Optimized depth-resolved estimation to measure optical attenuation coefficients from optical coherence tomography and its application in cerebral damage determination

Unleashing the power of optical attenuation coefficients to facilitate segmentation strategies in OCT imaging of age-related macular degeneration: perspective

The use of optical attenuation coefficients (OAC) in optical coherence tomography (OCT) imaging of the retina has improved the segmentation of anatomic layers compared with traditional intensity-based algorithms. Optical attenuation correction has improved our ability to measure the choroidal thickness and choroidal vascularity index using dense volume scans. Algorithms that combine conventional intensity-based segmentation with depth-resolved OAC OCT imaging have been used to detect elevations of the retinal pigment epithelium (RPE) due to drusen and basal laminar deposits, the location of hyperpigmentation within the retina and along the RPE, the identification of macular atrophy, the thickness of the outer retinal (photoreceptor) layer, and the presence of calcified drusen. OAC OCT algorithms can identify the risk-factors that predict disease progression in age-related macular degeneration.

Depth-dependent attenuation and backscattering characterization of optical coherence tomography by stationary iterative method

Significance

Extracting optical properties of tissue [e.g., the attenuation coefficient (μ ) and the backscattering fraction] from the optical coherence tomography (OCT) images is a valuable tool for parametric imaging and related diagnostic applications. Previous attenuation estimation models depend on the assumption of the uniformity of the backscattering fraction (R ) within layers or whole samples, which does not accurately represent real-world conditions.

Aim

Our aim is to develop a robust and accurate model that calculates depth-wise values of attenuation and backscattering fractions simultaneously from OCT signals. Furthermore, we aim to develop an attenuation compensation model for OCT images that utilizes the optical properties we obtained to improve the visual representation of tissues.

Approach

Using the stationary iteration method under suitable constraint conditions, we derived the approximated solutions of μ and R on a single scattering model. During the iteration, the estimated value of μ can be rectified by introducing the large variations of R , whereas the small ones were automatically ignored. Based on the calculation of the structure information, the OCT intensity with attenuation compensation was deduced and compared with the original OCT profiles.

Results

The preliminary validation was performed in the OCT A-line simulation and Monte Carlo modeling, and the subsequent experiment was conducted on multi-layer silicone-dye-TiO 2 phantoms and ex vivo cow eyes. Our method achieved robust and precise estimation of μ and R for both simulated and experimental data. Moreover, corresponding OCT images with attenuation compensation provided an improved resolution over the entire imaging range.

Conclusions

Our proposed method was able to correct the estimation bias induced by the variations of R and provided accurate depth-resolved measurements of both μ and R simultaneously. The method does not require prior knowledge of the morphological information of tissue and represents more real-life tissues. Thus, it has the potential to help OCT imaging based disease diagnosis of complex and multi-layer biological tissue.

QOCT-Net: A Physics-Informed Neural Network for Intravascular Optical Coherence Tomography Attenuation Imaging

Intravascular optical coherence tomography (IVOCT) provides high-resolution, depth-resolved images of coronary arterial microstructure by acquiring backscattered light. Quantitative attenuation imaging is important for accurate characterization of tissue components and identification of vulnerable plaques. In this work, we proposed a deep learning method for IVOCT attenuation imaging based on the multiple scattering model of light transport. A physics-informed deep network named Quantitative OCT Network (QOCT-Net) was designed to recover pixel-level optical attenuation coefficients directly from standard IVOCT B-scan images. The network was trained and tested on simulation and in vivo datasets. Results showed superior attenuation coefficient estimates both visually and based on quantitative image metrics. The structural similarity, energy error depth and peak signal-to-noise ratio are improved by at least 7%, 5% and 12.4%, respectively, compared with the state-of-the-art non-learning methods. This method potentially enables high-precision quantitative imaging for tissue characterization and vulnerable plaque identification.

Accuracy and precision of depth-resolved estimation of attenuation coefficients in optical coherence tomography

Significance

Parametric imaging of the attenuation coefficient μ OCT using optical coherence tomography (OCT) is a promising approach for evaluating abnormalities in tissue. To date, a standardized measure of accuracy and precision of μ OCT by the depth-resolved estimation (DRE) method, as an alternative to least squares fitting, is missing.

Aim

We present a robust theoretical framework to determine accuracy and precision of the DRE of μ OCT .

Approach

We derive and validate analytical expressions for the accuracy and precision of μ OCT determination by the DRE using simulated OCT signals in absence and presence of noise. We compare the theoretically achievable precisions of the DRE method and the least-squares fitting approach.

