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

Abstract

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. References and links:1. R. Siegel, J. Ma, Z. Zou, and A. Jemal, "Cancer statistics, 2014," CA Cancer J. Clin. 64(1), 9-29 (2014

Interstitial assessment of aggressive prostate cancer by physio‐chemical photoacoustics: An ex vivo study with intact human prostates

“…Photoacoustics (PA) is a technology combining the sensitivity of optical spectroscopy and the resolution of ultrasound imaging. Our recently developed PA spectral analysis (PASA) method has demonstrated the capability of determining intraocular tumor types and identifying aggressive prostate cancer . PASA at multiple wavelengths, namely PA physio‐chemical analysis (PAPCA), has shown the capability of comprehensively analyzing the microarchitectures associated with the major molecular components within the assessed tissue volume.…”

“…Therefore, the superficial illumination approach used in our previous studies is not applicable in the in vivo prostate imaging scenario. Most of the previous studies on the PA imaging of prostate cancer were performed with sliced prostate tissues ex vivo . Our recently developed needle PA probe facilitates the delivery of relatively uniform illumination along a fiber optic diffuser, and the reception of the high frequency PA signals with a needle hydrophone from nearby tissues .…”

“…Our recently developed PA spectral analysis (PASA) method [14][15][16][17] has demonstrated the capability of determining intraocular tumor types 18 and identifying aggressive prostate cancer. 19 PASA at multiple wavelengths, namely PA physiochemical analysis (PAPCA), has shown the capability of comprehensively analyzing the microarchitectures associated with the major molecular components within the assessed tissue volume. PAPCA has been validated in identifying the diseased conditions during the progression of nonalcoholic fatty liver diseases.…”

Characterizing cellular morphology by photoacoustic spectrum analysis with an ultra-broadband optical ultrasonic detector

“…For example, by using commercially available or homefabricated piezoelectric transducers, PASA has been explored for applications in diagnosis of prostate cancer [6,12,13] and evaluation of liver conditions [7,8,14]. In these studies, PASA was performed on the tissue level, and the targeted biological tissues (e.g., small vessels, cellular groups, and lipid clusters) have features on the scale of over 100 microns.…”

Frequency Domain Analysis of Multiwavelength Photoacoustic Signals for Differentiating Among Malignant, Benign, and Normal Thyroids in an Ex Vivo Study With Human Thyroids

“…Patterson et al performed a frequency domain analysis of RF photoacoustic data and used the results in combination with photoacoustic signal amplitudes to differentiate between neoplastic and normal prostate in an in vivo transgenic murine model. Xu et al investigated the correlation between parameters extracted from the frequency domain analysis of photoacoustic signals and the Gleason scores for prostate cancer in an ex vivo study with human prostate tissue. Wang et al theoretically determined the correlation between the spectral slope, extracted from the power spectrum of the photoacoustic signal, and different factors of the photoacoustic imaging system such as the laser pulse envelope, US transducer directivity, and signal bandwidth.…”