Browsing by Subject "Diffuse reflectance spectroscopy"

Diffuse reflectance spectroscopy (DRS) is a simple, yet powerful technique that has the potential to offer practical, non-invasive, and cost effective information for op- tical diagnostics and therapeutics guidance. Any progress towards moving DRS systems from their current laboratory settings to clinical settings, field settings and ambitiously to home settings, is a significant contribution to society in terms of reducing ever growing healthcare expenditures of an aging society. Additionally, im- proving on the existing mathematical models used to analyze DRS signals; in terms of speed, robustness, accuracy, and capability in accounting for larger feature space dimensionality (i.e. extraction of more tissue-relevant information) is equally im- portant for real-time diagnosis in the desired settings and to enable use of DRS in as many biomedical applications (e.g. skin cancer diagnosis, diabetics care, tissue oxygenation monitoring) as possible. Improving the reflectance signal complexity and density through novel DRS instrumentation, would facilitate development of the desired models or put the existing ones built on simulations in practical use; which otherwise could not go beyond being a theoretical demonstration.

DRS studies tissue morphology and composition through quantification of one or more (ideally all of them) of the tissue- and wavelength-specific optical properties: absorption coefficient (μa), reduced scattering coefficient (μ1s), scattering anisotropy (g), tissue thickness, and scattering phase function details (e.g. higher order moments of the scattering phase function). DRS involves sampling of diffusely reflected photons which experience multiple scattering and absorption as they travel within the tissue, at the tissue surface. Spatially resolved diffuse reflectance spectroscopy (SRDRS) is a subset of general DRS technique, which involves sampling of diffuse reflectance signals at multiple distances to an illumination source. SRDRS provides additional spatial information about the photon path; yielding depth-resolved tissue information critical to layered tissue analysis and early cancer diagnostics. Exist- ing SRDRS systems use fiber optic probes, which are limited in accommodation of large number and high-density collection fibers (i.e. yielding more and dense spa- tially resolved diffuse reflectance (SRDR) measurement data) due to difficulty of fiber multiplexing. The circular shape of the fibers restricts the implementable probe ge- ometries and reduces the fill factor for a given source to detector (i.e. collection fiber) separation (SDS); resulting in reduced light collection efficiency. The finite fiber nu- merical aperture (NA) reduces the light collection efficiency well as; and prevents selective interrogation of superficial tissues where most cancers emerge. Addition- ally, SRDR systems using fiber optic probes for photon collection, require one or more photodetectors (i.e. a cooled CCD); which are often expensive components of the systems.

This thesis deals with development of an innovative silicon SRDRS probe, which partially addresses the challenge of realizing high measurement density, miniaturized, and inexpensive SRDRS systems. The probe is fabricated by conventional, flexible and inexpensive silicon fabrication technology, which demonstrates the feasibility of developing SRDRS probes in any desired geometry and complexity. Although this approach is simple and straightforward, it has been overlooked by the DRS community due to availability of the conventional fiber optic probe technology. This new probe accommodates large number and high density of detectors; and it is in the form of a concentric semi-annular photodiode (PD) array (CMPA) with a central illumination aperture. This is the first multiple source-detector spacing Si SRDRS probe reported to date, and the most densely packed SRDRS probe reported to date for all types of SRDRS systems. The closely spaced and densely packed detectors enable higher density SRDR measurements compared to fiber-based SRDR probes, and the higher PD NA compared to that of fibers results in a higher SNR increasing light collection efficiency. The higher NA of the PDs and the presence of PDs positioned at very short distances from the illumination aperture center enable superficial tissue analysis as well as depth analysis.

