100 μm resolution and 30 directions.
Dynamic co-fluctuation patterns of fMRI brain activity in temporal lobe epilepsy
Authors: Sainburg Lucas , Rogers Baxter , Chang Catie , Englot Dario , Morgan Victoria
Published: August 2024

Temporal lobe epilepsy (TLE) presents with transient epileptic activity at rest, typically originating from the hippocampus. Here we measure dynamic functional connectivity (FC) at single functional MRI timepoints with edge timeseries to detect recurring hippocampal co-fluctuation patterns and their alterations in TLE. Three anterior hippocampus co-fluctuation patterns were detected in healthy controls. One pattern was altered in TLE, while another pattern was more frequent in TLE than controls. These changes reflect alterations in dynamic spatial patterns of FC from the epileptic focus in TLE.
A comparison of multi-echo and single-echo fMRI resting state mapping in neurosurgical patients
Authors: Radwan Ahmed , Emsell Louise , Peeters Ronald , Theys Tom , Dupont Patrick , Sunaert Stefan
Published: August 2024

We compared multi-echo (mTE) resting-state (rs) fMRI to single-echo (sTE) fMRI for seed-based mapping of seven canonical resting state networks (RSN) in 69 pre-surgical patients. Acquisition parameters were identical except for TE and statistical analyses were constrained by group-specific RSN masks. mTE-rsfMRI showed significantly higher functional-connectivity (fc) for all RSNs, while sTE showed comparatively fewer RSNs with areas of significantly higher fc (PFWE<0.05). Our results suggest that mTE-rsfMRI may be more sensitive than sTE-rsfMRI for mapping of the sensory-motor, default mode, salience, frontoparietal, dorsal attention, language and visual networks in a neurosurgical setting.
The Influence of Variability and Uncertainty in the Clinical Reference on MRI Radiomics Modelling and Performance
Authors: Xue Cindy , Chu Winnie , Yuan Jing , Zhou Yihang , Yung Raymond , Gladys Lo
Published: August 2024

Radiomics uses quantitative analysis of medical imaging based on machine learning techniques and has shown its potentials of aiding personalized clinical decisions. A high standard of clinical reference (or ground truth, endpoint) is vital in radiomics feature selection and modeling, but is commonly overlooked, and assumed to be perfect. However, in reality, there are uncertainties and variability in these clinical references due to many factors. We aim to quantitatively assess the influence of clinical reference uncertainty and variability on MRI Radiomics modeling via endpoint annotation permutation with different levels.
Multicenter reproducibility of hand-crafted radiomics and deep-learning based features for biparametric prostate MRI
Authors: Merisaari Harri , Verho Janne , Perez Ileana , Ettala Otto , Syvänen Kari , Taimen Pekka , Steiner Aida , Saunavaara Jani , Saukko Ekaterina , Boström Peter , Aronen Hannu , Jambor Ivan
Published: August 2024

In the current study, we aimed to explore reproducibility of various hand-crafted radiomics features, and deep learning autoencoder-based features within Gleason Grade Groups (GGG) using MULTI-IMPROD trial data. Differences between sites were evaluated with ANOVA test, corrected for GGG group, and multi-class AUC for GGG. We explored if systematic differences exist between the four centers taking part in the trial with conventionally used radiomic features. The results show differences between modalities, feature groups, and when intensity harmonization is applied for ADC.
Automatic Rectal Tumor Segmentation and Extramural Venous Invasion Diagnosis based on Deep Learning and Radiomics Model
Authors: Liu Jiyao , Zheng Rencheng , Wang Chengyan , Pei Yigang , Chu Yinghua , Wang He
Published: August 2024

This study developed an automatic diagnosis model for rectal cancer, which consists following steps: high-precision rectal tumor segmentation by Spatial Hybrid Network (SH-Net) and Adaboost Decision Tree based radiomics model to improve the diagnostic performance of extramural venous invasion (EMVI). The comparable diagnostic performance of the proposed model compared to the visual assessment by radiologists suggests the potential to help doctors with clinical diagnosis of EMVI.
Preoperative Prediction of Brain Invasion in Meningiomas: A Radiomics Model based on Multimodal MRI and Quantitative Clinical Factors
Authors: Li Jinli , Zhang Xianchang , Yang Ruijun , Feng Quanzhi , Yuan Dong , Zhang Jiajia , Han Tong
Published: August 2024

