bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated MRI radiomics, tumor microenvironment, and clinical risk factors improving survival prediction in patients with glioblastoma
Authors: Zhou Qing , Zhou Junlin
Published: November 2024

Motivation: The patients with glioblastoma (Gb) with poor prognosis and quality of life. Goal(s): To construct a comprehensive model for predicting the prognosis of patients with Gb using a radiomics method and integrating tumor microenvironment . Approach: In total, 149 patients with isocitrate dehydrogenase wild-type Gb were enrolled retrospectively. Selected the best feature combination related to Gb overall survival. Clinical-radiomics-TME models were established. Results: Lasso-Cox analyses were used to screen the factors related to OS in patients with Gb, including age, peritumoral edema, tumor purity, tumor-associated macrophages, and the 21 radiomics features. The clinical-radiomics-TME model had the best survival prediction ability, the C-indices was 0.727. Impact: Considering the poor prognosis of IDH wild-type Gb, we explored additional prognostic risk factors and established a survival prediction model. The clinical-radiomics-TME comprehensive model showed a significant improvement compared to other models and was most effective in predicting patient survival.
Combined DW-MRI and DW-MRS sensitivity to glioma tumour microenvironment: a preliminary study
Authors: Palombo Marco , Rot Samuel , Figini Matteo , Powell Elizabeth , Solanky Bhavana , Najac Chloe , Siow Bernard , Rees Jeremy , Hill Ciaran , Panagiotaki Eleftheria , Ronen Itamar , Hyare Harpreet
Published: November 2024

Motivation: Understanding the complexity of the tumour microenvironment is critical for understanding glioma progression and developing effective therapies. Goal(s): To develop a non-invasive imaging pipeline for characterization of the glioma tumor microenvironment. Approach: Combining DW-MRI and DW-MRS to enhance the characterization of a spectrum of gliomas as a feasibility study. Results: Changes in neuronal (tNAA) and glial (tCho) metabolites apparent diffusion coefficients suggest neuronal atrophy and glial activation/reaction in tumor core, respectively. Changes in intracellular and extracellular volume fractions and extracellular diffusivity quantified by DW-MRI support and complement metabolite DW-MRS result and further suggest a more infiltrative marging in IDH mutant tumors. Impact: Combination DW-MRI and DW-MRS has potential to characterize the glioma microenvironment for improved understanding of radio-resistance and developing more effective therapies.
MRI study of enlarged choroid plexus in patients with spinocerebellar ataxia type 3.
Authors: Zhen Zhiming , Huang Yonghua , Cao Chenghao , Hua Yanqiu , Ou Peiling , Chen Wei , Chen Wei , Zuo Zhentao , Liu Chen
Published: November 2024

Motivation: The role of cerebral immune and homeostatic structures of choroid plexus (CP) in SCA3 patients remains elusive. Goal(s): The objective of this study is to investigate the volumetric changes in the choroid plexus. Approach: Whole brain of SCA3 patients was imaged using a 3T MRI scanner and the volume of CP was analyzed. Results: The findings revealed that CP volume was significantly larger in the SCA3 group compared to normal control group, exhibiting a positive correlation with both the number of ATXN3 repeats and scores of motor function abnormalities. Impact: The abnormal change of CP volume may serve as a new marker for distinguishing SCA3 patients
Cerebrovascular reactivity in choroid plexus
Authors: JIN YUECEN , Turner Monroe , Hazel Kaisha , Zhao Yuguang , Hu Beini , Abdelkarim Dema , Thomas Binu , Rypma Bart , Lu Hanzhang , Liu Peiying
Published: November 2024

Motivation: Choroid plexus (CP) plays an important role in the production of CSF and the formation of the blood-CSF barrier, but its vascular function is unclear. Goal(s): We aim to quantify cerebrovascular reactivity (CVR) of CP in normal controls. Approach: We applied PCASL with 5%CO2 inhalation in 92 subjects and compared CVR in gray matter, white matter and CP between young and old subjects. Results: CVR of CP was significantly lower than that of gray and white matter, but showed no age-related difference. Impact: This work provides a reference for future studies on CVR changes of CP in pathological conditions.
Four-dimensional iterative motion correction (iMoCO) for isotropic stack-of-spirals cine imaging at 0.55T
Authors: Ramasawmy Rajiv , Javed Ahsan , Herzka Daniel , Kumar Prakash , Nayak Krishna , Lederman Robert , Campbell-Washburn Adrienne
Published: November 2024

Motivation: Three-dimensional (3D) isotropic cine imaging can be resliced and resampled for clinical diagnosis and planning for structural interventions. Currently, these 3D cine approaches are hampered by long scan times. Goal(s): To demonstrate cardiac-resolved iterative motion compensation (iMoCo) for a free-breathing stack-of-spirals 3D cine with optimized acquisition ordering at 0.55TApproach: The 3D cine was acquired in five healthy volunteers and one patient, reconstructed with cardiac-resolved iMoCo, and compared to a reference 2D cine. Results: The proposed method yielded high quality 3D cines. Volumetric measurements had good agreement with reference data (-2.3 ± 2.8% and 3.9 ± 10.4% in diastole and systole respectively). Impact: A gaussian-distributed stack-of-spirals sampling scheme paired with an iMoCo reconstruction improves image quality and sharpness for isotropic three-dimensional cines. This technique can be a useful tool for interventional planning and assessment or as a one-stop shop for diagnostic cardiovascular MRI.
Cross-species comparison: imaging and mapping gastric motor functions in humans and rats using contrast-enhanced rapid MRI
Authors: Wang Xiaokai , Alkaabi Fatimah , Scheven Ulrich , Choi Minkyu , Noll Douglas , Liu Zhongming
Published: November 2024