Breast conserving surgery (BCS) is a common treatment option for breast cancer patients. The goal of BCS is to remove the entire tumor from the breast while preserving as much normal tissue as possible for a better cosmetic outcome after surgery. Specifically, the excised specimen must have at least 2 mm of normal tissue surrounding the diseased mass. Unfortunately, a staggering 20-70% of patients undergoing BCS require repeated surgeries due to the incomplete removal of the tumor diagnosed post-operatively. Due to these high re-excision rates as well as limited post-operative histopathological sampling of the tumor specimen, there is an unmet clinical need for margin assessment. Quantitative diffuse reflectance spectral imaging has previously been explored as a promising, method for providing real-time visual maps of tissue composition to help surgeons determine breast tumor margins to ensure the complete removal of the disease during breast conserving surgery. We have leveraged the underlying sources of contrast in breast tissue, specifically total hemoglobin content, beta-carotene content, and tissue scattering, and developed various fiber optics based spectral imaging systems for this clinical application. Combined with a fast inverse Monte Carlo model of reflectance, previous studies have shown that this technology may be able to decrease re-excision rates for BCS. However, these systems, which all consist of a broadband source, fiber optics probes, an imaging spectrograph and a CCD, have severe limitations in system footprint, tumor area coverage, and speed for acquisition and analysis. The fiber based spectral imaging systems are not scalable to smaller designs that cover a large surveillance area at a very fast speed, which ultimately makes them impractical for use in the clinical environment. The objective of this dissertation was to design, develop, test, and show clinical feasibility of a novel wide field spectral imaging system that utilizes the same scientific principles of previously developed fiber optics based imaging systems, but improves upon the technical issues, such as size, complexity, and speed,to meet the demands of the intra-operative setting.

First, our simple re-design of the system completely eliminated the need for an imaging spectrograph and CCD by replacing them with an array of custom annular photodiodes. The geometry of the photodiodes were designed with the goal of minimizing optical crosstalk, maximizing SNR, and achieving the appropriate tissue sensing depth of up to 2 mm for tumor margin assessment. Without the imaging spectrograph and CCD, the system requires discrete wavelengths of light to launch into the tissue sample. A wavelength selection method that combines an inverse Monte Carlo model and a genetic algorithm was developed in order to optimize the wavelength choices specifically for the underlying breast tissue optical contrast. The final system design consisted of a broadband source with an 8-slot filter wheel containing the optimized set of wavelength choices, an optical light guide and quartz light delivery tube to send the 8 wavelengths of light in free space through the back apertures of each annular photodiode in the imaging array, an 8-channel integrating transimpedance amplifier circuit with a switch box and data acquisition card to collect the reflectance signal, and a laptop computer that controls all the components and analyzes the data.

This newly designed wide field spectral imaging system was tested in tissue-mimicking liquid phantoms and achieved comparable performance to previous clinically-validated fiber optics based systems in its ability to extract optical properties with high accuracy. The system was also tested in various biological samples, including a murine tumor model, porcine tissue, and human breast tissue, for the direct comparison with its fiber optics based counterparts. The photodiode based imaging system achieved comparable or better SNR, comparable extractions of optical properties extractions for all tissue types, and feasible improvements in speed and coverage for future iterations. We show proof of concept in performing fast, wide field spectral imaging with a simple, inexpensive design. With a reduction in size, cost, number of wavelengths used, and overall complexity, the system described by this dissertation allows for a more seamless scaling to higher pixel number and density in future iterations of the technology, which will help make this a clinically translatable tool for breast tumor margin assessment.

The visible wavelength range has proven to be a useful spectral window for observing biophotonic events such as absorption in materials (oxy-hemoglobin and deoxy-hemoglobin), light scattering in biological tissue, and biochemical and fluorescence reactions. Diffuse reflectance spectroscopy (DRS) is a technique that utilizes the diffuse reflectance spectra from turbid media (e.g. biological tissue) to quantify the optical properties (e.g. absorption and scattering) of those media. DRS in the visible wavelength range can be utilized to optically differentiate between healthy and cancerous tissue, and thus has applications in intra-operative tumor margin assessment.

The footprint of conventional DRS systems used for intra-operative tissue margin assessment prohibits their widespread use inside the surgical suite, where space is at a premium. Conventional quantitative DRS imaging systems utilize unwieldy fiber probes, cooled CCD cameras, and imaging spectrographs for imaging tissue margins. These system components not only increase system size, limiting their use inside the surgical suite, but also limit imaging resolution, imaging speed, and increase overall system cost.