This study aimed to construct a radiomic model based on a large patient cohort to predict brain invasion (BI) in meningioma. By analyzing 97 patients with BI and 935 patients without BI, we found that the clinical risk factors for BI were male sex, tumor located at the skull base, and peritumoral edema volume. A binary logistic regression model combining these risk factors and multimodal MRI radiological characteristics was established. The constructed model achieved an excellent performance (AUC: 0.928) in terms of BI classification with an accuracy of 91.77%, which may be helpful for personalized treatment plan in meningioma.
The Comparison of Diffusion Weighted Imaging and Advanced Diffusion Techniques in Predicting Postoperative Recurrence of Meningioma
Authors: Zheng Hui , Zheng Lingmin , Wang Zongmeng , Zhang Rufei , Song Yang , Lin Lin
Published: August 2024

Prior investigators have found that diffusion weighted imaging (DWI) contributes to improving the prediction of postoperative recurrence of meningioma. This study evaluated the feasibility of intravoxel incoherent motion (IVIM) and diffusional kurtosis imaging (DKI) in predicting postoperative recurrence of meningioma and compared them with DWI. Histogram metrics derived from DWI, IVIM, and DKI parameters were compared between the recurrent group and non-recurrent group. It was found that the lower ADC, D, f value and the higher D*, K value, the higher risk of postoperative recurrence of meningioma. However, IVIM and DKI derived parameters had similar diagnostic performance compared with DWI.
Early detection of brain tumor response during local hydrogel based treatment using CEST MRI
Authors: Park Se Weon , Lai Joseph H.C , Han Xiongqi , Huang Jianpan , Leung Vivian W.M , Xiao Peng , Chan Kannie W.Y
Published: August 2024

CEST MRI is a non-invasive molecular imaging approach, while APT has been applied to reveal molecular changes in brain tumors. Based on our theranostic hydrogel studies, here, we demonstrated the therapeutic effect on brain tumor with a continuous decrease in tumor size over 10 days. Importantly, the APT signal showed significant decrease on day 3 after treatment when tumor size did not have a significant change. Moreover, a strong correlation between APT signal and Ki-67 staining was shown. This could be a potential application to detect early tumor responses toward local hydrogel based treatment.
Differentiation of subtypes and genotypes in adult-type diffuse gliomas by APT imaging
Authors: Jiang Tongling , Wu Minghao , Xie Cong , Zhang Xianchang , Liu Yaou , Zhang Yi
Published: August 2024

APT-related metric maps were applied to differentiate subtypes and genotypes of adult-type diffuse gliomas following the latest 2021 WHO guidelines. One hundred and twenty-nine patients were imaged on a 3T scanner. Regions of interest were obtained with an automatic segmentation algorithm on conventional anatomical images, which were then resampled and matched with the CEST images. The mean CEST metric values were calculated in the automatically-defined regions of interest, and the receiver operating characteristic analysis was implemented, achieving generally successful performance in identifying the IDH status and part of the subtypes.
An application of diffusion tensor image analysis along perivascular space (DTI-ALPS) in grading gliomas and predicting IDH1 mutation status
Authors: Zhu Hongquan , Li Yuanhao , Li Li , Liu Weiyin , Zhu WenZhen
Published: August 2024

Glioma could impair the glymphatic function with reduced CSF outflow. We aimed to use DTI-ALPS method to investigate the pathological change of glymphatic function in gliomas and evaluate its value in grading gliomas and predicting IDH1 mutation status. The lower-grade gliomas (LrGGs) showed higher ALPS Index than glioblastomas (GBMs). IDH1 wild-type group showed decreased ALPS Index compared with the IDH1 mutant group in LrGGs. But there was no difference between the IDH1 subtypes in GBMs. The ALPS Index showed good efficiency in grading gliomas and predicting IDH1 mutation status, it may be a potential imaging biomarker for diagnosing gliomas.
Predicting IDH1 Expression using Computational Modeling of Interstitial Fluid Pressure in Glioblastoma
Authors: Zhou Jianan , Hu Wentao , Zhu Zhengyang , Zhang Xin , Dai Yongming , Zhang Bing
Published: August 2024

