bluuebunny/crossref_metadata_2025 huggingface dataset:
Free-Breathing Hyperpolarized Xenon-129 Spectroscopy with Cardiopulmonary Gating
Authors: Amzajerdian Faraz , Hamedani Hooman , Baron Ryan , Ismail Mostafa , Loza Luis , Ruppert Kai , Kadlecek Stephen , Rizi Rahim
Published: August 2024

While hyperpolarized 129Xe (HXe) MRI is capable of quantifying gas exchange, these measurements are heavily dependent on both cardiac and pulmonary activity. Since traditional HXe approaches are performed during extended breath-holds at fixed lung inflation levels, the measured gas exchange can differ greatly based on the chosen inflation position, and may thus not be representative of steady-state behavior. To explore the sensitivity of HXe to cardiac pulsations and the different phases of respiration, we acquired spectra continuously over approximately 40 breaths of low-dose HXe before retrospectively gating the signals based on both cardiac and respiratory cycles.
Microvascular response of an oxygen carrier in the penumbral tissue of fast and slow progressors in a canine large vessel occlusion model
Authors: Shazeeb Mohammed Salman , King Robert , Vardar Zeynep , Kolstad Josephine , Kuhn Anna , Anagnostakou Vania , Raskett Christopher , Winger Jonathan , Krtolica Ana , Henninger Nils , Gounis Matthew
Published: August 2024

In acute ischemic stroke due to large vessel occlusion (LVO), information about the penumbral tissue can be vital in making decisions on how to treat ischemic stroke patients in the clinic. This study investigated the use of intravoxel incoherent motion (IVIM) MRI in a canine LVO model to quantify the perfusion information in penumbral tissue of fast and slow progressors that received an oxygen carrier drug. The IVIM parameters were assessed to predict the onset of penumbral tissue death. The IVIM parameters showed a better utility in predicting penumbral tissue death in fast progressors compared to slow progressors.
Deep Learning Based Automated Multi-Organ Segmentation in Lymphoma Patients using Whole Body Multiparametric MRI Images
Authors: Masood Anum , Knapstad Sølvi , Johansen Håkon , Husby Trine , Eikenes Live , Goa Pål , Elschot Mattijs
Published: August 2024

Widespread of lymphoma cancer makes manual segmentation of metastatic lymph nodes a tedious task. Lymphoma cancer is assigned an anatomic stage using the Ann Arbor system which relies on the segmentation and localization of affected lymph nodes with respect to anatomical stations. We present a framework for multi-organ segmentation for multiparametric MRI images. Our modified nnUnet using a transfer learning approach achieved 0.8313 mean DSC and 0.659 IoU in lymphoma cancer dataset.
Fluid-Suppressed APTw is more accurate than Leakage-Corrected rCBV imaging in the distinction between tumor progression and radionecrosis
Authors: Nichelli Lucia , Papageorgakis Christos , Bensemain Mehdi , Jacob Julian , Valery Charles , Liebig Patrick , Zaiss Moritz , Lehéricy Stéphane , Casagranda Stefano
Published: August 2024

The distinction between radionecrosis and tumor recurrence is a common diagnostic dilemma, as current advanced multiparametric MRI protocols lack on accuracy. Fluid-Suppressed Amide Proton Transfer weighted (APTw) imaging has strong potentials in brain tumor post-therapeutic assessment. In this study we compare at 3T the diagnostic accuracy of Fluid Suppressed APTw with the most used advanced technique, i.e. the Leakage-Corrected relative Cerebral Blood Volume imaging obtained by DSC perfusion in 22 pre-irradiated metastases. Results show that Fluid-Suppressed APTw metrics can clearly make a distinction between these two pathologies, in contrast to Leakage-Corrected rCBV contrast.
4D flow MRI to evaluate flow and future liver remnant growth after portal vein embolization
Authors: Oechtering Thekla , Schubert Tilman , Zhao Qianqian , Alexandridis Roxana , Panagiotopoulos Nikolaos , Wieben Oliver , Johnson Kevin , Roldán-Alzate Alejandro , Reeder Scott
Published: August 2024

Early prediction of remnant liver growth after portal vein embolization (PVE) would enable earlier surgery in patients with liver malignancies and thus decrease the risk of tumor progression. Portal blood flow after PVE holds the potential to be an important predictor for hypertrophy of the non-embolized segments. We demonstrated the feasibility of 4D flow MRI quantification of portal blood flow before and after PVE in a porcine model. Flow changes immediately after PVE were predictive of the change in liver volume 2 weeks post PVE in both the embolized and non-embolized liver lobes.
Optimizing the NEXI acquisition protocol for quantifying human gray matter microstructure on a clinical MRI scanner using Explainable AI
Authors: Uhl Quentin , Pavan Tommaso , Feiweier Thorsten , Canales-Rodríguez Erick , Jelescu Ileana
Published: August 2024

We optimized the acquisition protocol for parameter estimation of the NEXI model, suited to characterize gray matter microstructure, using concepts from Explainable AI. The improvement over a “naïve” protocol was only marginal. The limit on NEXI parameter estimation precision and accuracy is largely driven by the model and the type of measurements available (linear diffusion encoding, in a combination of (b,t) pairs) and is likely already reached as can be estimated from CRLB. The silver lining is that a clinical acquisition protocol feasible on a 3T system with 80 mT/m gradients yields reasonable NEXI microstructure maps in the human brain.
Deep learning for quantitative evaluation of motion correction in dynamic contrast enhanced (DCE) MRI
Authors: Dejene Edengenet Mashilla , Kolbitsch Christoph
Published: August 2024

