| Computer # |
| 1482.
 | 81 | Feasibility of T2 mapping for the detection of myocardial injury in hypertrophic cardiomyopathy Shujuan Yang1 and Shihua Zhao1
1Fuwai Hospital, Beijing, China Keywords: Myocardium, Cardiomyopathy Motivation: The relationship between T2 value and myocardial injury has not been well demonstrated. Goal(s): To explore the association between T2 value and myocardial injury in HCM patients. Approach: 50 patients with HCM were prospectively recruited. Hs-cTnI was obtained as a marker of myocardial injury (>0.016ng/mL). ConSept T2 were measured from the maximal value of 16 segments and the middle septum. Results: The hs-cTnI elevated group had higher T2 global, ConSept T2, T2 max(P<0.05) than the normal hs-cTnI group. The ConSept T2 value were moderately correlated with hs-cTnI(r=0.52, P<0.001). In logistic regression analysis, ConSept T2 value was significantly associated with elevated hs-cTnI(P<0.01) Impact: This study provided
in-vivo evidence by CMR for the ongoing myocardial injury in HCM. |
| 1483.
 | 82 | Free breathing Dual-excitation flip-angle 3D T1 mapping using randomized stack of spiral acquisition Xitong Wang1, Ruixi Zhou2, Yang Yang3, and Michael Salerno1
1Stanford University, Stanford, CA, United States, 2Beijing University of Posts and Telecommunications, Beijing, China, 3University of California, San Francisco, San Francisco, CA, United States Keywords: Myocardium, Quantitative Imaging Motivation: Cardiac MR (CMR) imaging is a widely used technique that provides important diagnostic and prognostic information in cardiomyopathy. T1 maps and LGE can provide tissue characterization to detect myocardial fibrosis. Goal(s): Our group has developed a 2D free-breathing and self-gated cine and T1 mapping acquisition CAT-SPARCS. This work is to extend the acquisition to 3D T1 mapping. Approach: The proposed acquisition is enabled in a single free-running randomized stack of spiral sequence with a 3-minute acquisition and T1 map is reconstructed by dictionary learning method. Results: The T1 values from the proposed method are comparable to the clinically standard MOLLI sequence. Impact: Our technique could substantially shorten the clinical scan time providing both cine and T1 mapping images. |
| 1484.
 | 83 | Cardiovascular MR Multitasking T1-T2 Joint Mapping in Healthy Subjects and Cardiomyopathy Patients on both 1.5T and 3T Xianglun Mao1, Hsu-Lei Lee2, Katerina Eyre3, Debiao Li2,4, Anthony G Christodoulou4,5, Matthias G Friedrich3,6, Michael Salerno7, and Martin A Janich8
1Applied Science Lab West, GE HealthCare, Menlo Park, CA, United States, 2Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 3McGill University Health Centre, Mentreal, QC, Canada, 4Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, 5Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States, 6Area 19, Montreal, QC, Canada, 7Departments of Medicine and Radiology, Stanford University, Palo Alto, CA, United States, 8Applied Science Lab Europe, GE HealthCare, Munich, Germany Keywords: Myocardium, Quantitative Imaging, Free-breathing, Multi-parametric Mapping Motivation: CMR Multitasking has shown promise for non-ECG and free-breathing myocardial T1/T2 mapping in the heart, primarily on a single vendor 3T, but 2D T1-T2 CMR Multitasking has not yet been shown for different vendors (e.g., GE) and field strengths (e.g., 1.5T). Goal(s): To extend 2D T1-T2 CMR Multitasking to 1.5T and 3.0T GE MR systems. Approach: We implemented a 2D T1-T2 CMR Multitasking sequence on GE MR systems and evaluated its performance in healthy volunteers and patients at two sites. Results: 2D T1-T2 CMR Multitasking generated T1 and T2 maps with image quality comparable to the reference measurements. Impact: 2D T1-T2 CMR Multitasking provides an efficient and subject friendly (free-breathing, non-ECG) option for quantitative CMR assessment across sites and vendors. |
| 1485.