The immunohistochemistry features of glioblastoma have important influence on its occurrence and prognosis. Understanding the noninvasive detection of interstitial fluid pressure (IFP) and velocity (IFV) based on dynamic contrast enhanced (DCE)-MRI to explore the correlation between IFP and IFV with immunohistochemical markers of glioblastoma. The investigation demonstrates that IFP indicators have significant correlation with isocitrate dehydrogenase 1 (IDH1) expression and Ki-67 level of glioblastoma, and could help diagnose IDH1-mutation patients. Keywords Glioblastoma，Interstitial Fluid Pressure and Velocity，IDH1，Ki-67
Full brain relaxometry at 7T in 3 minutes by accelerated MR-STAT using a low-SAR flip angle train
Authors: Versteeg Edwin , Liu Hongyan , van der Heide Oscar , Fuderer Miha , van der Berg Cornelis , Sbrizzi Alessandro
Published: August 2024

MR-STAT is a framework that enables the estimation of multi-parametric quantitative MR-maps from a single short scan. Quantitative imaging at 7T can be used to probe the brain’s microstructure at high resolution. We show the first results of MR-STAT at 7T and show that SAR-limitations and B1+-inhomogeneities can be successfully addressed by designing a low-SAR flip angle train and using a B1+-prior during reconstruction. In addition, we use the increased SNR at 7T to achieve two-fold acceleration of the MR-STAT acquisition and show that high quality parameters can be obtained both on a gel-phantom and in-vivo (full-brain) in 3 minutes.
Using Diffusion-weighted MR spectroscopy to quantify age- and inflammation-associated changes in glial morphology in-vivo
Authors: Periche-Thomas Eva , Ronen Itamar , MacIver Claire , Sastin Dmitri , Underwood Jonathan , Coulson James , Leach Helena , Branzoli Francesca , Cercignani Mara , Harrison Neil
Published: August 2024

Age-associated cognitive decline and neurodegenerative disorders have been linked to altered immune function and inflammation, and particularly to the role of microglia. Current methods for imaging (micro)glia in humans are limited to TSPO-PET, a costly and invasive technique with poor cellular specificity. Here we acquired diffusion weighted (DW) MRS in 15 young and 15 older participants, each scanned twice, after Interferon-1beta or placebo. Results supported our prior hypotheses of selective effects of Interferon-1beta on the apparent diffusion coefficient of thalamic Choline (p<0.040), providing support for DW-MRS as a novel in-vivo method for quantifying glial morphology.
Robustness analysis of QSM radiomic features in patients with multiple sclerosis
Authors: Fiscone Cristiana , Rundo Leonardo , Lugaresi Alessandra , Manners David , Allinson Kieren , Baldin Elisa , Lodi Raffaele , Tonon Caterina , Testa Claudia , Castelli Mauro , Zaccagna Fulvio
Published: August 2024

This work evaluates the reliability of radiomic features in healthy controls and patients with multiple sclerosis using MR Quantitative Susceptibility Mapping (QSM), to guide the identification of future potential biomarkers. To ensure reproducibility, we assessed the non-lesioned parenchyma. Feature robustness was evaluated against the number of grey levels and echo times, measuring the Intraclass Correlation Coefficient (ICC). More than 65% of features were robust; different outcomes between regions were interpreted considering their anatomical characteristics (e.g. fibres’ orientation), confirmed by radiomic measurements (e.g. entropy). In future work, we are going to assess characterization and classification potential of those measurements.
A comparison of Gadolinium- and water-based blood-brain barrier dysfunction measures in patients with small vessel disease
Authors: Stringer Michael , Manning Cameron , Shao Xingfeng , Lee Hedok , Vallatos Antoine , Lord Hattie , Arteaga Carmen , Clancy Una , Garcia Daniela Jaime , Hernandez Maria Valdes , Wiseman Stewart , Locherty Rachel , Chappell Francesca , Brown Rosalind , Doubal Fergus , Marshall Ian , Benveniste Helene , Thrippleton Michael , Wang Danny , Wardlaw Joanna
Published: August 2024

