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Abstract
Microwave ablation is a minimally invasive image guided thermal therapy for cancer that can be adapted to endoscope use in the gastrointestinal (GI) tract. Microwave ablation in the GI tract requires precise control over the ablation zone that could be guided by high resolution imaging with quantitative contrast. Optical coherence tomography (OCT) provides ideal imaging resolution and allows for the quantification of tissue scattering properties to characterize ablated tissue. Visible and near-infrared OCT image analysis demonstrated increased scattering coefficients (μs) in ablated versus normal tissues (Vis: 347.8%, NIR: 415.0%) and shows the potential for both wavelength ranges to provide quantitative contrast. These data suggest OCT could provide quantitative image guidance and valuable information about antenna performance in vivo.
© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Barrett’s esophagus (BE) is a premalignant lesion strongly associated with the development of esophageal adenocarcinoma, a cancer with a 5-year survival rate of less than 15% [1]. Suspected lesions are evaluated with both endoscopy and endoscopic biopsy to diagnose the abnormal region as no dysplasia, low-grade dysplasia, high-grade dysplasia, or intramucosal carcinoma. In the case of high-grade dysplasia and intramucosal carcinoma, endoscopic resection is used to remove lesions followed by endoscopic radiofrequency ablation (RFA) to ensure total destruction of malignant tissue [2]. However, there has been high variability in RFA success rates for treatment of intestinal metaplasia or BE [3]. The eradication rates of high-grade dysplasia and intestinal metaplasia are lower than the eradication rate of low-grade dysplasia. Additionally, the presence of buried of glands may result in recurrence and have been observed in patients after RFA treatment [4–6]. Better treatment outcomes will require improved ablation methods as well as depth-resolved quantitative imaging of ablation zones.
Endoscopic microwave systems currently remain experimental [7] and have not reached clinical use in the GI tract. Microwave heating induces agitation of polar molecules in the tissue and is not limited by media with low electrical conductivity [8]. As a result, microwaves can penetrate electrically inhomogeneous tissues more uniformly than electrical current and may be a tool to increase the success of ablation therapy in more advanced stages of BE.
To treat BE successfully, the Barrett’s epithelium must be eradicated completely with minimal damage to the submucosa and surrounding healthy tissue [9, 10]. Magnetic resonance imaging, ultrasound, and computed tomography are current methods of image guidance in ablation therapy for larger organs such as the liver and kidneys [11]. However, these imaging modalities are insufficient to resolve the microscopic structures in esophageal tissue layers [12, 13]. Optical coherence tomography (OCT), a high-resolution and high-speed in vivo imaging method, has potential as an image guidance tool in ablation therapy. OCT detects backscattered light from tissue to provide rapid, label-free, volumetric assessment of tissue structure [14–16]. OCT signal is derived from sample optical properties which in tissue are dependent on ultrastructure of the extracellular matrix and cellular morphology [17, 18]. Furthermore, OCT has is capable of determining optical properties given the proper corrections to signal attenuation from system characteristics [18, 19]. A change in optical properties can indicate a progression from benign tissue into diseased state or injury [17, 20–22]. Alterations in tissue structure and optical properties caused by ablation could be measured using OCT image analysis to provide quantitative assessment of ablation zone formation in esophageal tissue.
Previous ablation studies have observed a change in the backscattering coefficient in tissue ablated via a laser [23]. RFA can also induce changes in optical properties that can be detected spectroscopically as the ablation zone forms [24, 25]. Previous work has indicated an increase in scattering and decrease in anisotropy of scattering when tissue is ablated, which agrees roughly with the effects of dehydration in tissue [25, 26]. It was also shown that temperatures above 60 °C induce protein aggregation from denaturation, which increases scattering [27, 28].
