bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of isocaloric ketogenic diet on fat content in the liver and muscle and volume of adipose tissue
Authors: Sedivy Petr , Setinova Barbora , Burian Martin , Pajuelo Dita , Hajek Milan , Sebo Viktor , Koc Michal , Siklova Michaela , Henikova Marina , Krauzova Eva , Gojda Jan , Rossmeislova Lenka , Kovar Jan , Dezortova Monika
Published: August 2024

The effect of a 28-day isocaloric ketogenic diet followed by a 2-day carbohydrate realimentation on adipose tissue and fat content in the liver and calf muscle in 22 obese women was studied using MRS and MRI methods. During the ketogenic diet, there was a significant decrease in liver fat volume (69±20 ml, i.e. decrease 43±4% of basal value) and liver fat content (2.7±0.6 %, i.e. 35±5% of basal value) and reduction cross-section in both subcutaneous (6 %) and visceral (7 %) fat. Contrary, the intramyocellular fat increased during the diet.
ADC as a quantitative value: classifying lymph node dignity in prostate cancer and inter-scanner variability
Authors: Bauer Jochen , Eveslage Maria , Noto Benjamin
Published: August 2024

Apparent diffusion coefficient (ADC) has potential as a quantitative imaging biomarker for differentiation of malignant from benign tissue. Here, we present a phantom and in vivo measurement of ADC reproducibility and a restrospective study in over 100 patients with prostate cancer to evaluate ADC as a classifier.
Accelerated diffusion-weighted imaging of the prostate employing Echo Planar Imaging with Compressed SENSE based reconstruction (EPICS)
Authors: Layer Yannik , Muertz Petra , Bischoff Leon , Katemann Christoph , Weiss Kilian , Luetkens Julian , Attenberger Ulrike , Pieper Claus
Published: August 2024

The aim of this single-center, prospective study was to evaluate an accelerated diffusion-weighted imaging sequence of the prostate using Echo Planar Imaging with Compressed SENSE based reconstruction and assess its performance in comparison to conventional DWI. The evaluated sequences considerably reduced the total DWI acquisition time by 43% and achieved overall good image quality without significant differences compared to the conventional DWI sequence. The reduced scan time allows for an increase of the overall number of scanned patients as well as increased patient convenience with less potential of motion artifacts and therefore benefits care of patients with suspected prostate cancer.
Improving Image Quality While Reducing Geometric Distortion of Diffusion-weighted MRI in prostate: Comparison of FOCUS-MUSE, MUSE, and SS DWI
Authors: Chen Yanling , Wang Huanjun , Guo Yan
Published: August 2024

The current study investigated the qualitative and quantitative image quality of three DWI sequences of the prostate: SS DWI, MUSE DWI and a new DWI sequence named FOCUS-MUSE DWI. Twenty-three healthy volunteers were enrolled. The diagnostic image quality score was assessed by two radiologists on the three DWI sequences. And the ADC values in the peripheral and transitional zone were measured together with the Dice Coefficient calculated for quantitative comparison. Our results indicated that FOCUS-MUSE DWI had a superior image quality and more stable ADC measurement compared with SS DWI and MUSE DWI. The geometric distortion level was also reduced.
Comparison of calculated DWI and single-shot EPI DWI for prostate cancer detection at 3T
Authors: TAMADA TSUTOMU , KOJIMA YUICHI , KIDO AYUMU , UEDA YU , TAKEUCHI MITSURU , ONO KENTARO , YAMAMOTO MIDORI , YAMAMOTO AKIRA , FUKUKURA YOSHIHIKO
Published: August 2024

We compared diagnostic performance of clinically significant PC (csPC) between calculated DWI (calDWI) which enable to synthesize DW images with any TR and TE and native acquired single-shot EPI DWI (nDWI). The calDWI was generated with TR of 1000 and TE of 0 ms. Three radiologists independently assessed eight regions of each prostate by PI-RADS v 2.1 DWI score. For diagnostic performance of csPC, AUC was comparable between calDWI and nDWI in two readers. The diagnostic specificity was significantly higher in calDWI than in nDWI in two readers. Compared with nDWI, calDWI had similar or higher diagnostic performance in csPC.
The diagnostic value of synthetic MRI combined with rFOV IVIM in transition zone prostate cancer
Authors: Zhou Qiqi , Liu Weiyin , Tang Qian , Sang Ling , Chen Wen , Xu Lin
Published: August 2024

This study investigated the value of relaxation time in synthetic MRI imaging combined with intravoxel incoherent motion (IVIM) imaging in differentiating transitional zone prostate cancer from benign prostatic hyperplasia (BPH). Finally, it was found that T2 value in synthetic MRI imaging and D value in IVIM imaging had higher diagnostic sensitivity and specificity, and their combined diagnostic performance was higher. It is helpful for the differential diagnosis of BPH and PCa in transitional zone.
Machine learning methods for cerebral perfusion status prediction
Authors: Cai Linkun , Niu Haijun , Zhao Erwei , Liu Yawen , Zhang Tingting , Liu Dong , Qiao Penggang , Ren Pengling , Zheng Wei , Wang Zhenchang
Published: August 2024

The diagnosis and evaluation of cerebral perfusion status are crucial for the management of brain diseases. However, the detection method of cerebral perfusion status is complicated. Considering that CBF is mainly supplied by the internal carotid artery (ICA), this paper proposes a novel cerebral perfusion status prediction model, which can automatically quantify the cerebral perfusion level of patients by modeling the association between ICA blood flow and cerebral perfusion. The experimental results on a real-world dataset using machine learning methods can achieve satisfactory performance. Thus, it can be used as an effective adjuvant tool for determining the cerebral perfusion status.
BayesNetCNN: incorporating uncertainty in neural networks for image-based classification tasks
Authors: Ferrante Matteo , Boccato Tommaso , Inglese Marianna , Toschi Nicola
Published: August 2024

