SignificanceCollagen and lipid are important components of tumor microenvironments (TME) and participates in tumor development and invasion. It has been reported that collagen and lipid can be used as a hallmark to diagnosis and differentiate tumors.AimWe aim to introduce photoacoustic spectral analysis (PASA) method that can provide both the content and structure distribution of endogenous chromophores in biological tissues to characterize the tumor-related features for identifying different types of tumors.ApproachEx vivo human tissues with suspected squamous cell carcinoma (SCC), suspected basal cell carcinoma (BCC), and normal tissue were used in this study. The relative lipid and collagen contents in the TME were assessed based on the PASA parameters and compared with histology. Support vector machine (SVM), one of the simplest machine learning tools, was applied for automatic skin cancer type detection.ResultsThe PASA results showed that the lipid and collagen levels of the tumors were significantly lower than those of the normal tissue, and there was a statistical difference between SCC and BCC (p < 0.05), consistent with the histopathological results. The SVM-based categorization achieved diagnostic accuracies of 91.7% (normal), 93.3% (SCC), and 91.7% (BCC).ConclusionsWe verified the potential use of collagen and lipid in the TME as biomarkers of tumor diversity and achieved accurate tumor classification based on the collagen and lipid content using PASA. The proposed method provides a new way to diagnose tumors.
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.
Port-wine stain (PWS) is a discoloration of human skin caused by a vascular anomaly (i.e., capillary malformation in the skin). In the past years, several techniques have been developed for characterization and treatment evaluation of PWS. However, each of them has some limitations. Optical methods working in the ballistic regime, such as dermoscopy and VISIA, do not have sufficient penetration to cover the entire scale of PWS. High frequency ultrasound, although with better imaging depth, does not offer sufficient contrast to differentiate PWS and normal skin tissue. Therefore, current endpoint clinical assessment for PWS still relies on physicians’ subjective judgement. In this study, photoacoustic (PA) imaging utilizing light emitting diodes (LED) as the light source was adapted to the evaluation of PWS and response to photodynamic therapy (PDT). PA images as well as US images of the targeted skin area before and at different time points after the treatment were acquired. The imaging results from adults and children were also compared. The imaging findings demonstrate that the PWS levels of adult patients are significantly higher than children (p<0.01), which fits well with the knowledge that the vessel malefaction degree develops with patients’ age. The 2-month follow-up study on four children shows that the average PWS level reduced for 33.60%onstrat (p<0.01) as a result of 3-4 times of PDT treatment. This initial clinical trial on patients suggests PA imaging holds potential for quantitative assessment of PWS in clinical settings.
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).
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