Results

Our analytical expressions agree with the numerical simulations for high signal-to-noise ratios and qualitatively describe the dependence on noise otherwise. A commonly used simplification of the DRE method results in a systematic overestimation of the attenuation coefficient in the order of μ OCT 2 × Δ , where Δ is the pixel stepsize. When μ OCT · | AFR | ≲ 1.8 , μ OCT is reconstructed with higher precision by the depth-resolved method compared to fitting over the length of an axial fitting range | AFR | .

Conclusions

We derived and validated expressions for the accuracy and precision of DRE of μ OCT . A commonly used simplification of this method is not recommended as being used for OCT-attenuation reconstruction. We give a rule of thumb providing guidance in the choice of estimation method.

Optical coherence tomography confirms non-malignant pigmented lesions in phacomatosis pigmentokeratotica using a support vector machine learning algorithm

INTRODUCTION

Phacomatosis pigmentokeratotica (PPK), an epidermal nevus syndrome, is characterized by the coexistence of nevus spilus and nevus sebaceus. Within the nevus spilus, an extensive range of atypical nevi of different morphologies may manifest. Pigmented lesions may fulfill the ABCDE criteria for melanoma, which may prompt a physician to perform a full-thickness biopsy.

MOTIVATION

Excisions result in pain, mental distress, and physical disfigurement. For patients with a significant number of nevi with morphologic atypia, it may not be physically feasible to biopsy a large number of lesions. Optical coherence tomography (OCT) is a non-invasive imaging modality that may be used to visualize non-melanoma and melanoma skin cancers.

MATERIALS AND METHOD

In this study, we used OCT to image pigmented lesions with morphologic atypia in a patient with PPK and assessed their quantitative optical properties compared to OCT cases of melanoma. We implement a support vector machine learning algorithm with Gabor wavelet transformation algorithm during post-image processing to extract optical properties and calculate attenuation coefficients.

RESULTS

The algorithm was trained and tested to extract and classify textural data.

CONCLUSION

We conclude that implementing this post-imaging machine learning algorithm to OCT images of pigmented lesions in PPK has been able to successfully confirm benign optical properties. Additionally, we identified remarkable differences in attenuation coefficient values and tissue optical characteristics, further defining separating benign features of pigmented lesions in PPK from malignant features.

In vivo characterization of cerebrovascular impairment induced by amyloid β peptide overload in glymphatic clearance system using swept-source optical coherence tomography

SIGNIFICANCE

Antiamyloid β ( A β ) immunotherapy is a promising therapeutic strategy for Alzheimer's disease (AD) but generates large amounts of soluble A β peptides that could overwhelm the clearance pathway, leading to serious side effects. Direct implications of A β in glymphatic drainage transport for cerebral vasculature and tissue are not well known. Studies are needed to resolve this issue and pave the way to better monitoring abnormal vascular events that may occur in A β -modifying therapies for AD.

AIM

The objective is to characterize the modification of cerebral vasculature and tissue induced by soluble A β abundantly present in the glymphatic clearance system.

APPROACH

A β 1 - 42 peptide was injected intracerebroventricularly and swept-source optical coherence tomography (SS-OCT) was used to monitor the progression of changes in the brain microvascular network and tissue in vivo over 14 days. Parameters reflecting vascular morphology and structure as well as tissue status were quantified and compared before treatment.

RESULTS

Vascular perfusion density, vessel length, and branch density decreased sharply and persistently following peptide administration. In comparison, vascular average diameter and vascular tortuosity were moderately increased at the late stage of monitoring. Endpoint density gradually increased, and the global optical attenuation coefficient value decreased significantly over time.

CONCLUSIONS

A β burden in the glymphatic system directly contributes to cerebrovascular structural and morphological abnormalities and global brain tissue damage, suggesting severe deleterious properties of soluble cerebrospinal fluid- A β . We also show that OCT can be used as an effective tool to monitor cerebrovascular dynamics and tissue property changes in response to therapeutic treatments in drug discovery research.

Using beam-offset optical coherence tomography to reconstruct backscattered photon profiles in scattering media

Raster scanning imaging technologies capture least scattered photons (LSPs) and reject multiple scattered photons (MSPs) in backscattered photons to image the underlying structures of a scattering medium. However, MSPs can still squeeze into the images, resulting in limited imaging depth, degraded contrast, and significantly reduced lateral resolution. Great efforts have been made to understand how MSPs affect imaging performance through modeling, but the techniques for visualizing the backscattered photon profile (BSPP) in scattering media during imaging are unavailable. Here, a method of reconstructing BSPP is demonstrated using beam-offset optical coherence tomography (OCT), in which OCT images are acquired at offset positions from the illumination beam. The separation of LSPs and MSPs based on the BSPP enables quantification of imaging depth, contrast, and lateral resolution, as well as access to the depth-resolved modulated transfer function (MTF). This approach presents great opportunities for better retrieving tissue optical properties, correctly interpreting images, or directly using MTF as the feedback for adaptive optical imaging.

