Transrectal ultrasound (TRUS) guided biopsy is the standard procedure for evaluating the presence of prostate cancer. TRUS, however, has limited sensitivity to prostate tumors, nor can it differentiate aggressive cancer from non-aggressive ones. The emerging photoacoustic (PA) imaging combined with TRUS offers a great promise to solve this overarching issue, especially when powered by tumor-targeting contrast agent. In this work, we studied the feasibility of PA imaging to cover the entire prostate by using light illumination via the urethral track. Experiment was conducted on whole human prostates ex vivo. The light source was an array of light emitting diodes (LED) which has many advantages compared to solid state laser. The LED array was placed in the urethra, delivering light with fluence within the ANSI safety limit. A PA and ultrasound (US) dual modality system acquired the images in the same way as in TRUS. The imaging target was a 1-mm tube filled with ICG solution, mimicking the situation of a prostate tumor labeled with ICG contrast agent. The imaging results demonstrated that PA imaging can detect the ICG-filled tube at any place in the prostate, with an imaging depth over 20 mm. This study validated that PA imaging, when performed in a transrectal manner and combined with transurethral light illumination, is capable of molecular level imaging of the entire prostate noninvasively. The high sensitivity offered by PA imaging in detecting aggressive prostate cancer may contribute to prostate cancer management, e.g., enabling more accurate guidance for needle biopsy.
Transrectal ultrasound (TRUS) guided biopsy is the standard procedure for evaluating the presence and aggressiveness of prostate cancer (PCa). The microarchitecture of each biopsied tissue is assigned a Gleason score, a highly prognostic architecture-based grading system for PCa. Due to the limited sensitivity of TRUS imaging to PCa, less than 10% of the sample cores are clinically significant, yet the false negative rate could be 20% at the initial biopsies. A diagnostic modality that can assess the microarchitectures within the prostates in vivo without tissue extraction could significantly reduce the unnecessary biopsy cores and the post-procedure complications. Our previous study has shown that photoacoustic physio-chemical analysis (PAPCA) can quantify the architectural heterogeneities in the prostate. Our recently developed needle PA probe has facilitated the minimally invasive acquisition of PA signals with sufficient temporal length and narrow dynamic range in deep tissue for statistics-based PAPCA.
This study investigates the PCa diagnosis by PAPCA of the signals acquired by the needle PA probe. A total of 45 interstitial measurements were acquired (21 in normal and 24 in cancerous regions) in 10 ex vivo human prostates. A significant difference was found in the architectural heterogeneities between the normal and cancerous regions (p<0.005). Areas-under-the-curve of 0.8 has been observed for identifying PCa using the quantitative features. Quantification of the architectural changes in vivo in a transgenic mouse model of PCa is under investigation. The preliminary test has shown a significant difference between the normal and cancerous mouse prostates ex vivo (p<0.005).
Photoacoustic physio-chemical analysis (PAPCA) is a recently developed technology capable of simultaneously quantifying the content of molecular components and the corresponding microarchitectures in biological tissue. We have successfully quantified the diagnostic information in livers with PAPCA. In this study, we implemented PAPCA to the diagnosis of prostate cancers. 4 human prostates were scanned ex vivo. The PA signals from normal and cancerous regions in the prostates were acquired by an interstitial needle PA probe. A total of 14 interstitial measurements, including 6 within the normal regions and 8 in the cancerous regions, were acquired. The observed changes in molecular components, including lipid, collagen and hemoglobin were consistent with the findings by other research groups. The changes were quantified by PA spectral analysis (PASA) at wavelengths where strong optical absorption of the relevant molecular components was found. Statistically significant differences among the PASA parameters were observed (p=0.025 at significance of 0.05). A support vector machine model for differentiating the normal and cancerous tissue was established. With the limited number of samples, an 85% diagnostic accuracy was found. The diagnostic information in the PCPCA can be further enriched by targeted optical contrast agents visualizing the microarchitecture in PCa tissues. F3 PAA-PEG nanoparticles was employed to stain the PCa cells in a transgenic mouse model, in which the microarchitectures of normal and cancerous prostate tissues are comparable to that in human. Statistically significant differences were observed between the contrast-enhanced normal and cancerous regions (p=0.038 at a significance of 0.05).
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