Malavika Chandra

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.

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.

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.

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.

Pancreatic tissue assessment using fluorescence and reflectance spectroscopy

The ability of multi-modal optical spectroscopy to detect signals from pancreatic tissue was demonstrated by studying human pancreatic cancer xenografts in mice and freshly excised human pancreatic tumor tissue. Measured optical spectra and fluorescence decays were correlated with tissue morphological and biochemical properties. The measured spectral features and decay times correlated well with expected pathological differences in normal, pancreatitis and adenocarcinoma tissue states. The observed differences between the fluorescence and reflectance properties of normal, pancreatitis and adenocarcinoma tissue indicate a possible application of multi-modal optical spectroscopy to differentiating between the three tissue classifications.

Sensing metabolic activity in tissue engineered constructs

Tissue engineered constructs can be employed to graft wounds or replace diseased tissue. Non-invasive methods are required to assess cellular viability in these constructs both pre- and post-implantation into patients. In this study, Monte Carlo simulations and fluorescence experiments were executed on ex vivo produced oral mucosa equivalent (EVPOME) constructs to investigate the fluorescence emitted at 355 nm excitation from these constructs. Both simulations and experiments indicated the need to investigate alternative excitation wavelengths in order to increase the cellular fluorescence from these constructs, while decreasing contributions from extra-cellular fluorophores.

Optical spectroscopy for clinical detection of pancreatic cancer

A prototype clinical fluorescence and reflectance spectrometer was developed and employed to detect human pancreatic adenocarcinoma. For the first time, quantitative pancreatic tissue models and chemometric algorithms were applied to successfully distinguish among tissue types.

Optical spectroscopy for quantitative sensing in human pancreatic tissues

Pancreatic adenocarcinoma has a five-year survival rate of only 6%, largely because current diagnostic methods cannot reliably detect the disease in its early stages. Reflectance and fluorescence spectroscopies have the potential to provide quantitative, minimally-invasive means of distinguishing pancreatic adenocarcinoma from normal pancreatic tissue and chronic pancreatitis. The first collection of wavelength-resolved reflectance and fluorescence spectra and time-resolved fluorescence decay curves from human pancreatic tissues was acquired with clinically-compatible instrumentation. Mathematical models of reflectance and fluorescence extracted parameters related to tissue morphology and biochemistry that were statistically significant for distinguishing between pancreatic tissue types. These results suggest that optical spectroscopy has the potential to detect pancreatic disease in a clinical setting.

Quantitative Optical Spectroscopy for Pancreatic Cancer Detection

We report novel optical diagnostic algorithms for clinical pancreatic tissue classification, including a photon-tissue interaction model developed to extract biophysical parameters from reflectance and fluorescence spectra to distinguish pancreatic adenocarcinoma from normal tissue and pancreatitis.

Quantitative, Noninvasive Optical Sensing in Tissue Engineered Oral Mucosal Constructs

Noninvasive characterization of ex-vivo produced oral-mucosal equivalent (EVPOME) tissues was simulated using a Monte Carlo code to predict spatially-resolved fluorescence in a multi-layered tissue model. Relative contributions to surface fluorescence from endogenous fluorophores were quantified.