Blood Flow Measurements Enable Optimization of Light Delivery for Personalized Photodynamic Therapy.

Fluence rate is an effector of photodynamic therapy (PDT) outcome. Lower light fluence rates can conserve tumor perfusion during some illumination protocols for PDT, but then treatment times are proportionally longer to deliver equivalent fluence. Likewise, higher fluence rates can shorten treatment time but may compromise treatment efficacy by inducing blood flow stasis during illumination. We developed blood-flow-informed PDT (BFI-PDT) to balance these effects. BFI-PDT uses real-time noninvasive monitoring of tumor blood flow to inform selection of irradiance, i.e., incident fluence rate, on the treated surface. BFI-PDT thus aims to conserve tumor perfusion during PDT while minimizing treatment time. Pre-clinical studies in murine tumors of radiation-induced fibrosarcoma (RIF) and a mesothelioma cell line (AB12) show that BFI-PDT preserves tumor blood flow during illumination better than standard PDT with continuous light delivery at high irradiance. Compared to standard high irradiance PDT, BFI-PDT maintains better tumor oxygenation during illumination and increases direct tumor cell kill in a manner consistent with known oxygen dependencies in PDT-mediated cytotoxicity. BFI-PDT promotes vascular shutdown after PDT, thereby depriving remaining tumor cells of oxygen and nutrients. Collectively, these benefits of BFI-PDT produce a significantly better therapeutic outcome than standard high irradiance PDT. Moreover, BFI-PDT requires ~40% less time on average to achieve outcomes that are modestly better than those with standard low irradiance treatment. This contribution introduces BFI-PDT as a platform for personalized light delivery in PDT, documents the design of a clinically-relevant instrument, and establishes the benefits of BFI-PDT with respect to treatment outcome and duration.

Effects of exercise training on calf muscle oxygen extraction and blood flow in patients with peripheral artery disease.

We employed near-infrared optical techniques, diffuse correlation spectroscopy (DCS), and frequency-domain near-infrared spectroscopy (FD-NIRS) to test the hypothesis that supervised exercise training increases skeletal muscle microvascular blood flow and oxygen extraction in patients with peripheral artery disease (PAD) who experience claudication. PAD patients ( n = 64) were randomly assigned to exercise and control groups. Patients in the exercise group received 3 mo of supervised exercise training. Calf muscle blood flow and oxygen extraction were optically monitored before, during, and after performance of a graded treadmill protocol at baseline and at 3 mo in both groups. Additionally, measurements of the ankle-brachial index (ABI) and peak walking time (PWT) to maximal claudication were made during each patient visit. Supervised exercise training was found to increase the maximal calf muscle blood flow and oxygen extraction levels during treadmill exercise by 29% (13%, 50%) and 8% (1%, 12%), respectively [ P < 0.001; median (25th percentile, 75th percentile)]. These improvements across the exercise group population were significantly higher than corresponding changes in the control group ( P < 0.004). Exercise training also increased PWT by 49% (18%, 101%) ( P = 0.01). However, within statistical error, the ABI, resting calf muscle blood flow and oxygen extraction, and the recovery half-time for hemoglobin\myoglobin desaturation following cessation of maximal exercise were not altered by exercise training. The concurrent monitoring of both blood flow and oxygen extraction with the hybrid DCS/FD-NIRS instrument revealed enhanced muscle oxidative metabolism during physical activity from exercise training, which could be an underlying mechanism for the observed improvement in PWT. NEW & NOTEWORTHY We report on noninvasive optical measurements of skeletal muscle blood flow and oxygen extraction dynamics before/during/after treadmill exercise in peripheral artery disease patients who experience claudication. The measurements tracked the effects of a 3-mo supervised exercise training protocol and revealed that supervised exercise training improved patient ability to increase microvascular calf muscle blood flow and oxygen extraction during physical activity.

Tissue Classification Using Optical Spectroscopy Accurately Differentiates Cancer and Chronic Pancreatitis.

OBJECTIVES: Current pancreatic cancer diagnostics cannot reliably detect early disease or distinguish it from chronic pancreatitis. We test the hypothesis that optical spectroscopy can accurately differentiate cancer from chronic pancreatitis and normal pancreas. We developed and tested clinically compatible multimodal optical spectroscopy technology to measure reflectance and endogenous fluorescence from human pancreatic tissues. METHODS: Freshly excised pancreatic tissue specimens (39 normal, 34 chronic pancreatitis, 32 adenocarcinoma) from 18 patients were optically interrogated, with site-specific histopathology representing the criterion standard. A multinomial logistic model using principal component analysis and generalized estimating equations provided statistically rigorous tissue classification. RESULTS: Optical spectroscopy distinguished pancreatic cancer from normal pancreas and chronic pancreatitis (sensitivity, 91%; specificity, 82%; positive predictive value, 69%; negative predictive value, 95%; area under receiver operating characteristic curve, 0.89). Reflectance alone provided essentially the same classification accuracy as reflectance and fluorescence combined, suggesting that a rapid, low-cost, reduced-footprint, reflectance-based device could be deployed without notable loss of diagnostic power. CONCLUSIONS: Our novel, clinically compatible, label-free optical diagnostic technology accurately characterizes pancreatic tissues. These data provide the scientific foundation demonstrating that optical spectroscopy can potentially improve diagnosis of pancreatic cancer and chronic pancreatitis.