The willingness to trust predictions formulated by automatic algorithms is key in a vast number of domains. We propose converting a standard neural network into a Bayesian neural network and estimating the variability of predictions by sampling different networks at inference time. We use a rejection-based approach to increase classification accuracy from 0.86 to 0.95 while retaining 75% of the test set for Alzheimer disease classification from MRI morphometry images. Estimating uncertainty of a prediction and modulating the behavior of the network to a desirable degree of confidence, represents a crucial step in the direction of responsible and trustworthy AI.
Pre-Clinical MRI radiomics and machine learning to predict survival after immunotherapy treatment
Authors: Riberdy Vlora , Guida Alessandro , Rioux James , Brewer Kimberly
Published: August 2024

Molecular MRI allows for immunotherapy treatment monitoring of glioblastoma, but analysis of multi-parametric data is complex. Machine learning algorithms can be applied to quantitative maps, to identify correlations between radiomic features and treatment outcomes. Feature selection is key when dealing with longitudinal preclinical data with multiple contrasts and small group numbers. We evaluated three feature selection methods in terms of their ability to produce predictive models of survival. The best performance was seen using recursive feature elimination applied to features from iron concentration maps of the tumor, which yielded an ROC AUC of 0.78 and an accuracy of 0.72.
Towards an optimal breast lesions predictive model by assessing different MRI protocols’ combinations: Radiomics analysis
Authors: Valizadeh Gelareh , Shoushtari Fereshteh Khodadadi , Koopaee Soheila , Salari Hanieh Mobarak , Golezar Mohammad Hossein , Gity Masomeh , Rad Hamidreza Saligheh
Published: August 2024

This study aimed to assess added value of various combinations of different MRI protocols and artificial intelligence techniques in differentiation capability between malignant and benign breast lesions. 61 benign and 69 malignant lesions were recruited. Radiomics features were extracted from three proposed scenarios, including original images of ADC and T2W (scenario-I), original images of ADC, T2W, and DCE (scenario-II), and the joint of original and the pre-filtered images (using wavelet) from ADC, T2W and DCE (scenario-III). Ten most relevant features were utilized for training 11 machine learning algorithms. Finally, decision tree achieved the highest results of accuracy using scenario-III.
129Xe MRI Ventilation Predicts Longitudinal Quality-of-Life Improvement in Post-Acute COVID-19 Syndrome
Authors: Kooner Harkiran , Sharma Maksym , McIntosh Marrissa , Dhaliwal Inderdeep , Nicholson J , Parraga Grace
Published: August 2024

Post-acute COVID-19 syndrome (PACS) is an umbrella term for symptoms and poor quality-of-life, four weeks+ after acute COVID-19 infection, reported in up to 30% of COVID-19 survivors. The longitudinal trajectory of PACS remains largely unknown. 129Xe MRI ventilation defects did not help to explain longitudinal quality-of-life outcomes in PACS and thus, texture analysis was used to evaluate potential ventilation features that could explain quality-of-life. We identified the 129Xe MRI ventilation texture features that predicted clinically relevant quality-of-life improvements 15-months post-infection, outperforming clinical models. These findings also suggest that ventilation texture features capture underlying pathophysiology not reflected by ventilation-defect-percent.
3 T MR Neuroimagingand CT Guided Injection for Atypical Facial Pain: A multimodality analysis of Pain Response
Authors: MaoJiang YANG , JianHao Liu , Bhetuwal ANUP , Xian QIONG , HanWen ZHANG , HanFeng YANG , Meining Chen , XiaoXue XU
Published: August 2024

At present, the pathogenesis of atypical facial pain is unknown. We conducted pain related analysis on the included patients through magnetic resonance imaging and trigeminal neurolysis, and the results suggest that trigeminal neuropathy may be a pathogenesis of atypical facial pain.
Connectomics Biomarkers of Gulf War Illness
Authors: Yang Guangming , Crosson Bruce , Haley Robert , Gopinath Kaundinya , Guo Ying
Published: August 2024

Around 200,000 veterans of the 1991 Gulf War (GW) suffer from GW illness (GWI). GWI is a poorly understood chronic medical condition, characterized by multiple symptoms. One factor that hampers mechanistic investigations into GWI is that there is considerable heterogeneity in symptoms across the GW veteran population. Only one case definitions of GWI addresses this heterogeneity. The Haley GWI case definition addresses this by further breaking down GWI into three main syndrome variants (Syn1, Syn2, and Syn3) based on factor analysis of symptoms presented by GWI veterans. In this study, we extracted rsfMRI connectomics biomarkers for different syndromes of GWI.
Comparing brain amyloid load using PET to grey matter perfusion using ASL on the OASIS-3 dataset
Authors: Sparks Sierra , Bulte Daniel , Pinto Joana
Published: August 2024

Alzheimer’s disease (AD) is the leading cause of dementia, and it is associated with cerebral amyloid beta accumulation and changes in cerebral perfusion. Amyloid PET imaging can be used to measure the amyloid beta load, while ASL-MRI is preferred for cerebral perfusion measurements, which may occur before amyloid beta accumulation. This study compares the amyloid beta load with the CBF in grey matter, in both cognitively healthy and cognitively impaired subjects from the OASIS-3 dataset. A logistic regression model using this data was able to classify the cognitive status of subjects with a 78.48% test accuracy.
Cerebrovascular reactivity is associated with longitudinal white matter hyperintensity progression in small vessel disease on 7T MRI
Authors: Pham Stanley , Versluis Danique , van den Brink Hilde , Dieleman Nikki , Zwanenburg Jaco , Biessels Geert Jan , Siero Jeroen
Published: August 2024

