Application of time-resolved autofluorescence to label-free in vivo optical mapping of changes in tissue matrix and metabolism associated with myocardial infarction and heart failure

Abstract

We investigate the potential of an instrument combining time-resolved spectrofluorometry and diffuse reflectance spectroscopy to measure structural and metabolic changes in cardiac tissue in vivo in a 16 week post-myocardial infarction heart failure model in rats. In the scar region, we observed changes in the fluorescence signal that can be explained by increased collagen content, which is in good agreement with histology. In areas remote from the scar tissue, we measured changes in the fluorescence signal (p < 0.001) that cannot be explained by differences in collagen content and we attribute this to altered metabolism within the myocardium. A linear discriminant analysis algorithm was applied to the measurements to predict the tissue disease state. When we combine all measurements, our results reveal high diagnostic accuracy in the infarcted area (100%) and border zone (94.44%) as well as in remote regions from the scar (> 77%). Overall, our results demonstrate the potential of our instrument to characterize structural and metabolic changes in a failing heart in vivo without using exogenous labels.

Keywords: (170.1610) Clinical applications; (170.3650) Lifetime-based sensing; (170.3890) Medical optics instrumentation; (170.4580) Optical diagnostics for medicine; (170.6935) Tissue characterization; (300.6500) Spectroscopy, time-resolved.

Figures

Fig. 1

(A) Experimental layout of the single point fluorescence lifetime probe system and its optical fiber configuration at the excitation (proximal) and sample (distal) ends. Optical fiber cores are colored blue for excitation fibers, white for fibers delivering white light and collecting the diffuse reflected light and green for fibers collecting the fluorescence. (B) System mounted on a portable trolley for ease of deployment in clinical settings. (C) Distal end of the fiber-optic probe.

Fig. 2

Emission spectra of endogenous fluorophores of interest excited at 375 nm and plotted to show their relation to the spectral range of the detection channels of the fluorescence lifetime point probe system. Curves are normalized to their maximum amplitude. Data measured as described in section 2.3.

Fig. 3

Diagram of the heart illustrating regions of interest (ROI) for our measurements: (A) anterior view; (B) posterior view. “RV” - right ventricle; “LV posterior” - left ventricle posterior wall; “LV anterior (scar)” - left ventricle anterior wall; and “border zone” - scar border zone or septum.

Fig. 4

Representative histology images from of AMC (left column) and MI-HF (right column) hearts. (A, E) RV; (B, F) LV posterior; (C, G) Border zone; (D, H) LV anterior

Fig. 5

Diffuse reflectance spectra in (a) RV, (b) LV posterior, (c) Border zone, (d) LV anterior. Dashed lines indicate +/− 1 SD.

Fig. 6

Absorbance spectra of key chromophores in cardiac tissue. The absorbance curves for human Hb and HbO2 were obtained from [52]. The absorbance curves for oxidized and reduced horse cytochrome C were obtained from [54]. The absorbance curves for horse Mb and MbO2 were obtained from [53]. The Hb and HbO2, Mb and MbO2 and reduced and oxidized cytochrome c pairs of curves were scaled in proportion with the largest of each curve being normalized to 1.

Fig. 7

Relative contribution for each spectral detection channel for AMC and MI hearts, displayed by ROI (top row) and channel center wavelength (bottom row). Dashed lines in bottom row graphs identify the spectral range of each detection channel of the FL point probe system.

Fig. 8

Autofluorescence lifetime parameters for each spectral channel, displayed by ROI.

Fig. 9

Results from PCA of all spectroscopic parameters for each ROI shown as scatter plots of the scores of the first two PC for each ROI: a) RV, b) LV posterior, c) border zone and d) LV anterior. Different markers in the scatter plot identify data obtained from different specimens. Black lines show the decision lines produced by LDA analysis.