Multi-modal fluorescence imaging of contracting intact hearts ESR4: Vineesh Kappadan Project Supervisor: Prof.Ulrich Parlitz & Dr.Jan Christoph Biomedical Physics Group Max Planck Institute for Dynamics and Self Organization, Göttingen, Germany Second Be-Optical Workshop Montpellier-La Grande Motte, France, March 18-19,2018 Max Planck Institute for Dynamics and Self-Organization
Introduction: Imaging a beating heart Electrical impulses are responsible for mechanical contraction Sinus Rhythm Contraction of a cardiomyocyte [Virtualheart.org F. Fenton] Excitation Contraction Coupling Ventricular Fibrillation Membrane Voltage Calcium Contraction [Numerical simulation by P. Bittihn, Biomedical Physics Group, MPIDS 2012]
Research goal: Study of electromechanical interactions Electro-mechanical interactions are bi-directionally coupled Excitation Contraction Coupling (ECC) Electrical activity Mechanical activity Mechano Electric Feedback (MEF) [Stretch activated channels] Study of electro-mechanical interactions of the heart simultaneous imaging of voltage and calcium from a beating heart
State-of-the-art: Fluorescent imaging of heart Action potential waves from a beating rabbit heart Signal distortion due to motion Motion artifacts : Challenge Inhomogeneous illumination also causes motion artifact by drifting the baseline Usage of pharmacological agents (Electromechanical uncouplers) to suppress mechanical motion (example: Blebbistatin) Adverse effects on the electrophysiology of heart [Stender et al.] Loss of correspondence between the camera pixel and heart tissue
Fluorescent imaging of voltage and calcium Heart loaded with voltage sensitive fluorescent dye Voltage dependent fluorescent emission Heart loaded with calcium sensitive fluorescent dye Calcium dependent fluorescent emission
Multiparametric Optical Mapping by Fluorescent Imaging Langendorff-perfused Rabbit heart loaded with voltage and calcium sensitive dyes 10mm Excitation 550nm camera 500fps 250fps 250fps 10mm Voltagesensitive Calciumsensitive Dye 1 Dye 2 Excitation 650nm dual-bandpass filter Lee et al, 2011 [1] 10mm [2] 2 x 250fps 2ms t 2 channels: illumination + exposure scheme LED switching box 1. P. Lee, P. Kohl; Heart Rhythm, 2011 2. I. Uzelac, J. Christoph, S. Luther, F. Fenton 2014
Solution to motion artifact: marker free motion tracking A six parameter affine model is used Assumption of brightness constancy Affine Transform Test image f(x,y) Reference image g(x,y) Difference image Goal is to minimize the quadratic error function E=σ R [ f x m 5, y m 6 g m 1 x + m 2 y + m 5, m 3 x + m 4 y + m 6 ] 2 Affine matrix A= m 1 m 2 m 3 m 4 m 5 and m 6 are displacement vectors [Periaswami et al. Differential affine motion estimation for medical image registration,international Symposium on Optical science and Technology, San Diego, 2000]
Contrast enhancement: To preserve brightness constancy Enhancement of image contrast by local normalization I CE (x,y)= I(x,y) min(s) max S min(s) S: sub region of the image surrounding the pixel (x,y) Contrast enhancement before motion tracking [ J. Christoph, J. Schröder-Schetelig, S. Luther. Electromechanical optical mapping, Prog. Biophys. Mol. Bio., 2017]
Motion tracking on experimental data during sinus rhythm Action potential Calcium concentration Without motion tracking With motion tracking+compensation
Motion tracking of heart with Action Potential (AP) Sinus rhythm Ventricular Fibrillation AP without motion tracking AP from a motion tracked+compensated heart Motion compensation by motion tracking
Time series during sinus rhythm Voltage signal without motion tracking Voltage signal from a motion compensated heart
Variation of time delay between voltage and calcium signals during Ventricular Fibrillation
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