bluuebunny/crossref_metadata_2025 huggingface dataset:
Highly Accelerated Cartesian Real-Time Cine CMR Using Subject-Specific Zero-Shot Deep Learning Reconstruction
Authors: Demirel Omer , Zhang Chi , Yaman Burhaneddin , Gulle Merve , Leiner Tim , Kellman Peter , Akçakaya Mehmet
Published: August 2024

Real-time cine CMR is an ECG-free free-breathing alternative for functionally assessing the heart. To achieve sufficient spatio-temporal resolutions, these require rapid imaging, e.g. compressed sensing (CS) with radial trajectories. However, at high accelerations, CS may suffer from residual aliasing and temporal blurring. Recently, deep learning (DL) reconstruction has gained immense interest for fast MRI. Yet, for free-breathing real-time cine, where subjects have different breathing and cardiac motion patterns, database learning of spatiotemporal correlations has been difficult. Here, we propose a physics-guided DL reconstruction trained in a subject-specific manner. Proposed method improves image quality compared to database-trained DL and conventional methods.
Deep kernel method for free-breathing and ungated cardiac MRI reconstruction
Authors: Zou Qing , Dzelebdzic Sanja , Hussain Tarique
Published: August 2024

We introduce a deep kernel model for the recovery of free-breathing and ungated cardiac MRI from highly undersampled measurements. The proposed scheme uses the cascade of two deep convolutional neural networks for the kernel representation of images. The parameters of the two CNNs in the proposed method are learned from the undersampled measurements directly in this work and hence the framework is unsupervised. The main benefits of the proposed scheme are (a) the elimination of the empirical choice of the feature map and kernel function in the kernel method, and (b) the unsupervised nature of the proposed framework.
Self-Gated Cardiac Phase-Contrast Balanced SSFP at 0.55T
Authors: McGrath Charles , Bieri Oliver , Kozerke Sebastian , Bauman Grzegorz
Published: August 2024

Free-running radial phase-contrast balanced steady-state free precession (PC-bSSFP) imaging including slice-select gradient inversion and respiratory and cardiac self-gating enables robust through-plane flow quantification in the aorta with excellent image signal-to-noise ratio (SNR) and contrast on a low-cost low-field 0.55T scanner. Relative to phase-contrast spoiled gradient echo (PC-GRE), PC-bSSFP offers SNR improvements by a factor of about two. Keywords: Flow, Low-Field, Balanced SSFP, Phase-Contrast, Self-gated
Predictive Value of Diffusion Magnetic Resonance Imaging for the Postoperative Outcome of Cervical Spondylotic Myelopathy
Authors: Ni Ming , Wen Xiaoyi , Zhang Mengze , Jiang Chenyu , Li Yali , Zhang Xianchang , Lang Ning , Zhao Qiang , Zhao Yuqing , Chen Wen , Jiang Liang , Yuan Huishu
Published: August 2024

This study used multi-factorial linear quantile mixed-effects regression models to predict the outcome of cervical spondylotic myelopathy (CSM) patients one year after surgery based on MRI. Six models were constructed using the linear quantile mixed model and linear mixed-effects regression model based on the diffusion magnetic resonance imaging (dMRI) data, all the imaging data (dMRI & Conventional MRI), and all the registered data (dMRI & Conventional MRI & clinical data). We found that fractional anisotropy (FA) values quantified by preoperative dMRI could predict the surgical outcome of CSM and showed a significant positive correlation with the postoperative outcome.
Automated cervical spinal cord atrophy detection from conventional 3D T1w brain MRI
Authors: Disselhorst Jonathan , Andělová Michaela , Ravano Veronica , Piredda Gian Franco , Kober Tobias , Vaněčková Manuela , Maréchal Bénédicte
Published: August 2024

Detecting atrophy in the spinal cord (SC) is highly relevant in multiple sclerosis (MS) and other neuroinflammatory and neurodegenerative diseases. The most used method is measuring mean upper cervical cord area (MUCCA) from SC images. MRI of SC is time consuming and not always available. We recently developed a method to measure MUCCA directly from conventional T1w brain images. This work compares MUCCA estimates derived from MPRAGE and MP2RAGE sequences, determine reference ranges from 98 healthy subjects and show their value to detect atrophy in patients with progressive MS and neuromyelitis optica. We observe very high agreement between methods.
Region-specific characteristics of brain oxygen extraction fraction: relationships to aging and white matter hyperintensities
Authors: Song Jie , Shi Wen , Hazel Kaisha , Pottanat George , Jones Ebony , Xu Cuimei , Lin Doris , Yasar Sevil , Albert Marilyn , Lu Hanzhang , Jiang Dengrong
Published: August 2024

Aging is a multifaceted process involving both structural and metabolic alterations. Cerebral oxygen-extraction-fraction (OEF) is an important physiological parameter indexing the brain’s oxygen metabolism. In this work, we assessed regional OEF in young and older adults, and investigated its associations with aging and white-matter-hyperintensities. We observed significant age-related increase in cortical OEF but not in subcortical OEF, suggesting that aging may have different effects on tissue metabolism in cortical and subcortical regions. Furthermore, we found a significant inverse correlation of WMH with OEF in internal-cerebral-veins, implying that OEF of subcortical structures may be useful in predicting WMH.
Shared and differed functional connectivity abnormalities for default mode network in mild cognitive impairment and Alzheimer’s disease
Authors: Wang Yaxuan , Long Fenghua , Gong Qiyong , Lui Su , Li Fei
Published: August 2024