 | 84 | Added value of T1 mapping derived phenotypes and polygenic risk score (PRS) for the prediction of common cardiac diseases Meng Liu1, Shuo Wang2, Mengyao Yu1, Longyu Sun1, Mengting Sun1, Xumei Hu1, Qing Li1, Xinyu Zhang1, Yinghua Chu3, and Chengyan Wang1
1Human Phenome Institute, Fudan university, Shanghai, China, 2Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China, 3Simens Healthineers Ltd, Shanghai, China Keywords: Myocardium, Myocardium, cardiac diseases Motivation: Limited attention has been given to the evaluation of the predictive capacity of T1 mapping in the context of cardiac diseases in the present. Goal(s): To improve clinical diagnostic precision by integrating T1 value of different AHA segments into the prediction model and find the important AHA segments for cardiac diseases prediction. Approach: Our study employed nnU-Net to segment T1 mapping images, then to quantify T1 values of AHA segments to establish a hybrid prediction model for some common cardiac diseases. Results: The results demonstrate that the incorporation of the hybrid prediction model with T1 mapping leads to enhanced performance.
Impact: The added value of T1
mapping enhanced the performance of the common cardiac disease prediction model.
It empowered clinicians to identify potential cardiac issues earlier and making
clinicians pay more attention to certain AHA segments of the cardiac diseases. |
| 1486.
 | 85 | A deep learning-based approach for automatic myocardial T1 map analysis Jiahuan Dai1, Ancong Wang1, Yingwei Fan1, Yafeng Li2, Yongsheng Jin3, Haiyan Ding 4, Xiaoying Tang1, and Rui Guo1
1Shool of Medical Technology, Beijing Institute of Technology, Beijing, China, 2China Electronics Harvest Technology Co.,Ltd, Beijing, China, 3Department of Infectious Diseases, The Affiliated Hospital of Yan’an University, Yan’an, Shanxi, China, Beijing, China, 4Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, Beijing, China Keywords: Myocardium, Myocardium, deep learning Motivation: In cardiovascular magnetic resonance, T1 analysis is generally completed in a manual manner, which is a labor-intensive and time-consuming procedure and could be automated by deep-learning algorithms. Goal(s): This study aims to develop a deep learning-based technique for directly analyzing T1 for a T1 map. Approach: We built a cascaded neural network to predict T1 of the left-ventricle myocardium, septum, blood, and AHA segments and generate LV mask to improve performance. Results: The automatic T1 analysis performed by the proposed approach had good agreement with manual analysis. The mean difference was ~10 ms. Impact: The proposed approach could automatically estimate the left ventricle, septum, and blood T1. Along with automatic motion correction and T1 calculation algorithms, the proposed approach could further simplify and improve the automatization of the workflow of myocardial T1 mapping examination. |
| 1487.
 | 86 | Free-breathing 3D whole-heart simultaneous bright- and black-blood anatomical imaging and T1/T2 mapping at 0.55T Ivan Kokhanovskyi1,2,3,4, Carlos Castillo-Passi3,4,5, Michael G. Crabb3, Carl Ganter1, Karl P. Kunze3,6, Radhouene Neji3, Dimitrios Karampinos1, Marcus R. Makowski1,2, Claudia Prieto3,4,7, and Rene M. Botnar2,3,4,5,7
1Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany, 2Institute for Advanced Study, Technical University of Munich, Munich, Germany, 3School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 4Millenium Institute for intelligent Healthcare Engineering, Santiago, Chile, 5Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 6MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom, 7School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile Keywords: Myocardium, Heart, Bright- and black-blood imaging, T1/T2 mapping Motivation: To overcome the limitations of clinical examinations, which require several sequential acquisitions under multiple breath-holds, and to make cardiac MR more accessible and affordable at lower field strength. Goal(s): To develop a novel 3D free-breathing sequence for simultaneous assessment of cardiovascular anatomy via bright- and black-blood imaging and myocardial tissue quantification in an easy to use one-click-scan at 0.55T. Approach: Implementation of a novel iNAV-based 5-heartbeat interleaved sequence (proACTION) with distinct IR and T2 preparation modules and non-rigid motion correction at 0.55T. Results: proACTION provides good delineation of cardiac and vascular structures with accurate joint T1/T2 parametrical mapping in healthy subjects. Impact: Comprehensive 3D whole-heart evaluation of cardiovascular anatomy and tissue characterization with T1/T2 maps can be obtained in an efficient, free-breathing, and easier to use one-click-scan with proACTION at 0.55T. |
| 1488.