Respiratory motion can impair the accurate estimation of physiological parameters in DCE-MR of the liver. A Deep learning network is proposed to quantitatively investigate the impact of respiratory motion on the estimation of physiological parameter maps. The proposed network provides quantitative parameters for DCE-MR and uncertainty estimates for these parameters. Here we could show that the estimated epistemic uncertainty of k_trans is sensitive to motion. This could provide important information about how well motion correction worked and how reliable the obtained quantitative DCE parameters are.
Assessing Sex Differences in Abdominal Fat Depots of People with Obesity under Weight Loss using Automated Segmentation
Authors: Wu Mingming , Somasundaram Arum , Rupp Selina , Han Jessie , Naebauer Stella , Junker Daniela , Reik Anna , Wiechert Meike , Hauner Hans , Holzapfel Christina , Karampinos Dimitrios
Published: August 2024

A deep-learning algorithm based on the nnU-Net and using water-fat images enabled robust automatic segmentation of abdominal organs including visceral and subcutaneous adipose tissue, liver, iliopsoas and erector spinae muscle groups. Each organ's volume and fat content were examined in a weight loss study comprising 127 subjects with BMI of 30-39.9kg/m2, who followed a low caloric diet (LCD). Dixon water-fat images were acquired before and after diet. Differences in fat distribution among abdominal organs and fat content was assessed among both sexes. Differences in the changes of organ volume and fat fraction as a response to the LCD were revealed.
Assessing Muscle Invasiveness In Bladder Cancer Based On Multiple Diffusion Models
Authors: Guo Junting , Zhang Lu , Li Shuo , Li Ding , Fan Zhichang , Chen Meining , Yang Guoqiang , Li Yan , Wang Bin , Wang Le , Wang Xiaochun
Published: August 2024

Accurate assessment of the presence or absence of muscle invasiveness in bladder cancer is essential for selecting the best treatment options. In this study, we used 6 diffusion models including mono-exponential model (Mono), continuous-time random-walk (CTRW), incoherent motion within the voxel (IVIM), stretched exponential model (SEM), diffusion kurtosis imaging (DKI) and fractional-order calculus (FROC) model to assess muscle invasiveness in bladder cancer. The study showed that Mono,CTRW,IVIM,SEM and DKI could provide biomarkers for muscle invasion and distinguish non-muscle-invasive and muscle-invasive bladder cancer, and the combination of CTRW and FROC could further improve the classification accuracy.
Multi-channel 7 Tesla sodium MRI of the brain in children with epileptogenic SCN1A sodium channel mutations – a pilot study
Authors: Cleary Jon , Rot Samuel , Ayre Michael , Bridgen Philippa , Dokumaci Ayse , Blunck Yasmin , Syeda Warda , Solanky Bhavana , Malik Shaihan , Lim Ming , Wheeler-Kingshott Claudia Gandini , Tang Shan-Shan , Carmichael David
Published: August 2024

SCN1A gene mutations disrupt sodium channel (NaV1.1) function, causing childhood epilepsy which can be severe. Predicting functional consequences in these children is challenging and new prognostic imaging biomarkers are needed. Sodium MRI directly assesses brain sodium and is a potential in vivo imaging biomarker. Using a multiecho sodium sequence, at 7T, we found children with SCN1A mutations had increased relative sodium concentrations across a large number of brain regions compared to controls. The cause of this change is likely complex, and may reflect an interplay between neuronal/axonal/glial dysfunction – with disruptions in microstructure and physiology – and possible medication effects.
Selective MRI reacquisition to extend the working range of retrospective motion correction
Authors: Laustsen Malte , Slipsager Jakob , Gaaß Thomas , Frost Robert , van der Kouwe André , Ganz Melanie , Hanson Lars
Published: August 2024

Retrospective motion correction (RMC) can substantially reduce motion artifacts in 3D brain MRI. However, for extensive motion, RMC performance is limited. We evaluate RMC with selective reacquisition (RMC+reacq) to expand the range of correctable motion, while directly comparing to prospective motion correction (PMC) for volumetric brain MRI, using external motion tracking. Both approaches lead to significant image quality improvement and the performance of RMC+reacq and PMC was only found statistically significant in 1 of 9 comparisons. These results suggest that RMC with selective reacquisition can match the performance of PMC for 3D-MPRAGE and 3D-FLAIR sequences.
Multivariate Patterns of Brain Functional Connectome Underlying COVID-related Negative Affect Symptoms
Authors: Pan Nanfang , Qin Kun , Wang Song , Gong Qiyong
Published: August 2024

In the investigation of mental health issues following the unprecedented COVID-19 pandemic, we used the pre-COVID neuroimaging data to predict the severity of negative affect during the pandemic in a general population. Notably, covariation patterns of mode stress and mode anxiety were identified, and the brain DAN network plays a critical role in both modes. Based on individualized patterns, we may identify individuals who confer high vulnerability to pandemic-induced stress or anxiety symptoms. Our findings may facilitate the understanding of neural correlates underlying pandemic-induced negative affect, and the susceptibility neuromarkers may serve as targets for early prevention and psychological intervention.
Examining the temporal evolution of top-down task dependent modulations across cortical depths.
Authors: Vizioli Luca , Dowdle Logan , Moeller Steen , Ugurbil Kamil , Yacoub Essa
Published: August 2024

We demonstrate the feasibility of simultaneously acquiring submillimeter and subsecond functional images to examine the temporal evolution of task-dependent modulations across cortical depths elicited by socially relevant stimuli such as faces at the single subject level. We achieved this using NORDIC denoising. Our results highlight the complexity of laminar fMRI results in humans which can be better resolved by high spatiotemporal recordings. We suggest that, when studied with sufficient, sub-second temporal resolution, depth-dependent fMRI has the potential to address laminar communication within and across areas, which is crucial to understanding the complexity of human hierarchal organization at the mesoscale level.
Optogenetic fMRI reveals neural adaptation properties beyond local olfactory circuits
Authors: Ma Teng , Wang Xunda , Xie Linshan , Wen Junjian , Chong Pit Shan , Cao Peng , Lim Lee Wei , Wu Ed X. , Leong Alex T. L.
Published: August 2024

