Minimally-invasive alternatives for prostate cancer treatment are an unmet clinical need. We are currently conducting clinical trials using interstitial photothermal therapy (PTT) in focal (intermediate-risk) prostate cancer, targeting the largest (index) lesion, utilizing near-infrared (NIR) laser light that is delivered via one or more laser fibers placed interstitially to cover the target volume. This procedure is done using an interventional MRI suite where real-time MR thermometry is used to monitor treatment progression as a surrogate for tissue coagulation. We investigate here if photoacoustic imaging (PAI) could be used instead of MR thermometry to provide direct and higher specificity/sensitivity monitoring of the coagulation-front, particularly for the purpose of avoiding rectal wall damage. For this, we developed an in vivo canine PTT model and experiments were performed in 6 beagles with intact normal prostates, using similar approaches to those used in ongoing clinical trials. PTT also performed in vivo as well as in ex vivo porcine muscle. Initial results demonstrated the feasibility of both the PTT technique as well as an optimized monitoring platform. In ex vivo porcine muscle PAI demonstrated correlation with temperature (R2 = 0.66) that provided the impetus to move in vivo. However, due to noise and the relatively small changes in the PAI signal with coagulation this did not provide as much imaging depth or resolution as MR thermometry, the current gold standard. With newer PAI probes and deployment of the PAI light sources, it may be possible to increase the sensitivity of PAI for in vivo treatment monitoring. This work was supported by the Terry Fox Research Institute (Grant #1075).
We investigate the feasibility of photoacoustic (PA) imaging to quantify the concentration of surface-localized nanoparticles, using tissue-mimicking phantoms and imaging with a commercial PA instrument at 815 nm and a linear-array transducer at a center frequency of 40 MHz. The nanoparticles were J-aggregating porphysomes (JNP) comprising self-assembling, all-organic porphyrin-lipid micelles with a molar absorption coefficient of 8.7×108 cm−1 M−1 at this wavelength. The PA signal intensity versus JNP areal concentration followed a sigmoidal curve with a reproducible linear range of ∼17 fmol/mm2 to 11 pmol/mm2, i.e., ∼3 orders of magnitude with ±34% error. For physiologically-relevant conditions (i.e., optical scattering-dominated tissues: transport albedo >0.8) and JNP concentrations above ∼330 fmol/mm2, the PA signal depends only on the nanoparticle concentration. Otherwise, independent measurement of the optical absorption and scattering properties of the underlying tissue is required for accurate quantification. The implications for surface PA imaging, such as in the use of targeted nanoparticles applied topically to tissue as in endoscopic diagnosis, are considered.
Accurate endoscopic detection and dysplasia in patients with Barrett’s esophagus (BE) remains a major unmet clinical need. Current diagnosis use multiple biopsies under endoscopic image guidance, where up to 99% of the tissue remains unsampled, leading to significant risk of missing dysplasia. We conducted an ex vivo clinical trial using photoacoustic imaging (PAI) in patients undergoing endoscopic mucosal resection (EMR) with known high-grade dysplasia for the purpose of characterizing the esophageal microvascular pattern, with the long-term goal of performing in vivo endoscopic PAI for dysplasia detection and therapeutic guidance. EMR tissues were mounted immediately on an agar layer and covered with ultrasound gel. Digital photography guided the placement of the PAI transducer (40 MHz center frequency). The luminal side of the specimen was scanned over a field of view of 14 mm (width) by 15 mm (depth) at 680, 750, 824, 850 and 970 nm. Acoustic images were simultaneously acquired. Tissues were then sliced and fixed in formalin for histopathology with H and E staining. Analysis consisted of co-registration and correlation between the intrinsic PAI features and the histological images. The initial PAI + ultrasound images from 8 BE patients have demonstrated the technical feasibility of this approach and point to the potential of PAI to reveal the microvascular pattern within EMR specimens. There are several technical factors to be considered in rigorous interpretation of the PAI characteristics, including the loss of blood from the ex vivo specimens and the limited depth penetration of the photoacoustic signal.
The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%/100%, for SCC and BCC versus AK (57 versus 14 lesions) was 95%/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device.
We present a Monte Carlo lookup table (MCLUT)-based inverse model for extracting optical properties from tissue-simulating phantoms. This model is valid for close source-detector separation and highly absorbing tissues. The MCLUT is based entirely on Monte Carlo simulation, which was implemented using a graphics processing unit. We used tissue-simulating phantoms to determine the accuracy of the MCLUT inverse model. Our results show strong agreement between extracted and expected optical properties, with errors rate of 1.74% for extracted reduced scattering values, 0.74% for extracted absorption values, and 2.42% for extracted hemoglobin concentration values.
Diffuse reflectance and fluorescence spectroscopy are popular research techniques for noninvasive disease diagnostics. Most systems include an optical fiber probe that transmits and collects optical spectra in contact with the suspected lesion. The purpose of this study is to investigate probe pressure effects on human skin spectroscopic measurements. We conduct an in-vivo experiment on human skin tissue to study the short-term (<2 s) and long-term (>30 s) effects of probe pressure on diffuse reflectance and fluorescence measurements. Short-term light probe pressure (P0 < 9 mN/mm2) effects are within 0 ± 10% on all physiological properties extracted from diffuse reflectance and fluorescence measurements, and less than 0 ± 5% for diagnostically significant physiological properties. Absorption decreases with site-specific variations due to blood being compressed out of the sampled volume. Reduced scattering coefficient variation is site specific. Intrinsic fluorescence shows a large standard error, although no specific pressure-related trend is observed. Differences in tissue structure and morphology contribute to site-specific probe pressure effects.Therefore, the effects of pressure can be minimized when the pressure is small and applied for a short amount of time; however, long-term and large pressures induce significant distortions in measured spectra.
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