We hypothesize that both visible and near infrared (NIR) OCT are sensitive to changes in scattering that result from microwave ablation of the esophagus. The difference in wavelength between NIR and visible OCT affects resolution and maximum imaging depth, but also allows probing of different length scales of the tissue structure, and so has potential to provide complementary information about the ablated tissue. Analysis of OCT signals may be used to map the extent of the ablation zone with resolution not achievable by other imaging methods. Previous OCT imaging of esophageal ablation has quantified coagulum thickness as a metric for determination of ablation extent, however quantification of the scattering coefficient, μs, would provide a useful method to discriminate the transition zone of the ablation [29]. The transition zone is particularly difficult to characterize, not just by OCT, but also other methods of optical property determination [30]. Quantification of scattering properties in the ablation zone would provide valuable metrics for high-resolution image guidance.
The purpose of this study is to evaluate the optical scattering properties of microwave ablated esophagus samples with NIR and visible light OCT systems and demonstrate the sensitivity of each system to ablation-induced changes in scattering. Currently, NIR OCT has been demonstrated as capable of reporting scattering measurements that are useful in diagnosis [31]. Quantitative imaging of scattering changes will provide a tool for ex vivo studies and, in the future, may lead to real-time guidance during therapy.
2. Methods
2.1. Ablation
Microwave ablations were performed within one hour of harvest on sections of esophagus from three swine. Microwaves were delivered from a 2.45 GHz generator through a coaxial antenna placed against the luminal surface of the esophagus (Certus 140; NeuWave Medical Inc, Madison, WI). Generator power was set to 20 W and applied for either 40 seconds or 20 seconds. Different application times were used to show the sensitivity of the proposed technique to tissues with different amounts of thermal injury. Ablations using the 40 second application time were replicated in three locations on each of the three esophagus samples. Tissue was then imaged with both visible and NIR OCT. After imaging, several samples were stained with triphenyltetrazolium chloride (TTC) to demarcate zones of necrosis from viable tissues. These methods are summarized in Fig. 1.
Fig. 1 The schematic illustration of methods: (a): ex-vivo ablation of swine esophagus, OCT B-scans that are acquired with the NIR (b) and visible light OCT systems(c), TTC staining (d) of the sample and the H&E staining of normal and ablated tissues (e).
2.2. OCT image instrumentation and image processing
Two separate OCT systems – one visible spectrum and one near-infrared (NIR) – were used to image ablated and normal tissues (summarized in Table 1). The visible OCT system uses a SuperK Extreme supercontinuum source (NKT Photonics, Birkerød, Denmark). A reflective collimator was used to expand the beam, a 50:50 beam splitter divided the reference and sample arms (Thorlabs Inc., Newton, NJ). A glass wedge served as the reference arm while the sample arm consisted of a pair of 5 mm galvanometer mirrors, and an LSM03-VIS objective with an effective focal length of 39 mm for scanning (Thorlabs Inc., Newton, NJ). The spectrometer was constructed using a 600 grooves/mm visible transmission grating (later changed to 833 grooves/mm for a larger field of view) and a 100 mm focal length achromatic doublet lens (Thorlabs Inc., Newton, NJ) placed 100 mm from the grating (telecentric) to focus on to an AViiVA EM4 linear camera (e2v Technologies, Essex, England) as shown in Fig. 2. Visible OCT interferograms were acquired with custom MATLAB code which limited A-line acquisition rate to the camera integration time to reduce relative intensity noise [32]. NIR OCT imaging was performed using a Thorlabs Telesto II base (TEL1300V2-BU, Thorlabs Inc., Newton, NJ) coupled to a Thorlabs Adjustable Scanner (OCTP-1300(/M, Thorlabs Inc., Newton, NJ). The LSM03 scan lens kit (OCT-L3, Thorlabs Inc., Newton, NJ) was used to focus light onto the sample. All NIR OCT data was acquired using ThorImage.
