Cardiac Imaging

Heart Failure

Heart failure affects ≥5 million people in the USA. About half the people who develop heart failure die within 5 years of diagnosis. It is a leading cause of hospitalization, death, and disability in developed countries, creating a significant social and economic burden for patients and health care systems. The treatment costs are estimated to be $32 billion each year. While the underlying cause of heart failure may be quite varied, common features of the failing heart include myocyte hypertrophy and fibrosis. Currently, most methods for the detection of heart failure focus on geometric abnormalities utilizing MRI, ultrasound and CT. Although there have been tremendous improvements in diagnostics for cardiac disease, many of the current techniques are useful only when significant cardiac dysfunction is present. It is well documented that early detection can rescue patients from acute failure and save lives. Early detection of ventricular dysfunction, before progression to full heart failure, is essential to improve patient outcomes.

Cardiac Fibers

Cardiac fibers directly affect the mechanical and physiological properties of the heart. During the cardiac cycle from systole to diastole, cardiac fibers are the basic units that pump blood from the ventricles into circulation. Cardiac fiber orientation plays an important role in determining the stress distribution within the myocardial walls. Abnormal cardiac fiber orientations in heart failure patients adversely impact cardiac function and also contribute to arrhythmias that can lead to sudden death. Mapping cardiac fiber orientation enables monitoring of the development and progression of heart failure and provides insight into the mechanism of heart failure for early detection. It is reported that cardiac fiber angles changes through the wall from epicardium to endocardium and that the angles increase from systole to diastole. In a normal heart, the change of fiber orientation is from around -75° at the epicardium to +75° at the endocardium.

Alterations of cardiac fiber orientation can have significant pathological consequences. Animal studies have shown that ventricular transmural fiber rotation was significantly changed in hypertrophic versus normal hearts and that muscle fiber stress and strain across the ventricular wall are very sensitive to the transmural distribution of helix angle. During heart beating, the fiber angles in systole are increased through the wall relative to their counterpart in diastole.

Selected Publications

  1. Shi T, Shahedi M, Caughlin K, Dormer JD, Ma L, Fei B. Semi-automated three-dimensional segmentation for cardiac CT images using deep learning and randomly distributed points. In Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling 2022 Apr 4 (Vol. 12034, pp. 424-430). SPIE.

    Fei_2022_SPIE_Ted_Cardiac_Segmentation [PubMed] [PDF]
  2. Zhou X, Dormer JD, Fei BW. Development of a polarized hyperspectral microscope for cardiac fiber orientation imaging. Diagnostic and Therapeutic Applications of Light in Cardiology 2020; 11215(112150V). International Society for Optics and Photonics,
    Zhou_2020_Cardiology [PubMed] [PDF]
  3. Tran CT, Halicek M, Dormer JD, Tandon A, Hussain T, Fei BW (Corresponding author). Fully automated segmentation of the right ventricle in patients with repaired Tetralogy of Fallot using U-Net. Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging; 11317(113171M). International Society for Optics and Photonics,

    Tran_2020_SPIE [PDF]
  4. Dormer J, Bhuiyan M, Rahman N, Deaton N, Sheng J, Padala M, Desai J, Fei BW (Corresponding author). Image guided mitral valve replacement: registration of 3D ultrasound and 2D x-ray images. Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling; 11315(113150Z). International Society for Optics and Photonics,

    Dormer_2020_SPIE [PubMed] [PDF]
  5. Dormer JD, Guo R, Shen M, Jiang R, Wagner MB, Fei BW (Corresponding author). Ultrasound segmentation of rat hearts using convolutional neural networks. Proceedings of SPIE: The International Society for Optical Engineering;10580.

    Dormer_2018_MedImaging_1 [PubMed] [PDF]
  6. Dormer J, Reilly CM, Schreibmann E, Fei BW (Corresponding author). Using convolutional neural networks to identify patients at risk for cardiovascular disease using 3D patches radiomic analysis for cardiovascular disease prediciton using wavelet features. The Annual Meeting of the Biomedical Engineering Society.

  7. Dormer JD, Jiang R, Wagner MB, Fei BW, A new method to quantify fiber orientation similarity in registered volumes “, Proc. SPIE 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment, 101361I, March 10, 2017, Orlando, FL.

    Dormer_2017_MedImaging1 [PubMed] [PDF]
  8. Dormer J, Qin X, Shen M, Wang S, Zhang X, Jiang R, Wagner MB, Fei BW (Corresponding author). Determining cardiac fiber orientation using FSL and registered ultrasound/DTI volumes. Proceedings of SPIE – The International Society for Optical Engineering 2016; 9790: 979015. PubMed PMID:27660384.

    Dormer_2016_MedImaging [PubMed] [PDF]
  9. Fei BW, Qin X, Wang S, Shen M, Wagner M, Zhang X, Cardiac Fiber Imaging Using High-Frequency Ultrasound in Animal Models, The Annual Meeting of the American Association of Physics in Medicine (AAPM), Austin, TX, July 20-24, 2014.

  10. Wang S, Qin X, Zhang X, Wagner MB, Fei BW, Imaging and visualization of cardiac muscle microstructure in rats using high-resolution MRI, The Annual Meeting of The International Society for Magnetic Resonance in Medicine (ISMRM) 2014, May 10-16, 2014 Milan, Italy.

  11. Qin X, Wang S, Shen M, Zhang X, Wagner MB, Fei BW (Corresponding author). Mapping cardiac fiber orientations from high-resolution DTI to high-frequency 3D ultrasound. Proceedings of SPIE – The International Society for Optical Engineering 2014; 9036:90361O. PubMed PMID:25328641.

    Qin_2014_MedImaging_1 [PubMed] [PDF]
  12. Qin X, Cong Z, Halig LV, Fei BW (Corresponding author). Automatic segmentation of right ventricle on ultrasound images using sparse matrix transform and level set. Proceedings of SPIE – The International Society for Optical Engineering 2013; 8669. PubMed PMID:24236228.

    Qin_2013_MedImaging_1 [PubMed] [PDF]
  13. Qin X, Cong Z, Fei BW (Corresponding author). Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set. Physics in Medicine and Biology 2013; 58:7609-24.

    Qin_2013_PMB [PubMed] [PDF]
  14. Mafi J, Fei BW, Roble S, Dota A, Katrapati P, Bezerra HG, Wang H, Wang W, Ciancibello L, Costa M, Simon DI, Orringer CE, Gilkeson RC. Assessment of coronary artery calcium using dual-energy subtraction digital radiography. Journal of Digital Imaging 2012; 25:129-36.

    Mafi_2012_JDI [PubMed] [PDF]
  15. Chen X, Li K, Gilkeson R, Fei BW (Corresponding author). Gaussian weighted projection for visualization of cardiac calcification. Proceedings of SPIE – The International Society for Optical Engineering 2008; 6918. PubMed PMID:24386529.

    Chen_2008_MedImaging [PubMed] [PDF]