We performed a meta-analysis to investigate shared and different alterations of resting-state functional connectivity (rsFC) for default mode network (DMN) in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). We found both patients with MCI and AD showed hypoconnectivity within DMN in bilateral medial prefrontal cortex (mPFC)/anterior cingulate cortex (ACC) and precuneus/posterior cingulate gyrus (PCC), indicating possibly shared neuropathologic mechanism underlying common cognitive dysfunction. Moreover, we identified distinct alterations of rsFC for DMN in some brain regions, which suggested potential imaging markers to distinguish the two diseases.
Multicompartment Imaging of the Brain Using a Comprehensive MR Imaging Protocol
Authors: Lo James , Chang Eric , Du Jiang , Bydder Graeme , Ma Yajun
Published: August 2024

In this study, we developed a comprehensive MR imaging protocol to quantify all the major components of the brain. This protocol includes four different kinds of sequences: a magnetization transfer prepared Cones (MT-Cones) for two-pool MT modeling, a short-TR adiabatic inversion-recovery prepared Cones (STAIR-Cones) for myelin water imaging, a proton-density weighted Cones (PDw-Cones) for total water imaging, and a highly T2 weighted Cones (T2w-Cones) for extracellular water imaging. Using a combination of these techniques, we successfully quantified the proton fractions of brain macromolecules, myelin water, intracellular water, and extracellular water components in three healthy volunteers with a 3T clinical scanner.
Are fMRI findings on emotional aging affected by cerebrovascular aging?
Authors: Donaldson Loretta , Joshi Parimal , Kartchner Lincoln , Akar Sara , Liu Peiying
Published: August 2024

Age-related changes in emotional circuitry have been studied using BOLD fMRI and revealed age-related increases in the activation of the prefrontal cortex and inconsistent findings in the amygdala. Previous emotional aging studies did not account for vascular aging which causes a reduction in cerebrovascular reactivity (CVR). Using picture viewing task fMRI and gas inhalation MRI, the fMRI signals are calibrated by the vascular measures to improve the inference of neural activity. After accounting for vascular changes, age-invariant activity was seen in the amygdala, and increased age-related activation of prefrontal regions was observed compared to activation before vascular correction.
Simulated and experimental approaches to perfusion cooling in Sim4Life: verification and applications to RF heating of implants
Authors: Louka Amgad , Chronik Blaine , Handler William
Published: August 2024

Perfusion cooling of implants is an emergent field that has the potential to greatly improve patient access to MRI for those living with implants that previously failed the radiofrequency heating test (ASTM F2182). Many implants fail by a small margin, meaning they would likely be safe inside the body when perfusion is considered. Here, we present initial steps for the experimental verification of perfusion simulations in Sim4Life, which showed reasonable agreement and provided some insight on future experimental perfusion platforms. From there, a perfusion cooling factor can be quantified for use during regulatory approval of these implants.
Surgical modification of deep brain stimulation lead trajectories reduces RF heating during 3 T MRI: From phantoms to implementation in patients
Authors: Vu Jasmine , Bhusal Bhumi , Rosenow Joshua , Golestanirad Laleh
Published: August 2024

MRI at 3 T is restricted for patients with deep brain stimulation (DBS) systems due to potential radiofrequency (RF) heating. Here, we present the first large-scale, systematic study to determine how trajectory-related parameters affect RF heating and quantify the extent of RF heating reduction. Introducing concentric loops close to the surgical burr hole substantially reduced RF heating. Increasing the number of loops correlated well with decreased heating. Recommendations based on the results from phantom experiments were easily adopted during the surgical procedure within 30 seconds. Subsequent replication of the trajectories based on postoperative computed tomography images confirmed low RF heating.
RF coil safety validation with a 3D SAR measurement setup
Authors: Zulkarnain Nur Izzati Huda , Ates Mert , Cole Grace , Sadeghi-Tarakameh Alireza , Jungst Steve , DelaBarre Lance , Adriany Gregor , Eryaman Yigitcan
Published: August 2024

We implemented a framework to validate the RF safety of MRI coils experimentally using a phantom in our RF safety lab which supports coil excitation using up to 16 individually-controlled power amplifiers. A 3D measurement setup and a dosimetric probe were used to map the spatial distribution of the specific absorption rate (SAR). To demonstrate the accuracy of the framework, we compared the simulated and measured 10 g averaged SAR of a rectangular loop element and an 8-channel transmit/receive head coil. We obtained quantitative agreements with 7.8% and 11.6% root-mean-squared error for the loop element and head coil respectively.
Tuning and validation of an image registration procedure for patient-specific SAR simulation
Authors: Montin Eros , Carluccio Giuseppe , Collins Christopher , Lattanzi Riccardo
Published: August 2024

In this article, we build an automatic pipeline for patient-specific assessment of SAR. Given a target MR image and an atlas comprising a reference image and a model, an MR-shaped model can be obtained by registering the AIM with the target MR and applying the resulting displacement fields to the corresponding ABM. The results of the analysis on simulated data showed that the proposed automatic pipeline was reliable and accurate both in terms of SAR distribution and the similarity of the patient-specific models.
Investigating the origin of negative BOLD responses using laminar CBF, CBV, T2 BOLD and CMRO2 fMRI in human visual cortex at 7T
Authors: Shao Xingfeng , Kim Jung Hwan , Ress David , Zhao Chenyang , Shou Qinyang , Jann Kay , Wang Danny JJ
Published: August 2024