Motivation: Direct and granular cross-species comparisons of gastric motor functions remain scarce in the literature. Goal(s): This study aims to establish functional similarities and distinctions of the stomach between humans and rats, and lay the foundation for integrating preclinical findings into clinical gastrointestinal studies. Approach: Using comparable MRI protocols, we examined the interspecies parallels and distinctions in their functions as pressure and peristaltic pumps. Results: Similarities were confirmed with high-resolution spatial maps, including intragastric pressure gradient and spatial distribution of peristaltic amplitude and frequency, despite their differences in scale. We highlighted the pronounced variance in initialization and spatial coordination of peristaltic contractions across species. Impact: This work serves as the first one to map and compare gastric motor events with comparable MRI protocols, laying the foundation for preclinical rat research to clinical translation using contrast-enhanced gastrointestinal MRI.
Post-Mortem Changes of Anisotropic Mechanical Properties in the Porcine Brain Assessed by MR Elastography
Authors: Wang Shuaihu , Eckstein Kevin , Guertler Charlotte , Johnson Curtis , Okamoto Ruth , McGarry Matthew , Bayly Philip
Published: November 2024

Motivation: Anisotropic mechanical properties of brain tissue define the mechanobiology of injury and disease, but most measurements of direction-dependent properties have been performed post-mortem. Goal(s): To characterize the post-mortem changesApproach: We use magnetic resonance elastography and diffusion tensor imaging with a transversely-isotropic nonlinear inversion algorithm to estimate anisotropic mechanical properties of minipig brain, both in vivo and at specific times after death. Results: White matter is stiffer, more dissipative, and more anisotropic than gray matter when the minipig is alive, but except for tensile anisotropy, these differences largely disappear post-mortem. Overall, brain tissue becomes stiffer, less dissipative, and less mechanically anisotropic after death. Impact: Our demonstration of significantly different mechanical properties in living versus post-mortem minipig brains is critical to improving computational models of TBI and correctly interpreting their predictions, which have relied on post-mortem measurements of brain material properties for several decades.
Combining Hyperpolarized 129Xe MR Imaging and Spectroscopy to Estimate Pulmonary Vascular Resistance
Authors: Costelle Anna , Mummy David , Lu Junlan , Leewiwatwong Suphachart , Rajagopal Sudarshan , Driehuys Bastiaan
Published: November 2024

Motivation: Pulmonary hypertension (PH) and reduced capillary blood volume, VC’, have competing effects on oscillations of the hyperpolarized 129Xe red blood cell (RBC) resonance, rendering it difficult to distinguish PH. Goal(s): Our goal was to correct RBC oscillations for reduced VC', then use corrected oscillations to estimate pulmonary vascular resistance (PVR). Approach: We developed a model of RBC oscillations as a function of VC’ in a cohort without known PH and used this model to derive a correction factor. Corrected oscillations were regressed against known PVR in a cohort with suspected PH. Results: Corrected oscillations improved PH sensitivity and were significantly correlated to PVR. Impact: Correcting oscillations in the hyperpolarized 129Xe red blood cell resonance for reduced pulmonary capillary blood volume improves sensitivity to pulmonary hypertension and permits estimation of pulmonary vascular resistance, thereby offering a non-invasive diagnostic alternative to right heart catheterization.
Bilateral corticospinal tract asymmetry predicts motor recovery after transcranial direct current stimulation in subacute stroke patients
Authors: Lin Bing-Fong , Yang Wei , Hsu Shih-Pin , Lee I-Hui , Lu Chia-Feng
Published: November 2024

Motivation: A reliable neuroimaging biomarker to predict motor improvement after neuromodulation is lacking. Goal(s): We compared the integrity of bilateral corticospinal tracts and evaluated the asymmetry before tDCS. The association between the motor improvement and pretreatment integrity of the CST was identified to predict motor recovery in subacute stroke patients. Approach: We calculated the asymmetry and fractional anisotropy between bilateral CST. The linear regression analysis was conducted to predict the motor recovery. Results: The patients with more severe motor impairment have higher asymmetry in CST. The tDCS regression models achieved an R2=0.796 and 0.624 for predicting FMA at three months after stroke onset. Impact: The ischemic stroke patients with higher degree of right white matter integrity have better response to neural modulation effects of tDCS treatment. The identified DTI predictors could be the basis for optimizing the treatment protocols of tDCS in stroke patient.
Predicting the onset of ischemic stroke with multi-parametric mapping based on multiple overlapping-echo detachment (MQMOLED) technique
Authors: Ye Ming , Zeng Junbo , Yang Qizhi , Lin Ying , Bao Jianfeng , Zhong Jianhui , Wu Zhigang , Chen Zhong , Cai Congbo , Cai Shuhui
Published: November 2024

Motivation: Multi-parametric quantitative magnetic resonance imaging can characterize tissue properties of ischemic stroke patients noninvasively, but it is generally time consuming and susceptible to motions. Goal(s): Investigate the value of single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MQMOLED) method in distinguishing acute (≤7 days) and non-acute (>7 days) ischemic stroke patients. Approach: MQMOLED was applied on ischemic stroke patients (N = 94) to obtain their T2 and ADC maps, based on which histogram analysis was performed. Results: The combination of histogram parameters of T2 and ADC maps effectively discriminated between acute and non-acute ischemic stroke patients (AUC = 0.928). Impact: The MQMOLED approach shows improvement in predicting acute and non-acute stroke patients. Ultrafast and motion-robust MQMOLED can be included in routine clinical MRI protocols to help patient stratification management for a timely beneficial therapy.
Fluid-Physics Informed Deep-Learning Enabled 2-point Velocity Encoded 4D flow MRI
Authors: Berhane Haben , Maroun Anthony , Baraboo Justin , Allen Bradley , Markl Michael
Published: November 2024