 | 87 | Native T1 Mapping Radiomics for Classifying Severity of Pulmonary Regurgitation in Patients with Repaired Tetralogy of Fallot Jo-Hua Peng1, Ming-Ting Wu2, Nai-Yu Pan3, Teng-Yi Huang3, Yi-Jui Liu4, Ken-Pen Weng5,6, and Hsu-Hsia Peng1
1Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, 2Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan, 3Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, 4Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, 5Department of Pediatrics, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan, 6Dpartment of Pediatrics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan Keywords: Myocardium, Radiomics Motivation: Pulmonary regurgitation (PR) severity is an important prognostic indicator in repaired Tetralogy of Fallot (rTOF) patients. Radiomics analysis may reveal hidden information about cardiomyopathy in these patients. Goal(s): This study aimed to develop a radiomics-based classification model by native T1 mapping to identify rTOF patients with moderate-to-severe PR and severe PR. Approach: A total of 623 radiomic features were extracted from native T1 mapping. We used machine learning for feature selection to identify the best radiomic features that maximize the diagnostic value for classifying cardiac diseases. Results: Optimal performance was achieved in the proposed segmental mid-slice T1 mapping model. Impact: The segmental mid-slice radiomics of native T1 mapping showed better classification performance than conventional native T1 values in identifying rTOF patients with moderate-to-severe PR and severe PR. The discerned tissue characteristics offered additional physiopathological information beyond native T1 values. |
| 1489.
 | 88 | Characristics of left ventricular T1 mapping and left atrial strain for distinguishing myocardial amyloidosis and hypertrophic cardiomyopathy Honghu Shen1, Jianxiu Lian2, Xinyu Zhu1, Lin Wang1, and Pengfei Liu1
1The First Affiliated Hospital of Harbin Medical University, Harbin, China, 2Philips Healthcare, Beijing, China Keywords: Myocardium, Cardiomyopathy, T1mapping;feature tracking;strain Motivation: Left ventricular hypertrophy（LVH）is a common manifestation of many cardiac diseases, including myocardial amyloidosis (CA), hypertrophic cardiomyopathy (HCM), among others. Clinical diagnosis of the etiology of LVH has some difficulties Goal(s): Differences in myocardial T1 values and left atrial strain between CA and HCM patients remain unclear Approach: In this study, T1mapping and feature tracking based on left atrial were applied to identify CA and HCM Results: Results illustrated that T1 values and left atrial strain were significantly different between CA and HCM. T1 mapping combined with left atrial reservoir function (Εs) could effectively distinguish CA from HCM. Impact: T1mapping
and feature tracking techniques, as emerging imaging techniques in cardiac
magnetic resonance(CMR) in recent years, have been widely used in the study of
various myocardial diseases because they do not require the injection of
contrast agents. |
| 1490.