We proposed a 7T laminar concurrent ASL, VASO and BOLD fMRI sequence to obtain quantitative CBF, CBV, T2-BOLD and CMRO2 measurements with high resolution and specificity to detect layer-dependent vascular and metabolic activities. Ipsilateral visual stimuli (eccentricity of 4°–6°) induced ring-shaped BOLD and CBF signal increase on cortical surface corresponding to the pattern of visual stimulus while decreased BOLD/CBF signals can be seen in adjacent fovea regions. In negative BOLD response (NBR) regions, moderate decrease in T2-BOLD and CBV signals and strong CBF and CMRO2 decreases especially in deep cortical layers were observed, suggesting suppressed neuronal activities in NBR regions.
Non-Contrast MRI of Micro-Vascularity of the Feet and Toes
Authors: Bae Won , Malis Vadim , Yamamoto Asako , Kassai Yoshimori , Isogai Jun , Nakamura Katsumi , Lane John , Miyazaki Mitsue
Published: August 2024

Non-contrast MR perfusion techniques were developed to assess micro-vascularity of the foot in humans. Using flow-out spin labeling with 3D SSFSE acquisition at multiple Tis, we obtained perfusion signal into distal feet and toes. Signal vs. TI data was fit to determine perfusion metrics including peak height (PH), apparent blood volume (aBV) and apparent blood flow (aBF). Compared to 1-tag, when 4-tag pulses were used PH, aBV, and aBF were significantly greater, suggesting increased signal afforded by the 4-tag pulses. This will be useful for subjects with low blood flow, such as those with peripheral artery disease.
Application of fast, oblique 2D-UTE to musculoskeletal imaging with a library of predistorted slice select gradient waveforms
Authors: Harkins Kevin , Chadwick Nicholson , Does Mark
Published: August 2024

The adoption of 2D UTE for general musculoskeletal imaging has been slowed by technical limitations—especially gradient errors that cause slice profile distortions. In this work, a library of predistorted gradient waveforms were used to interpolate slice select gradient waveforms for oblique oriented half-pulse 2D UTE. Example multi-echo and multi-slice acquired 2D UTE images are shown in the tibia, ankle, & knee. Positive contrast in collagen rich tissues like bone and tendon could provide a new source of information to potentially diagnose MSK injuries.
Volume isotropic 3D bone Imaging with broadband IR-prepared FLORET UTE and Fibonacci interleaved trajectory ordering
Authors: Yoneyama Masami , Azuma Minako , Enzaki Masahiro , Krishnamoorthy Guruprasad , Robison Ryan , Ball Iain , Hamano Hiroshi , Van Cauteren Marc
Published: August 2024

MR bone imaging has gained more attention for detecting and assessing bone pathology. In this study, we proposed a new technique consisting of broadband inversion recovery preparation with FLORET UTE with Fibonacci interleaved trajectory ordering (FLORET BoneVIEW) to obtain 3D isotropic bone images within a clinically feasible scan time. FLORET BoneVIEW has great potential to help a more accurate assessment of bone pathology as an alternative to CT bone imaging.
Deep-learning-based scoring for inflammatory lesions using SPARCC system
Authors: Lin Yingying , Ho Yin Chung , Chan Shirley Chui Wai , Lee Kam Ho , Cao Peng
Published: August 2024

Our work proposed a work pipeline to automatic score the inflammatory lesion based on the SPARCC scoring system. This pipeline included the reference vessel intensity set-up, template-based registration, and lesion detection with scoring. With this pipeline, a time-saving and objective scoring method based on SPARCC scoring system could be achieved and widely applied to AS patient management. Our result showed reasonable performance for score-2 and score-3 lesions demonstrating the deep learning initial capacity of performing the SPARCC scoring.
Distinct dACC Glutamate Modulation during Inhibitory Motor Control Driven by Negative Emotional Stimuli in Trauma-Exposed Youth using 1H fMRS
Authors: France John , Khatib Dalal , Valbrun Sharuel , Davie William , Eichstaedt Jillian , Diwadkar Vaibhav , Jovanovic Tanja , Stanley Jeffrey
Published: August 2024

We investigated changes in glutamate in the dACC in children exposed to childhood trauma during motor control function with and without inhibition as well as with and without stimuli depicting negative affect using 1H fMRS. Independent of motor control with/without inhibition, trauma-exposed children exhibited a significant reduction in dACC glutamate when stimuli of negative affect were present, relative to stimuli without affect. These results provide greater insight on the neurochemistry supporting the influence of negative emotional context on motor control and highlight potential novel biomarkers for risk and resilience to posttraumatic stress.
A common brain network underlying successful neuromodulatory treatment of Obsessive-Compulsive Disorder
Authors: Germann Jurgen , Elias Gavin , Wong Emily , Yamamoto Kazuaki , Vetkas Artur , Gouveia Flavia , Loh Aaron , Boutet Alexandre , Lozano Andres
Published: August 2024

Obsessive-compulsive disorder (OCD) is a debilitating condition, with up to 20% of patients being refractory to medical treatment. For these severe cases, neuromodulatory techniques targeting distinct brain areas have been successful. In this work, we used normative functional connectomics to identify the brain network underlying symptom improvement in OCD. A pan-modality efficacy map identified cortical and subcortical areas as key regions, and this specific network could be used to successfully predict clinical improvement. These results suggest that symptom reduction following neuromodulation involves the engagement of a common functional network that could be investigated as a biomarker of treatment success.
ACC Connectivity Changes during ALIC Deep Brain Stimulation for Obsessive Compulsive Disorder
Authors: Bohara Sushil , Slepneva Natalya , Norbu Tenzin , Lee Moses , Morrison Melanie
Published: August 2024

