Bhumi Bhusal¹, Fuchang Jiang¹, Pia Panravi Sanpitak¹, Boris Keil², Gurinder Kaur Multani², Nicolas Kutscha², Giorgio Bonmassar³, Gregory Webster¹, Andrada Popescu⁴, Daniel Kim¹, and Laleh Golestanirad^1
1Northwestern University, Chicago, IL, United States, ²TH Mittelhessen University of Applied Sciences, Giessen, Germany, ³Massachusetts General Hospital, Charlestown, MA, United States, ⁴Lurie Children's Hospital, Chicago, IL, United States

 Infants and children with congenital heart disease may require cardiovascular implantable electronic devices (CIEDs), which typically precludes future evaluation by MRI due to risks associated with RF heating of implants. Here we demonstrate that a novel concept based on patient-adjustable rotating RF coil technology that was originally developed to reduce RF heating of brain implants can be adopted in pediatric patients with CIEDs to substantially reduce RF heating.  Our simulations in a cohort of children with both epicardial and endocardial devices showed an 87% reduction in average SAR compared to conventional body coils.

Wolfgang G Rehwald^1,2, Rafael Rojas², Nestor Mena², Ryan Seward², George Gamoneda², Jeana Dement², Elizabeth Jenista², David Wendell², Han Kim², Enn-Ling Chen², Igor Klem², Vera Kimbrell², and Raymond Kim^2
1Siemens Healthineers, Durham, NC, United States, ²Duke Cardiovascular MR Center, Duke University, Durham, NC, United States

Standard segmented delayed enhancement (DE) is particularly motion sensitive owing to its interleaved reordering required for inversion recovery (IR). Ghosting artifacts frequently result from imperfect breath holding. The sequence cannot run free-breathing (FB). We present a novel DE technique, PROGRESSIVE, using a partially continuous reordering and dummy pulses for simultaneous motion robustness and IR-compatibility. We tested PROGRESSIVE in simulations, a motion phantom, and a cohort of patients. PROGRESSIVE images were devoid of ghosting. When acquired FB, quality was significantly better than standard DE, and equally good during perfect breath holding. PROGRESSIVE has the potential for FB self-navigated DE imaging.

El-Sayed H Ibrahim¹, Elizabeth Gore¹, Sherry-Ann Brown¹, and Carmen Bergom^2
1Medical College of Wisconsin, Milwaukee, WI, United States, ²Washington University, St Louis, MO, United States

Along with systemic therapies, radiation therapy (RT) plays a key role in treating lung cancer, despite high incidence of RT-induced cardiac complications. Most lung cancer patients present with cardiac risk factors that result in compromised baseline cardiac function that puts the patients at higher risk of developing cardiac complications. In this study, we investigate characteristics of baseline cardiovascular function in lung cancer patients undergoing RT. The results showed that the patients had borderline cardiac function and reduced myocardial strain measurements. Myocardial T1/T2 values in the patients were slightly high and the hemodynamic measurements showed different pattern than that in volunteers.

Zhengyang Ming^1,2, Caroline M. Colbert^1,2,3, Ruan Dan^1,4, Holden H. Wu^1,2, Anthony G. Christodoulou⁵, J. Paul Finn^1,2, Peng Hu^1,2, and Kim-Lien Nguyen^1,2,3
1Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, Los Angeles, CA, United States, ²Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, ³Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States, ⁴Department of Radiation Oncology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, ⁵Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Conventional 2D cardiac cine imaging relies on ECG-gating whereas self-gated approaches mitigate ECG-dependency by assuming that cardiac motion is periodic with well-defined frequencies. This assumption breaks down when patients have irregular cardiac rhythm. We propose a segmented Cartesian golden step balanced steady-state free precession sequence (bSSFP) with motion navigators and a clustering algorithm to alleviate the dependency on regular motion assumptions and to emphasize the intrinsic similarity of mechanical motion. Compared to standard ECG-gated 2D bSSFP cine performed in normal sinus rhythm, initial validation using our approach achieved similar image quality and quantitative metrics for cardiac function.