We studied the association between cerebrovascular reactivity measured with blood oxygenation level-dependent (BOLD-CVR) to hypercapnia and progression of white matter hyperintensities (WMH) on 7T MRI in cerebral small vessel disease (SVD). BOLD-CVR was assessed in voxels of four different categories which represent the fate of a voxel after two-year follow-up. The BOLD-CVR in normal appearing white matter (NAWM) that converted into WMH was significantly lower than the BOLD-CVR of voxels that remained WMH (0.39 [0.16-0.63] vs 0.98 [0.75-1.21]) (p<0.0001). The association between BOLD-CVR and WMH progression signifies the potential of BOLD-CVR to be a predictor of disease progression in SVD.
High-resolution MRI combined arterial spin labeling may distinguish between transient ischemic attack and stroke in intracranial stenosis
Authors: Li Ling , Zhang Xiaoling , Lei Xiaoyan , Tang Min , Yan Xuejiao , Wen Yu , Zhang Jing , Ai Kai
Published: August 2024

In order to prevent TIA patients from further developing into irreversible stroke, it is important to predict the occurrence of stroke in TIA patients. In this study, high-resolution magnetic resonance imaging (HRMRI) and arterial spin labeling (ASL) were used to investigate the differences of middle cerebral artery (MCA) plaque and hemodynamics in patients with ischemic stroke and TIA, and to establish a predictive model for ischemic stroke. The results showed that positive remodeling, enhancement ratio and 2.5s ATA present could be used to predict the occurrence of stroke in patients with TIA, and the prediction model had excellent diagnostic performance.
Multi-parametric Z-spectral MRI of stroke patients
Authors: Wang Zhengxiong , Xu Yongzhou , Wu Peng , Han Lu , Wei Xinhua
Published: August 2024

Multi-parametric Z-spectral MRI has been successfully implemented in vivo. In this study, multi-contrast Z-spectra fitted with four Lorentzian functions were acquired from eighteen ischemic stroke patients. We found that this novel method could differentiate lesions from normal brain tissues, and multiple Z-spectral contrasts showed a satisfying correlation with the apparent diffusion coefficient (ADC). Multi-parametric Z-spectral MRI could specifically characterize the metabolic alterations of ischemic brain tissues in stroke patients.
Predicting Adult-type Diffuse Gliomas Grade: A Comparison of Four Radiomics-based Diffusion Prediction Models
Authors: Wang Peng , He Jinlong , Wu Qiong , Xie Shenghui , Weng Lixin , Wang Shaoyu , Zhang Huapeng , Song Yang , Gao Yang
Published: August 2024

Application of MRI diffusion models can aid in the formulation of logical treatment strategies by non-invasively predicting gliomas pathogenic grade. However, it appears that the thorough comparison of diffusion models has not been addressed or has only been partially addressed. The objective of this study was to compare the potential clinical uses of four radiomics-based diffusion prediction models for predicting adult-type diffuse gliomas grade. According to the findings, the relatively simple model (i.e. diffusion tensor imaging) had the same potential for clinical use than the more sophisticated diffusion models. This suggests that additional point-to-point research is required.
A Subregion-based RadioFusionOmics Model Discriminates between Grade 4 Astrocytoma and Glioblastoma on Multisequence MRI
Authors: Wei Ruili , Pang Xinrui , Wang Ye , Liang Fangrong , Xu Yongzhou , Yang Ruimeng
Published: August 2024

The 2021 update of WHO CNS5 underlines the importance of IDH genotype prediction in the setting of adult-type grade 4 glioma. We developed a RFO model to discriminate between grade 4 astrocytoma and glioblastoma using subregional radiomics signatures from conventional MRI sequences. The fusion models from multiparametric MR images outperformed that from single sequence. The comparison between two different subregion manners revealed that voxel-wise habitats defined by clustering procedure yielded a higher discriminative capability. Our results also implied that tumor edema may contain underlying heterogeneous metrics between grade 4 astrocytoma and GBM.
The Value of Multi-parametric MRI-Based Radiomics Model in Predicting the IDH1 Mutation in Glioma
Authors: zhang Shao , Chen Zhi , Chen Xiao , Wang Zhuo , Zhou Yun , Liu Shi , Zhang Ruo , Xiong Yu , Chen Bing
Published: August 2024

This study aims to explore the value of multi-parametric MRI-based radiomics model for non-invasively predicting IDH1 mutation in glioma. It was shown that among various single-sequence radiomics models, the contrast-enhanced T1-weighted image radiomics model should be considered as an optimal model in predicting IDH1 mutation, while the combined model based on three sequences could further improve the predicting performance.
Quantitative MRI Measurement of Lung Development in Early Onset Fetal Growth Restriction
Authors: Schellenberg Janina , Tontivuthikul Paponrad , Chappell Joanna , Mufti Nada , Flouri Dimitra , Ourselin Sebastien , David Anna , Aughwane Rosalind , Melbourne Andrew
Published: August 2024

Fetal growth restriction (FGR) occurs when a fetus does not reach its full growth potential, predisposing the fetus to long-term impacts on lung function at birth and into childhood. We propose a novel model of fetal lung tissue based on combined diffusion and relaxation and apply this to a cohort of FGR and appropriately grown controls. We show differences in lung model parameters in FGR relative to controls and with gestational age. We also link these parameters to measurement of feto-placental oxygenation. This methodology could potentially provide a non-invasive method to assess fetal lung development.
Age matters: radiofrequency heating of epicardial and endocardial electronic devices in adults and children varies with body size and lead length
Authors: Jiang Fuchang , Henry Kaylee , Bhusal Bhumi , Sanpitak Pia , Webster Gregory , Popescu Andrada , Bonmassar Giorgio , Laternser Christina , Kim Daniel , Golestanirad Laleh
Published: August 2024