 | 89 | A Study on the Feasibility and Accuracy of Rapid T1 Mapping Utilizing Deep Learning Techniques in Cardiac Magnetic Resonance Imaging Weisu Li1, Fan Yang2, Jing Li1, Junpu Hu3, Jian Xu4, Qing Liu1, and Dong Li2
1Tianjin Beichen Hospital, Tianjin, China, 2Tianjin Medical University General Hospital, Tianjin, China, 3United Imaging Healthcare, Shanghai, China, 4United Imaging Healthcare, Houston, TX, United States Keywords: Myocardium, Quantitative Imaging, T1 Map,Deep Learning,MOLLI Motivation: To overcome limitations of prolonged acquisition and breath-hold(BH) times in Cardiac Magnetic Resonance Imaging (CMR), specifically MOLLI sequence, enhance patient comfort and compliance. Goal(s): Aimed to validate MyoMapNet sequence with inline reconstruction against the standard MOLLI protocol, focusing on image quality and T1 measurement accuracy, reducing scan time and BH durations. Approach: 20 subjects were imaged using two sequences. Image quality was assessed via edge sharpness and signal intensity ratios,T1 accuracy was determined through myocardial segment analysis. Results: MyoMapNet achieved comparable image quality and T1 accuracy to MOLLI with shorter acquisition times, demonstrating no significant difference in myocardial and blood pool T1 values. Impact: MyoMapNet offers a rapid and reliable alternative for
myocardial T1 mapping, reducing scan time and heart rate dependence, which can
improve patient throughput and comfort in clinical CMR workflows. Future
studies will expand to post-contrast T1 values and ECVs. |
| 1491.
 | 90 | A self-supervised motion-correction approach for cardiac T1 mapping Yu Lian1, Zixing Liu2, Ancong Wang1, Yingwei Fan1, Haiyan Ding3, Xiaoying Tang1, and Rui Guo1
1School of Medical Technology, Beijing Institute of Technology, Beijing, China, 2School of Life Science, Beijing Institute of Technology, Beijing, China, 3Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China Keywords: Myocardium, Myocardium Motivation: Deep-learning algorithm has the potential to alleviate the impaction from motion in myocardial T1 mapping. However, there is no ground truth for the training. Goal(s): The aim of this study is to develop a deep learning-based algorithm to correct motion in myocardial T1 mapping using a self-supervised manner. Approach: We proposed a deep-learning approach and trained it using synthesized reference from the input T1-weighted images, eliminating the need for ground truth. Results: Our results indicated that a self-supervised deep-learning approach could align the left-ventricle myocardium and therefore improve the T1 map quaintly and accuracy. Impact: A
self-supervised deep-learning
approach could automatically perform motion correction for cardiovascular
magnetic resonance T1
mapping, alleviating the impaction from motion and improving the quality of
pixel-wise T1 map. |
| 1492.
 | 91 | Entropy of MRI T1 mapping as a novel biomarker to evaluate heart diastolic function and stiffness Lili Zhang1, Ida Marie Hauge-Iversen1,2, Einar S. Sjaastad Norden1,2, Haelin Kim1, Ivar Sjaastad1, and Emil Knut Stenersen Espe1,2
1Institute of Experimental Medical Research, Oslo, Norway, 2KG Jebsen Center for Cardiac Research, Oslo, Norway Keywords: Myocardium, Cardiomyopathy, T1 mapping, entropy, fibrosis Motivation: Cardiac T1 maps are a promising choice for texture analysis due to their pixel values originating from fitting, making them less prone to variations. Entropy of T1 map as a measure of myocardial tissue heterogeneity may reflect the disruption of myocardial fiber structure and/or the infiltration of extracellular matrix. Goal(s): We aim to investigate the relationship between myocardial tissue properties and diastolic function, as well as myocardium stiffness. Approach: We applied TA on native T1 maps of a pressure-overload rat model 12 weeks after the operation. Results: Entropy exhibited a strong correlation with both chamber stiffness and diastolic function biomarkers. Impact: Our data
indicates that impaired diastolic function may be due to disorganized/disrupted
myocardium, rather than increased fibrosis solely. Our research sheds new light
on understanding the relationship between extracellular matrix and cardiac function. |
| 1493.