Motivation: 4D Flow MRI enables comprehensive hemodynamic assessments, but its clinical usage is hindered by long scan times. Goal(s): To enable a 2-point velocity encoded 4D flow MRI by using deep-learning to estimate the missing two velocity vector-components, reducing scan time by 50%. Approach: Convolutional neural networks (CNNs) were trained with a single velocity vector-component as input data to generate a 3D velocity vector field (complete 4D flow dataset). CNN performance was evaluated in peak velocity, net and peak flow, and Qp/Qs compared to standard 4D flow MRI. Results: AI-derived 4D flow MRI showed strong-to-excellent agreement to standard 4D flow MRI across all comparisons. Impact: This technique enables reduction of 4D flow MRI scan time and data acquired by 50%. Future work will focus on coupling our method with conventional imaging acceleration techniques to achieve greater scan time reductions and/or improvements in temporal resolution.
Association of Dynamic Contrast Enhanced (DCE) MRI of Abdominal Aortic Aneurysm (AAA) Wall with Progression: A Prospective Study
Authors: Zhou Ang , Dong Huiming , Leach Joseph , Schollenberger Jonas , Zhu Chengcheng , Lee Yoo Jin , Iannuzzi James , Gasper Warren , Saloner David , Mitsouras Dimitrios
Published: November 2024

Motivation: Abdominal Aortic Aneurysms (AAAs) are common, and rupture has >80% mortality. The standard of care is regular surveillance and repair when maximum diameter thresholds are reached. Many ruptures occur before AAA reach these thresholds at surveillance. Goal(s): The goal of this prospective study was to determine if AAA wall contrast kinetics using DCE MRI, presumably associated with inflammatory microvasculature, independently predict progression. Approach: 23 AAA patients were followed over a mean follow-up interval of 14±6 months. Results: Ktrans was significantly associated with progression after controlling for AAA maximum diameter. This suggests that DCE MRI may provide useful information regarding future AAA progression. Impact: Contrast kinetics in AAA wall tissue assessed by DCE MRI may be useful for improving AAA risk stratification.
ODF-Fingerprinting reconstruction of corticospinal tracts for preoperative planning of brain tumor resection
Authors: Filipiak Patryk , Clarke Kamri , Shepherd Timothy , Gondal Saad , Bruno Mary , Placantonakis Dimitris , Baete Steven
Published: November 2024

Motivation: Tractography enables preoperative visualization of major neural pathways altered or displaced by a brain tumor; however, it often fails to reconstruct the cortical terminations of corticospinal tracts due to the complex bending and branching formations of fibers. Goal(s): We aim to improve tracking of corticospinal tracts in their most challenging regions of hand and face projections to the motor cortex. Approach: We refine reconstruction of fibers inside corticospinal tracts by incorporating ODF-Fingerprinting into the tracking pipeline. Results: With ODF-Fingerprinting, we increased the overlap between the reconstructed corticospinal tracts and the cortical regions activated during task-based functional MRI involving hand and face movement. Impact: Our improved reconstruction can help decrease the incidence of postoperative deficits by identifying the structural neural connections that need to be spared during tumor resection.
Dichotomizing Motor and Non-motor Correlates of Cholinergic Network Denervation in Parkinson’s Disease using Correlational Tractography
Authors: Seow Pohchoo , Shih Yao Chia , Hartono Septian , Lee Weiling , Chai Pik Hsien , Chen Celeste , Tan Eng King , Chan Ling Ling
Published: November 2024

Motivation: Cholinergic denervation underlying clinical manifestations in Parkinson’s disease (PD) is complicated. Goal(s): To clarify motor vs non-motor correlates of cholinergic denervation in PD and identify potential novel therapeutic targets. Approach: We evaluated for significant associations between projections of the nucleus basalis of Meynert and pedunculopontine nucleus and motor/non-motor scores using correlational tractography in a case-control PD cohort. Results: Intracellular and extracellular diffusivity demonstrated significant correlations with motor, cognitive and sleep assessment scores in patients. Significantly reduced intra- and extracellular diffusivity of the PPN-cholinergic-motor projection were seen. The cholinergic projections were dichotomized where the most correlated segments innervated ventral posterolateral thalamic nuclei. Impact: The motor and non-motor correlates of cholinergic denervation show potential as objective clinical markers to characterize the PD spectrum while mapping of the cholinergic projection with highest correlation could identify substructure areas as novel stimulation target.
Investigation of Human Brain Parabrachial Nucleus (PBN) - Central Amygdala (CeA) Pathway by Diffusion Tractography
Authors: Kodiweera Chandana , Kim Byeol , Wager Tor
Published: November 2024

Motivation: The parabrachial nucleus (PBN) to the central amygdala (CeA) is a critical pathway for multiple types of aversive, unconditional threat behaviors including chronic pain states in animals. However, there do not exist connectivity studies on this pathway in the human brain by diffusion tractography. Goal(s): Study of connectivity between PBN and CeA by diffusion tractography. Approach: Probabilistic tractography with the ball-and-stick model (FSL) and multi-shell, multi-tissue constrained spherical deconvolution, and fixel-based analysis (MRTRIX). Results: The study showed the existence of a PBN-CeA pathway in the human brain. Average streamline density of this pathway differs across the subjects while the cross section is comparable. Impact: This study has discovered that a PBN-CeA pathway exists in both hemispheres of the human brain, which is consistent with our previous functional connectivity study. This finding will open up new avenues of research on fear conditioning, anxiety, and pain.
Sticks or no sticks? White matter microstructure in multiple sclerosis from high-b scaling
Authors: Coelho Santiago , Stepanov Valentin , Jeet Nalini , Shepherd Timothy , Novikov Dmitry , Fieremans Els
Published: November 2024