Clinically relevant non-invasive blood-brain barrier (BBB) function imaging techniques are needed to monitor the role of neuroinflammation and endothelial cell dysfunction, particularly in small vessel disease (SVD). Diffusion-weighted ASL measures water exchange rate (kw), a promising endogenous BBB function metric, but has not been assessed in sporadic SVD. We measured kw in SVD patients to explore associations with established Gadolinium-based contrast agent (GBCA) BBB permeability measures and SVD severity. We found only limited associations between kw and GBCA metrics, although patients with more severe SVD tended to have higher kw, reflecting that the methods may probe different mechanisms.
Diffusion Bubble Model: A Novel Method For Detecting Neuroinflammation in Mouse Brain With Sanfilippo Syndrome
Authors: Zhang Erjun , Londono Irene , Fouquet Jérémie , Pshezhetsky Alexey , De Leener Benjamin , Lodygensky Gregory
Published: August 2024

The Diffusion Bubble Model (DBM) is a new method for detecting neuroinflammation in the brains of mice with Sanfilippo Syndrome. This rare and debilitating disorder primarily affects children and causes progressive neurodegeneration. DBM utilizes diffusion spectrum derived from dMRI to detect brain injuries such as inflammation. It can work in both white and gray matter with limited number of diffusion directions. The study found that brain injuries with inflammation had reduced the fraction of the slow diffusion component and increasing the fraction of the fast diffusion component. The findings may establish non-invasive biomarkers for detecting and evaluating neuroinflammation diseases.
ADVANCED DIFFUSION IMAGING METHODS TO ASSESS THE MICROSTRUCTURE OF MULTIPLE SCLEROSIS LESIONS
Authors: Stölting Anna , Bulcke Colin Vanden , Macq Benoit , Maggi Pietro
Published: August 2024

Paramagnetic Rim Lesions (PRL) in Multiple Sclerosis (MS) are associated with increased disability and axonal damage. We examined PRL microstructure using Track Density Imaging (TDI) and four diffusion MRI (dMRI) models, including Microstructure Fingerprinting (MF). When compared to non-PRL, PRL showed larger size, higher T1-values, lower neurite density index and fibre volume fraction on dMRI (p < 0.001) and reduced track density on TDI (p < 0.0001), suggesting impaired axonal density/integrity in PRL. Results obtained with the novel MF model are in line with those obtained with other dMRI models, indicating its potential for studying MS lesion pathology.
T1ρ and magnetization transfer experiments on a point-of-care 46 mT MRI system
Authors: Lena Beatrice , Najac Chloé , Václavu Lena , O'Reilly Thomas , Webb Andrew
Published: August 2024

Contrast mechanisms such as T1ρ and MT are interesting for point-of-care (POC) low field systems, to supplement/augment standard T1- and T2- weighting. However they typically require high B0 homogeneity. Here, we use a high homogeneity Halbach-magnet array POC to perform experiments involving either direct on- or off-resonance pulses, and to calculate T1ρ and MT ratio in tissue-mimicking phantoms. T1ρ showed different white matter (WM)/gray matter (GM) contrast compared to T2. The measured magnetization transfer ratio (MTR) showed higher values in the WM than in the GM.
Cerebral Time-of-flight Magnetic Resonance Angiography at Ultra-low-field: A Preliminary Study at 0.055 Tesla
Authors: Su Shi , Hu Jiahao , Xiao Linfang , Ding Ye , Lau Vick , Zhao Yujiao , Zhang Junhao , Man Christopher , Leong Alex , Wu Ed
Published: August 2024

Recent development of ultra-low-field (ULF) MRI presents opportunities for low-cost and portable brain imaging in point-of-care scenarios or/and low- and mid-income countries. Magnetic resonance angiography (MRA) is an essential part of MR neuroimaging protocols especially for stroke assessment, yet its feasibility at ULF remains unknown. In this study, we explore the time-of-flight MRA at 0.055 Tesla. We demonstrate cerebral MRA using flow-compensated gradient echo sequences, enabling visualization of main cerebral arteries and veins. We envision that usable and quality brain MRA can be potentially achieved at ULF with further sequence/reconstruction optimization and use of intravascular contrast agent.
Amide Proton Transfer Weighted Imaging to differentiate prostate suspicious nodules: Comparison with PI-RADS v2.1 score
Authors: He Guanyong , Han Liying , Yan Ronghua , Li Hao , Wu Zhigang , Gu Qingping , Cheng Guanxun
Published: August 2024