Table 1. OCT system comparison
Esophageal tissues were then imaged with OCT within five hours of ablation. Imaging of normal and healthy regions of tissue samples was performed in the same imaging session. During this time, tissues were kept hydrated in normal phosphate buffered saline. Standard OCT image processing, with the addition of subtracting a fit of noise from a glass slide image, was applied to all data captured using the visible and NIR OCT systems. Briefly, after k-space linearization and numerical dispersion compensation, the spectral shape of the source in the interferogram was corrected using the average interferogram [33]. Following a Hann-windowed Fourier transform, a fit of the system noise was obtained from the noise floor in an image of a glass slide and then subtracted in all subsequent images. Subtracting the fitted noise floor removes depth-dependent signal decay that would corrupt calculation of optical properties. Fringe contrast falls off as a function of frequency in the spectrometer and leads to artificial attenuation of the image with depth. Additionally, OCT signal is attenuated as the image depth exceeds the depth of focus. Both of these factors must be corrected so that the depth-dependent attenuation of the OCT signal is only due to scattering. Spectrometer sensitivity fall-off and confocal fall-off have been well-characterized previously and are corrected for the OCT systems employed in this study [18, 19, 34, 35]. These processing steps are summarized and demonstrated in Fig. 3.
Fig. 3 The image processing procedure begins by subtracting the mean B-scan interferogram from each A-line interferogram (Idet), isolating the desired signal, Iac, from the source spectrum. This subtraction eliminates the DC term in the interference equation (Eq. (1). The A-line image is then calculated by taking the Fourier Transform of Iac. The system noise floor, I(z)noise, is determined by fitting an image of glass, I(z)glass. I(z)noise is subtracted from I(z) before applying fall-off corrections to I(z). The spectrometer fall-off correction (blue) is fixed while the confocal roll-off correction (red) is centered at the focal position, which must be known when imaging. The final image intensity is well-corrected until the noise floor of the image is encountered at the limit of imaging depth.
2.3. Boundary detection
A surface detection algorithm was implemented to determine the location of the tissue surface as well as the upper and lower boundaries of the ablation zones. Surface location was determined using a smoothed first derivative of a single A-line that is averaged with 2-8 neighboring A-lines. The location of the maximum of the first derivative was identified as the tissue surface. Local maxima were found to be the surface of the ablation zone or transitions to other tissue layers. Each A-line was then shifted to align the tissue or ablation zone surface. Flattening the tissue allows for lateral averaging that is only limited by the homogeneity of the tissue. The surface profile could also be smoothed to reduce errors from low signal-to-noise levels and tissue texture by accounting for the neighboring surface locations.
2.4. Optical property determination in OCT
It has been demonstrated previously that the intensity of the OCT signal as a function of depth can be used to extract the backscattering coefficient and scattering coefficient [15, 34]. The intensity of the OCT signal is proportional to the local backscattering coefficient and the scattering coefficient is obtained as a Beer-Lambert decay of the signal squared. OCT signal intensity follows the intensity of interference, which can be found in Chapter 7 of Born and Wolf. (Eq. (1) [36].
In the above equation, Idet is the intensity of the interferogram detected on the camera, Er and Es are the complex amplitudes of the reference and sample arms respectively. Subtracting the spectral shape by measuring the individual arms, as described in the signal processing above, eliminates the DC and autocorrelation terms (, ) and isolates the cross-terms of Eq. (1). The cross terms express the interference phase as a function of circular wavenumber (k), and object position (z), Φ(k, z). Equation 2a describes the intensity of the cross term as a product of the amplitudes of the reference and sample arms. These amplitudes are modulated by reference arm reflectivity (Eq. 2b) and the sample backscattering and scattering coefficients (Eq. 2c), where I0 is the initial intensity of the beam. The object in the interferogram is defined as a series of complex exponentials (Eq. 2a) as relayed in Eq. (2).6 of Drexler and Fujimoto [37].
The Fourier transform of Eq. 2a recovers the OCT image (Eq. 3) and is scaled by the terms in Eqs. 2b and 2c. The scattering coefficient is independent of the interference fringe frequency, allowing it to be removed from the Fourier transform, becoming a scaling term. However, the Beer-Lampert law attenuates light intensity, meaning it remains under the square root along with the reference arm reflectivity.
The Fourier Transform yields Eq. (3) where I0 is the initial intensity after the beam splitter, R is the reflectivity of the reference arm, and 2zn the total optical path delay accounting for the double pass and physical distance multiplied by the refractive index of the media. Of interest in this study are the backscattering (μb) and scattering (μs) coefficients, which are functions of depth, z. Squaring Eq. (3) gives an exponential function depending on depth which can be fit for μs.