Motivation: Representing axons as impermeable sticks is a cornerstone of white matter modeling, e.g. for the Standard Model and related models. However, the validity of this framework in pathology remains unknown. Goal(s): Validate the modeling assumption of axons as impermeable sticks in multiple sclerosis white matter. Approach: We analyze the functional form of the orientationally-averaged signal as a function of b-value up to b=10,000 s/mm2. Results: We find that normal-appearing white matter, T1 black-holes, and T1-hypointense lesions show distinct deviations from the healthy tissue power-law b-1/2 signal scaling. Simulations reveal these deviations may be specific markers for microglia inflammation and unmyelinated leaky axons. Impact: We assess the validity of the modeling assumption of water diffusion along impermeable axons in multiple sclerosis tissue. Pathological processes such as microglial inflammation or demyelination show different behaviors in this experimental regime, highlighting the potential for an imaging biomarker.
White matter changes across the migraine cycle evaluated with Diffusion Tensor Imaging and the impact of Free Water
Authors: Guadilla Irene , Fouto Ana , Planchuelo-Gómez Álvaro , Tristán-Vega Antonio , Ruiz-Tagle Amparo , Esteves Inês , Caetano Gina , Silva Nuno , Vilela Pedro , Gil-Gouveia Raquel , Aja-Fernández Santiago , Figueiredo Patrícia , Nunes Rita
Published: November 2024

Motivation: About 25% of female migraine patients suffer from menstrual-related migraine, which has been poorly studied. Goal(s): To identify white matter alterations across the migraine cycle in patients with episodic menstrual-related migraine without aura. Approach: Diffusion MRI allows to assess alterations in the brain tissue microenvironment. Moreover, including the free-water contribution in the diffusion signal can give information about biological mechanisms, such as inflammation, and more directly expose the tissue alterations by removing free water contamination. Results: Significant differences were found in the diffusion parameters of the white matter tracts of the menstrual-related migraine patients. Impact: We found significant alterations in the diffusion parameters of the white matter tracts of episodic menstrual-related migraine patients across migraine cycle using standard diffusion tensor imaging (DTI) and Free-Water corrected DTI.
In Vivo Monitoring of Renal Tubule Volume Fraction During Acute Tubular Pressure Increase Using Dynamic T2 Mapping
Authors: Tasbihi Ehsan , Gladytz Thomas , Millward Jason M. , Periquito Joāo , Starke Ludger , Waiczies Sonia , Cantow Kathleen , Seeliger Erdmann , Niendorf Thoralf
Published: November 2024

Motivation: The increasing incidence of kidney diseases is a global concern and current biomarkers are inadequate. Changes in renal tubule volume fraction (TVF) may serve as a rapid biomarker for kidney disease and provide a better understanding of renal (patho-)physiology. Goal(s): This study aims to measure TVF in in vivo rat kidney during acute tubular pressure increase. Approach: This study uses the amplitude of the long T2-component as a surrogate for TVF in rats, by applying multiexponential analysis of the T2-driven signal decay. Results: The results demonstrate that our approach is promising for research into quantitative assessment of renal TVF in in vivo applications. Impact: This is the first report on in vivo assessment of relative changes in the renal TVF, which provides a potential rapid, noninvasive marker for kidney disease. This approach will be invaluable for gaining a better mechanistic understanding of renal (patho-)physiology.
Multi-Modal Protein-Engineered Theranostic Fibers: Drug encapsulation, Imaging, and enhanced 19F MRS
Authors: Britton Dustin , Legocki Jakub , Aristizabal Orlando , Mishkit Orin , Liu Chengliang , Jia Sihan , Renfrew Paul , Bonneau Richard , Montclare Jin , Wadghiri Youssef
Published: November 2024

Motivation: Theranostic materials allows for simultaneous therapeutic and diagnostic disease intervention. Goal(s): We aimed to engineer a protein-based theranostic with multiple imaging modalities. Approach: Using noncannonical amino acid incorporation of trifluoroleucine (TFL), we synthesize fluorinated coiled-coil, Q2TFL, imageable by 1H MRI and high-frequency ultrasound, and sensitive to 19F MRS. Results: Q2TFL demonstrates reduced signal contrast in 1H MRI, echogenic signals under high-frequency ultrasound, and enhances sensitivity in linear ratiometric 19F MRS. This allows for thermoresponsiveness and potential protein conformation analysis. Q2TFL serves as a promising platform for versatile and effective theranostic agents, bringing together therapeutic and diagnostic modalities in a compact and efficient manner. Impact: Q2TFL, a fluorinated protein fiber, enables drug delivery and offers unique multimodal imaging. It acts as a temperature probe and protein structure monitor, paving the way for innovative theranostic biomaterials.
Metabolic detection of BTK inhibition in mantle cell lymphoma models
Authors: Nath Kavindra , Gupta Pradeep , Orlovskiy Stepan , Sen Neil , Wang Shengchun , Tomar Jyoti , Nelson David , Arias-Mendoza Fernando , Glickson Jerry , Wasik Mariusz
Published: November 2024

Motivation: The current approaches to assess Bruton’s kinase inhibitor (BTK) therapeutic effects in cancer are not ideal. Goal(s): Employing metabolic imaging, we evaluated the mode of action of ibrutinib (IBR), a BTK inhibitor, in mantle cell lymphoma (MCL) cells and xenografts. Approach: Our approach using 1H MRS demonstrated that, in sensitive MCL models, IBR significantly impacted critical metabolic pathways, including glycolysis, glutaminolysis, and phospholipid metabolism, but had far less of an impact on IBR-poorly responsive cells. Results: Changes in 1H MRS detectable lactate, alanine, and choline concentrations on various MCL models emerged as promising biomarkers of response or resistance to IBR. Impact: Decreased intra-tumoral concentrations of lactate, alanine, and choline measured by 1H MRS during treatment can potentially become early and sensitive biomarkers of BTK inhibition in MCL and, likely, other lymphoma treatments.
Multifunctional Nanocomposite for Enhanced Diagnosis and Therapeutic Intervention in Breast Cancer via T1-T2 dual-enhanced and NIR II imaging
Authors: Guan Xiuhong , Huang Xin , Wang Zhiyong , Xie Guoxi , He Ci
Published: November 2024

