Quantifying Gleason scores with photoacoustic spectral analysis: feasibility study with human tissues

Abstract

Gleason score is a highly prognostic factor for prostate cancer describing the microscopic architecture of the tumor tissue. The standard procedure for evaluating Gleason scores, namely biopsy, is to remove prostate tissue for observation under microscope. Currently, biopsies are guided by transrectal ultrasound (TRUS). Due to the low sensitivity of TRUS to prostate cancer (PCa), non-guided and saturated biopsies are frequently employed, unavoidably causing pain, damage to the normal prostate tissues and other complications. More importantly, due to the limited number of biopsy cores, current procedure could either miss early stage small tumors or undersample aggressive cancers. Photoacoustic (PA) measurement has the unique capability of evaluating tissue microscopic architecture information at ultrasonic resolution. By frequency domain analysis of the broadband PA signal, namely PA spectral analysis (PASA), the microscopic architecture within the assessed tissue can be quantified. This study investigates the feasibility of evaluating Gleason scores by PASA. Simulations with the classic Gleason patterns and experiment measurements from human PCa tissues have demonstrated strong correlation between the PASA parameters and the Gleason scores.

Keywords: (110.5125) Photoacoustics; (120.3890) Medical optics instrumentation; (170.6510) Spectroscopy, tissue diagnostics; (170.6935) Tissue characterization.

Fig. 1

Simulation of PASA on Gleason patterns. (a) The Gleason patterns. (b) Representative simulated signals generated by Gleason grades 1 and 5. The fine architecture of Gleason grade 1 is below the ultrasonic resolution (200 µm, determined by the default sensor bandwidth of 0-15MHz). The signal form Gleason grade 1 is smooth and thereby carries less high frequency components than that generated by Gleason grade 5. (c) The power spectra of the PA signals generated by Gleason grades 1-5. The linear fit to the power spectrum for Gleason grade 1 was plotted in red dashed line, of which the slope is tan(θ).

Fig. 2

Histology photographs of prostate tissues used in this study and representative PA spectra generated by the tissues. (a) Normal. (b) Gleason 6. (c) Gleason 7. (d) Gleason 9. Arrows indicate the clustered cancer cells. Scale bar: 250 μm. (e) and (f) are representative PA signals generated by a benign and a Gleason 9 samples, respectively. More fluctuations can be seen in the PA signal from the Gleason 9 sample. (g) The power spectra of the PA signals generated by the prostate tissues with different Gleason scores. Black dashed line indicates the noise level. Due to the low signal-to-noise ratio (SNR) in the experiment case, only the spectra above the noise floor (black dashed line) were fit to linear models. The frequency range for linear fitting to the Gleason 9 spectrum in (g) is from 0.1 MHz to 3.8 MHz as marked by the cyan dashed line. The slope of the linear fit to Gleason 9 spectrum (magenta dashed line) is tan (θ).

Fig. 3

(a) Setup for PA scan of human PCa tissues. The sliced prostate tissue was fix on a glass slide and stained by H&E staining. The glass slide was covered by US gel and attached to the surface of a tank of water. A needle hydrophone was inserted into the gel volume for PA wave reception. The PA signals were amplified, recorded by an oscilloscope and post-processed by a PC. 532-nm laser was used due to the high optical absorption of the pink H&E stain at this wavelength. (b) Each sample was measured along four different orientations.

Fig. 4

Averaged slopes from PASA for each Gleason grade. At higher Gleason grades (i.e. 3-5), the slope values appear to increase linearly with respect to the Gleason grade, as marked by the green dashed line.

Fig. 5

Results from ex vivo human prostate tissues. (a) Slope values acquired from normal and cancerous prostate tissues. (b) Boxplot of the cancerous data with respect to Gleason scores.