Chronic deep brain stimulation (DBS) of the anterior limb of the internal capsule (ALIC) is an emergent therapy for severe cases of obsessive-compulsive disorder (OCD), however patient response is variable with only 50-60% of patients classified as responders. Toward optimizing therapy for the individual patient and improving overall treatment efficacy, here we used fMRI during ALIC stimulation to evaluate changes in OCD network functional connectivity. In 5 patients, we found that DBS, when in a therapeutic configuration for the patient, may be reducing abnormal hyperconnectivity to improve symptoms, while nontherapeutic configurations may be disrupting fronto-posterior connections causing unwanted symptoms.
7T MRI and PET in Tourette Syndrome: Correlations between subcortical dopamine receptor availability and susceptibility
Authors: Gkotsoulias Dimitrios , Rullmann Michael , Schmitt Simon , Bujanow Anna , Zientek Franziska , Messerschmidt Konstantin , Müller-Vahl Kirsten , Barthel Henryk , Möller Harald
Published: August 2024

We present interim results of the first combined 7T MRI and [11C]-SCH23390 PET study in Gilles de la Tourette syndrome (GTS). Dopamine D1-receptor availability is assessed in combination with Quantitative Susceptibility Mapping (QSM). Our results indicate reduced iron concentrations in subcortical grey matter of GTS patients compared to age- and sex-matched controls, accompanied by reduced D1-receptor binding potential in several regions. Correlations between local iron distribution and D1-receptor binding potential in basal ganglia support the hypothesis that iron homeostasis might play a significant role in dysregulations of the dopaminergic system that eventually lead to the characteristic symptomatology of GTS.
Systemic inflammation causes cerebral hypoperfusion, reductions in brain susceptibility and hippocampal hypoxia: a 9.4T MRI animal study
Authors: Shafqat Qandeel , Wu Ying , Ohaezukosi Uche , Makarowski Ty , Sun Hongfu , Tariq Rehman , Dunn Jeff
Published: August 2024

Inflammation is a pathological characteristic of multiple sclerosis (MS). Individuals with MS are reported to experience reductions in cerebral blood flow (CBF) and brain hypoxia (low oxygenation). The cause of these phenomena is not well-known. We studied the possible association between inflammation and hypoxia in an inflammatory mouse model by quantifying CBF (arterial-spin labeling MRI) and magnetic susceptibility (quantitative susceptibility mapping), as well as measuring hippocampal oxygen using oxygen-sensitive probes. We found that inflammation is associated with reductions in CBF, brain susceptibility, and hippocampal oxygenation. This supports the idea that inflammation can induce brain hypoxia and disrupt cerebrovascular autoregulation.
Diffusion MRI as a marker of neuroinflammation following intracerebral haemorrhage
Authors: Thomas Josephine , Haroon Hamied , Pinteaux Emmanuel , Lawrence Catherine , Allan Stuart , Dickie Ben
Published: August 2024

Diffusion tensor imaging (DTI) and neurite orientation and density imaging (NODDI) is used to observe regional changes in brain microstructure following intracerebral haemorrhage (ICH) in rats. On day 7 following ICH, DTI and NODDI metrics were significantly altered in haemorrhaged sub-regions as well as healthy appearing overlying cortex, compared to contralateral tissue. Histological analysis suggest these changes are driven by altered cell density and populations, with notable regional changes in microglia/macrophages. In summary, DTI and NODDI parameters are altered in ICH and may reflect changes in the immune cell populations in both haemorrhaged and overlying normal-appearing cortex.
Sex chromosomes and sex hormones differentially mitigate radiation-induced neuroanatomic deficits in Ccl2 knockout mice.
Authors: Yeung Jonas , De Young Taylor , Spring Shoshana , Xiao Qi , Lerch Jason , Palmert Mark , Nieman Brian
Published: August 2024

Females tend to exhibit worse cognitive outcomes than males after pediatric cranial radiation therapy (CRT). Previous literature suggest that these sex differences may be driven by neuroinflammatory responses that involve CCL2. The objective of this study was to determine whether protection from Ccl2 knockout is mediated by sex hormones or sex chromosomes. We employ MRI on a CRT mouse model with mixed sex hormone and chromosome complements (i.e., four core genotypes model) to determine neuroanatomical changes. We found that both male chromosome and male sex hormones separately benefit regions of the brain in CCL2 deficient mice after CRT.
Association of thalamic neuroinflammation and the functional connectivity in a rat model of traumatic brain injury – a longitudinal study
Authors: Dvorakova Lenka , Salo Raimo , Stenroos Petteri , Paasonen Ekaterina , Jokivarsi Kimmo , Paasonen Jaakko , Gröhn Olli
Published: August 2024

Post traumatic brain injury (TBI) neuroinflammation has been linked to many long-term outcomes of TBI. To better understand the interrelationship of the neuroinflammation and changes of functional connectivity, we followed rats after TBI in a series of functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) experiments. We observed hypoconnectivity in the corticothalamic connections, which was laterally altered at the acute time point and correlated with the observed level of neuroinflammation in the lateroposterior thalamic nuclei. This sheds light on the potential role of focal post-traumatic neuroinflammation shaping large scale functional connectivity in the post-traumatic brain.
A Correlational Study of Changes in Behaviour and MRI Measures in the CNS in the EAE Mouse Model of Multiple Sclerosis
Authors: Muhammed Rania , Tariq Rehman , Ohaezukosi Uche , Shafqat Qandeel , Wu Ying , Dunn Jeff
Published: August 2024