Children with congenital heart defects often have life-sustaining indications for an epicardial cardiac implantable electronic device (CIED). However few data exist on endocardial systems in children. Additionally, the FDA has never approved an epicardial system as MRI-Conditional due to limited data on potential heating risk. To provide evidence-based knowledge on RF-induced heating of CIEDs in children and adults with epicardial and endocardial leads of different lengths, we recorded the temperature increase of 120 clinically relevant trajectories positioned into adult and pediatric phantoms. Our results highlight the need for age and device-specific assessments of MRI safety in children with CIEDs.
Cardiac Magnetic Resonance Imaging at 3T Characterizes the Myocardium for Pediatric Cardiac Transplant Recipients: New Biomarker Development
Authors: Samyn Margaret , Gordon Adam , Yan Ke , Zhang Jian , Duffin Aspen , Soslow Jonathan , Damon Bruce , Gerardin Jennifer , Goot Benjamin , Cava Joseph , Kindel Steven
Published: August 2024

Pediatric heart transplant recipients undergo frequent invasive cardiac catheterization with endomyocardial biopsy for routine allograft surveillance. Risks associated with catheterization and sampling error call into question this accepted “gold standard.” Cardiac magnetic resonance imaging (CMR), with parametric imaging, may advance myocardial surveillance in this population. Fifty-two pediatric patients (transplanted at ≤18 years old) underwent CMR (September 2016 to June 2019) at 3T to evaluate myocardial health using MOLLI sequence. Healthy transplant recipients had normal global biventricular function, native T1 higher than published values for healthy children at 3T with similar extracellular volume (ECV) despite history of treated rejection.
Out-of-phase Ventiilation Observed With Dynamic Hyperpolarized Xenon-129 Mri In A Pig Thoracic Insu!ciency Syndrome Model
Authors: Hamedani Hooman , Amzajerdian Faraz , Kadlecek Stephen , Ruppert Kai , Ismail Mostafa , Loza Luis , Duncan Ian , Boyes Madeline , Hopster Klaus , Hilliard Rachel , Schaer Thomas , Sinder Benjamin , Snyder Brian , Moore Axel , Elliott Dawn , Meadows Kyle , Rizi Rahim
Published: August 2024

In a pilot study of thoracic insufficiency syndrome in a pig model, we demonstrated dynamic hyperpolarized xenon-129 (HXe) MRI’s ability to noninvasively measure respiratory dysfunction in terms of gas distribution and mixing in the lungs, and specifically showed ‘out of phase’ ventilation in constricted regions of the lung. This marker of ventilation—i.e., the temporal characteristic of signal build-up during inhalation and its wash-out during exhalation—is inaccessible without our dynamic imaging technique. This technique can be implemented clinically to enhance our understanding of TIS pathophysiology and evaluate treatment strategies aimed at fostering age appropriate alveolarization.
Automated multi organ segmentation for 3D fetal body MRI: differences in the normal growth charts for different acquisition parameters
Authors: Uus Alena , Story Lisa , Hall Megan , Kyriakopoulou Vanessa , Collado Alexia Egloff , Zampieri Carla Avena , Matthew Jacqueline , Grigorescu Irina , Tanritanir Ayse Ceren , Hajnal Joseph , Hutter Jana , Rutherford Mary , Deprez Maria
Published: August 2024

This work presents the first deep learning pipeline for segmentation of multiple body organs from motion corrected 3D ssTSE fetal MRI. It is used to compare growth charts of the normal body organ development during 21-37 week GA range for 254 fetal datasets with different acquisition protocols (field strength and TE).
Respiratory binning with PilotTone Navigator For Motion Compensated Liver DW-MRI
Authors: VASYLECHKO SERGE , ARIYUREK CEMRE , AFACAN ONUR , KURUGOL SILA
Published: August 2024

Respiratory motion substantially affects the accuracy of quantitative DWI-MR techniques in the upper abdomen. A conventional approach for motion correction in abdominal MRI uses a respiratory belt or other navigators for prospective triggering. This study explores use of a new approach - PilotTone (PT) navigator for binning.
Recovering slice location for unconventional acquisition plane with deep learning algorithm: cardiac magnetic resonance case
Authors: Rebbah Habib , Boutelier Timothé
Published: August 2024

In cardiac MR field, the slice location along the long axis is a key parameter for the standardization proposed by the American heart association. We explore here the ability of a CNN to estimate it.
Feasibility of fat quantification of in vivo mouse liver at 9.4T
Authors: Wang Zhongmiao , Bo Tingting , Chen Chen , Min Yuqin , Cai Xinxin , Lin Huimin , Lei Hongxia , Zhai Renkuan , Wang Jiqiu , Yan Fuhua , Ning Guang
Published: August 2024

The feasibility of determination of fat in living mouse liver is demonstrated at 9.4T using gradient-echo sequence and the Fat Analysis and Calculation Technique (FACT)—Transition Region Extraction (TREE) algorithm. The proton density fat fraction map is obtained, which is positively correlated with steatosis. The proposed technique is a promising non-invasive tool for diagnosing fatty liver diseases.
MR-based segmental quantification of hepatic lipid content in patients with suspected iron overload
Authors: Wunderlich Arthur , Cario Holger , Kannengießer Stephan , Grunau Veronika , Götz Michael , Beer Meinrad , Schmidt Stefan
Published: August 2024

Purpose To investigate the segmental distribution of hepatic fat fraction in hematologic patients. Methods The liver of 44 patients examined with 3D MR multi-echo gradient-echo was segmented semiautomatically and subdivided into nine segments. Segmental fat content was determined on PDFF maps and tested for statistically significant differences. Results Highly significant differences were detected. Segments 1 to 3 had the highest fat content, segments 7 and 8 the lowest. Conclusions Our results suggest that liver segments may represent functional aspects in fat metabolism and/or storage in addition to their anatomical significance. Fat distribution in hematologic patients was similar to living donors.
Detection of sparse and dense prostate cancers using bi-parametric MRI combined with radiomics features
Authors: Zhou Bingni , Chen Zhangzhe , Chen Rucuan , Liu Wei , Gan Hualei , Zhang Yong , Zhou Liangping , Liu Xiaohang
Published: August 2024