Influence of probe pressure on the diffuse correlation spectroscopy blood flow signal: extra-cerebral contributions.

A pilot study explores relative contributions of extra-cerebral (scalp/skull) versus brain (cerebral) tissues to the blood flow index determined by diffuse correlation spectroscopy (DCS). Microvascular DCS flow measurements were made on the head during baseline and breath-holding/hyperventilation tasks, both with and without pressure. Baseline (resting) data enabled estimation of extra-cerebral flow signals and their pressure dependencies. A simple two-component model was used to derive baseline and activated cerebral blood flow (CBF) signals, and the DCS flow indices were also cross-correlated with concurrent Transcranial Doppler Ultrasound (TCD) blood velocity measurements. The study suggests new pressure-dependent experimental paradigms for elucidation of blood flow contributions from extra-cerebral and cerebral tissues.

Diffuse optical characterization of an exercising patient group with peripheral artery disease.

Peripheral artery disease (PAD) is a common condition with high morbidity. While measurement of tissue oxygen saturation (S(t)O(2)) has been demonstrated, this is the first study to assess both S(t)O(2) and relative blood flow (rBF) in the extremities of PAD patients. Diffuse optics is employed to measure hemodynamic response to treadmill and pedal exercises in 31 healthy controls and 26 patients. For S(t)O(2), mild and moderate/severe PAD groups show pronounced differences compared with controls. Pre-exercise mean S(t)O(2) is lower in PAD groups by 9.3% to 10.6% compared with means of 63.5% to 66.2% in controls. For pedal, relative rate of return of S(t)O(2) to baseline is more rapid in controls (p < 0.05). Patterns of rBF also differ among groups. After both exercises, rBF tend to occur at depressed levels among severe PAD patients compared with healthy (p < 0.05); post-treadmill, rBF tend to occur at elevated levels among healthy compared with severe PAD patients (p < 0.05). Additionally, relative rate of return to baseline S(t)O(2) is more rapid among subjects with reduced levels of depression in rBF (p = 0.041), even after adjustment for ankle brachial index. This suggests a physiologic connection between rBF and oxygenation that can be measured using diffuse optics, and potentially employed as an evaluative tool in further studies.

In vivo optical spectroscopy for improved detection of pancreatic adenocarcinoma: a feasibility study.

Pancreatic adenocarcinoma has a five-year survival rate of less than 6%. This low survival rate is attributed to the lack of accurate detection methods, which limits diagnosis to late-stage disease. Here, an in vivo pilot study assesses the feasibility of optical spectroscopy to improve clinical detection of pancreatic adenocarcinoma. During surgery on 6 patients, we collected spectrally-resolved reflectance and fluorescence in vivo. Site-matched in vivo and ex vivo data agreed qualitatively and quantitatively. Quantified differences between adenocarcinoma and normal tissues in vivo were consistent with previous results from a large ex vivo data set. Thus, optical spectroscopy is a promising method for the improved diagnosis of pancreatic cancer in vivo.

Characterizing human pancreatic cancer precursor using quantitative tissue optical spectroscopy.

In a pilot study, multimodal optical spectroscopy coupled with quantitative tissue-optics models distinguished intraductal papillary mucinous neoplasm (IPMN), a common precursor to pancreatic cancer, from normal tissues in freshly excised human pancreas. A photon-tissue interaction (PTI) model extracted parameters associated with cellular nuclear size and refractive index (from reflectance spectra) and extracellular collagen content (from fluorescence spectra). The results suggest that tissue optical spectroscopy has the potential to characterize pre-cancerous neoplasms in human pancreatic tissues.

Photon-tissue interaction model enables quantitative optical analysis of human pancreatic tissues.

A photon-tissue interaction (PTI) model was developed and employed to analyze 96 pairs of reflectance and fluorescence spectra from freshly excised human pancreatic tissues. For each pair of spectra, the PTI model extracted a cellular nuclear size parameter from the measured reflectance, and the relative contributions of extracellular and intracellular fluorophores to the intrinsic fluorescence. The results suggest that reflectance and fluorescence spectroscopies have the potential to quantitatively distinguish among pancreatic tissue types, including normal pancreatic tissue, pancreatitis, and pancreatic adenocarcinoma.