To fit bulk scattering properties more rigorously, regions of homogenous scattering were segmented in tissue and phantom images. The fit range began 5 pixels below the surface to avoid specular reflection artifacts and was manually terminated either above the noise floor or above the next tissue layer boundary, typically 50 to 100 μm. In this case, the scattering coefficient can be determined by fitting a single value of μs for the segmented region. Taking the natural log of the image reduces Eq. (3) to a linear function with a slope of -2znμs and allows fitting by linear regression to obtain μs. Signal noise in fitting was reduced by averaging 2-5 laterally adjacent Measuring attenuation pixel-to-pixel in depth provides a local determination of μs(z), but suffers from speckle, tissue variation, and other sources of noise. Image blurring by 2-4 pixels reduces this noise but at the cost of resolution. Despite nontrivial noise contributions, an approximate value for μs as a function of depth was extracted by locally solving the Beer-Lambert law at each pixel as described in section 3.2. In all cases, tissue refractive index of 1.38 was assumed. The attenuation measured is μt, the sum of μs and μa, the absorption coefficient. However, we assume μs>>μa such that μt = μs.2.5. Phantom fabrication and validation of scattering coefficient determination
Optical scattering phantoms were fabricated using 0.40 µm polystyrene microspheres (Bangs Labs, Fishers, IN) suspended in water and diluted to provide a range of scattering values. The concentrations of microspheres in the phantoms were adjusted to give scattering properties mimetic of tissue according to a Mie calculator [38]. A phantom with approximately 2.0% (wt/wt) polystyrene in water was used for the highest scattering phantom with μs of approximately 400 cm−1 and was diluted by a factor of two until μs reached 25 cm−1.
2.6. Tissue histology
After imaging, ablated and normal tissues were prepared for histologic analysis. Samples were embedded in cryosectioning gel before being frozen on a metal block with dry ice, then placed on a cryostat and sectioned into 4 μm slices. Slices were stained with hematoxylin and eosin and imaged for a gross estimation of morphology of normal and ablated tissue.
3. Results
3.1. Determining tissue structure with OCT
OCT imaging was able to provide high resolution images of both normal and ablated tissues. The depth limit of OCT imaging is governed by light scattering within the tissues and by Fourier domain sampling rates. NIR OCT was subject to less scattering and was capable of imaging 1.5-2.0 mm into tissue, which was sufficient to reach the submucosa. In contrast, the visible light OCT signal was completely attenuated by 300 μm into tissue, restricting images to the epithelial layer due to the increase in scattering at shorter wavelengths [36]. While the imaging depth is reduced in the visible system, there appears to be more contrast, suggesting a greater sensitivity to scattering.
Comparison with histology confirmed the structures visualized in OCT (Fig. 4). Of particular note, regions in histology that appear as cavitation correspond to regions of hyperscattering in the OCT B-scan, which is consistent with previous findings [29]. Hematoxylin and eosin staining were unable to directly visualize the ablation region due to microwave fixation preserving the cell membrane structure [39]. Images of stained tissues showed degradation of tissue which were not observed as often in OCT, a common problem with histology of ablated tissue. TTC staining provided visual confirmation of a region of completely necrotic tissue at the ablation core while tissue outside of the ablation zone remained viable. TTC staining was not used for quantification due to the need for sectioning to analyze the depth of the ablation.
Fig. 4 (a) Normal esophagus H&E staining, (c) visible and (e) NIR OCT images from different tissue sites. Ablated tissue imaged by (b) H&E staining, (d) visible and (f) NIR OCT. The ablation zone becomes apparent in OCT due to increased backscattering which displays as higher intensity in the image. All scale bars represent 300 μm in each direction. All zoomed insets are approximately 125 μm axially and 800 μm laterally.