Multiple sclerosis is an inflammatory disease of the central nervous system, with a posited hypoxia-inflammation cycle hypothesis. Hypoxia may increase disease severity in MS. We found R2* was increased (an MRI marker of hypoxia) in the cortex. We observed increased sickness and R2* in EAE mice compared to controls, but reduced CBF in both CFA-PTx and EAE. Inflammation is in both groups, while autoimmunity is only in EAE. Reduced CBF may relate to inflammation, whereas hypoxia may relate to autoimmune-mediated damage and increase disease severity.
Localization Regime of Diffusion (LoRD) in mouse and pig cortical gray matter and its sensitivity to soma size
Authors: Lee Hong-Hsi , Wang Nian , Fieremans Els , Huang Susie , Novikov Dmitry
Published: August 2024

It is non-trivial to decompose the diffusion MRI signal, as conventionally measured using relatively weak gradients, into contributions from multiple compartments and estimate the cell sizes. Instead, using strong diffusion gradients, a universal compartment-independent localization regime emerges, as they saturate all magnetization except that near cell membranes. The signal sensitivity to the membrane and its surface-to-volume ratio enables the soma size estimation without modeling multiple compartments. Here, we observed the unique functional form of localization regime and estimate the soma size in mouse and pig brains cortical gray matter on a Bruker CryoProbe system.
Quantifying human gray matter microstructure using NEXI and 300 mT/m gradients
Authors: Uhl Quentin , Pavan Tommaso , Molendowska Malwina , Jones Derek , Palombo Marco , Jelescu Ileana
Published: August 2024

For the first time, we report Neurite Exchange Imaging (NEXI) microstructure model parameters estimates in human cortex in vivo. We also investigate the performance of two extensions of this model, the addition of a dot compartment and a correction for wide pulses. Parameter estimates are consistent with previous findings in the rat cortex in vivo. Importantly, NEXI estimates displayed good scan-rescan reproducibility while retaining sensitivity to inter-subject differences. Future work will focus on improving the precision, in particular of the exchange time estimates, possibly leveraging multi-dimensional diffusion MRI acquisitions.
Measuring time-dependent diffusion on a high-performance head-only gradient system at 3T: influence and correction of gradient nonlinearity
Authors: Dai Erpeng , Zhu Ante , Yang Grant , Quah Kristin , Tan Ek , Fiveland Eric , Foo Thomas , McNab Jennifer
Published: August 2024

Oscillating gradient spin echo (OGSE) sequence is an effective approach to measure time-dependent diffusion processes at short diffusion times. High-performance, head-only gradient systems open new opportunities for using OGSE to study time-dependent diffusion with both high b-values and oscillating frequencies, such as diffusion kurtosis imaging (DKI). One source of error that can be more problematic for the head-only gradients is gradient nonlinearity (GNL). Here, we measure the time dependence of diffusion tensor imaging (DTI)/DKI in human brains with OGSE on a head-only MAGNUS gradient and investigate the influence of GNL on the time dependence measures of diffusivity/kurtosis.
Denoising 4D-Flow using Self-Supervised Deep Learning and its effect on test-rest reproducibility
Authors: Jolicoeur Brock , Rivera-Rivera Leonardo , Roberts Grant , Eisenmenger Laura , Johnson Kevin
Published: August 2024

Through a self-supervised deep learning denoising algorithm, more precise cerebrovascular measurements of flow, maximum fluid velocity, and vessel cross-sectional area were obtained from undersampled neurovascular 4D-Flow MRI data. This algorithm was applied to back-to-back scans to illustrate its effectiveness in reducing measurement variance.
Deep learning-based segmentations challenge established link between stroke volume and functional outcome after thrombectomy
Authors: Digernes Ingrid , Røvang Martin , Nome Terje , Nome Cecilie , Skattør Thor Håkon , Enriquez Brian , MacIntosh Bradley , Aamodt Anne Hege , Bjørnerud Atle
Published: August 2024

Using a standard 3D nnUNET model that was pretrained to segment WMH on FLAIR, we obtained good stroke lesion segmentation accuracy (median Dice = 0.80) when the model was re-trained to segment the stroke lesion on DWI in a smaller stroke sample (N = 82). Applying the segmentation model to DWIs from 307 thrombectomy patients, we found no association between pre-treatment lesion volume and functional outcome at 90 days after thrombectomy. Our results indicate that the established assumption of lesion size being a strong predictor of functional outcome should be investigated further for patients receiving mechanical thrombectomy.
A unified deep learning model for simultaneous cardiac cine MRI reconstruction, motion estimation and segmentation.
Authors: Qian Pengfang , Yang Junwei , Zhou Zijian , Hu Peng , Qi Haikun
Published: August 2024

Various deep learning methods have been proposed for cardiac cine MRI, including accelerated image reconstruction, cardiac motion estimation and segmentation, which are traditionally considered as separate tasks without exploiting the inter-task correlation. In this study, we propose a unified deep learning model to perform accelerated cine image reconstruction, motion estimation and segmentation simultaneously in an iterative framework, where correlations between tasks are exploited by compensating motion in reconstruction, semi-supervising segmentation using pseudo-labels generated by motion and improving motion estimation using intermediately reconstructed images. Experiment results show that the multi-task model outperformed single-task networks.
CVT Detection with Routine Brain MRI Sequences by Multi-Modal Multi-Task Deep Learning algorithm
Authors: Yang Xiaoxu , Yu Pengxin , Zhang Haoyue , Zhang Rongguo , Liu Yuehong , Jia Xiuqin , Sun Penghui , Liu Xin , Ji Xunming , Yang Qi , Zhang Chen
Published: August 2024