This is a preliminary study which combined bi-parametric MRI with radiomics feature to detect sparse and dense prostate cancers. Fifty-five patients underwent diffusion weighted and T2 weighted imaging. One hundred and nine peripheral zone (PZ) tumors were reviewed using whole-mount histologic findings. The total number of 381 radiomics features were extracted to construct the models for differentiation. Dense tumors showed ADC values significantly lower than sparse tumors and normal PZ tissues. ADC alone should provide sufficient diagnosis efficiency. However, radiomics features can significantly improve the detection of sparse tumors which showed the similar ADC values as compared to normal tissues.
Evaluation of the clinical value of Synthetic MRI in the prostate cancer diagnosis: a comparison of quantitative relaxation with conventional MRI
Authors: Tian Jun , Pylypenko Dmytro , Li Haige
Published: August 2024

This study aimed to investigate the feasibility of synthetic MRI in distinguishing PCa from benign hyperplasia, and quantitative relaxation was compared with conventional MRI to evaluate the precision of obtained values with synthetic MRI. 38 patients (54 lesions) with cancer and/or hyperplasia were recruited. Quantitative MRI sequences, including T1, T2 mapping and MAGIC, were used. Significantly different T1 and T2 values were shown between cancer and noncancerous tissue, located in peripheral and center zones, as well as between cancer and glandular hyperplasia and stromal hyperplasia. These findings suggest synthetic-MRI may be effective in differentiating PCa from benign hyperplasia.
Temporal dynamic change patterns of intrinsic brain activity in multidomain brain networks in subcortical stroke patients
Authors: Wang Caihong , Liu Jingchun , Guo Jun , Miao Peifang , Wei Ying , Wang Kaiyu , Cheng Jingliang
Published: August 2024

This study aimed to explore the temporal dynamic change patterns and the mechanisms of verbal memory deficit in chronic subcortical stroke patients with motor pathway based on the static and dynamic amplitude of low-frequency fluctuations. A total of 136 patients and 88 normal controls were included in the study. We found verbal memory deficits in the patients of chronic subcortical stroke involving the motor pathway, especially in patients with partial recovery. Moreover, subcortical stroke-induced functional deficits may not only occur in the motor system but also in the cognitive functional system.
Quantitative susceptibility mapping reveals an association between iron load in gray matter nuclei and different cerebral perfusion patterns
Authors: Guo Yu , Dou Weiqiang , Mao Huimin , Wang Xinyi
Published: August 2024

The main purpose was to explore iron alterations in gray matter (GM) nucleus of patients with unilateral middle cerebral artery (MCA) stenosis or occlusion with varied cerebral perfusion states using quantitative susceptibility mapping (QSM). Sixty-one patients with unilateral MCA stenosis or occlusion were divided into three groups based on different cerebral perfusion patterns and examined with QSM. Iron-related susceptibility of GM nucleus subregions were assessed. The results showed that iron deposition in bilateral putamen and globus pallidus at the lesion side significantly increased in patients with extensive impaired but not hypo- or normal cerebral perfusion.
Automated Analysis of Dynamic Diffusion Abnormalities and Infarct Growth Following Ischemic Injury
Authors: Gangolli Mihika , Kharlamov Alexander , Chung David , Boada Fernando , Yushmanov Victor , Pham Dzung , Butman John , Jones Stephen
Published: August 2024

An automated analysis pipeline was developed to detect and analyze the trajectories of dynamic diffusion abnormalities (DDAs) in a rat model of severe ischemic injury. DDAs were detected in both hemispheres of the brain and perilesional DDAs propagated along the infarct boundary. Infarct volume, quantified using apparent diffusion coefficient (ADC), increased during the recording period concomitantly with detected DDAs. Our approach could provide the means to explore the causal relationship between DDAs hypothesized to correspond with peri-infarct depolarizations and secondary expansion of infarcted tissue.
Artificial Intelligence-Driven Image Quality Assessment for Intracranial Vessel Wall Magnetic Resonance Imaging
Authors: Peng Wenjia , Zhao Haiyan , Zhang Xuefeng , Chen Luguang , Li Hao , Wang Shuo , Lu Jianping
Published: August 2024

Image quality control is a prerequisite for quantitative image analysis. We develop a convolutional neural network-based model for assessing the image quality of intracranial vessel wall MRI. Experimental results show that the model prediction is in good agreement with a senior radiologist, with a Cohen’s Kappa of 0.689. The model demonstrates real-time evaluation speed which is 500 times faster than the radiologist. It has the potential to be used in performing quality control on historical data for research purposes, and also can be used to examine the image quality immediately after the clinical MRI scan.
Comparison of 7T MRA and DSA in assessment of the Suzuki staging system for Moyamoya disease
Authors: Duan Qi , Lyu Jinhao , Duan Caohui , Bian Xiangbing , Qu Jianxun , Lou Xin
Published: August 2024

Moyamoya disease (MMD) is an uncommon chronic cerebrovascular disease and a leading cause of stroke in pediatric and young patients. Suzuki staging system based on conventional digital subtraction angiography (DSA) is a useful and important index in clinical. However, DSA is invasive and unnecessary in some situations. 7T TOF-MRA enables the visualization of the "puff of smoke" collateral network in MMD compared to 1.5T and 3T. We tried to grade the Suzuki staging system by using 7T TOF-MRA in MMD patients. Our results indicated that 7T TOF-MRA showed excellent performance as DSA on grading the Suzuki staging system in MMD.
Following evolving pH changes in the penumbra using a novel MRI method
Authors: Demetriou Eleni , Taylor Valerie , Tachrount Mohamed , Jokivarsi Kimmo , Grohn Olli , Jager Rolf , Shmueli Karin , Golay Xavier
Published: August 2024