3.2. Validation of bulk and depth-resolved scattering coefficients in phantoms
To validate quantification of bulk scattering measurements using OCT, liquid phantoms were imaged with both systems (Fig. 5) and subjected to identical post-processing as described above to determine μs. Both systems demonstrated good agreement between the expected values of μs calculated based on the Mie theory for the sphere size and concentrations used and measured values of μs with the exception of the most scattering phantom (Fig. 5c,d). For the highest scattering phantom, the signal decays to the noise floor in only 75 μm leaving relatively few pixels for fitting. Additionally, the strong scattering increases the autocorrelation artifact, which further reduces both the valid range available to fit and the rate of signal decay resulting in underestimates of μs.
Fig. 5 OCT image of polystyrene/water phantoms (a) with good uniformity across the sample (b). Measured vs. predicted scattering values for NIR (c) and visible (d) OCT systems showed good agreement and linear trends. Predicted scattering values were computed from Mie theory using polystyrene sphere size and concentration in water.
It should also be noted that the NIR system demonstrated a consistent offset between measured and expected scattering coefficients. This offset was approximately 10 cm−1, which could be explained by the absorption coefficient of water (1-10 cm−1) in the wavelength range of the NIR system (1300 ± 85 nm) along with depth-dependent fall-off which may not have been completely corrected. The intrinsic coupling of scattering and absorption coefficients (μt = μs + μs) makes absorption from water a likely source of error.
The decay in the OCT signal as a function of depth can also be used to calculate the local value of μs. Speckle and noise of the signal will introduce variability which can be suppressed through small local averaging (less than 10 pixels in each direction). After correcting phantom intensity images (Fig. 6, top) for depth-dependent attenuation from the system, images were smoothed with a 10x10 boxcar filter. The Beer-Lambert law was then used to solve for μs at each pixel: the discrete derivative along z of the natural log of the B-scan was taken and then divided by -(2nΔz) where Δz is the axial pixel size and accounts for double pass in reflection and n is the refractive index, assumed to be 1.38 for tissue. The attenuation value can be directly converted to μs from Eq. (3) and its values can be used to construct an image of the scattering coefficient (Fig. 6, bottom). While the effects of signal decay are mitigated in the intensity images (Fig. 6, top) using a log-scale display, the decay is present and consistent throughout the phantom value until the noise floor is reached (Fig. 6, bottom). The decrease in scattering coefficient between images of the phantoms demonstrate the ability of OCT to image samples via the scattering coefficient, which is desirable in characterization of tissue for potential use in both diagnostics and image-guided therapy.
Fig. 6 Intensity OCT images of the different scattering phantoms (top). Depth-resolved determination of scattering demonstrates uniform scattering within phantoms throughout the available depth (bottom). Axis of scattering graph in cm−1 and shows good agreement between predicted and measured μs when averaged and adjusted for smoothing.
3.3. En face mapping of average tissue scattering coefficients
Using both visible and NIR OCT, fitting over regions of interest for μs demonstrated significant differences between normal and ablated tissues. Furthermore, there were variations in μs within the ablated zone owing to the inhomogeneous heating pattern of the antenna. Patterns in the scattering can be observed in Fig. 8 which provides a map of maximum intensity or backscattering (Fig. 7, left) and a map of the scattering coefficient (Fig. 7, right) fit over a small tissue volume. The major axis of the antenna was found to have the greatest increase in scattering. The scattering coefficients presented in Table 2 demonstrate the substantial increase in µs as the core of the ablation zone was reached.
Fig. 7 A maximum intensity plot (left) demonstrates the increase in backscattering while a scattering map (right) shows increased attenuation in the leasion which was not found to correlate to surface location. Blue pixels indicate locations where either surface location or fitting failed.
Table 2. Optical properties relative to non-ablated tissue (normal) samples.