A deep learning algorithm for detecting cerebral venous thrombosis using routine brain MRI achieved higher patient-level sensitivity than radiologists and reduced the number of overlooked thrombosed segments. The proposed deep learning (DL) algorithm achieved area under the receiver operating characteristic curve of 0.96 for detecting patient with cerebral venous thrombosis. The sensitivity of DL algorithm was higher than that of radiologists and obtained high specificity on patient-level. Compared to radiologists, DL algorithm found more thrombosed segments, indicating greater sensitivity and a sufficient specificity at the segment-level.
Various parameters derived from mono-exponential DWI, IVIM, SEM, DKI and CTRW in breast cancer diagnosis and the prediction of prognostic factors
Authors: Qin Yanjin , Zhang Yunfei , Dai Yongming , Ai Tao
Published: August 2024

In the present study, we compared the potential of various diffusion parameters derived from five models in distinguishing breast lesions, including the mono-exponential model (Mono), intravoxel incoherent motion (IVIM) model, diffusion kurtosis imaging (DKI) model, stretched exponential model (SEM), and continuous-time random-walk (CTRW) mode. We found that diffusion-related parameters by the SEM and CTRW models are superior to ADC in discriminating breast lesions. Multiple diffusion parameters by all five diffusion models are related while the information provided is diverse.
Preoperative prediction of Ki-67 expression of hepatocellular carcinoma using T1 mapping on gadoxetic acid-enhanced MRI
Authors: Zhao Yue , Guan Xiuhong , Xu Yongzhou , Jiang Xinqing , Yang Ruimeng
Published: August 2024

The cell proliferation index, Ki-67 labeling index (LI) indicates the status of cell proliferation activity which corresponds with tumor biological behavior, treatment efficacy and prognosis. If the preoperative Ki-67 expression status in HCC can be accurately predicted noninvasively, it may provide important information for clinical decision-making. T1 mapping is useful for preoperative prediction of Ki-67 LI of HCC. The nomogram Combining T1 mapping on gadoxetic acid-enhanced MRI and clinical indicators has good predictive efficacy for preoperative prediction of Ki-67 LI, which can promote the individualized risk stratification and further treatment decision of HCC patients.
Detection rate of prostate cancer using mpMRI-Inbore targeted prostate biopsy, mpMRI-TRUS guided biopsy and TRUS guided biopsy
Authors: Mewar Sujeet , Sharma Sanjay , Dhamijia Ekta , Thulkar Sanjay , Gupta S. Datta , Panaiyadiyan Sridhar , Jagannathan Naranamangalam R. , Kumar Rajeev , Kumar Virendra
Published: August 2024

The present study demonstrated the comparison of detection rate of PCa between the three groups of patients recruited based on PSA > 4 ng/ml and abnormal DRE. The PCa detection rate of mpMRI-Inbore biopsy (Group I) was found 50 % while for mpMRI-TRUS guided biopsy (Group II) 26 %. The combined detection rate of techniques with and without mpMRI was also calculated and found 44 %, for mpMRI-Inbore biopsy and mpMRI-TRUS guided biopsy, while 34.5 %, in TRUS guided biopsy (Group III). Study shows that there is a significant advantage of mpMRI Inbore biopsy compared to TRUS guided prostate biopsy.
Value of multiple mathematical models of advanced zoomed DWI for the evaluation of tumor-stroma ratio in rectal cancer
Authors: Wan Lijuan , Zhang Hongmei , Zhu Yumeng , Jiang Yueluan , Yang Guang
Published: August 2024

Tumor-stroma ratio (TSR) can reflect the relationship between tumor cells and tumor microenvironment. Evaluation of the TSR timely and accurately is important because of its role in predicting prognosis and making individualized treatment plans. Diffusion parameters obtained from multiple mathematical models of DWI can reflect microscopic characteristics of tumors. Multi b-value DWI with the advanced zoomed DWI technology can provide a higher-spatial-resolution with less artifacts. This study aimed to investigate the value of zoomed multi b-value DWI for predicting TSR in rectal cancer. The results suggested that distributed diffusion coefficient (DDC) is a promising indicator to identify high TSR group.
Evaluating intra-voxel incoherent motion in the uterine cervix: healthy volunteer repeatability and therapy-induced changes in tumours
Authors: Datta Anubhav , McHugh Damien , Dubec Michael , Buckley David , Little Ross , Berks Michael , Cheung Susan , West Catharine , Choudhury Ananya , Hoskin Peter , O'Connor James
Published: August 2024

There is a need for robust imaging biomarkers which can be used to assess early tumour response to therapy. Intra-voxel incoherent motion (IVIM) can provide information about tumour microstructure and microvasculature, but requires technical and biological validation. This work evaluates IVIM repeatability in the uterine cervix of healthy volunteers, assesses the sensitivity of IVIM parameters to therapy in patients with uterine cervical cancer, and evaluates model suitability through a model comparison framework.
Quantitative assessment of the lumbar paraspinal muscle in patients with unilateral lumbar disc herniation by IDEAL-IQ MR sequence
Authors: Chen Junrong , Lan Jiujun , Li Ze , Fu Min , Yuan Xiaochun , Liang Huilou
Published: August 2024

The development, progression, treatment and rehabilitation of lumbar disc herniation (LDH) are strongly associated with morphology and structural characteristics of lumbar paraspinal muscle. The IDEAL-IQ MR sequence allows the direct quantification of lumbar paraspinal muscle properties including fat fraction (FF) and cross-sectional area (CSA). The side-to-side differences between quantitative properties of bilateral paraspinal muscles in patients with unilateral LDH remain unclear. Therefore, this study aimed to investigate the possible unilateral changes of the paraspinal muscles in patients with unilateral LDH. Our results found no difference in FF and CSA values of paraspinal muscles between the affected and unaffected sides.
Improvement of Experimental SNR in Mock Transcranial MRgFUS System with Strategic Design of Transfer Medium and Transducer Ground Plane at 3T
Authors: Lakshmanan Karthik , Brown Ryan , Carluccio Giuseppe , Collins Christopher
Published: August 2024