Motivation: Breast cancer exhibits high incidence and mortality rates. We reports a functional nanosystem composed of Pluronic F127, manganese chloride (MnCl2), and IR780 dye. The nanosystem possesses multimodal imaging capabilities using near-infrared II (NIR-II) and T1-T2 dual-enhanced MRI, guiding photothermal therapy, and enhancing the STING pathway to combat triple-negative breast cancer. Goal(s): Effectively suppress TNBC growth and metastasis, with good biocompatibility.. Approach: MC@NS nanosystem could diagnose the tumor and confirm the time window of treatment via NIR II/MRI dual-modal imaging, and effectively suppress tumor growth thought phototherapy, STING pathway and anti-tumor immunity. Results: It effectively suppress tumor growth thought phototherapy, STING pathway and immunotherapy. Impact: This nanosystem, through T1-T2 dual-enhanced MRI and NIR II multimodal imaging, enabled tumor diagnosis and guided photothermal therapy, effectively suppressing tumor growth by combining photothermal therapy and STING pathway to enhance immunogenic cell death, providing a novel theranostic strategy.
An AI-Based Solution for MR Image Analysis of the Female Reproductive System
Authors: Khaghani Javad , Khallaghi Siavash , Basar Saqib , Chodakiewitz Yosef , Attariwala Rajpaul , Hashemi Sam
Published: November 2024

Motivation: To quantify female reproductive anatomy in MR imaging. Goal(s): To develop an AI-based solution to segment the regions of interest (RoIs) for the uterine zone, ovaries, pelvic fluid, and detect benign uterine conditions. Approach: A deep learning based method is applied on a large representative population of 9334 sagittal T2-weighted female pelvis scans to extract normative menstrual cycle- and aging-curves for various RoIs. Results: Our proposed normative curves define the standard menstrual cycle and aging trends. RoI segmentation, fibroid, and cyst detection models achieve average foreground dice, specificity and accuracy scores of 83.9%, 95.2% and 94.37%, respectively. Impact: Proposing a robust, precise AI solution for analyzing female reproductive organs on MR imaging, including uterine zones, ovaries, pelvic fluid, and fibroids/cysts. Using this, we define standard aging and menstrual cycle curves for women.
APTw Combined with Multiple Models DWI of Endometrial Cancer: Correlations between Multimodal Parameters and HIF-1α Expression
Authors: Ma Changjun , Tian Shifeng , Song Qingling , Chen Lihua , Lin Liangjie , Wang Jiazheng , Liu Ailian
Published: November 2024

Motivation: Hypoxia inducible factor (HIF-1α) is a major transcriptional factor regulating gene expression under hypoxic conditions and could serve as an important biomarker for tumor aggressiveness or radiation resistance. Goal(s): This study aimed to investigate whether the multimodal functional MRI technique can be used for quantitatively measuring HIF-1α expression. Approach: APT, ADC, D, D*, f, MK, and MD values were calculated and compared between HIF-1α high expression and HIF-1α low expression groups. Results: APT, ADC, D, D*, MK and MD values were significantly higher in high HIF-1α expression than in low HIF-1α expression groups, whereas f value was significantly lower in high HIF-1α expression . Impact: The quantitative parameters of APTw combined with multi-model diffusion-weighted sequences allowed quantitative assessment of EC HIF-1α expression, and the combined quantitative parameters further enhanced the assessment efficacy.
Data-driven Electrical Conductivity Reconstructions via transceive phase and signal magnitude gradient data from the three imaging directions
Authors: Park Chan-Hee , Meerbothe Thierry , Jung Kyu-Jin , Cui Chuanjiang , Park Mina , Nam Yoonho , van den Berg Cornelis , Mandija Stefano , Kim Dong-Hyun
Published: November 2024

Motivation: Phase-based conductivity reconstructions suffer from poor structural information and lack of conductivity information from through plane (z-direction) phase variations. Goal(s): To present an end-to-end process that utilizes gradient information from the transceive phase and tissue magnitude in all three directions (in-plane: x/y and through plane: z) to address the issue of boundary artifacts in conductivity reconstructions and lack of conductivity information from the z-direction. Approach: This method was trained on simulated data (SNR=50), and tested both on simulated and measured in-vivo data. Results: This approach reduces boundary errors and shows higher accuracy in conductivity reconstructions compared to conventional methods. Impact: In contrast to existing tissue conductivity reconstruction algorithms that operate under the assumption of negligible through-plane (z) transceive phase contributions, our approach demonstrates enhanced efficacy and more accurate conductivity reconstructions by explicitly considering through-plane phase variations.
Predicting VETC in Hepatocellular Carcinoma Using Radiomic Features from Peritumoral Mechanical Strain Assessed by MR Elastography
Authors: Zheng Keni , Li Mengsi , Sui Yi , Shan Xiang , Hojo Emi , Manduca Armando , Ehman Richard , Wang Jin , Yin Ziying
Published: November 2024