To compare scattering coefficient values from regions of normal, ablated, and transition zones, regions of interest were determined by finding the surface of tissue or the ablation zone and extended to between 50 and 100 μm in depth, corresponding to approximately ls in tissue. These restrictions also ensured only the uppermost layer (epithelium) of normal tissue was compared with corresponding layer of ablated tissue. The tissue surface was consistently used for the start of fitting in the normal tissue, however the surface location algorithm was adjusted to detect the surface of the ablation zone for proper segmentation of transition and ablation zones before fitting. Applying these restrictions to fitting a volume of tissue allows visualization of the decrease in backscattering and μs as distance from the antenna placement increases (Fig. 7). The results of Table 2 also demonstrate that both systems were sensitive to changes in μs, the magnitudes of which were well within the range of the phantom calibrations. Mapping these changes in μs in an en face view (Fig. 7, right) allows for both qualitative and quantitative characterization of normal, transition, and ablated tissue.
3.4. Depth-resolved mapping tissue scattering coefficients
Intensity of the OCT signal is proportional to μb(z), meaning that an intensity image serves as a map of μb(z) after correcting for depth-attenuation of the OCT signal due to the system. Changes in the backscattering were observed in intensity images for tissues ablated for both a short time of 20 seconds (Fig. 8(a),(e)) and for longer times of 40 seconds (Fig. 8(c),(g)). To complement these observed changes in backscattering, depth-resolved measurements of attenuation were converted to μs(z). Analogous to the phantom images in Fig. 6, an image of the local scattering coefficient was created by mapping μs(z) as intensity on a single color axis (Fig. 8(b),(d),(f),(h)). In 20 second ablations (Fig. 8(b),(f)) there is a minor increase in scattering that is more noticeable in the visible image (Fig. 8(b)). The increase in scattering is more apparent in the 40 second ablation images (Fig. 8(d),(h)). The increased visibility of the scattering in the visible images is attributed to the absolute increase in scattering values at visible wavelengths.
Fig. 8 OCT intensity images (left) and μs(z) images (right) demonstrates changes in tissue scattering after ablation. In normal OCT B-scan images, pixel intensity is proportional to the backscattering, μb(z), which demonstrates increased backscattering in ablation. Scattering maps of 20 second ablations (b,f) show less contrast between normal and ablated tissue as compared to 40 second ablations (d,h). Visible OCT images (a-d) show grater detail due to increased μs in both normal and ablated tissue, however NIR images had a larger FOV (e-h). Heatmap colorbar scaled between 0 and 800 cm−1.
Bands along the surface of the tissue or surface of the lesion present themselves as negative scattering due to the transition from a low-backscattering region to a high-backscattering region (i.e. intensity increases between pixels). The bands visualize the method by which surface detection was performed. A lower boundary of the ablation zone can be seen in another artifact that appears as high scattering values outside physiological ranges where the tissue transitions from highly backscattering ablation zone to less backscattering normal tissue or noise floor. While useful for qualitative assessment of the size of the ablation zone, these artifacts should be removed from any quantitative assessment of scattering.
The distinct change in μb but small change in μs suggest that at low ablation temperatures, the scattering anisotropy (g) decreases. At longer ablation times, a greater change in μs was observed, indicating higher scattering once higher temperatures are reached. As expected, these measurements of μs suffered from image noise which can be reduced by smoothing or blurring the image, but at the cost of spatial resolution.
4. Discussion
Microwave ablation therapy benefits substantially from image guidance to monitor ablation size and would be improved with additional quantitative metrics at imaging. Here we have determined a significant increase in the scattering coefficient, μs, in tissue that was subjected to microwave ablation using both visible and NIR OCT. Linear fitting of log-scale data produced maps of optical properties across volumetric scans 5000x300x100 μm (Fig. 7). Interestingly, OCT imaging of the ablated region reveals a thin layer (~25 μm) that has lower backscattering intensity and lower apparent scattering coefficient. This layer is not obvious in histology and suggests lower temperatures than the ablation threshold due to the cooling mechanism of the antenna or from fluid retention. Depth-resolved fitting allowed generation of attenuation images that showed changes in optical properties throughout the ablation zone and between tissue layers. Several potential factors exist that may contribute to the observed changes in optical properties, which have been characterized previously [17, 21, 22]. The explanation is likely three-fold: contraction of the tissue, disruption of the extracellular matrix, and cell morphology changes.