We show that novel modifications to a mock Transcranial MR-guided Focused Ultrasound (TMRgFUS) system show potential to greatly improve MR performance. By using a transfer medium with reduced electric permittivity combined with slots in the transducer array ground plane we measure a 2-3 fold increase in SNR across the middle of a head-phantom portion of a mock TMRgFUS system.
Free-breathing 3D Stack-of-Spiral Cardiac Quantitative Susceptibility Mapping for Noninvasive Measurement of Cardiac Chamber Oxygenation
Authors: Li Jiahao , Villar-Calle Pablo , Zhang Jinwei , Li Chao , Nguyen Thanh , Wang Yi , Kim Jiwon , Weinsaft Jonathan , Spincemaille Pascal
Published: August 2024

A free-breathing 3D stack-of-spiral data acquisition was developed for motion-free cardiac quantitative susceptibility mapping, to tackle the challenge where even a short breath-hold is difficult for patients to perform. ECG and respiratory bellow signal were recorded for retrospective motion binning. A 5D dataset incorporating additional cardiac and respiratory phase dimensions were reconstructed with joint spatiotemporal regularization to generate a motion-free cardiac QSM. In healthy volunteers, this method was compared with a motion-averaged reconstruction and with a separate breath-hold spiral cardiac QSM using Cartesian navigator QSM as reference. Equivalent right-to-left heart chamber differential blood oxygenation was observed among all method studied.
Multimodal neuroimaging of Col4A1-mutant mouse models of Gould Syndrome
Authors: Gao Xiao , Wang Xiaowei , Labelle-Dumais Cassandre , Gould Douglas , Chaumeil Myriam
Published: August 2024

Gould syndrome is a multisystem disorder whose manifestations are highly variable. Animal studies suggest that allelic heterogeneity and genetic context contribute to the clinical variability. Clinical manifestations associated with Gould syndrome include blood–brain barrier (BBB) leakage, microbleeds, and white matter lesions. Here, we use multimodal MRI at 14.1Tesla to characterize radiological findings observed in mouse models of Gould syndrome caused by mutations in Collagen type IV alpha 1 (Col4a1). We show that multimodal MRI can successfully differentiate between disease subtypes based on anatomical changes as well as prevalence, number, volume and type of brain lesions.
Cerebral Amyloid Angiopathy (CAA) is associated with gray matter R2 relaxation rate: An ex-vivo MRI and pathology study
Authors: Yasar Md Tahmid , Evia Arnold , Bennett David , Schneider Julie , Arfanakis Konstantinos
Published: August 2024

Cerebral amyloid angiopathy (CAA) is characterized by accumulation of amyloid-β protein in the walls of cortical and leptomeningeal small vessels. CAA is common in older adults and is associated with intracerebral hemorrhage, microbleeds, cognitive decline and dementia. The present study in a large number of community-based older adults (N=802) combined ex-vivo MRI and detailed neuropathology and showed for the first time that CAA is associated with higher transverse relaxation rate, R2, in gray matter, independent of other neuropathologies and demographics. The regions that showed this association included cortical regions in the temporal and frontal lobes as well as subcortical structures.
Towards a probabilistic structural atlas of brainstem nuclei in elderly humans using in-vivo 7 Tesla multi-contrast MRI
Authors: Koley Subhranil , Singh Kavita , Garcia-Gomar Maria G. , Bianciardi Marta
Published: August 2024

Brainstem nuclei are involved in several vital functions; impairment in their structure and function is manifested in several clinical conditions of elderly humans, including sleep/arousal/movement/vestibular/anxiety disorders, chronic pain and altered autonomic functions. Brainstem evaluation in health and disease is currently limited by the difficulty of localizing these regions in conventional MRI. We developed an in-vivo probabilistic atlas of 31 brainstem nuclei in elderly humans by the use of multi-contrast 7 Tesla MRI in 15 elderly subjects and of an existing brainstem nuclei atlas in younger adults. This atlas can be applied to conventional MRI and aid brainstem investigation in aging.
The ensemble of optimized Deep Learning Neural Networks improves the estimate of the Choroid Plexus Volume: application to Multiple Sclerosis
Authors: Visani Valentina , Natale Valerio , Colombi Annalisa , Tamanti Agnese , Bertoldo Alessandra , Marjin Corina , Pizzini Francesca , Calabrese Massimiliano , Castellaro Marco
Published: August 2024

The Choroid Plexus (ChP) is a brain vascular tissue involved in regulatory processes. ChP Volume (ChPV) modifications are related to neurodegenerative disorders, consequently, it was suggested the use of ChPV as biomarker. This work proposes a method for the automatic segmentation of ChP based on Deep-Learning Neural-Networks (DNNs) hyperparameters optimization. Ninety-Six hyperparameters and architectures combinations were trained on T1-w MRI in MONAI, first selection was made on bias and variance and best DNNs were ensembled by major voting. Ensemble model outperforms single DNNs and freely available software (FreeSurfer, Gaussian Mixture Model), highlighting the ensembles DNNs exploitability to automatically estimate ChPV.
Automated Brain Tumour Segmentation in Glioblastoma: Can similar performance be achieved using a shorter imaging protocol?
Authors: Passarinho Catarina , Lally Oscar , Figueiredo Patrícia , Nunes Rita
Published: August 2024