 | 92 | Free-breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model Wonil Lee1,2, Paul Kyu Han1,2, Thibault Marin1,2, Ismael Brahim Georges Mounime1,2,3, Samira Vafay Eslahi1,2, Yanis Djebra1,2, Didi Chi1,2, Georges El Fakhri4, and Chao Ma1,2
1Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, 2Department of Radiology, Harvard Medical School, Boston, MA, United States, 3LTCI, Telecom Paris, Institut Polytechnique de Paris, Paris, France, 4Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States Keywords: Myocardium, Cardiovascular, Extracellular volume fraction (ECV) Motivation: Extracellular volume (ECV) is an emerging biomarker for diffuse fibrosis, which is known to be particularly challenging to detect. Existing methods are limited to single-slice acquisition with or without breath-hold. Goal(s): To develop a new method for free-breathing, 3D ECV mapping of the whole heart. Approach: 3D cardiac T1 mapping was performed before and after contrast agent injection using a free-breathing, ECG-gated IR-FLASH sequence followed by a linear tangent space alignment model-based image reconstruction. Results: The estimated ECV values from the proposed method were comparable to those from the reference MOLLI method. Impact: The
proposed method allows for free-breathing, 3D ECV mapping of the whole heart in
a practically feasible imaging time. The proposed method is potentially useful
ECV quantitation in healthy and diseased populations with diffuse fibrosis. |
| 1494.
 | 93 | Diagnosing LGE-negative hypertrophic cardiomyopathy with T1 mapping and feature tracking: a preliminary study Shan Li1, yan Xing2, kexin qin3, Xiaocheng Wei4, Hongzhe Tian1, Huipeng Ren1, and Huan Wang1
1Baoji Central Hospital, Baoji, China, 2The First Affiliated Hospital of Xinjiang Medical University, urumchi, China, 3Baoji Hospital of Traditional Chinese Medicine, Baoji, China, 4GE HealthCare MR Research, Beijing, China Keywords: Myocardium, Quantitative Imaging, HCM Motivation: The presence of myocardial fibrosis in HCM has significant prognostic power in the prediction of severe cardiac complications in HCM. Goal(s): To compare native T1、ECV and myocardial strain parameters in patients with LGE-negative HCM with healthy participants to evaluate for the presence of subtle myocardial fibrosis and regional myocardial function in HCM. Approach: Seventeen patients with LGE-negative HCM and twenty-eight healthy participants were underwent the MRI scan and the quantitative parameters were analyzed. Results: Overall native T1 and ECV values were increased in HCM patients ; GLS, GRS, and GCS were all decreased in HCM patients with LGE negative. Impact: The
cardiac magnetic resonance T1 mapping technique combined with the feature
tracking technique can reflect subtle myocardial fibrosis, myocardial
deformation, and impaired myocardial systolic function earlier in HCM patients
from LGE negative patients. |
| 1495.
 | 94 | Myocardial cine T1 mapping using dynamic multiple trigger delay acquisition Isao Shiina1, Michinobu Nagao2, Masami Yoneyama3, Hiroshi Hamano3, Jihun Kwon3, Yasuhiro Goto1, Yutaka Hamatani1, Kazuo Kodaira1, Takumi Ogawa1, Mana Kato1, Yasuyuki Morita1, and Shuji Sakai2
1Department of Radiological Services, Tokyo Women's Medical University Hospital, Tokyo, Japan, 2Department of Diagnostic imaging & Nuclear Medicine, Tokyo Women's Medical University Hospital, Tokyo, Japan, 3Philips Japan, Tokyo, Japan Keywords: Myocardium, Cardiomyopathy, myocardium/T1Mapping Motivation: Myocardial T1-mapping is a widely used quantitative method to evaluate the characteristics of myocardium. Commonly, the cardiac trigger delay (TD) during the diastolic phase depends on the settings of the system. However, because myocardial characteristics can affect both diastole and systole, acquiring T1 mapping at various cardiac phases may have clinical significance. Goal(s): To acquire cardiac T1 mapping at various cardiac phases in one scan. Approach: Dynamic trigger delay Results: The proposed technique was successfully implemented. Application of image registration technique has improved the accuracy of T1 value quanitification. Impact: CINE T1 mapping can acquire quantitative mapping of
several different cardiac phases simultaneously in one scan; it may be useful
for more detailed diagnosis of myocardial properties. |
| 1496.