Spectral areas and ratios classifier algorithm for pancreatic tissue classification using optical spectroscopy.

Pancreatic adenocarcinoma is one of the leading causes of cancer death, in part because of the inability of current diagnostic methods to reliably detect early-stage disease. We present the first assessment of the diagnostic accuracy of algorithms developed for pancreatic tissue classification using data from fiber optic probe-based bimodal optical spectroscopy, a real-time approach that would be compatible with minimally invasive diagnostic procedures for early cancer detection in the pancreas. A total of 96 fluorescence and 96 reflectance spectra are considered from 50 freshly excised tissue sites-including human pancreatic adenocarcinoma, chronic pancreatitis (inflammation), and normal tissues-on nine patients. Classification algorithms using linear discriminant analysis are developed to distinguish among tissues, and leave-one-out cross-validation is employed to assess the classifiers' performance. The spectral areas and ratios classifier (SpARC) algorithm employs a combination of reflectance and fluorescence data and has the best performance, with sensitivity, specificity, negative predictive value, and positive predictive value for correctly identifying adenocarcinoma being 85, 89, 92, and 80%, respectively.

Optical spectroscopy detects histological hallmarks of pancreatic cancer.

An empirical model was developed to interpret differences in the experimentally measured reflectance and fluorescence spectra of freshly excised human pancreatic tissues: normal, adenocarcinoma, and pancreatitis (inflammation). The model provided the first quantitative links between spectroscopic measurements and histological characteristics in the human pancreas. The reflectance model enabled the first (to our knowledge) extraction of wavelength resolved absorption and reduced scattering coefficients for normal and diseased human pancreatic tissues. The fluorescence model employed reflectance information to extract attenuation free "intrinsic" endogenous fluorescence spectra from normal pancreatic tissue, pancreatic adenocarcinoma, and pancreatitis. The method developed is simple, intuitive, and potentially useful for a range of applications in optical tissue diagnostics. This approach is potentially applicable to in vivo studies, because it can account for the absorptive effects of blood in tissues.

Probing pancreatic disease using tissue optical spectroscopy.

Pancreatic adenocarcinoma, one of the leading causes of cancer death in the United States, has a five-year survival rate of only 4%. Present detection methods do not provide accurate diagnosis in the disease's early stages. To investigate whether optical spectroscopy could potentially aid in early diagnosis and improve survival rates, reflectance and fluorescence spectroscopies were employed for the first time in a limited pilot study to probe freshly excised human pancreatic tissues (normal, pancreatitis, and adenocarcinoma) and in vivo human pancreatic cancer xenografts in nude mice. In human pancreatic tissues, measurements were associated with endogenous fluorophores NAD(P)H and collagen, as well as tissue optical properties, with larger relative collagen content detected in adenocarcinoma and pancreatitis than normal. Good correspondence was observed between spectra from adenocarcinoma and cancer xenograft tissues. Reflectance data indicated that adenocarcinoma had higher reflectance in the 430- to 500-nm range compared to normal and pancreatitis tissues. The observed significant differences between the fluorescence and reflectance properties of normal, pancreatitis, and adenocarcinoma tissues present an opportunity for future statistical validation on a larger patient pool and indicate a potential application of multimodal optical spectroscopy to differentiate between diseased and normal pancreatic tissue states.

Quantitative molecular sensing in biological tissues: an approach to non-invasive optical characterization.

A method to non-invasively and quantitatively characterize thick biological tissues by combining both experimental and computational approaches in tissue optical spectroscopy was developed and validated on fifteen porcine articular cartilage (AC) tissue samples. To the best of our knowledge, this study is the first to couple non-invasive reflectance and fluorescence spectroscopic measurements on freshly harvested tissues with Monte Carlo computational modeling of time-resolved propagation of both excitation light and multi-fluorophore emission. For reflectance, quantitative agreement between simulation and experiment was achieved to better than 11%. Fluorescence data and simulations were used to extract the ratio of the absorption coefficients of constituent fluorophores for each measured AC tissue sample. This ratio could be used to monitor relative changes in concentration of the constituent fluorophores over time. The samples studied possessed the complexity and variability not found in artificial tissue-simulating phantoms and serve as a model for future optical molecular sensing studies on tissue engineered constructs intended for use in human therapeutics. An optical technique that could non-invasively and quantitatively assess soft tissue composition or physiologic status would represent a significant advance in tissue engineering. Moreover, the general approach described here for optical characterization should be broadly applicable to quantitative, non-invasive molecular sensing applications in complex, three-dimensional biological tissues.