Review of methods and applications of attenuation coefficient measurements with optical coherence tomography

Abstract

The optical attenuation coefficient (AC), an important tissue parameter that measures how quickly incident light is attenuated when passing through a medium, has been shown to enable quantitative analysis of tissue properties from optical coherence tomography (OCT) signals. Successful extraction of this parameter would facilitate tissue differentiation and enhance the diagnostic value of OCT. In this review, we discuss the physical and mathematical basis of AC extraction from OCT data, including current approaches used in modeling light scattering in tissue and in AC estimation. We also report on demonstrated clinical applications of the AC, such as for atherosclerotic tissue characterization, malignant lesion detection, and brain injury visualization. With current studies showing AC analysis as a promising technique, further efforts in the development of methods to accurately extract the AC and to explore its potential use for more extensive clinical applications are desired.

Keywords: light attenuation coefficient; optical coherence tomography; tissue differentiation.

Fig. 1

(a) Images of human retina obtained by commercialized OCT (a) in comparison with AC mapping. Dashed arrow in (b) points to the RNFL of the retina. Solid arrows in (a) and (b) point to a shadow resulting from a superficial retinal blood vessel (reprinted with permission from Ref. 14).

Fig. 2

CF method applied to ex vivo atherosclerotic plaque characterization, where thick lines show the fitting over areas of interest (reprinted with permission from Ref. 3).

Fig. 3

(a) Depth profile (A-scan) of a layered phantom and (b) the pixelwise attenuation estimated using the DR method. With DR estimation, pixel-specific AC measurement can be achieved. Thick red lines indicate depth ranges, where measurements were taken (reprinted with permission from Ref. 15).

Fig. 4

Simulation results of the effect of (a) AC contrast and (b) layer thickness on DR, DRC, and DRC with various filters [gSmooth, total variance (TV), and intensity weighted horizontal total variation (iwhTV) denoising]. The energy error depth figure of merit is defined as the depth at which the excess energy exceeds 5%; hence, larger energy error depth equates to better performance. Stars indicate positions of the boundary between the layers. From the results, it is evident that DRC outperforms DR with and without denoising (reprinted with permission from Ref. 23).

Fig. 5

Numerical simulation of attenuation in a single-layer phantom with homogeneous scattering under noiseless conditions. Note the light does not fully attenuate at the end of the depth region. (a) Simulation OCT signals for varying scattering coefficients. (b) Plot of attenuation versus depth using the DR method; the small graph to the right highlights the large error over the depth range of 2.5 to 3 mm. (c) Plot of attenuation versus depth using the ODRE method shows constant attenuation for all depths, as expected (reprinted with permission from Ref. 26).

Fig. 6

(a) RNFL thickness mapping versus (b) RNFL AC plot of a glaucomatous eye. Red arrow indicates the location of affected tissue, which coinciding with reduced thickness in inferotemporal region (reprinted with permission from Ref. 24).

Fig. 7

(a) H&E stained histology, (b) en face OCT image, and (c) AC map of a healthy lymph node at a depth $z=240\mu \mathrm{m}$. (d) Example of correction profile (red) used to correct the raw A-scans (gray) and generate the corrected reflectance profile (black). (e)–(g) Averaged A-scans of colored boxes are shown, where $x$ axis is depth and by linear fitting identifiable features in lymph node can be identified: (e) paracortex (dark blue), (f) medullary sinuses (light blue), and (g) fibrous capsule (red) (reprinted with permission from Ref. 4).

Fig. 8

(a) and (b) Changes in two regions of brain tissue OAC as a function of time. Region 1 (red box area): ischemic damaged regions; region 2 (blue box area): undamaged regions (reprinted with permission from Ref. 26).

Fig. 9

(a, d) Backscattering and (b, e) attenuation coefficient images of artery segments with (g) color map combining (c, f) attenuation and backscattering coefficients. Upper row: lipid-rich plaque; lower row: fibrocalcific plaque (reprinted with permission from Ref. 3).