 | 95 | Cardiac Phantom-based Inter-site Calibration of T2, T1, and ECV Measurements Carly Anne Lockard1, Ruei-yuan Tu1, Ke Yan2, Aspen Duffin2, Kimberly Crum3, Scott Auerbach4, Brian Fonseca4, Markus Renno5, Kenneth Knecht5, Margaret M Samyn2, Jonathan Soslow3, and Bruce M Damon1
1Stephens Family Clinical Research Institute, Carle Clinical Imaging Research Program, Carle Foundation Hospital, Urbana, IL, United States, 2Medical College of Wisconsin, Milwaukee, WI, United States, 3Vanderbilt University, Nashville, TN, United States, 4Children’s Hospital Colorado, Denver, CO, United States, 5Arkansas Children’s Hospital, Little Rock, AR, United States Keywords: Myocardium, Heart, Transplant, T1-mapping, T2-mapping, ECV, Rejection, Calibration Motivation: Acute rejection is the leading cause of death in pediatric heart transplant (PHTx) recipients. Endomyocardial biopsy is currently required to monitor for rejection. Quantitative cardiac magnetic resonance (CMR) is a potential non-invasive monitoring tool, with T2, T1, and ECV mapping providing information about fibrosis and edema. However, measurements vary between sites. Goal(s): To measure inter-site/temporal variability and calibrate multisite PHTx CMR data. Approach: We investigated manganese-chloride solution cardiac phantom T2 and T1 repeatability and inter-site variation, and impact of calibration on PHTx data. Results: Calibration reduced inter-site variability in phantom and PHTx measurements. Impact: Our preliminary results illustrating
inter-site variation in CMR-relevant phantom T2 and T1 measurements support the
need for inter-site calibration when multi-center trials are conducted using CMR
parametric imaging (T2, T1, and calculated ECV). |
| 1497.
 | 96 | Accelerating Free Breathing Motion-Corrected Late Gadolinium Enhancement Imaging Using Simultaneous Multi-Slice Imaging Grzegorz Tomasz Kowalik1, Karl Kunze1,2, Filippo Bosio1, Peter Speier3, Daniel Staeb4,5, Radhouene Neji1,2, Reza Razavi1, Sohaib Nazir1,6, Amedeo Chiribiri1, and Sébastien Roujol1
1King's College London, London, United Kingdom, 2MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom, 3Cardiovascular predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, 4MR Research Collaborations, Siemens Healthcare Limited, Melbourne, Australia, 5Department of Radiology, The University of Melbourne, , Melbourne, Australia, 6Royal Brompton Hospital, London, United Kingdom Keywords: Myocardium, Heart, LGE Motivation: Free breathing motion-corrected late gadolinium enhancement (FB-MOCO-LGE) is commonly used for scar assessment in patients unable to breathhold. Reduction of FB-MOCO-LGE scan time will contribute reducing overall examination time and cost. Goal(s): To evaluate the potential of simultaneous multi-slice (SMS) imaging in reducing FB-MOCO-LGE acquisition time while maintaining image quality. Approach: To Implement a 2x SMS-bSSFP technique with phase-sensitive inversion recovery (PSIR) reconstruction. Evaluation of FB-MOCO-LGE and SMS FB-MOCO-LGE was conducted on 20 patients. Results: The SMS approach demonstrated a significant two-fold reduction in acquisition time without compromising myocardial sharpness or signal-to-noise ratio and minimal impact on image quality. Impact: SMS-enabled FB-MOCO-LGE enables halves acquisition time with
minimal on image quality. Therefore, this approach show promise for reducing
LGE protocol duration and cost of cardiac MRI examination. |