Motivation: Vessels encapsulating tumor clusters (VETC) is a powerful indicator of aggressive Hepatocellular carcinoma (HCC) associated with recurrence, which is expected to be noninvasively identified using imaging techniques. Goal(s): This study aims to develop a potential mechanical biomarker utilizing radiomics features extracted from MR Elastography (MRE)-assesed peritumoral shear strain to predict VETC in HCC. Approach: Radiomics features were extracted from the tumor boundary on an octahedral shear strain (OSS) map. Feature selection techniques were used to identify relevant features to construct a radiomics score. Results: Three radiomics features were utilized to construct a radiomics score, demonstrating potential for MRE-based strain analysis in predicting VETC. Impact: A radiomics score constructed by radiomics features derived from MRE-based strain analysis in the peritumoral region show promise in predicting VETC in HCC patients. This study results show non-invasive VETC prediction potential in HCC, impacting personalized treatment and patient outcomes.
Value of quantitative relaxation mapping calculated from Multiple-Repetition Multiple-Echo DWI acquisition in prostate cancer detection
Authors: Tamada Tsutomu , Ueda Yu , Takeuchi Mitsuru , Higaki Atsushi , Kojima Yuichi , Fukukura Yoshihiko , Yamamoto Akira
Published: November 2024

Motivation: The detection rate of csPCa in PI-RADS 3 lesions is only 25-38%. This leads to unnecessary biopsies. Goal(s): Can multiparametric quantitative maps based on estimated T1 and T2 help differentiate clinically significant prostate cancer (csPCa) from non-csPCa in PI-RADS 3 lesions?Approach: We compare T1, T2, and ADC obtained from Multiple-Repetition time Multiple- Echo time (MRME) based DWI (MRME-DWI) between csPCas and non-csPCas in PI-RADS 3 lesion using MRI-ultrasound fusion targeted biopsy as the reference standard. Results: The T1, T2, and ADC were significantly lower for csPCas than non-csPCas. Combining these indices yields an AUC of 0.82. Impact: MRME-DWI can simultaneously obtain T1, T2, and ADC from a single region of interest in a single imaging session. Combining these quantitative measures is expected to improve the detection rate of clinically significant prostate cancer in PI-RADS 3 lesions.
Estimating diffusion fractional anisotropy of disease in patients with advanced prostate and breast cancers. A single-center study.
Authors: Yu Sheng , Candito Antonio , Zormpas-Petridis Konstantinos , Ribeiro Ana , Hopkinson Georgina , Winfield Jessica , Tunariu Nina , Messiou Christina , Koh Dow-Mu , Blackledge Matthew
Published: November 2024

Motivation: Whole-body diffusion-weighted imaging in oncology assumes isotropic diffusion therefore that data probing the directional dependence of diffusion in body cancer applications is scarce. Goal(s): To report the distribution of fractional anisotropy (FA) values in metastatic bone disease for a cohort of patients who underwent multi-directional diffusion weighted imaging. Approach: Deep learning was used to auto-segment metastatic lesions; FA values are calculated for each segmented region and the distributions reported. Results: FA distributions from 85 patients with metastatic disease (50 prostate, 33 breast) are reported and are deemed to be low (mean FA range breast group: 0.2179 - 0.3132; prostate group: 0.2866 - 0.3717). Impact: We have conducted diffusion tensor imaging analysis for whole body DWI data and carried out the first bone lesion FA comparison study. This work provides a rationale for choice of diffusion-weighting gradient schemes in clinical imaging.
Predictive value of mono-exponential and mathematical models in rectal cancer responsiveness to neoadjuvant chemoradiotherapy
Authors: Zhou Mi , Chen Meining , Zhang Qin , Yin Longlin
Published: November 2024

Motivation: Although it is challenging to predict LARC responsiveness to nCRT, the potential of emerging non-Gaussian DWI models for this purpose remains unexplored. Goal(s): To assess the efficacies of mono-exponential ADC and various non-Gaussian DWI models, including SEM, FROC, and CTRW, in predicting LARC responsiveness to nCRT. Approach: This prospective study included 103 LARC patients. Various DWI models were assessed, and post-surgery histopathology was utilized to classify patients based on responsiveness to nCRT. Results: Non-Gaussian models, especially CTRW parameters, demonstrated robust capacity to predict both pCR and T-downstaging. The combination of CTRW parameters yielded the best diagnostic performance. Impact: This study demonstrated the potential for novel non-Gaussian DWI models to enhance predictions of LARC responsiveness to nCRT, facilitating optimized treatment plans and encouraging further research in precision oncology.
Astrocytes contribute to signals of Hyperpolarized 13C pyruvate in the brain
Authors: Ono Maiko , Wulaer Bolati , Yamasaki Tomoteru , Sakamoto Toshihiro , Araki Rikita , Hirata Kosei , Saito Keita , Takakusagi Yoichi , Zhan Ming-Ron , Nagai Jun , Takado Yuhei
Published: November 2024

Motivation: Hyperpolarized MR (HP-MR) 13C pyruvate is a valuable probe for evaluating glycolytic flux, but it remains unknown which cells contribute to the HP-MR signals in the brain. Goal(s): To verify whether astrocyte metabolism is involved in the signal of HP-MR 13C pyruvate in the brain. Approach: We perturbed Gq-GPCR/calcium (Ca2+) signaling in astrocytes using the hM3Dq DREADD system and examined the fluctuations of the HP-MR pyruvate signals in awake mice. Results: In HP-MR experiments conducted 30 minutes after the elevation of astrocyte Ca2+, the lactate/pyruvate ratio decreased compared to the control, and the bicarbonate/pyruvate ratio also decreased. Impact: Investigating the involvement of astrocyte metabolism in brain hyperpolarized MR(HP-MR) 13C pyruvate signals, astrocyte GPCR/Ca2+ signaling was perturbed using DREADD, revealing a decrease in lactate/pyruvate and bicarbonate/pyruvate ratios in HP-MR experiments, suggesting metabolic alterations in response to astrocyte GPCR/Ca2+ modulation.
First in-human MR Metabolic Imaging of the Brain Using Hyperpolarized [1-13C]alpha-ketoglutarate
Authors: Kim Yaewon , Dang Duy , Slater James , Riselli Andrew , Gordon Jeremy , Chang Susan , Li Yan , Autry Adam , Lafontaine Marisa , Escobar Evelyn , Chen Hsin-Yu , Tan Chou , Suszczynski Chris , Bok Robert , Vigneron Daniel
Published: November 2024