Here, our goal was to visualise dynamic pH changes in a rat model of MCAO and their relation to other imaging techniques for identifying the penumbra zone which is used to guide therapeutic intervention.
The Value of Multiparametric MRI-based Radiomics Features in Distinguishing Primary Central Nervous System Lymphoma from High-grade Glioma
Authors: zhang Shao , Chen Zhi , Chen Xiao , Wang Zhuo , liu Shi , Zhou Yun , Zhang Ruo , Xiong Yu , Chen Bing
Published: August 2024

In this study, we aim to explore the radiomics model constructed by a single sequence or a combined sequences whether has the same or better performance, and to explore the effect of different choices of region of interest to the performance of radionmics model.
Evaluation of relaxometry in differentiating recurrence and necrosis of high-grade glioma after radiotherapy using synthetic MR
Authors: YANLING LIU , YUELONG CUI , ZHEN NIU , JINXIA GUO , SHASHA ZHANG , JUNLI ZHANG , YONG WANG
Published: August 2024

This study is to utilize the relaxometry generated by unenhanced and Gd-enhanced synthetic MRI to identify the recurrence and necrosis in patient with high grade glioma after radiotherapy. The results indicated enhanced T1 was significantly shortened in tumor and peripheral edema region for recurrent tissue in compare with necrosis and showed well ability of differentiation
Boosting The Deep Learning Performance in Predicting IDH Mutation in Gliomas Using Multiparametric MRI Including SWI, FLAIR and CE-T1WI
Authors: Azamat Sena , Buz-Yaluğ Buse , Ozcan Alpay , Danyeli Ayça Ersen , Pamir Necmettin , Dinçer Alp , Ozduman Koray , Ozturk-Isik Esin
Published: August 2024

Gliomas with IDH mutations tend to have a better prognosis regardless of the histopathological grade. The main aim of this study was to identify isocitrate dehydrogenase (IDH) mutations in glioma patients using deep learning models based on SWI, FLAIR and CE-T1W images separately and together. As a result, a 2D CNN model based on multiparametric MRI resulted in an accuracy of 92.8%, while CNN based on just SWI had 72.2% and CNN based on just FLAIR had 61.1% accuracies for predicting IDH mutation in gliomas.
Automatic Segmentation of Vasculature in DCE-MRI of Brain Tumors and its Influence in Grading
Authors: Kesari Anshika , Yadav Virendra , Jafari Raufiya , Gupta Rakesh , Patir Rana , Vaishya Sandeep , Ahlawat Sunita , Singh Anup
Published: August 2024

Quantitative DCE-MRI parameters are sensitive to tumor microvasculature and have shown potential in tumor grading. Generally, value of some of these parameters increases with tumor grades. During analysis of tumor region, large-blood-vessels (LBV) can influence the actual changes due to tumor microvasculature and hence provide erroneous results. Objectives of this study were to develop an automatic framework for segmentation of the LBV present within and outside of the tumor region and to reduce errors in tumor grading. The statistical analysis of parameters in tumor region showed significant differences between with and without LBV. Moreover, LBV removal improved tumor classification accuracy.
Attention Deep-Shallow Network (ADSN): A Deep Learning Model for IDH and TERTp Mutation Detection in Gliomas using 1H-MRS
Authors: Bas Abdullah , Sacli-Bilmez Banu , Danyeli Ayca , Can Ozge , Ozduman Koray , Dincer Alp , Ozturk-Isik Esin
Published: August 2024

Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp) mutations affect the clinical behavior and survival rate of diffuse gliomas. According to the latest WHO 2021 brain tumor classification, IDH mutation is an important factor for grouping adult-type diffuse gliomas. The preoperative detection of these mutations is very critical for treatment planning. In this study, we propose enhanced 1D-CNN models by adding an attention mechanism as a prior network to focus on relevant spectral frequencies of 1H-MRS to identify IDH-mutant (IDH-mut), TERTp-mutant (TERTp-mut), and IDH-wt, TERTp-mut (TERTp-only) gliomas using three binary models
Autopsy-based radio-pathomic maps of tumor probability delineate tumor presence within radiological segmentations
Authors: Bobholz Samuel , Lowman Allison , Duenweg Savannah , Winiarz Aleksandra , Stebbins Margaret , Kyereme Fitzgerald , Connelly Jennifer , Coss Dylan , Mueller Wade , Agarwal Mohit , Banerjee Anjishnu , LaViolette Peter
Published: August 2024

This study applied autopsy-based radio-pathomic maps to the pre-surgical PENN-GBM dataset to test the hypothesis that the predicted tumor composition of the contrast-enhancing and FLAIR-hyperintense regions identify distinct pathological features of glioblastoma. We find that greater predicted tumor within the contrast-enhancing region is indicative of IDH1-wildtype mutation status, and show that larger tumors tend to have less predicted tumor within contrast-enhancement and more tumor within non-enhancing FLAIR hyperintensity. This technique could be used to non-invasively identify more aggressive tumors.
Feasibility of Blood oxygen level dependent magnetic resonance imaging for distinguishing HSPN from HSP in children Synopsis
Authors: Su Hang , Zhang Gang , Wu Jingjing , Xing Wei , Hu Yufu , Shen Zhiwei , Jiang Ke , Sun Yuying , Zhang Xia , Ren Xianqing
Published: August 2024

Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) could be used to detect renal tissue oxygen levels noninvasively, and the T2* time induced by the paramagnetic effect of deoxyhemoglobin can be obtained to indirectly assess blood oxygen utilization. Previous research has proven that BOLD-MRI can detect renal oxygenation levels with high sensitivity and the accuracy of the data has been validated by invasive probe measuring techniques. In this work, we investigated the clinical feasibility of T2* mapping for the detection of HSPN and HSP in children, since we predicted that HSPN would also result in aberrant renal blood oxygenation signals.
T2 mapping of patellar cartilage after single and first-time traumatic lateral patellar dislocation episode
Authors: Voronkova Elena , Menshchikov Petr , Melnikov Ilya , Bozhko Olga , Manzhurtsev Andrei , Ublinskiy Maxim , Vorobyev Denis , Kupriyanov Dmitriy , Akhadov Tolib
Published: August 2024

The purpose of the study was to examine short-term consequences of the single and first-time lateral patellar displacement on patellar cartilage quality in teenagers using T2 mapping. The research showed a principal difference in T2 changes between medial and lateral cartilage facet. The medial part usually suffering first after LPD, the absence of T2 changes for the mild group may indicate completed reparative processes, while the decrease in T2 denotes that the reparation is still ongoing. T2 increase in lateral patellar regardless chondromalacia severity indicates secondary damage.
Normative brain atlas of T2/T1 relaxometry ratio for detection of microstructural pathology
Authors: Ravano Veronica , Caneschi Samuele , Krasensky Jan , Andelova Michaela , Kudrna Matej , Uher Tomas , Piredda Gian Franco , Disselhorst Jonathan , Maréchal Bénédicte , Thiran Jean-Philippe , Richiardi Jonas , Vaneckova Manuela , Hilbert Tom , Kober Tobias
Published: August 2024

Quantitative MRI allows the characterization and comparison of microstructural tissue properties and, by defining normative ranges for healthy tissue, detection of pathology. The simultaneous evaluation of multiple qMRI measures facilitates the understanding of what biological mechanisms underlie the observed deviations in relaxometry. Here, we introduce the ratio between quantitative T2 and T1 maps (T2/T1) as a microstructural property whose deviations from normative values could be predictive or characteristic of brain pathologies. A T2/T1 voxel-wise normative atlas was created and allowed characterization of tissue changes in two multiple sclerosis patients, providing complementary information to the existing T1 and T2 atlases.
Implementation of gradient nonlinearity correction for ADC measurements in head and neck cancer
Authors: Paudyal Ramesh , Shah Akash , Konar Amaresha , Yu Victoria , Malyarenko Dariya , Lee Nancy , Chenevert Thomas , Shukla-Dave Amita
Published: August 2024

The present study evaluated the correction efficacy for ADC values bias due to the gradient nonlinearity of the MRI system on primary tumors, neck nodal metastases, and masseter muscle in the head and neck region using a vendor-provided LOw VAriance (LOVA) ADC technique. The LOVA ADC technique was developed and implemented to compensate for gradient linearity errors that may allow consistent ADC values in large FOV independent of the offset from the scanner isocenter. Our results confirmed the potential of the LOVA technique to improve ADC accuracy independent of location and scanner gradient characteristics.
Neural Network-Based Removal of Colored Noise in MR Fingerprinting
Authors: Meineke Jakob , Wülker Christian , Tkach Jean , Nagaraj Usha , Doneva Mariya , Nielsen Tim
Published: August 2024

A neural network for the estimation and removal of colored noise in non-Cartesian MRI is trained and subsequently applied for denoising coefficient images in MR Fingerprinting. It is shown that the neural network does not introduce bias in the quantitative parameter maps and improves their precision. Invivo T1- and T2-maps are demonstrated to be visually improved.
Cartesian MR-STAT vs spiral MR Fingerprinting: a comparison
Authors: van der Heide Oscar , Doneva Mariya , Koken Peter , Meineke Jakob , Fuderer Miha , van den Berg Cornelis , Sbrizzi Alessandro
Published: August 2024

MR Fingerprinting (“MRF”) and MR Spin Tomography in Time-domain (“MR-STAT”) are quantitative MRI techniques that allow multiple quantitative tissue parameter maps (e.g. T1, T2 and proton density) to be estimated from a single short scan. In this work, we compare the accuracy and precision of Cartesian MR-STAT and spiral MRF on gel phantoms and in-vivo. On gel phantoms we get excellent agreement with reference measurements. In-vivo we observe differences in reconstructed T1 values. As for the precision, a more in-depth study is required to take into account differences in noise-suppression mechanisms (i.e. k-space apodization and spiral sampling window).
3D Extension of the multi parametric acquisition Multi-Phase balanced non-Steady State Free Precession
Authors: Byanju Riwaj , Kotek Gyula , Vogel Mika , Hernandez-Tamames Juan , Poot Dirk
Published: August 2024

We propose a 3D extension of the novel MP-b-nSSFP sequence, which interleaves RF pulse types for Multiparametric mapping from the transient response. Comparing selective versus non-selective refocusing pulses we observe lower bias with non-selective pulses, despite modelling the spatially varying effect of the pulses in the fitting process. Phantom and in-vivo comparison to QRAPTEST (MAGIC) are performed.
Sub-second T2 mapping of the whole brain via multiband SENSE multiple overlapping-echo detachment imaging and deep learning
Authors: Li Simin , Kang Taishan , Wu Jian , Chen Weikun , Wu Zhigang , Wang Jiazheng , Cai Congbo , Cai Shuhui
Published: August 2024