Silicon is an attractive candidate for the development of compact, customized photodetector elements for biophotonic imaging applications such as intra-operative tumor margin assessment using DRS. This thesis deals with the design and development of a customized DRS imaging probe composed of custom silicon imaging arrays for intra-operative breast tumor margin assessment. The first generation of the customized imaging probe consisted of a 4x4 array of annular epitaxial Si pn junction photodiodes (PDs) with a measured responsivity of 0.28 A/W - 0.37 A/W for λ= 470 nm - 600 nm, and a measured dark current density of 1.456 nA/cm2 - 4.48 nA/cm2. The imaging array was used to detect diffuse reflectance when placed in direct contact with tissue. A quartz light delivery tube coupled to a xenon lamp was optimized to deliver light to the tissue through the holes of the annular imaging array across a 256 mm2 imaging area. The pixel-to-pixel spacing in the imaging array was 4.5 mm, the highest resolution reported to date for a multi-pixel DRS probe. This resolution was limited by pixel-to-pixel optical crosstalk, which was theoretically calculated and experimentally characterized, to validate the theoretical model for future designs. This first generation probe was successfully tested on diffuse reflectance standards, tissue-mimicking phantoms, animal tissue, and human breast tissue, and yielded an SNR of 30 dB - 55 dB on all measured specimens.

The next generation of the customized imaging probe consisted of a 4x4 array of annular thin-film Si pn junction PDs heterogeneously bonded to a transparent Pyrex substrate, to enable integration with a guided wave light delivery system. The 4x4 thin-film PD array design and development was prototyped using a 1x2 thin-film PD array heterogeneously bonded to a Pyrex substrate. The responsivity and dark current of the thin-film PDs in the 1x2 array were measured to be 0.19 A/W - 0.34 A/W for λ= 470 nm - 600 nm and 0.63 nA/cm2, respectively. The process for the 1x2 thin-film PD array was scaled to fabricate a 4x4 array of thin-film PDs for DRS, and the 4x4 array was optically and electrically characterized. These heterogeneously bonded thin-film single crystal Si PDs have the highest uncooled responsivity to dark current density ratio (greater than 0.30 - 0.54 cm2/nW for λ= 470 nm - 600 nm) reported to date, to the best of our knowledge. The 1x2 array of thin-film PDs were also heterogeneously bonded to a flexible substrate without any degradation in PD optical and electrical characteristics, opening the door towards conformal tissue imaging.

Worldwide, head and neck squamous cell cancers (HNSCC) account for over 375,000 deaths annually. The majority of these cancers arise in the outermost squamous cells which progress through a series of precancerous changes before developing into invasive HNSCC. It is widely accepted that prognosis is strongly correlated to the stage of diagnosis, with early detection more than doubling the patient’s chance of survival. Currently, however, 60% of HNSCCs are diagnosed when they have already progressed to stage 3 or stage 4 disease. The current diagnostic method of visual examination often fails to recognize early indicators of HNSCC, thereby missing an important prevention window.

Determination of cancer from non-malignant tissues is dependent on pathological examination of lesion biopsies. Thus, all patients with any clinically suspicious lesions undergo surgical biopsies. Furthermore, these surgical biopsies carry risks. In addition to the risk of general anesthesia for patients undergoing panedoscopy, some patients have poor healing and develop ulcerations or infections as a result of surgical biopsy at any anatomical site. Additionally, studies have shown that approximately 50% of suspected biopsies are later pathologically confirmed normal. An enormous amount of labor, facility, and monetary resources are expended on non-malignant biopsies and patients who ultimately have no malignancy. It would be of immense overall benefit to clinicians and patients to have a non-invasive and portable technique that could rapidly identify those patients that would benefit from further surgical biopsy from those that only need follow-up clinical observations.

Once carcinoma is confirmed in a patient, treatment currently involves modalities of surgery, radiation, and chemotherapy. Radiotherapy plays a significant role, particularly in the management of localized HNSCC, because it is a non-invasive and function-preserving modality. However, the effectiveness of radiotherapy is limited by hypoxia. Previous studies showed that tumors reoxygenated during radiotherapy treatment may have a better prognosis. Despite decades of work, there is still no reliable, cost-effective way for measuring tumor hypoxia over multiple time points to estimate the prognosis.