Tissue contraction in ablation has been well documented and would easily contribute to the increase in scattering by simply changing the concentration of scatterers per unit volume or the differential scattering cross section per unit volume [21, 26, 40]. Dehydration of the tissue would also contribute to both effects and should be carefully considered in any in vivo or ex vivo experiments.
The extracellular matrix is also vulnerable to changing as a result of thermal ablation. In particular, collagen shrinkage was characterized at temperatures around 60 °C and observed to change from organized fibers to an amorphous structure as a function of temperature [41]. Changes in the ECM composition are known to affect the scattering phase function, which describes the magnitude of scattering as a function of angle relative to the incidence [21]. This would imply that the fraction of scattered light that backscatters would be higher in ablated tissues where the tissue has become less forward-scattering or more isotropic. This could explain the increase in the apparent backscattering seen in the low power ablation images (Fig. 8) without a dramatic increase in μs.
There have been many attempts to characterize thermal damage during ablation on a cellular level. Between 60 °C and 140 °C, protein denaturation, cell shrinkage and hyperchromaticity occur in ablated liver tissue [28]. The most significant ultrastructural change after heat injury was found in mitochondria with intramithocondrial dense granules, vesicularization of cristae, myelin damage, and swelling of intracristal areas [27]. Each of these effects can alter light scattering and OCT signal.
Visible and NIR OCT provide different resolution and imaging depth, and scattering at these wavelengths are also sensitive to different structures, potentially to providing complementary information. This study demonstrates that both modalities can quantify differences between the optical properties of ablated and normal tissues. These differences can be seen with a resolution that has not yet been attained by conventional image-guidance methods. This information could provide axial and lateral information on the shape of the ablation core and transition zone, especially as processing methods and visible OCT system capabilities are improved. OCT imaging revealed a fine layer of lower scattering that is not evident in histology which may not have been completely ablated. The use of optical properties derived via OCT to diagnose and visualize cancerous lesions is also of clinical importance [42, 43]. These data are particularly useful when assessing antenna performance and offer advantages over histology methods. Viability staining was the only histological tool able to confirm cell areas of necrosis from microwave ablation due the microwave fixation effect. Agreement between TTC stained tissue cross-sections and OCT images imply that increase in μb before a change in μs is observed could be a sign of non-viable cells after ablation.
Quantitative analysis of OCT signals may provide a new metric for studying, monitoring, and guiding ablation therapies. Ablation therapies utilize image guidance to minimize damage to healthy tissue. Pervious work has observed hyper-scattering present in ablated tissue [29]. Rigorous determination of scattering in the ablation zone provides a useful criterion for determining the boundaries of the ablated zone. OCT endoscopes can be used to acquire scattering data for real time identification of ablation boundaries.
5. Conclusion
Thermal ablation techniques, including microwave ablation, require precise control over ablation zone in all directions. This is especially important in the GI tract where tissue structure is fine, complicating the goal of sparing healthy adjacent tissues while still ensuring total ablation of malignant tissue. Here, by quantification of scattering properties, the thermal damage extent and ablation boundaries are shown in high resolution. Such feedback will help to evaluate new ablation device designs and may eventually provide guidance during ablation procedures. The only platform which can provide such detail in heat-tissue interactions is numerical simulation where numerous assumptions are made about tissue properties. Histology and visual assessment of tissue often do not provide sufficient feedback to analyze the ablation during surgical intervention. By determining optical properties via OCT, an automated mapping of the ablation zone could be achieved for use in treatment of Barrett’s esophagus.
Funding
National Science Foundation (NSF) (1240416); National Cancer Institute (NCI) of the National Institutes of Health (NIH) (R01CA185747, 5R01CA183101).
Acknowledgements
The authors thank the University of Wisconsin Translational Research Initiatives in Pathology laboratory, in part supported by the UW Department of Pathology and Laboratory Medicine and UWCCC grant P30 CA014520, for use of its facilities and services.
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Disclosures
CLB: Ethicon/NeuWave Medical (C,P), Symple Surgical (C,I,P), Elucent Medical (I,P).
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