Motivation: Isocitrate dehydrogenase (IDH) mutational status is crucial for accurate diagnosis and prognosis of malignant gliomas. However, the current clinical assessment of IDH mutation requires an invasive brain biopsy for pathological testing. Goal(s): We aimed to perform first in-human MR studies using hyperpolarized [1-13C]alpha-ketoglutarate as a new probe of IDH mutational status via cancer metabolic reprogramming, along with cerebral bioenergetics. Approach: We acquired 13C MRS data from healthy brain volunteers (N=6) and glioma patients (N=6) who received hyperpolarized aKG. Results: Feasibility and safety were demonstrated in these 12 studies, with signals observed from [1-13C]alpha-ketoglutarate and its metabolite glutamate in the obtained 13C MRS data. Impact: MR molecular imaging with the new probe hyperpolarized [1-13C]alpha-ketoglutarate provided novel measurements of aKG metabolism and can investigate glioma IDH mutational status by detecting glutamate or the oncometabolite, 2-hydroxyglutarate.
Deuterium metabolic imaging detects early treatment response to mitochondrial complex 1 inhibition
Authors: Low Jacob , Cao Jianbo , Hesse Friederike , Wright Alan , Brindle Kevin
Published: November 2024

Motivation: The oxidative subtype of glioblastoma (GB) has potential mitochondrial therapeutic vulnerabilities that can be targeted for treatment. Goal(s): To detect early response to a mitochondrial complex 1 inhibitor, IACS-010759, using deuterium metabolic imaging (DMI). Approach: Measurements of oxygen consumption, extracellular acidification rate and 2H-labelled lactate production in GB cell suspensions in vitro and 2H-labelled lactate and Glx production from [6,6’-2H2]glucose in GB xenografts in vivo, pre- and post-treatment. Results: DMI detects an in vivo response to treatment with IACS-010759 from measurements of decreased 2H-labeled Glx production and increased 2H-labeled lactate production. Impact: Deuterium metabolic imaging can be used to detect the early response of a glioblastoma model to treatment with a mitochondrial complex 1 inhibitor.
Cardiac Diffusion in Python (CarDpy): An Open-Source Toolbox for Cardiac Diffusion Tensor Data Processing
Authors: Cork Tyler , Hannum Ariel , Loecher Michael , Ennis Daniel
Published: November 2024

Motivation: cDTI provides several new and useful MRI biomarkers, but robust and reliable data processing pipelines are still needed to adequately handle cDTI data. Goal(s): Goal: To demonstrate the benefits of an open-source Python cDTI data processing toolbox and its impact on measurement accuracy and precision. Approach: A direct averaging and tensor-fitting data processing technique was compared to our open-source data processing pipeline. Data from healthy subjects was used to demonstrate improvements in the accuracy and uncertainty of cDTI metrics. Results: Our open-source cDTI data processing toolbox provides smoother parametric maps that are more accurate with less uncertainty compared to direct averaging and tensor-fitting. Impact: Development of Cardiac Diffusion in Python (CarDpy), an open-source python toolbox for cardiac diffusion tensor imaging (cDTI) data processing to facilitate reproducible cDTI research for new and established researchers. A strong foundation, plus software modularity encourages contributions from the community.
A repository-integrated framework for rapid clinical analysis of MR-derived hypoxia maps.
Authors: Cristinacce Penny Hubbard , Gill Andrew , Birchall Jonathan , Keaveney Sam , Berks Michael , Kim Mina , Gallagher Edith , Grist James , Markus Julia , Doran Simon , Little Ross , McGowan Daniel , Higgins Geoff , O'Connor James , Parker Geoff , Roach Joy
Published: November 2024

Motivation: Translation of quantitative biomarkers requires a reproducible and efficient analysis environment to underpin assessments of clinical utility. Goal(s): This study aimed to provide a 24-hour turnaround of clinically relevant MR-derived hypoxia maps for use in biopsy planning. Approach: The analysis framework was integrated into an XNAT imaging repository and applied to oxygen-enhanced and dynamic-contrast-enhanced images to quantify and map the extent of hypoxia within low-grade glioma. Results: A group of geo-dispersed researchers consistently delivered MR-derived hypoxia maps to the clinical study team for use alongside 18F-FDOPA PET in biopsy site definition prior to surgery. Impact: A framework of repository-integrated analysis enabled rapid turnaround of quantitative MR imaging biomarkers for clinical decision-making. Specifically, biopsy-planning using MR-derived hypoxia mapping of low-grade glioma was delivered with standardised, reproducible, auditable results in under 24 hours.
The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): A Challenge for Reproducible DCE-MRI AI-based Analysis
Authors: Kargar Soudabeh , Kershaw Lucy , Kazerooni Anahita Fathi , Bell Laura , Van der Heijden Rianne , Mutsaerts Henk-Jan , Gurney-Champion Oliver , Shalom Eve , Paschoal Andre , Jen Mu-Lan , Hoodeshenas Safa , Serkova Natalie , Van Houdt Petra , Suzuki Yuriko , Kim Harrison
Published: November 2024

Motivation: There is a need for reproducibility, repeatability, and accuracy. Previously, OSIPI organized a challenge for benchmarking DCE software. As the use of artificial intelligence grows, we now set out to repeat the challenge, focusing on deep learning techniques. Goal(s): To encourage researchers put their quantitative methods to test and stimulate collaboration and to charter the heterogeneity of DCE analysis software. Approach: To use deep learning techniques to estimate perfusion parameters in DCE-MRI of the uterus. We share repeated in-vivo data to assess the algorithm’s precision, and simulated DCE-data to test the accuracy. Results: Top three winners may present their method at ISMRM 2025. Impact: As quantitative perfusion MRI receives more importance and attention, the need for reproducibility, repeatability, and accuracy is inevitable. A public challenge within the MRI community is a great way to highlight the quantification of DCE-MRI.
TensorFit: an open-source tool for fast MRS metabolite quantification.
Authors: Turco Federico , Slotboom Johannes
Published: November 2024