To address these unmet clinical needs, three aims were proposed. The first aim was to improve early detection by identifying biomarkers of early pre-cancer as well as developing an objective algorithm to detect early disease. Neovasculature is an important biomarker for early cancer diagnosis. Even before the development of a clinically detectable lesion, the tumor vasculature undergoes structural and morphological changes in response to oncogenic signaling pathways [8]. Without receiving a sufficient supply of oxygen and nutrients to proliferate, early tumor growth is limited to only 1-2 mm. High-resolution optical imaging is well suited to characterize the earliest neovascularization changes that accompany neoplasia owing to its sensitivity to hemoglobin absorption and resolution to visualize capillary level architecture. Dark field microscopy is a low-cost and robust method to image the neovasculature. We imaged neovascularization in vivo in a spontaneous hamster oral mucosa carcinogen model using a label-free, reflected-light spectral dark field microscope. Hamsters’ cheek pouches were painted with 7, 12-Dimethylbenz[a]anthracene (DMBA) to induce precancerous to cancerous changes, or mineral oil as control. Spectral dark field images were obtained during carcinogenesis and in control oral mucosa, and quantitative vascular features were computed. Vascular tortuosity increased significantly in oral mucosa diagnosed as hyperplasia, dysplasia and squamous cell carcinoma (SCC) compared to normal. Vascular diameter and area fraction decreased significantly in dysplasia and SCC compared to normal. The areas under the receiver operative characteristic (ROC) curves (AUC) computed using a Support Vector Machine (SVM) were 0.95 and 0.84 for identifying SCC or dysplasia, respectively, vs. normal and hyperplasia oral mucosa combined. To improve AUCs for identifying dysplasia, quantitative vascular features were computed again after the vessels were split into large and small vessels based on diameter. The large vessels preserved the same significant trends, while small vessels demonstrated the opposite trends. Significant increases in diameter and decreases in area fraction were observed in SCC and dysplasia. The AUCs were improved to 0.99 and 0.92 for identifying SCC and dysplasia. These results suggest that dark field vascular imaging is a promising tool for pre-cancer detection.

Optical imaging can also be applied to quantifying other important characteristics of solid tumors in head and neck cancer (HNC), such as hypoxia, abnormal vascularity and cell proliferation. Diffuse reflectance spectroscopy is a simple and robust method to measure tissue oxygenation, vascularity and cell density. It is particularly suitable for applications in the operation room because of its compact design and portability. In addition, a fiber probe-based system is ideal for obtaining measurements at suspicious lesions in the head and neck area during surgery. Thus, my second aim was to reduce the number of unnecessary HNSCC biopsies by developing a robust tool and rapid analysis method appropriate for clinical settings. We propose the use of morphological optical biomarkers for rapid detection of human HNSCC by leveraging the underlying tissue characteristics in the aerodigestive tracts Prior to biopsy, diffuse reflectance spectra were obtained from malignant and contra-lateral non-malignant tissues of 57 patients undergoing panendoscopy. Oxygen saturation (SO2), total hemoglobin concentration ([THb]), and the reduced scattering coefficient were extracted using an inverse Monte Carlo (MC) method previously developed by former student in our lab. Differences in malignant and non-malignant tissues were examined based on two different groupings: by anatomical site and by morphological tissue type. Measurements were acquired from 252 sites, 51 of which were pathologically classified as SCC. Optical biomarkers exhibited statistical differences between malignant and non-malignant samples. Contrast was enhanced when parsing tissues by morphological classification rather than by anatomical subtype for unpaired comparisons. Corresponding linear discriminant models using multiple optical biomarkers showed improved predictive ability when accounting for morphological classification, particularly in node-positive lesions. The false-positive rate was retrospectively found to decrease by 34.2% in morphologically- vs. anatomically-derived predictive models. In glottic tissue, the surgeon exhibited a false-positive rate of 45.7% while the device showed a lower false-positive rate of only 12.4%. Additionally, comparisons of optical parameters were made to further understand the physiology of tumor staging and potential causes of high surgeon false-positive rates. Optical spectroscopy is a user-friendly, non-invasive tool capable of providing quantitative information to discriminate malignant from non-malignant head and neck tissues. Predictive models demonstrated promising results for diagnostics. Furthermore, the strategy described appears to be well suited to reduce the clinical false-positive rate.