Olfactory adaptation due to repeated odor cues has been studied extensively by fMRI or electrophysiology studies in several primary olfactory regions (i.e., anterior olfactory nucleus, AON, and piriform cortex, Pir). However, the modulatory role of other primary olfactory regions (e.g., amygdala and entorhinal cortex) and their integrations with high-order olfactory regions during olfactory adaptation is likely underestimated due to the documented weak and unstable responses at regions beyond AON and Pir with conventional presentation of odor stimuli. Here, we deployed an optogenetic fMRI approach to improve sensitivity in detecting olfactory responses and examine their adaptation at the systems level.
Circadian influence on brain connectivity revealed by resting-state fMRI in awake mice
Authors: Rathnayaka Muditha , Yang Rui , Rodriguez Yeison , Wansapura Janaka , Li Nan
Published: August 2024

Circadian rhythms control almost all our vital physiology and cognitive functions. Disruptions of circadian rhythms are also reported in multiple neuropsychiatric disorders. However, the neural network-level study of the circadian system in vivo has been understudied. Here we use awake mice resting-state fMRI to characterize the functional connectivity changes at different time points in the circadian cycle. Our results indicate that circadian oscillations can alter the functional connectivity across the brain with various changes depending on the local circuits. Particularly, the midbrain dopaminergic system showed a trend of stronger connectivity to the cortex at night compared to the morning.
An Open 60-channel Tx/ 32-channel Rx RF Coil System for Routine Use at 7T
Authors: Sajewski Andrea , Santini Tales , DeFranco Anthony , Keil Boris , Jin Hecheng , Berardinelli Jacob , Li Jinghang , Chu Cong , Martins Tiago , Ibrahim Tamer
Published: August 2024

A 60-channel transmit array for 7T neuro MRI was implemented using the Tic-Tac-Toe coil design. The transmit coil and the receive insert are open in the front to promote patient comfort and reduce claustrophobia. By performing RF shimming on three head models, we optimized the coil for a range of ages and head sizes/shapes for use in sTx mode. Simulations, experimental B1+ maps and in-vivo images demonstrate consistency across subjects, showing extended coverage into the temporal lobe, cerebellum, brainstem and C5-C6 spinal cord segments. High quality images are currently being acquired using this coil in over 30 human studies.
Effects of double-ECG gating in synchronized breathing myocardial arterial spin labeling
Authors: Aramendía-Vidaurreta Verónica , Solís-Barquero Sergio M. , Vidorreta Marta , Ezponda Ana , Bastarrika Gorka , Fernández-Seara María A.
Published: August 2024

Myocardial perfusion can be quantitatively measured noninvasively using arterial spin labeling (ASL). Motion due to the cardiac cycle is tackled with the use of single- or double-ECG gating. The goals of this study were to investigate the performance of double-gating, in synchronized breathing myocardial ASL with presaturation pulses by comparison with single-gating, and to compare the different quantification strategies for double-gated data. This study showed that double-gating is more robust to heart rate variability than single-gating in synchronized breathing ASL sequences with presaturation pulses, but accurate saturation-recovery fitting requires the acquisition of several baseline images.
Joint Velocity and Acceleration Encoding for Improved Pressure Gradient Mapping in Flow Imaging
Authors: Loecher Michael , Nair Priya , Ennis Daniel
Published: August 2024

In this work, we introduce an optimized motion encoding strategy for flow measurements that simultaneously and non-colinearly encodes velocity and acceleration into data phase. This enables velocity-based flow measurements and improves pressure gradient mapping derived from the acceleration data. The method is tested in a stenotic flow phantom, where the proposed method shows good velocity agreement with conventional 4D-flow methods, while also producing improved pressure gradient maps when compared to both 4D-flow and a CFD reference.
MR Fingerprinting in the Knee Cartilage Compared to Conventional Methods in Combination with Automated Cartilage Segmentation
Authors: Bencikova Diana , Cloos Martin , Janacova Veronika , Trattnig Siegfried , Juras Vladimir
Published: August 2024

Quantitative MRI has been shown to be sensitive to early stages of cartilage degeneration in osteoarthritis, but conventional MRI techniques can measure only single parameter at a time. This poses time constraints and co-registration challenges. With MR Fingerprinting, multiple parameters can be assessed within single measurement. Here, we evaluated prototype MRF sequence in NIST phantom and healthy volunteers in combination with automatic cartilage segmentation procedure and compared to conventional techniques. We could show that the values provided by MRF sequence agreed with the values provided by conventional techniques. Therefore MRF is accurate and practical diagnosis tool for articular cartilage examination.
Knee Bone and Cartilage Segmentation using Deep Learning Model Trained with Heterogeneous Data: Preliminary Results
Authors: Zhang Xiaoxia , Moura Hector , Zibetti Marcelo , Regatte Ravinder
Published: August 2024

In this study, we pre-trained a deep learning model for knee bone and cartilage segmentation with open dataset (MICCAI grand challenge "K2S 2022"), and then fine-tuned it with a small size of locally acquired data for customized task, in which we explored different contrasts as well. We can benefit from the large dataset size to increase the segmentation accuracy and generalization capabilities while reducing the labor and time of manual segmentation for training data. The preliminary results of a small dataset with 10 subjects using a simple 2D U-net are promising for single contrast and multi contrast images.
Modeling inflow effects in fast fMRI to quantify fluid flow
Authors: Ashenagar Baarbod , Gomez Daniel , Lewis Laura
Published: August 2024