Motivation: Addressing the time constraints in Magnetic Resonance Spectroscopy (MRS) metabolite quantification, TensorFit aims to overcome processing delays hindering clinical use. Goal(s): TensorFit seeks to accelerate MRS analysis with a strong focus in time efficiency, using GPU acceleration, and modeling capabilities within the Torch framework. Approach: Implemented in Python, employs Torch for efficient forward- and back-propagation, allowing rapid quantification of large datasets. It supports GPU usage, and integration with SpectrIm-QMRS for clinical practices. Results: TensorFit achieves speed-ups surpassing existing methods by up to 200x on GPU and 17x on CPU, making it a powerful tool for metabolite quantification in EPSI data. Impact: TensorFit speed-up MRS metabolite quantification in clinical practices, enabling ultra-fast analysis. This tool could lead to enhance the use of high-resolution MRS adquisition for both research and clinical practices.
Metabolite-cycling at 14.1T: sequence implementation and initial explorations using SPECIAL and diffusion-weighted SPECIAL
Authors: Mosso Jessie , Döring André , Kreis Roland , Cudalbu Cristina , Lanz Bernard
Published: November 2024

Motivation: Water suppression leads to saturation of exchanging protons which biases metabolite concentration estimates and prevents the study of downfield resonances in the 1H spectrum. Goal(s): Apply metabolite-cycling (MC) to study these resonances with high sensitivity using the short-TE, full-intensity SPECIAL sequence at ultra-high field on an animal scanner. Approach: The MC pulse was optimized for 14.1T. MC SPECIAL and MC diffusion-weighted SPECIAL were implemented and tested in vivo. Results: Underestimation of specific upfield metabolite concentrations with water-suppressed SPECIAL compared to MC SPECIAL was observed. Downfield resonances attribution was further validated with diffusion-weighted acquisitions, uniquely showing the presence of macromolecules in the 6.5-7.5ppm region. Impact: The introduction of metabolite-cycling in the short echo-time, full intensity SPECIAL and diffusion-weighted SPECIAL 1H MRS sequences at 14.1T paves the way for in-depth exploration of the downfield resonances of the 1H spectrum with high sensitivity on animal scanners.
Robust Volumetric Diffusion-Weighted MRSI via Time-Resolved Phase Reconstruction and Correction
Authors: Wang Zepeng , Sutton Bradley , Lam Fan
Published: November 2024

Motivation: To address the long-standing phase correction challenge and enhance the robustness for diffusion-weighted MRSI. Goal(s): To correct the significant phase variations due to macroscopic and microscopic motions in in vivo diffusion-weighted MRSI acquisition. Approach: We developed a novel fast diffusion-weighted MRSI sequence integrating time-resolved, sparsely sampled, volumetric phase navigators, a subspace-based phase image reconstruction, and a sensitivity-encoded phase-corrected reconstruction. The corrected diffusion-weighted MRSI data were processed by state-of-the-art subspace-based spatiospectral processing methods. Results: Improved data quality, diffusion-weighted spatiospectral reconstruction and metabolite-specific diffusion parameter estimation achieved by the proposed method are demonstrated using in vivo data. Impact: A novel integrative acquisition and reconstruction solution for robust, phase-corrected 3D in vivo diffusion-weighted MRSI was presented, an important step towards developing diffusion-weighted MRSI for its translation to quantitative, molecule-specific microstructural imaging.
A deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression
Authors: Lee Wonil , Zhuo Yue , Marin Thibault , Han Paul , Chi Didi , El Fakhri Georges , Ma Chao
Published: November 2024

Motivation: Unsuppressed water and lipid signals are several orders of magnitude stronger than the metabolite signals in MRSI, imposing significant challenges in MRSI data processing and image reconstruction. Goal(s): To develop a novel deep learning-based method for nuisance signal removal from MRSI data acquired without suppression. Approach: A neural network with a U-net structure was designed to remove nuisance signals in MRSI, where the input of the network was the Hankel matrix formed by the time-domain MRSI signal. Results: The proposed method was validated using in vivo MRSI data, showing superior performance over the conventional method. Impact: A deep learning-based method is proposed for nuisance signal removal in MRSI. It could enable MRSI without water or lipid suppression with robust performance in practical settings.
3D MR Fingerprinting for Prostate at 0.55 T
Authors: Freites Jesus Ernesto Fajardo , Kaur Tejinder , Cruz Gastao , Seiberlich Nicole , Gulani Vikas , Jiang Yun
Published: November 2024

Motivation: 0.55 T MRI scanners have lower fields inhomogeneities and bigger bore size when compared to higher fields, allowing to scan larger body habitus patients, and to perform MRI-guided biopsies. Goal(s): To generate 1x1x3 mm3 T1 and T2 maps of the prostate and T1 and T2 weighted images with improved contrast from MRF at 0.55 T. Approach: We use a 3D MRF-FISP sequence with Stack of Spirals acquisition and a low-rank denoising method. Results: We show T1 and T2 maps and T1 and T2 weighted images and report on values for the prostate NPZ and NTZ of 5 subjects and for a biopsy-confirmed lesion. Impact: Implementing prostate MR Fingerprinting at 0.55 T, allows multiparametric quantitative assessment of the gland while gaining advantages that 0.55 T scanners offer respect to higher field ones. This includes lower fields inhomogeneities, bigger bore size and a lower equipment cost.