Differentiation of otitis media-causing bacteria and biofilms via Raman spectroscopy and optical coherence tomography

In the management of otitis media (OM), identification of causative bacterial pathogens and knowledge of their biofilm formation can provide more targeted treatment approaches. Current clinical diagnostic methods rely on the visualization of the tympanic membrane and lack real-time assessment of the causative pathogen(s) and the nature of any biofilm that may reside behind the membrane and within the middle ear cavity. In recent years, optical coherence tomography (OCT) has been demonstrated as an improved in vivo diagnostic tool for visualization and morphological characterization of OM biofilms and middle ear effusions; but lacks specificity about the causative bacterial species. This study proposes the combination of OCT and Raman spectroscopy (RS) to examine differences in the refractive index, optical attenuation, and biochemical composition of Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, and Pseudomonas aeruginosa; four of the leading otopathogens in OM. This combination provides a dual optical approach for identifying and differentiating OM-causing bacterial species under three different in vitro growth environments (i.e., agar-grown colonies, planktonic cells from liquid cultures, and biofilms). This study showed that RS was able to identify key biochemical variations to differentiate all four OM-causing bacteria. Additionally, biochemical spectral changes (RS) and differences in the mean attenuation coefficient (OCT) were able to distinguish the growth environment for each bacterial species.

Depth-resolved extraction of optical attenuation for glaucoma assessment in clinical settings: a pilot study

We assessed the ability of the optical attenuation coefficient (AC) to detect early-stage glaucoma with two AC estimation algorithms: retinal layer intensity ratio (LIR) and depth-resolved confocal (DRC). We also introduced new depth-dependent AC parameters for retinal nerve fiber layer assessment. Optical coherence tomography B-scans were collected from 44 eyes of age-similar participants with eye health ranging from healthy to severe glaucoma, including glaucoma suspect patients. Mean AC values estimated from the DRC method are comparable to ratio-extracted values (p > 0.5 for all study groups), and the depth-dependent AC_DRC parameters enhance the utility of the AC for detection of early-stage glaucoma.

Optical Coherence Tomography Measurements of the Retinal Pigment Epithelium to Bruch Membrane Thickness Around Geographic Atrophy Correlate With Growth

PURPOSE

The retinal pigment epithelium (RPE) to Bruch membrane (BM) distance around geographic atrophy (GA) was measured using an optical attenuation coefficient (OAC) algorithm to determine whether this measurement could serve as a clinical biomarker to predict the annual square root enlargement rate (ER) of GA.

DESIGN

A retrospective analysis of a prospective, observational case series.

METHODS

Eyes with GA secondary to age-related macular degeneration (AMD) were imaged with swept-source OCT (SS-OCT) using a 6 × 6-mm scan pattern. GA lesions were identified and measured using customized en face OCT images, and GA annual square root ERs were calculated. At baseline, the OACs were calculated from OCT datasets to generate customized en face OAC images for GA visualization. RPE-BM distances were measured using OAC data from different subregions around the GA.

RESULTS

A total of 38 eyes from 27 patients were included in this study. Measured RPE-BM distances were the highest in the region closest to GA. The RPE-BM distances immediately around the GA were significantly correlated with GA annual square root ERs (r = 0.595, P < .001 for a 0- to 300-µm rim around the GA). No correlations were found between RPE-BM distances and previously published choriocapillaris (CC) flow deficits in any subregions.

CONCLUSIONS

RPE-BM distances from regions around the GA significantly correlate with the annual ERs of GA. These results suggest that an abnormally thickened RPE/BM complex contributes to GA growth and that this effect is independent of CC perfusion deficits.

Automatic geographic atrophy segmentation using optical attenuation in OCT scans with deep learning