Fast fMRI has recently been shown to be an effective method for detecting dynamic changes in cerebrospinal fluid flow, enabling measurement of a critical process for maintenance of brain health. However, while the inflow signal measured using fast fMRI is a surrogate for the underlying flow dynamics, it does not directly reflect the velocity and dynamics of flow. To understand the mapping between flow and the flow-enhanced MR signals they generate, we developed and validated a mathematical forward model that uses velocity as input and simulates dynamic fMRI inflow signal intensities for each slice of the imaging volume.
Clinical feasibility of contrast-enhanced ASL for blood-brain barrier water exchange rate measurements
Authors: Powell Elizabeth , Dickie Ben , Ohene Yolanda , Parker Geoff , Parkes Laura
Published: August 2024

Contrast-enhanced ASL (CE-ASL) has been proposed as a method for measuring blood-brain barrier water exchange, and is a technique that could be used in conjunction with DCE/DSC-MRI to provide complementary information on brain vasculature. We demonstrate in this work the clinical feasibility and consistency of the CE-ASL technique in simulations and in healthy volunteers. Using simulations, we characterise the expected accuracy and precision of parameter estimates. We then evaluate the consistency of CE-ASL measurements across six healthy volunteers.
Neurovascular decoupling in type 2 diabetes: A meta-analysis and an independent validation of Neuroimaging
Authors: Li Zeyang , Yu Ying , Cui Guang-Bin , Yan Lin-Feng
Published: August 2024

Disrupted neurovascular (NV) coupling is considered as a potential mechanism of Type 2 diabetes mellitus (T2DM) induced mild cognitive impairment (MCI). The study quantitatively explored whether NV decoupling were associated with cognitive impairment in patients with T2DM by means of neuroimaging meta-analysis and an independent validation. In T2DM, NV uncoupling existed in many brain regions, and the degree of uncoupling was related to cognition. It contributed to a better understanding of the mechanism in T2DM cognitive impairment and would be a promising neuroimaging biomarker. This study combined meta-analysis and independent validation model can be extended to other similar studies.
Lung perfusion imaging: influence of signal-to-concentration transformation method and comparison with 129Xe biomarkers
Authors: Tibiletti Marta , Hughes Paul , Eaden James , Naish Josephine , Marshall Helen , Waterton John , Bianchi Stephen , Wild Jim , Parker Geoff
Published: August 2024

Quantitative pulmonary perfusion can be derived from MR imaging with injection of contrast agent (CA). Tracer-kinetic theory yields physiological parameters such as pulmonary blood flow (PBF), blood volume (PBV) and mean transit time (MTT) but relies on accurate calculation of CA concentration. Previous studies have used ‘subtraction’ or ‘normalisation’ methods without T1-mapping. Using both simulations and data from interstitial lung disease patients, we demonstrate how the ‘subtraction’ method weights PBV by local lung density. This causes likely spurious correlations with hyperpolarised 129Xe biomarkers linked to lung ventilation, microstructure and density, potentially obscuring information of diagnostic interest.
Modeling of Gradient-Induced Magnet Heating using Equivalent Current Surface and Multi-Physics Finite-Element Methods
Authors: Bratch Alexander , Roemer Peter , Adriany Gregor , Ugurbil Kamil , Rutt Brian
Published: August 2024

With increasing prevalence of ultra-high field magnets and high-performance gradients, it is important to understand gradient-induced magnet heating, which can yield significant helium boil-off. Here, we propose a method to model this effect requiring no knowledge of gradient coil construction. Using measured gradient stray fields, we construct equivalent current surface models of gradient coils that can be input into finite element model of magnet systems to predict the deposited energy. We validate this equivalent current surface method using a gradient with a known winding pattern and further validate the energy deposition models by measuring power deposition in a 7T magnet.
4D flow MRI for investigation of fetal cardiovascular hemodynamics in healthy development and ductal dependent lesions
Authors: Englund Erin , Fujiwara Takashi , Smith Sarah , Cuneo Bettina , Moghari Mehdi Hedjazi , Meyers Mariana , Friesen Richard , Browne Lorna , Barker Alex
Published: August 2024

Fetal cardiovascular MRI has the potential to aid in the diagnosis and evaluation of congenital heart disease. Here, a fast, Doppler ultrasound- gated, 4D flow MRI acquisition with online reconstruction was achieved in twelve healthy fetuses and six patients with suspected congenital cardiovascular defects. Analysis of the 4D flow data revealed expected flow distributions across vascular territories in the healthy cohort. Using 4D flow MRI, we were also able to evaluate the presence and impact of ductal dependent lesions in patients with suspected congenital heart disease, finding confirmation of presence/absence of pathology on post-natal imaging.
Quantitative multiparametric MRI describes neuromelanin-linked pathogenesis in the AAV-hTyr rat model of Parkinson’s disease
Authors: Pérot Jean-Baptiste , Santin Mathieu , Ruze Anthony , Soustelle Lucas , Rebbah Sana , Mouton Laura , Valabregue Romain , Vila Miquel , Lehéricy Stéphane
Published: August 2024

Imaging of the neuromelanin (NM) has recently developed as a relevant biomarker of Parkinson’s disease (PD). Here, we present a longitudinal, quantitative, multiparametric study on the AAV-hTyr rat model of PD with NM accumulation in the right substantia nigra. Our protocol allowed to obtain NM-sensitive image, as well as R1, R2* and qMT in a single session. Longitudinal acquisition on AAV-hTyr rats showed inverted U-shaped curve of NM-MRI contrast-to-noise ratio, suggesting NM accumulation followed by neurodegeneration. R1, R2*, MPF and motor symptoms support this hypothesis. Our work may help to understand the pathogenesis of this PD model and identify biomarkers.
Evaluation of tumor physiology after single-fraction irradiation in a mouse model of pancreatic ductal adenocarcinoma using mpMRI
Authors: Paudyal Ramesh , Rusell James , LoCastro Eve , Lekaye Carl , Deasy Joseph , Humm John , Shukla-Dave Amita
Published: August 2024

