Optical mapping of contracting hearts

Abstract

Optical mapping is a widely used tool to record and visualize the electrophysiological properties in a variety of myocardial preparations such as Langendorff-perfused isolated hearts, coronary-perfused wedge preparations, and cell culture monolayers. Motion artifact originating from the mechanical contraction of the myocardium creates a significant challenge to performing optical mapping of contracting hearts. Hence, to minimize the motion artifact, cardiac optical mapping studies are mostly performed on non-contracting hearts, where the mechanical contraction is removed using pharmacological excitation-contraction uncouplers. However, such experimental preparations eliminate the possibility of electromechanical interaction, and effects such as mechano-electric feedback cannot be studied. Recent developments in computer vision algorithms and ratiometric techniques have opened the possibility of performing optical mapping studies on isolated contracting hearts. In this review, we discuss the existing techniques and challenges of optical mapping of contracting hearts.

Keywords: action potential duration; motion artifacts; motion tracking; optical mapping; ratiometry; ventricular fibrillation.

Figure 1. Principle of optical mapping

The heart stained with a voltage‐sensitive fluorescent dye is illuminated with a specific wavelength of light (e.g. 532 nm for the excitation of Di‐4‐ANEPPS). The dye emits voltage‐dependent fluorescent light, which is first filtered using an emission filter and then captured on a high‐resolution photodetector. The recorded intensity on the photodetector is post‐processed to obtain optical action potential signals.

Figure 2. Causes of motion artifact

A, example traces of optical action potentials (OAPs) from a Langendorff‐perfused rabbit heart with and without contractile motion. Optical action potentials in contracting condition are characterized by motion artifacts as indicated by the distortions in the baseline and the repolarization phase of action potentials, whereas OAPs are not distorted when the motion is suppressed using blebbistatin. B, variation of motion artifacts and motion amplitude at two different locations (pixel a and pixel b, ∆d _pixel = 7 mm) on the heart. OAPs (continuous black line) from the pixels are distorted differently and hence the motion artifacts are different at these locations despite similar contractile motion amplitudes (dashed red line), indicative of other factors, including inhomogeneous illumination and dye loading, which can contribute to the motion artifacts. C, factors contributing to motion artifact: relative motion between the heart and the detector, inhomogeneous illumination, and variations in dye concentration. A and B are modified from our previous study (Kappadan, 2021).

Figure 3. 2D motion tracking

A, motion tracking algorithm computes the geometrical transformation between test (T) images and a reference (R) image and aligns the test images with the reference image (image registration). a, the difference image between the test and the reference image shows significant motion artifacts before motion tracking (R − T). Motion artifacts are significantly reduced in the difference image after motion tracking (R − T_t). b, displacement vectors computed via the motion tracking algorithm at three different time points (40 ms intervals) during cardiac contraction. B, motion amplitude maps (in pixels) computed using 2D motion tracking during ventricular pacing and fibrillation, showing relatively less motion in VF than during ventricular pacing. Panel modified from our previous study (Kappadan et al., 2020). C, example of motion tracking in frog heart, where blebbistatin does not work. Motion tracking significantly reduced the distortion of optical action potentials (motion artifacts). Signals are spatially averaged from 3 × 3 pixels. D, validation of motion tracking: comparison of motion tracked optical action potential and a microelectrode action potential recording of a frog heart at 1.5 s period showing good agreement between the signals.

Figure 4. Excitation and emission ratiometry

A, schematic representation of excitation ratiometry using Di‐4‐ANEPPS. Excitation ratiometry uses two excitation light sources to excite the dye and a single emission filter–camera combination to collect the action potential‐modulated fluorescent light. Exciting the dye with blue and green excitation wavelengths produces positive (dashed blue line above the continuous blue line) and negative (dashed green line below the continuous green line) fractional change in fluorescence (∆F) during action potential depolarization. The emission filter–camera combination collects emitted fluorescent light for blue and green excitation; taking the ratio of the fluorescence intensities minimizes the motion artifacts originating from illumination and dye loading inhomogeneities. B, principle of emission ratiometry. Emission ratiometry uses a single excitation light to excite the dye and two emission wavelength bands (with positive and negative ∆F) to collect the voltage‐dependent fluorescence emission. The emission filters transmit the fluorescent light into two cameras that are aligned to look at the same portion of the cardiac tissue. The ratio of the fluorescence intensities of the two cameras reduces dye loading and illumination motion artifacts. C, example of OAP signals showing motion artifact reduction using excitation ratiometry. D, motion artifact reduction using emission ratiometry.

Figure 5. Combination of excitation ratiometry and motion tracking

Flowchart representation of motion correction technique in optical mapping studies of beating hearts. A, Langendorff‐perfused contracting hearts stained with Di‐4‐ANEPPS are illuminated with blue and green LEDs that are interlaced in time. B, the LED switching (500 Hz) is synchronized with the camera (500 fps) such that odd frames of camera record optical action potential for blue excitation and even camera frames of camera record action potentials for green excitation (or vice versa). C, sorting of camera frames into odd and even corresponding to blue (raw blue) and green (raw green) excitation. D, application of motion tracking algorithm to optical mapping videos of blue and green excitation separately. E, the ratio between motion‐tracked videos of blue (tracked blue) and green (tracked green) excitation is computed to minimize motion artifacts.

Figure 6. Motion artifact reduction using combined motion tracking and excitation ratiometry

A, OAP signals from the left ventricle of isolated contracting rabbit heart using motion tracking and excitation ratiometry. Neither motion tracking nor ratiometry removed motion artifacts completely, but a combination of those (bottom row, middle) substantially reduced the artifacts, with signal quality comparable to paralysed‐heart experiments using blebbistatin. For this example, spatial average of 3 × 3 pixels was performed. B, single pixel OAP traces from four different locations on the left ventricular surface before (dashed) and after (bold) motion correction (motion tracking and ratiometry). A single camera frame is shown on the left for reference. The single pixel OAP is significantly distorted due to motion artifacts when motion correction was not applied.

Figure 7. Comparison of activation and APD maps on a contracting heart with and without motion correction

A, action potential activation maps before and after motion correction. The fast upstroke of action potential is less affected due to motion and thus activation maps are comparable before and after motion correction. B, APD₈₀ maps before and after motion correction. The combination of motion tracking and ratiometry significantly improved APD measurement as compared to either of the methods alone.