Most quantitative magnetic resonance imaging (qMRI) methods are time-consuming. Multiple overlapping-echo detachment (MOLED) imaging can achieve quantitative parametric mapping for a single slice within hundred milliseconds. To further accelerate MOLED, we combine MOLED with multiband SENSE (MB-SENSE) technology to achieve simultaneous multi-slice T2 mapping. To solve the problem of reconstructed image quality degraded caused by a high multiband factor MB, a plug-and-play (PnP) approach with prior denoisers was applied for image restoration to realize denoising at a high MB. The proposed multiband multiple overlapping-echo detachment (MB-MOLED) imaging can achieve sub-second T2 mapping of the whole brain with a high MB.
Imaging Biomarkers of Therapeutic Response to Melanoma to Kinase Inhibitors
Authors: Gupta Pradeep Kumar , Orlovskiy Stepan , Tomar Jyoti S , Arias-Mendoza Fernando , Nelson David , Pickup Stephen , Shestov Alexander , Leeper Dennis , Glickson Jerry , Nath Kavindra
Published: August 2024

In vivo 1H/31P MRS were used to monitor the effects of Kinase Inhibitor (KI) therapy in two metabolically different human melanoma xenografts models. Our goal is to determine the metabolic changes in human melanoma xenograft models when treated with two KIs, a BRAF and a MEK inhibitor. KI combination is more effective than single-drug therapy. Differences in relative levels of metabolites and bioenergetics between two human melanoma xenografts models may produce differential therapeutic responses to BRAF and MEK inhibitors. In melanoma, metabolic changes in response to targeted kinase inhibitor therapy occur rapidly and are connected to subsequent tumor response.
Application of 3D MR MENSA in preoperative evaluation of lumbar disc herniation: a prospective study
Authors: Pan Xuelin , Wen Yuting , Li Zhenlin , Rong Xin , Zhang Miaoqi
Published: August 2024

In this work, we propose a preoperative magnetic resonance examination of patients with lumbar disc herniation using the 3D MENSA sequence. This sequence was superior to cube, cube stir sequence in subjective and objective evaluation. The preoperative 3D MRI MENSA sequence is able to clearly depict the nerve roots and offer desirable contrast between the nerve roots, ligamentum flavum, bone, and intervertebral discs. Patients with lumbar degeneration can effectively benefit from the MENSA sequence since it provides informative imaging information to help understand disc herniation and compression of adjacent tissues when developing preoperative surgical strategies.
Preoperative prognostic Stratification for Patients with HCC Using Gadoxetic acid-enhanced MR Imaging
Authors: Gao Feifei , Wei Yi , Li Qian , Wei Xiaocheng , Nie Lisha , Zhang Miaoqi , Song Bin
Published: August 2024

Accurate preoperative risk stratification is of critical importance for determine patients who will benefit from liver resection. Our study developed three subgroups of patients with HCC associated with different prognosis (RFS and OS) after resection based on preoperative MR imaging features using the Survival Classification and Regression Tree (CART) method. The generated subgroups using CART method demonstrated good discriminatory for preoperatively stratification of the prognosis. Therefore, the CART model of this present study may help clinicians to consider non-surgical treatment more often in worse prognostic patients and as well as inform more intense surveillance following resection.
Gd-EOB-DTPA Enhanced 3D T1WI: Utility of Compressed Sensing with Deep Learning Reconstruction for Liver Tumor Detection Improvement
Authors: Nagata Hiroyuki , Ohno Yoshiharu , Yoshikawa Takeshi , Yamamoto Kaori , Ikedo Masato , Yui Masao , Shinohara Maiko , Iwase Akiyoshi , Matsuyama Takahiro , Ueda Takahiro , Ikeda Hirotaka , Ozawa Yoshiyuki , Toyama Hiroshi
Published: August 2024

We hypothesize that CS with DLR can improve spatial resolution, image quality and tumor detection on Gd-EOB-enhanced 3D T1WI in suspected liver tumor patients. The purpose of this study was to determine the utility of CS and DLR for image quality and liver tumor detection improvements on high-resolution 3D CE-T1WI (HR-CE-T1WI) as compared with conventional 3D CE-T1WI with PI (conventional CE-T1WI) in patients with suspected liver tumors.
DCE-MR Lymphangiography Demonstrates Significantly Different Lymphatic Drainage in Patients with a FOXC2 Gene Mutation Compared to Controls
Authors: Mills Michael , Brezgyte Greta , Ho Bernard , Pearce Julian , Gordon Kristiana , Mortimer Peter , Ostergaard Pia , Howe Franklyn
Published: August 2024

MRI can investigate lymphatic dysfunction and lymphoedema (a chronic swelling of interstitial fluid), however little quantitative research has been published. Dynamic Contrast-Enhanced Magnetic Resonance Lymphangiography (DCE-MRL) allows identification of lymph vessels in both healthy and lymphoedematous limbs, and was used to study the oedematous limbs of patients where the lymphoedema was associated with a mutation of the FOXC2 gene. Signal measured in leg lymphatics of these patients (n=6) peaked significantly earlier than in non-oedematous limbs (n=6) and demonstrated higher peak signals, despite an impaired lymphatic system and therefore an expectation of more sluggish drainage.
Cerebral perfusion in Parkinson's disease with depression: an arterial spin-labeling magnetic resonance imaging study
Authors: Li Xinyang , Tian Yaotian , Wang Xiaonan , Pfeuffer Josef , Maréchal Bénédicte , Tobias Kober , Wu Yanglei , Li Chunmei , Chen Min
Published: August 2024

Arterial spin labeling-magnetic resonance imaging (ASL-MRI) combined with inline T1-weighted-based brain morphometry was used to evaluate regional cerebral blood flow in this study, which explored alteration of cerebral perfusion in Parkinson’s disease (PD) patients with depression and investigated its underlying neural mechanism. The results showed decreased cerebral perfusion in several brain regions in PD patients compared to healthy controls and a correlation between decreased cerebral perfusion of the right occipital white matter and right cingulate gyrus in PD patients with depression. This finding suggested that hypoperfusion of the limbic system is involved in the pathogenesis of PD with depression.