Pancreatic ductal adenocarcinoma (PDAC) is the leading cause of cancer deaths worldwide. Quantitative multiparametric magnetic resonance imaging (mpMRI) allows for measuring the tumor's physiological characteristics, such as cellularity and vascularity/permeability. This study aimed to evaluate tumor physiology using mpMRI after single-fraction irradiation in a mouse model. The results demonstrated the changes in the functional status of mpMRI metrics. They were validated with in vivo histology markers of tumor perfusion (Hoechst 33342) and tissue morphology (Hematoxylin and eosin staining).
Resting-state fMRI study of vigilance level under endogenous modulation based on ReHo and fALFF in humans under normal entrained conditions
Authors: Xing Hanqi , Wu Zhiwei , Ma Mengya , Song Ziyang , Song Yang , Wu Yunzhu , Chang Yue , Dai Hui
Published: August 2024

Time-dependent neuromodulation mechanisms in human cognitive-behavioral tasks are not yet fully established. The present study aimed to analyze the changes in resting-state functional magnetic resonance imaging (rs-fMRI) blood oxygen level dependent (BOLD) signals over the 24-h day and their correlation with vigilance level. We recruited 20 healthy volunteers to be scanned at six-time points 24 hours a day. Compared to 9:00, 13:00, 17:00, and 21:00h, thalamic BOLD signals increased and vigilance level decreased at 1:00 and 5:00h. We speculate that the BOLD signals increased in the thalamus may represent a compensatory mechanism for maintaining relative vigilance level.
Unlocking 20-fold acceleration towards 0.5-second whole-brain HCP-style fMRI
Authors: Demirel Omer , Vizioli Luca , Yaman Burhaneddin , Moeller Steen , Dowdle Logan , Yacoub Essa , Ugurbil Kamil , Akçakaya Mehmet
Published: August 2024

Functional MRI (fMRI) is acquired with simultaneous multi-slice (SMS) imaging and in-plane acceleration to provide sufficient coverage and spatio-temporal resolutions. However, further accelerations are desirable to achieve BRAIN initiative targets. In this work, we investigate self-supervised deep learning reconstruction at 20-fold (SMS×in-plane=5×4) retrospective and prospective accelerations. Results show DL at 20-fold retrospective acceleration is similar to split slice-GRAPPA at 10-fold acceleration. Furthermore, we show that DL method trained on retrospective 20-fold acceleration generalizes well and successfully reconstructs prospectively 20-fold accelerated fMRI data.
Rapid and high-resolution bSSFP fMRI using 3D stack of spirals at 9.4 T
Authors: Valsala Praveen Iyyappan , Ehses Philipp , Veldmann Marten , Scheffler Klaus
Published: August 2024

We explored the spatio-temporal resolution and coverage of bSSFP BOLD contrast using a highly segmented 3D spiral readout. The functional activation maps acquired with the novel functional contrast for full visual field checkerboard stimulus is presented at submillimeter resolutions (0.6 mm3 & 0.8 mm3) and at 1.2 mm3 for whole brain coverage. We also demonstrated rapid slice-selective water excitation using binomial pulses.
Functional MRI to monitor disease progression in patients with rare kidney disease
Authors: Caroli Anna , Villa Giulia , Daina Erica , Brambilla Paolo , Gamba Sara , Leone Valentina , Carrara Camillo , Rizzo Paola , Noris Marina , Remuzzi Giuseppe , Remuzzi Andrea
Published: August 2024

This study investigates the correlation between MRI and histologic and clinical findings in 7 patients with C3 glomerulopathy and immune complex–associated membranoproliferative glomerulonephritis, rare diseases denoted by poor prognosis and no specific therapies. Patients underwent repeated kidney MRI, biopsy, and laboratory testing. Kidney diffusivity and perfusion were assessed by diffusion-weighted and phase-contrast MRI. Laboratory and MRI parameters changed very differently from case to case over 1 year. Perfusion biomarkers significantly correlated with histological and clinical findings. Both perfusion and diffusion biomarkers correlated with the clinical evolution of the disease. Current findings highlight MRI potential to monitor kidney disease progression.
Age-related alterations in soma and neurite fraction obtained from high-gradient diffusion MRI data across the lifespan
Authors: Lee Hansol , Lee Hong-Hsi , Eskandarian Laleh , Gaudet Kyla , Tian Qiyuan , Krijnen Eva , Klawiter Eric , Huang Susie
Published: August 2024

We studied alterations in soma and neurite signal fractions with age based on Soma And Neurite Density imaging (SANDI) in 43 healthy adults across the lifespan using multi-shell dMRI measurements acquired on the MGH Connectome scanner. We observed decreases in soma fraction with age in all cortical lobes, especially in the frontal lobe. The neurite fraction predominantly decreased with age in the genu of corpus callous. These results suggest a regionally selective aging effect on changes in compartmental composition within the brain, potentially reflecting alterations in microstructure associated with neurodegeneration.
Epigenetic age acceleration predicts subject-specific white matter degeneration in the human brain.
Authors: Newman Benjamin , Danoff Joshua , Lynch Morgan , Giamberardino Stephanie , Gregory Simon , Connelly Jessica , Druzgal T , Morris James
Published: August 2024

Epigenetic clocks provide powerful tools for estimating health and lifespan but their ability to predict brain degeneration and neuronal damage during the aging process is unknown. This study uses the epigenetic clock GrimAge to longitudinally investigate brain cellular microstructure in axonal white matter from a healthy aging cohort. We reconstructed subject-specific axonal networks damaged by white matter hyperintensities, a visible neurological manifestation of small vessel disease. A chronological age-adjusted version of GrimAge was significantly correlated with longitudinal markers of neuronal decline. This study is the first to establish a relationship between accelerated epigenetic GrimAge and brain cellular microstructure in humans.
Development and Validation of a Radiomics Model in Differentiating Sinonasal Mucosal Melanomas from Sinonasal Lymphomas
Authors: Li Shengyong , Guo Linying , Zhang Jing , Song Yang , Zhang Shengjian , Jiang Rifeng , Yang Guang , Tang Zuohua
Published: August 2024