A deep learning algorithm was developed to automatically identify, segment, and quantify geographic atrophy (GA) based on optical attenuation coefficients (OACs) calculated from optical coherence tomography (OCT) datasets. Normal eyes and eyes with GA secondary to age-related macular degeneration were imaged with swept-source OCT using 6 × 6 mm scanning patterns. OACs calculated from OCT scans were used to generate customized composite en face OAC images. GA lesions were identified and measured using customized en face sub-retinal pigment epithelium (subRPE) OCT images. Two deep learning models with the same U-Net architecture were trained using OAC images and subRPE OCT images. Model performance was evaluated using DICE similarity coefficients (DSCs). The GA areas were calculated and compared with manual segmentations using Pearson's correlation and Bland-Altman plots. In total, 80 GA eyes and 60 normal eyes were included in this study, out of which, 16 GA eyes and 12 normal eyes were used to test the models. Both models identified GA with 100% sensitivity and specificity on the subject level. With the GA eyes, the model trained with OAC images achieved significantly higher DSCs, stronger correlation to manual results and smaller mean bias than the model trained with subRPE OCT images (0.940 ± 0.032 vs 0.889 ± 0.056, p = 0.03, paired t-test, r = 0.995 vs r = 0.959, mean bias = 0.011 mm vs mean bias = 0.117 mm). In summary, the proposed deep learning model using composite OAC images effectively and accurately identified, segmented, and quantified GA using OCT scans.

Evaluation of Mannitol Intervention Effects on Ischemic Cerebral Edema in Mice Using Swept Source Optical Coherence Tomography

Cerebral edema is a serious complication of ischemic cerebrovascular disease and mannitol is a commonly used dehydrating agent for relieving cerebral edema. However, the edema state and surrounding vascular perfusion level during mannitol treatment remains unclear, which affects the clinical application of the medicine. In this paper, we demonstrated the role of swept-source optical coherence tomography (OCT) in the evaluation of mannitol efficacy using mouse models. The OCT-based angiography and attenuation imaging technology were used to obtain the cerebral vascular perfusion level and cerebral edema state at different times. Vascular parameters and edema parameters were quantified and compared. Experimental results show that mannitol can significantly reduce the water content in the central region of edema, effectively inhibiting the rapid growth of the edema area, and restoring cerebral blood flow. On average, the edema area decreased by 33% after 2 h, and the vascular perfusion density increased by 12% after 5 h. This work helps to provide a valuable theoretical basis and research ideas for the clinical treatment of cerebral edema.

Label-free functional and structural imaging of liver microvascular complex in mice by Jones matrix optical coherence tomography

We demonstrate label-free imaging of the functional and structural properties of microvascular complex in mice liver. The imaging was performed by a custom-built Jones-matrix based polarization sensitive optical coherence tomography (JM-OCT), which is capable of measuring tissue's attenuation coefficient, birefringence, and tiny tissue dynamics. Two longitudinal studies comprising a healthy liver and an early fibrotic liver model were performed. In the healthy liver, we observed distinctive high dynamics beneath the vessel at the initial time point (0 h) and reappearance of high dynamics at 32-h time point. In the early fibrotic liver model, we observed high dynamics signal that reveals a clear network vascular structure by volume rendering. Longitudinal time-course imaging showed that these high dynamics signals faded and decreased over time.

Application of OCT-Derived Attenuation Coefficient in Acute Burn-Damaged Skin

BACKGROUND AND OBJECTIVES

There remains a need to objectively monitor burn wound healing within a clinical setting, and optical coherence tomography (OCT) is proving itself one of the ideal modalities for just such a use. The aim of this study is to utilize the noninvasive and multipurpose capabilities of OCT, along with its cellular-level resolution, to demonstrate the application of optical attenuation coefficient (OAC), as derived from OCT data, to facilitate the automatic digital segmentation of the epidermis from scan images and to work as an objective indicator for burn wound healing assessment.

STUDY DESIGN/MATERIALS AND METHODS

A simple, yet efficient, method was used to estimate OAC from OCT images taken over multiple time points following acute burn injury. This method enhanced dermal-epidermal junction (DEJ) contrast, which facilitated the automatic segmentation of the epidermis for subsequent thickness measurements. In addition, we also measured and compared the average OAC of the dermis within said burns for correlative purposes.

RESULTS

Compared with unaltered OCT maps, enhanced DEJ contrast was shown in OAC maps, both from single A-lines and completed B-frames. En face epidermal thickness and dermal OAC maps both demonstrated significant changes between imaging sessions following burn injury, such as a loss of epidermal texture and decreased OAC. Quantitative analysis also showed that OAC of acute burned skin decreased below that of healthy skin following injury.

CONCLUSIONS

Our study has demonstrated that the OAC estimated from OCT data can be used to enhance imaging contrast to facilitate the automatic segmentation of the epidermal layer, as well as help elucidate our understanding of the pathological changes that occur in human skin when exposed to acute burn injury, which could serve as an objective indicator of skin injury and healing.