To further improve the speed for extracting the tissue oxygenation and [THb] to reduce the time when patients were under anesthesia, the third aim was to develop a rapid heuristic ratiometric analysis for estimating tissue [THb] and SO2 from measured tissue diffuse reflectance spectra. The analysis was validated in tissue-mimicking phantoms and applied to clinical measurements in head and neck, cervical and breast tissues. The analysis works in two steps. First, a linear equation that translates the ratio of the diffuse reflectance spectra at 584 nm to 545 nm to estimate the tissue [THb] using a Monte carlo (MC)-based lookup table was developed. This equation is independent of tissue scattering and oxygen saturation. Second, SO2 was estimated using non-linear logistic equations that translate the ratio of the diffuse reflectance spectra at 539 nm to 545 nm into the tissue SO2. Correlations coefficients of 0.89 (0.86), 0.77 (0.71) and 0.69 (0.43) were obtained for the tissue hemoglobin concentration (oxygen saturation) values extracted using the full spectral MC and the ratiometric analysis, for clinical measurements in head and neck, breast and cervical tissues, respectively. The ratiometric analysis was more than 4000 times faster than the inverse MC analysis for estimating tissue [THb] and SO2 in simulated phantom experiments. In addition, the discriminatory power of the two analyses was similar. These results show the potential of such empirical tools to rapidly estimate tissue hemoglobin and oxygenation for real-time applications.

In addition to its use as a diagnostic marker for various cancers, tissue oxygenation is believed to play a role in the success of cancer therapies, particularly radiotherapy. However, since little effort has been made to develop tools to exploit this relationship, the fourth aim was to estimate patient prognosis by measuring tumor hypoxia over multiple time points so physicians are able to develop more informed and effective clinical treatment plan. To test if oxygenation kinetics correlates with the likelihood for local tumor control following fractionated radiotherapy, we again used diffuse reflectance spectroscopy to noninvasively measure tumor vascular oxygenation and [THb] associated with radiotherapy of 5 daily fractions (7.5, 9 or 13.5 Gy/day) in FaDu xenografts. Spectroscopy measurements were obtained immediately before each daily radiation fraction and during the week after radiotherapy. SO2 and [THb] were computed using an inverse MC model. Oxygenation kinetics during and after radiotherapy, but before a change in tumor volume, was associated with local tumor control. Locally controlled tumors exhibited significantly faster increases in oxygenation after radiotherapy (days 12-15) compared with tumors that recurred locally. (2) Within the group of tumors that recurred, faster increases in oxygenation during radiotherapy (days 3-5) were correlated with earlier recurrence times. An AUC of 0.74 was achieved when classifying the local control tumors from all irradiated tumors using the oxygen kinetics with a logistic regression model. (3) The rate of increase in oxygenation was radiation dose dependent. Radiation doses ≤9.5 Gy/day did not initiate an increase in oxygenation whereas 13.5 Gy/day triggered significant increases in oxygenation during and after radiotherapy. Additional confirmation is required in other tumor models, but these results suggest that monitoring tumor oxygenation kinetics could aid in the prediction of local tumor control after radiotherapy.

Angiogenesis is a highly regulated process to support tissue growth. Neovasculature is designed by nature to grow toward areas lacking nutrition and oxygen. Cancer cells proliferate too quickly to have their nutritional and oxygen needs completely satisfied, which results in an imbalanced state of angiogenesis leading to tortuous blood vessels, hypoxic tissues and radioresistance. We characterized the tumor-induced vascular features with simple, robust and low-cost dark field microscopy and spectroscopy to enable early cancer diagnosis, improvement of surgical biopsy accuracy and better predict the prognosis of radiotherapy for HNC. Our results demonstrated that these noninvasively measured, label-free vascular features are able to detect pre-cancer, reduce unnecessary surgical biopsies and predict prognosis of radiotherapy.