Diagnosis of prostate cancer (PCa) remains a challenge since PCa often occurs simultaneously with benign prostatic hyperplasia and has similar nodule appearance on T2-weighted imaging and diffusion weighted imaging. Amide proton transfer weighted (APTw) imaging is an endogenous biomarker to detect proteins and peptides in tissues non-invasively. Results of this study indicate the APTw ratio (rAPTw) values of PCa were significantly higher than those of prostate benign nodules. Therefore, rAPTw value is potentially a promising and valuable non-invasive biomarker in differentiating PCa from benign nodules.
Decomposition of clinical ADC into intracellular and extracellular-extravascular contributions in prostate cancer using histology
Authors: Garcia-Ruiz Alonso , Grussu Francesco , Sen Snigdha , Jin Chen , Freeman Alex , Haider Aiman , Punwani Shonit , Alexander Daniel , Perez-Lopez Raquel , Panagiotaki Eleftheria
Published: August 2024

Diffusion MRI has shown promising results for characterizing prostate cancer. However, diagnostic clinical apparent diffusion coefficient (ADC) has limited specificity and interpretability. Towards addressing these limitations, we aim to unravel clinical ADC into microstructural components using histology. Histology from two prostatectomies with prostate cancer (Gleason 3+4, 4+3) were analysed in benign, inflammation and cancer regions. Cell and tissue properties were used to decouple clinical ADC into intracellular, extracellular-extravascular ADCs. Results revealed significantly low intracellular ADC in cancer. Low ADC was also found for inflammation, which could explain ADC’s low specificity, demonstrating the added value of histology data for clinical ADC.
Human Prostate MRI at ultra-high-performance gradient of 200 mT/m and 500 T/m/s
Authors: Zhu Ante , Tarasek Matthew , Hua Yihe , Fiveland Eric , Yeo Desmond , Maier Stephan , Mazaheri Yousef , Szczepankiewicz Filip , Westin Carl-Fredrik , Tempany Clare , Akin Oguz , Foo Thomas
Published: August 2024

Diffusion MRI has been shown to yield imaging biomarkers for prostate cancer identification and grading. However, the image quality remains poor due to the limited gradient performance of clinical whole-body MRI systems. We assessed the technical feasibility of human prostate MRI in a 42-cm inner-diameter gradient coil operating at maximum gradient amplitude of 200 mT/m and slew rate of 500 T/m/s. No sensation of peripheral nerve stimulation was reported. Significantly reduced image distortion and higher image signal-to-noise ratios were achieved in diffusion MRI due to shorter echo times and shorter echo spacings, compared to diffusion MRI at whole-body MRI systems.
Free-breathing mapping of stress/rest myocardial T1 reactivity with Ferumoxytol-enhanced imaging using a widely available sequence
Authors: Unal Hazar Benan , Zeynali Shahriar , Raman Subha , Tamarappoo Balaji , Dharmakumar Rohan , Sharif Behzad
Published: August 2024

Myocardial T1 reactivity, defined as the relative T1 change from rest to stress, has been proposed as a marker for detection of ischemic heart disease. Commonly used MOLLI T1 mapping is sensitive to B0 field inhomogeneities and can have susceptibility/banding artifacts because of bSSFP readouts, especially at 3T. In this study, we investigated the feasibility of free-breathing SR-FLASH T1 mapping for ferumoxytol-enhanced (FE) dobutamine-stress T1 reactivity studies at 3T in preclinical settings. We showed the feasibility of using a widely available perfusion sequence for T1 reactivity studies under Ferumoxytol-enhancement.
Joint cardiac tissue velocity and diffusion tensor mapping
Authors: Weine Jonathan , Buoso Stefano , McGrath Charles , Kozerke Sebastian
Published: August 2024