The same deep learning model was trained for automated segmentation of glioblastoma tumour regions using either four or two MRI modalities. The performance of the model trained with only two images was found to be comparable to that of the longer protocol, suggesting that the excluded images and the consequent longer training time did not contribute significantly to the accuracy of the model. These findings strongly imply that this training approach may be beneficial for clinical applications, as it would result in reduced costs due to shorter scanner times, lower computational requirements and increased patient throughput, without compromising segmentation accuracy.
Attention mechanisms for sharing low-rank, image and k-space information during MR image reconstruction
Authors: Xu Siying , Hammernik Kerstin , Krumm Patrick , Gatidis Sergios , Küstner Thomas
Published: August 2024

Cardiac CINE MR imaging requires long acquisitions under multiple breath-holds. With the development of deep learning-based reconstruction methods, the acceleration rate and reconstructed image quality have been increased. However, existing methods face several shortcomings, such as limited information-sharing across domains and generalizability which may restrict their clinical adoption. To address these issues, we propose A-LIKNet which incorporates attention mechanisms and maximizes information sharing between low-rank, image, and k-space in an interleaved architecture. Results indicate that the proposed A-LIKNet outperforms other methods for up to 24x accelerated acquisitions within a single breath-hold.
Real-time deep learning non-Cartesian image reconstruction using a causal variational network
Authors: Kumar Prakash , Nayak Krishna
Published: August 2024

Real-time MRI captures movements and dynamic processes in human body without reliance on any repetition or synchronization. Many applications require low-latency (typically <200ms) for guidance of interventions or closed-loop feedback. Standard constrained optimization methods are too slow to be implemented “online”. We demonstrate a non-Cartesian deep learning image reconstruction method based on the end-to-end variational network. Training data are created using traditional high latency compressed sensing reconstruction as the reference, with the goal of achieving similar results with low latency. We demonstrate reconstruction latencies of 95ms per frame, with nRMSE of 0.045 and SSIM of 0.95.
Deep-learning-based transformation of magnitude images to synthetic raw data for deep-learning-based image reconstruction
Authors: Zijlstra Frank , While Peter
Published: August 2024

This study demonstrates using generative deep learning for transforming magnitude-only images into synthetic raw data for deep-learning-base image reconstruction. Using relatively few raw datasets, a set of neural networks was trained to generate the missing phase and coil sensitivity information in magnitude-only images. These maps are then recombined into synthetic raw data. We trained end-to-end variational networks for 4-fold accelerated compressed sensing reconstruction on the FastMRI dataset, with increasing training set size. Synthetic raw data showed similar improvements as real raw data with increasing data. This shows promise for applying deep-learning-based image reconstruction when raw data is scarce.
SubZero: Subspace Zero-Shot MRI Reconstruction
Authors: Yu Heng , Arefeen Yamin , Bilgic Berkin
Published: August 2024

Recently introduced zero-shot self-supervised learning (ZS-SSL) has shown potential in accelerated MRI in a scan-specific scenario, which enabled high quality reconstructions without access to a large training dataset. ZS-SSL has been further combined with the subspace model to accelerate 2D T2-shuffling acquisitions. In this work, we propose a parallel network framework and introduce attention mechanism to improve subspace based zero-shot self-supervised learning and enable higher acceleration factors. We name our method SubZero and demonstrate that it can achieve improved performance compared with current methods in T1 and T2 mapping acquisitions .
A noise-robust accelerated MRI reconstruction using CycleGAN
Authors: Kim Seonghyuk , Lee Wonil , Jeong Namho , Kim Jeewon , Lee Jongyeon , Kang Beomgu , Park HyunWook
Published: August 2024

We propose a novel loss function that increases noise-robustness in accelerated parallel MR image reconstruction. The loss function is based on the variance of the background area in the noisy undersampled image and that of the difference image between noisy undersampled image and the synthesized undersampled image. The proposed loss function provides stronger regularization and robustness when applied along with other constraints. We show that the application of the proposed loss function boosts performance of the network, yielding improved quality of reconstructed image.
Attention-Based Multi-Offset Deep Learning Reconstruction for Accelerating Chemical Exchange Saturation Transfer MRI
Authors: Yang Zhikai , Yang Liu , Prabakaran Rohith Saai Pemmasani , ILYAS AbdulMojeed , Huang Jianpan , Chan Kannie W. Y.
Published: August 2024

We proposed an attention-based multi-offset network to exploit redundant anatomy information for the reconstruction of CEST-MR image (AMO-CEST). To the best of our knowledge, this is the first work using deep learning with varied radial sample patterns and multi-offset slices as input to accelerate CEST-MRI. Compared with other deep learning-based methods on the four times under-sampling mouse brain CEST dataset, the AMO-CEST achieved the best performance with an MMSE of, a PSNR of dB, and an SSIM. In conclusion, the proposed AMO-CEST network can accelerate the CEST-MRI at high down-sampling rate while maintaining good image quality.
Accelerated 3D Myelin Water Imaging: Jointly Unrolled Cross-domain Optimization-based Spatio-Temporal Reconstruction Network
Authors: Lee Jae-Hun , Han Dongyeob , Kim Jae-Yoon , Kim Dong-Hyun
Published: August 2024

Recently, acceleration of 3D multi-echo gradient-echo (mGRE) acquisition for myelin water imaging (MWI) has been achieved using parallel imaging (PI) or deep learning network. However, these methods typically allow a low acceleration factor (R) for MWI because of the high sensitivity of the MWI estimation routine with respect noise/artifacts. Here, we developed a reconstruction deep learning network called the jointly unrolled cross-domain optimization-based spatio-temporal reconstruction network. According to retrospective and prospective reconstruction results, the proposed method achieved high-fidelity performance on the reconstructed mGRE images and MWI maps.