 

Yitong Yang¹, Zahraw Shah², Athira Jacob³, Jackson Hair¹, Teodora Chitiboi³, Tiziano Passerini³, Jerome Yerly⁴, Lorenzo Di Sopra⁴, Davide Piccini⁵, Zahra Hosseini⁶, Puneet Sharma³, Anurag Sahu⁷, Matthias Stuber⁴, and John Oshinski^1,8
1Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, United States, ²Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States, ³Siemens Medical Solutions USA, Princeton, NJ, United States, ⁴Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland, ⁵Siemens Healthcare, Lausanne, Switzerland, ⁶Siemens Medical Solutions USA, Atlanta, GA, United States, ⁷Cardiology, Emory University School of Medicine, Atlanta, GA, United States, ⁸Radiology, Emory University School of Medicine, Atlanta, GA, United States

Rapid and accurate quantification of left ventricular volume is essential for studying cardiac function. In this work, two reconstruction techniques for free-breathing, ECG-gated, radial, golden-angle phyllotaxis acquisition of whole-heart CMR are assessed for their accuracy in quantifying left ventricular volume using deep learning (DL)-based automatic cardiac chamber segmentation. The off-line reconstruction that resolves 4D (3D+respiratory) images had better agreement between the DL-based segmentation and an expert’s manual segmentation than the in-line reconstruction that corrects for respiratory motion, as assessed by the average volume difference (p=0.026) and 3D Dice coefficients (p=0.032).

Yu Wang¹, Changyu Sun¹, Sona Ghadimi¹, Auger C. Daniel¹, Pierre Croisille^2,3, Magalie Viallon^2,3, Jie Jane Cao⁴, Yang Joshua Cheng⁴, Andrew D. Scott^5,6, Pedro F. Ferreira^5,6, John N. Oshinski⁷, Daniel B. Ennis⁸, Kenneth C. Bilchick⁹, and Frederick H. Epstein^1,10
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, ²University of Lyon, UJM-Saint-Etienne, INSA, CNRS UMR 5520, INSERM U1206, CREATIS, Saint-Etienne, France, ³Department of Radiology, University Hospital Saint-Etienne, Saint-Etienne, France, ⁴St. Francis Hospital, DeMatteis Center for Research and Education, Cardiac Imaging, Greenvale, NY, United States, ⁵Cardiovascular Magnetic Resonance Unit, The Royal Brompton Hospital, London, United Kingdom, ⁶National Heart and Lung Institute, Imperial College, London, United Kingdom, ⁷Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States, ⁸Department of Radiology, Stanford University, Stanford, CA, United States, ⁹Cardiovascular Division, Department of Medicine, University of Virginia Health System, Charlottesville, VA, United States, ¹⁰Radiology, University of Virginia, Charlottesville, VA, United States

Cine DENSE provides both myocardial contours and intramyocardial displacements. We propose to use DENSE to train deep networks to predict intramyocardial motion from contour motion. Two workflows were implemented: a two-step FlowNet2-based framework with a through-time correction network and a 3D (2D+t) Unet framework. Both networks depicted cardiac contraction and abnormal motion patterns. The 3D Unet showed excellent reliability for global circumferential strain (E_cc) and good reliability for segmental E_cc, and it outperformed commercial FT for both global and segmental E_cc.

Siyeop Yoon¹, Xiaoying Cai^1,2, Eiryu Sai¹, Salah Assana¹, Amine Amyar¹, Kelvin Chow³, Amanda Paskavitz¹, Julia Cirillo¹, Warren J. Manning¹, and Reza Nezafat^1
1Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States, ²Siemens Medical Solutions USA, Inc., Boston, MA, United States, ³Siemens Medical Solutions USA, Inc., Chicago, IL, United States

We developed and evaluated an inline cascaded parallel imaging and generative adversarial network for cardiac MRI. The preliminary results show excellent image quality of the cardiac cine images in four heat-beat.

El-Sayed H Ibrahim¹, John Baker¹, and Carmen Bergom^2
1Medical College of Wisconsin, Milwaukee, WI, United States, ²Washington University, St Louis, MO, United States

Radiation therapy (RT) plays an integral role in treating a number of thoracic cancers, despite risks of radiation-induced cardiotoxicity. The purpose of this study is to investigate the capability of advanced the MRI-generated contractility index (ContractiX) for early detection of RT-induced cardiotoxicity in a pre-clinical rat model of thoracic cancer RT. While EF increased post-RT, peak systolic strain and ContractiX significantly decreased post-RT, with more relative reduction in ContractiX compared to strain. Therefore, ContractiX is a sensitive early marker for detection of subclinical cardiac dysfunction post-RT in pre-clinical models.