Myocardial strains and microstructure are considered important indicators of muscle contractility and function, which can be investigated with cardiac diffusion tensor imaging (cDTI) and tissue-velocity mapping. In this work we perform simulations incorporating contractile motion and model based diffusion contrast to investigate jointly encoding the information by modifying existing cDTI protocols. Key characteristics of the results agree with practical findings and suggest sufficient estimation accuracy for velocities and diffusion tensors.
High on Sparsity: Inter-Bin Compensation of Cardiac Motion for Improved Assessment of Left Ventricular Function Using 5D whole-heart MRI
Authors: Yerly Jérôme , Roy Christopher , Prsa Milan , Milani Bastien , Stuber Matthias
Published: August 2024

The reconstruction of 5D cardiac and respiratory motion-resolved images with the free-running framework (FRF) requires careful optimization of the regularization weights to avoid compression of physiological motion, which in turn may lead to underestimated left ventricular ejection fraction (LVEF). This study presents a novel cardiac and respiratory motion-resolved reconstruction with inter-bin compensation of cardiac motion. We demonstrate that the proposed framework significantly improves image quality while preserving accurate LVEF when compared to the original 5D framework. This work highlights important considerations when reconstructing cardiac resolved images without compensation and provides a robust approach for the assessment of LVEF.
Time-dependent Diffusion in the Human Heart In Vivo
Authors: Teh Irvin , Coveney Sam , Foster Richard J. , Szczepankiewicz Filip , Lasič Samo , Lundell Henrik , Shelley David , Mueller Lars , Afzali Maryam , Sharrack Noor , Yuldasheva Nadira Y. , Plein Sven , Dall'Armellina Erica , Schneider Jürgen E.
Published: August 2024

Conventional spin-echo based cardiac diffusion tensor imaging (DTI) has a relatively limited range of encoding frequencies, and hence limited sensitivity to diffusion at different length scales. Here, we explored the feasibility of applying a broader range of frequencies to evaluate the effects of time-dependent diffusion. We employed diffusion encoding waveforms with up to 4th order motion-compensation in a cohort of healthy volunteers, and report trends of decreasing MD and FA with increasing encoding frequencies. The availability of higher frequencies enhances the sensitivity of DTI to shorter length scales, and may be more greatly weighted towards diffusion properties of sub-cellular structures.
Simplified Protocol with mSAVA for 3D Imaging of T1, T2, Extracellular Volume, Bright-Blood and Dark-Blood Late Gadolinium Enhancement
Authors: Si Dongyue , Cheng Lan , Kong Xiangchuang , Guo Rui , Herzka Daniel , Ding Haiyan
Published: August 2024

Multi-parametric SAturation recovery and Variable flip Angle (mSAVA) acquires four 3D volumes with different T1 and T2 weightings during free-breathing to simultaneously generate whole heart T1 and T2 parametric maps. We proposed a fast and simple CMR protocol using pre- and post-contrast mSAVA acquisitions to additionally generate ECV maps, and bright-blood and dark-blood LGE images. mSAVA could comprehensively assess the myocardium over the whole heart within ~6+6 min in a cohort of twenty patients.
Super-resolution algorithms for simultaneous 1H MRF/23Na MRI: Comparison between U-Net, PLS-regression, and hybrid methods
Authors: Rodriguez Gonzalo , de Moura Hector Lise , O'Donnell Lauren , Regatte Ravinder , Madelin Guillaume
Published: August 2024

We compared three algorithms to generate a high-resolution (HR) 23Na image from simultaneously-acquired low-resolution (HR) 23Na density-weighted MRI and HR 1H density, T1 and T2 maps from MRF in brain at 7 T: U-net, PLS-regression, and hybrid. The multi-scale structural similarity index between generated HR 23Na images and HR ground truth was higher than 0.95 for the three methods. Overall, the hybrid method showed better results, generating the sharpest HR image while keeping the highest similarity between the acquired and generated LR images.
Motion Correction in Brain MRI using Deep Image Prior
Authors: Lee Jongyeon , Lee Wonil , Park HyunWook
Published: August 2024

Motion correction in MRI has been successful with deep learning techniques to reduce motion artifacts. However, these methods were based on supervised learning, which have required a large dataset to train neural networks. To overcome this issue, we propose a new technique to correct motion artifacts without any training dataset, which optimizes a neural network only with a single motion-corrupted image. We adopt Deep Image Prior framework to capture image priors from a convolutional neural network using motion simulation based on MR physics. Using the deep image prior, our method finely reduces motion artifacts without any dataset.