Sinonasal mucosal melanomas (SNMM) are clinically more aggressive than its cutaneous counterpart and presented markedly poor prognosis. To differentiate sinonasal melanomas from sinonasal lymphomas, a radiomics model was built using features from multi-parametric MRI, including T1-weighted imaging (T1WI), T2 weighted imaging (T2WI), DWI and C-T1WI. In this multicenter retrospective study, 189 patients diagnosed with SNMMs or sinonasal lymphoma were enrolled from three institutions. The proposed model achieved AUCs of 0.884 and 0.870 in the internal and external validation set, respectively.
A Pilot Evaluation of TSE MVXD based IVIM in Characteristics and Diagnosis of Nasopharyngeal Carcinoma
Authors: Zhou Yifen , Chen Rui , Ye Huifen , Wu Zhigang , Xu Yongzhou , Liu Zaiyi , Wang Guangyi
Published: August 2024

Diagnosis of Nasopharyngeal Carcinoma (NPC) remains challenge since the contrast-enhanced T1-weighted imaging (CE-T1WI) may lead to harmful impact by the accumulation of contrast agent in patients and its potential adverse reactions. TSE MVXD DWI based IVIM, a considerable alternative, was performed on 32 NPC patients with significant tumors to evaluate the relation with CE-T1WI. As the result showed, the TSE MVXD DWI based IVIM had significantly relation with CE T1WI. It is potentially a promising and valuable non-invasive method in the detection of NPC.
Can we predict motion artifacts in clinical MRI before the scan completes?
Authors: Hoffmann Malte , Singh Nalini , Dalca Adrian , Fischl Bruce , Frost Robert
Published: August 2024

Subject motion remains the major source of artifacts in magnetic resonance imaging (MRI). Motion correction approaches have been successfully applied in research, but clinical MRI typically involves repeating corrupted acquisitions. To alleviate this inefficiency, we propose a deep-learning strategy for training networks that predict a quality rating from the first few shots of accelerated multi-shot multi-slice acquisitions, scans frequently used for neuroradiological screening. We demonstrate accurate prediction of the scan outcome from partial acquisitions, assuming no further motion. This technology has the potential to inform the operator's decision on aborting corrupted scans early instead of waiting until the acquisition completes.
Towards Integrating DL Reconstruction and Diagnosis: Meniscal Anomaly Detection Shows Similar Performance on Reconstructed and Baseline MRI
Authors: Konovalova Natalia , Tolpadi Aniket , Liu Felix , Bhattacharjee Rupsa , Gassert Felix , Giesler Paula , Luitjens Johanna , Majumdar Sharmila , Pedoia Valentina
Published: August 2024

Meniscal lesions are a common knee pathology, but pathology detection from MRI is usually evaluated on full-length acquisitions. We trained UNet and KIKI I-Net reconstruction algorithms with several loss function configurations, showing k-space losses are not required to obtain robust reconstructions. We trained and evaluated Faster R-CNN to detect meniscal anomalies, showing similar performance on R=8 reconstructions and fully-sampled images, demonstrating its utility as an assessment tool for reconstruction performance and indicating reconstructed images are viable for downstream clinical postprocessing tasks.
Contrast-agnostic segmentation of the spinal cord using deep learning
Authors: Bédard Sandrine , El Baz Adrian , Macar Uzay , Cohen-Adad Julien
Published: August 2024

Several methods to segment the spinal cord have emerged over the past decade. However, they are dependent on the image contrast, resulting in differences of spinal cord cross-sectional area (CSA), a relevant biomarker in neurodegenerative diseases. We propose a novel method using deep learning that produces the same segmentation regardless of the MRI contrast. Moreover, the segmentation is “soft” (non-binary) and can therefore encode partial volume information. CSA computed with this contrast-agnostic soft segmentation method has lower intra- and inter-subject variability, making it particularly relevant for multi-center studies.
Progressive cortical cerebrovascular reactivity reduction occurs in Parkinson's disease: a longitudinal study
Authors: Li Hongwei , Wang Jian , Jia Jia , Shao Xiali , Wang He , Jin Lirong
Published: August 2024

Increasing evidence showed subtle cerebrovascular reactivity (CVR) impairment in neurodegenerative disease. In the longitudinal study herein, we aimed to investigate regional CVR changes in the patients with Parkinson’s disease (PD) at baseline and 2 years follow up, and CVR was derived from resting state fmri scans. PD patients showed significantly reduced CVR in the left inferior occipital gyrus and right superior temporal cortex. In addition, the reduction of CVR may associate with executive function deficits. Our results also showed that there was a tendency for functional connectivity to be weakened from posterior to anterior with the progression of the disease.
Robustness of Autoencoder-based Classifier for fMRI-based Optimization of Single-sided Deep Brain Stimulation
Authors: Ajala Afis , Qiu Jianwei , Karigiannis John , Santyr Brendan , Germann Jurgen , Boutet Alexandre , Marinelli Luca , Bhushan Chitresh , Madhavan Radhika , Yeo Desmond , Lozano Andres
Published: August 2024

Successful treatment of Parkinson’s disease using deep brain stimulation (DBS) of the sub-thalamic nucleus (STN) requires an optimal set of DBS parameters that involves time-consuming programming sessions (~1 year) by the current standard-of-care optimization protocol. Functional magnetic resonance imaging (fMRI) and deep learning with autoencoder-based feature extraction from DBS-fMRI responses have provided a way to rapidly optimize the DBS parameters. In this work, we examine the robustness of the unsupervised autoencoder-based feature extraction method to changes in the activation patterns of the DBS-fMRI responses, which may be caused by patient motion, difference in stimulation side and disease condition.
Optimization of structural connectomes and scaled patterns of structural-functional decoupling in Parkinson’s disease
Authors: Shang Song'an , Dou Weiqiang , Jing Ye
Published: August 2024

Parkinson’s disease (PD) is manifested with disrupted topology of structural connection network (SCN) and functional connection network (FCN). However, SCN and its interactions with FCN remain to be further investigated. This multimodality study attempted to precisely characterize the SCN using diffusion kurtosis imaging (DKI) and further identify the neuropathological pattern of SCN-FCN decoupling. Our study verified the optimization of SCN by applying DKI metrics and its implications for the clinical diagnosis of PD. Moreover, SCN-FCN decoupling is consequent from mismatched disruptions of the SCN and FCN, identifying pathophysiological neuroimaging features for disturbed neural circuits in PD.
Retrospective analysis of Hyperpolarized 129Xe MRI Gas Exchange Images in Healthy and Post-COVID-19 Individuals acquired at Three Sites
Authors: Niedbalski Peter , Mummy David , Dai Haoran , Bechtel Aryil , Schmidt Alexandra , Frizzell Bradie , Kabir Sakib , Leipsic Jonathon , Leung Janice , Driehuys Bastiaan , Que Loretta , Castro Mario , Sin Don , Eddy Rachel
Published: August 2024

Gas exchange hyperpolarized 129Xe MRI (Xe-MRI) is increasingly being considered as an outcome measure in multi-site clinical trials, but there is limited evidence of between-site comparability. In this study, we analyzed 121 gas exchange Xe-MRI images in healthy and post-acute COVID-19 participants independently acquired at three sites. In healthy volunteers, quantitative Xe-MRI measures are indistinguishable across sites. In post-acute COVID-19, cross-site differences in Xe-MRI measures are evident but appear to be driven by differences in patient population. Moreover, Xe-MRI measures across sites correlate strongly with pulmonary function testing. These results support the feasibility of multi-site trials using gas exchange Xe-MRI.
UTE-MRI with Single- and Dual-Echo Methods vs. CT: Differentiation Capability of Non- or Minimally Invasive Adenocarcinomas from Other Cancers
Authors: Ohno Yoshiharu , Yui Masao , Yamamoto Kaori , Ikedo Masato , Oshima Yuka , Hamabuchi Nayu , Hanamatsu Satomu , Nagata Hiroyuki , Ueda Takahiro , Ikeda Hirotaka , Takenaka Daisuke , Yoshikawa Takeshi , Iwase Akiyoshi , Ozawa Yoshiyuki , Toyama Hiroshi
Published: August 2024

We hypothesized that pulmonary MRIs with UTE using single- or dual-echo techniques may be equal to or more useful than standard-dose thin-section CT for evaluating solid portion size and C/T ratio. The purpose of this study was thus to compare capabilities of pulmonary MRIs with UTE using single- and dual-echo techniques (UTE-MRISingle and UTE-MRIDual) and thin-section CT for quantitative differentiation of non- and minimally invasive adenocarcinomas from other lung cancers.
Comparison of Capability for Therapeutic Outcome Prediction among CEST, DWI and PET/CT in Non-Small Cell Lung Cancer Conservative Therapy
Authors: Ohno Yoshiharu , Yui Masao , Yamamoto Kaori , Yoshikawa Takeshi , Takenaka Daisuke , Ikedo Masato , Iwase Akiyoshi , Oshima Yuka , Hamabuchi Nayu , Hanamatsu Satomu , Nagata Hiroyuki , Ueda Takahiro , Ikeda Hirotaka , Ozawa Yoshiyuki , Toyama Hiroshi
Published: August 2024

We hypothesize that CEST imaging has a potential for therapeutic outcome prediction in NSCLC patients treated with chemoradiotherapy and may play as one of the predictors in this setting. The purpose of this study was to compare the capability for therapeutic outcome prediction among CEST imaging, DWI and FDG-PET/CT in NSCLC patients with conservative therapy.
Cerebrospinal fluid pathways are perturbed in aging and prodromal Alzheimer’s disease
Authors: Kylkilahti Tekla , Wictor Max , Berron David , Töger Johannes , Bloch Karin Markenroth , Mattson-Carlgren Niklas , Hansson Oskar , Lundgaard Iben
Published: August 2024

Cerebrospinal fluid (CSF) circulation through the parenchyma by the glymphatic system has been suggested to play a role in the clearance of metabolic waste from the brain, including Amyloid β. In this 7T MRI study of CSF flow in the cerebral aqueduct, we find that ageing, cognitive status and amyloid status influence CSF dynamics and morphology of the aqueduct. These changes appear to precede major cognitive changes in Alzheimer’s disease. Disruption of flow dynamics and anatomy of CSF flow pathways may reflect dysfunctional CSF circulation in downstream compartments of the glymphatic system, and contribute to amyloid accumulation in the brain.
Deep Learning-Based Automatic Segmentation of Arterial Plaques in MR Vessel Wall Images
Authors: Yang Long , Yang Xiong , Gong Zhenhuan , Mao Yufei , Cheng Guanxun , Wu Ke , Li Cheng , Li Ye , Liang Dong , Liu Xin , Zheng Hairong , Hu Zhanli , Zhang Na
Published: August 2024

Manual segmentation of atherosclerotic plaque for quantitative assessment is a time-consuming process. In this study, a convolutional neural network based automatic segmentation method named Vessel-Segnet was proposed for quantitative evaluation of lumen, vessel wall and plaque based on MR vessel wall images. The proposed method achieved the best segmentation performance with the highest dice similarity coefficient and the lowest average surface distance among six models. In terms of morphological quantitative evaluation, the proposed method achieved excellent agreement with manual method. Overall, the proposed method can quickly and accurately realize the segmentation of lumen, vessel wall and plaque for quantitative evaluation.
Characterization of white matter microstructural abnormalities in cerebral small vessel disease with cerebral microbleeds
Authors: Sui Chaofan , Wen Hongwei , Wang Shengpei , Feng Mengmeng , Xin Haotian , Gao Yian , Li Jing , Guo Lingfei , Liang Changhu
Published: August 2024

To characterize white matter (WM) microstructural abnormalities in patients with cerebral small vessel disease (CSVD) coexisting with cerebral microbleeds (CMBs) and to further investigate the exact mechanism by which CMBs influence cognitive decline in patients with CSVD at the group and individual levels. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 49 CSVD patients with CMBs (CSVD-c), 114 CSVD patients without CMBs (CSVD-n), and 83 controls were analyzed using DTI-derived tract-based spatial statistics to detect WM diffusion changes among groups.
Pretherapeutic specific gray matter volume for predicting MRgFUS thalamotomy-mediated tremor response in Parkinson's disease
Authors: Wang Xiaoyu , Lou Xin
Published: August 2024

This is the first study to assess magnetic resonance-guided focused ultrasound (MRgFUS) VIM thalamotomy on gray matter (GM) volume in tremor-dominant Parkinson’s disease (PD). MRgFUS has good efficacy and safety in the treatment of PD. We used three methods to extract specific GM volumes of nine PD patients before and after treatment for calculating their difference and correlation analysis. We found that the specific GM regions may predict tremor responses in PD after thalamotomy, and the results help to better understand the distant effect of MRgFUS thalamotomy and the involvement of GM in tremor control in PD.
Altered neurochemical profiles and volume loss in the cerebellum and brainstem as biomarkers in spinocerebellar ataxia type 1
Authors: Kapteijns Kirsten , van Prooije Teije , van Asten Jack , Verbeek Marcel , van de Warrenburg Bart , Scheenen Tom
Published: August 2024

Spinocerebellar ataxia type 1 is a rare, progressive movement disorder primarily affecting the cerebellum and closely connected brain regions. We assessed the dynamics of MR biomarkers and their utility as progression and/or predictive biomarkers in SCA1. SCA1 patients showed an altered neurochemical profile when compared to controls. Additionally, we measured a lower volume of affected regions in patients, clearly distinguishing them from controls. Altered volume correlated strongest with clinical scores, confirming the potential to use MR-markers to monitor SCA1 progression. Furthermore, MRS markers correlated with consequent change in volumetric measures, showing preliminary evidence for their predictive value in SCA1.
Whole-Tumour Histogram Analysis of Multiple Diffusion Metrics for Meningiomas Grade
Authors: She Dejun , Huang Hao , Zhao Xiance , Cao Dairong
Published: August 2024

An accurate assessment of the World Health Organization grade is vital in meningiomas. While many studies have investigated the usefulness of conventional DWI and DTI for noninvasive grading intracranial meningiomas, there are neither any studies comparing three advanced diffusion model including DKI, MAP and NODDI with DTI for predicting meningioma grade. Thus, it is vital to evaluate whether these advanced models derived from diffusion spectrum imaging can also be beneficial in grading meningiomas. Our results suggested that whole tumour histogram analyses of the diffusion metrics from multiple diffusion models are promising methods in grading meningiomas.
Magnetization Transfer Imaging using non-balanced SSFP at Ultra-Low Field
Authors: Balaji Sharada , Dvorak Adam , Padormo Francesco , Teixeira Rui Pedro , Poorman Megan , MacKay Alex , Wood Tobias , Williams Steven , Deoni Sean , Kolind Shannon , Ljungberg Emil
Published: August 2024

We have demonstrated a method for introducing Magnetization Transfer (MT) weighting in a non-balanced SSFP sequence (PSIF) at 64mT by changing the total power of the on-resonance RF excitation pulse. The presence of the MT effect was validated through simulations, experiments in phantoms of water, cream, and hair conditioner, as well as in-vivo. Changes to the signal amplitude in the conditioner from the flip angle and pulse width of the RF pulse illustrated the presence of MT saturation. An example protocol with MT weighting was applied in-vivo to generate magnetisation transfer ratio maps.
Myocardial T1 Mapping Using Single-Shot Inversion-Recovery Radial FLASH: Comparison of Subspace and Nonlinear Model-Based Reconstruction
Authors: Schilling Martin , Blumenthal Moritz , Wang Xiaoqing , Uecker Martin
Published: August 2024

Linear subspace-based models are a powerful method for reconstruction in quantitative magnetic resonance imaging (qMRI). Compared to nonlinear model-based reconstructions, they are computationally more efficient and avoid partial volume effects. Both methods have not yet been compared with respect to myocardial T1 mapping using single-shot inversion-recovery radial FLASH. This work quantitatively compares the two methods for different regularization parameters. Reconstruction quality and T1 maps of both methods are comparable.
Quantitative Parameter Mapping in the Abdomen at 7T using Radial QTI Encoding
Authors: Schulte Rolf , Cencini Matteo , Lancione Marta , Pirkl Carolin , Menzel Marion , Cecchi Paolo , Aringhieri Giacomo , Radu Constantin , Tosetti Michela
Published: August 2024

Quantitative MRI offers diagnostic insights into tissue properties and enables the characterisation of diseases, while reducing variability between operators, sites and vendors. A 2D and a 3D radial sequence using Quantitative Transient State Imaging (QTI) were implemented and optimised to map T1, T2 and Proton Density in the abdomen at 7T. Resulting in-vivo multi-parametric maps were of motivating quality, while validation in the Eurospin TO5 phantom showed good agreement with T1 and T2 Gold standard measurements.