Method for parametric imaging of attenuation by intravascular optical coherence tomography

Catheter-based intravascular optical coherence tomography (IVOCT) is a powerful imaging modality for visualization of atherosclerosis with high resolution. Quantitative characterization of various tissue types by attenuation coefficient (AC) extraction has been proven to be a potentially significant application of OCT attenuation imaging. However, existing methods for AC extraction from OCT suffer from the challenge of variability in complex tissue types in IVOCT pullback data such as healthy vessel wall, mixed atherosclerotic plaques, plaques with a single component and stent struts, etc. This challenge leads to the ineffectiveness in the tissue differentiation by AC representation based on single scattering model of OCT signal. In this paper, we propose a novel method based on multiple scattering model for parametric imaging of optical attenuation by AC retrieval from IVOCT images conventionally acquired during cardiac catheterization. The OCT signal characterized by the AC is physically modeled by Monte Carlo simulation. Then, the pixel-wise AC retrieval is achieved by iteratively minimizing an error function regarding the modeled and measured backscattered signal. This method provides a general scheme for AC extraction from IVOCT without the premise of complete attenuation of the incident light through the imaging depths. Results of computer-simulated and clinical images demonstrate that the method can avoid overestimation at the end of the depth profile in comparison with the approaches based on the depth-resolved (DR) model. The energy error depth and structural similarity are improved by about 30% and 10% respectively compared with DR. It provides a useful way to differentiate and characterize arterial tissue types in IVOCT images.

Characterizing thrombus with multiple red blood cell compositions by optical coherence tomography attenuation coefficient

Embolectomy is one of the emergency procedures performed to remove emboli. Assessing the composition of human blood clots is an important diagnostic factor and could provide guidance for an appropriate treatment strategy for interventional physicians. Immunostaining has been used to identity compositions of clots as a gold-standard procedure, but it is time-consuming and cannot be performed in situ. Here, we proposed that the optical attenuation coefficient of optical coherence tomography (OCT) can be a reliable indicator as a new imaging modality to differentiate clot compositions. Fifteen human blood clots with multiple red blood cell (RBC) compositions from 21% to 95% were prepared using healthy human whole blood. A homogeneous gelatin phantom experiment and numerical simulation based on the Lambert-Beer's law were examined to verify the validity of the attenuation coefficient estimation. The results displayed that optical attenuation coefficients were strongly correlated with RBC compositions. We reported that attenuation coefficients could be a promising biomarker to guide the choice of an appropriate interventional device in a clinical setting and assist in characterizing blood clots.

Optimized OCT-based depth-resolved model for attenuation compensation using point-spread-function calibration

Optical coherence tomography (OCT) with a robust depth-resolved attenuation compensation method for a wide range of imaging applications is proposed and demonstrated. The proposed novel OCT attenuation compensation algorithm introduces an optimized axial point spread function (PSF) to modify existing depth-resolved methods and mitigates under and overestimation in biological tissues, providing a uniform resolution over the entire imaging range. The preliminary study is implemented using A-mode numerical simulation, where this method achieved stable and robust compensation results over the entire depth of samples. The experiment results using phantoms and corneal imaging exhibit agreement with the simulation result evaluated using signal-to-noise (SNR) and contrast-to-noise (CNR) metrics.

Bayesian analysis of depth resolved OCT attenuation coefficients

Optical coherence tomography (OCT) is an optical technique which allows for volumetric visualization of the internal structures of translucent materials. Additional information can be gained by measuring the rate of signal attenuation in depth. Techniques have been developed to estimate the rate of attenuation on a voxel by voxel basis. This depth resolved attenuation analysis gives insight into tissue structure and organization in a spatially resolved way. However, the presence of speckle in the OCT measurement causes the attenuation coefficient image to contain unrealistic fluctuations and makes the reliability of these images at the voxel level poor. While the distribution of speckle in OCT images has appeared in literature, the resulting voxelwise corruption of the attenuation analysis has not. In this work, the estimated depth resolved attenuation coefficient from OCT data with speckle is shown to be approximately exponentially distributed. After this, a prior distribution for the depth resolved attenuation coefficient is derived for a simple system using statistical mechanics. Finally, given a set of depth resolved estimates which were made from OCT data in the presence of speckle, a posterior probability distribution for the true voxelwise attenuation coefficient is derived and a Bayesian voxelwise estimator for the coefficient is given. These results are demonstrated in simulation and validated experimentally.

Parametric imaging of attenuation by optical coherence tomography: review of models, methods, and clinical translation

SIGNIFICANCE

Optical coherence tomography (OCT) provides cross-sectional and volumetric images of backscattering from biological tissue that reveal the tissue morphology. The strength of the scattering, characterized by an attenuation coefficient, represents an alternative and complementary tissue optical property, which can be characterized by parametric imaging of the OCT attenuation coefficient. Over the last 15 years, a multitude of studies have been reported seeking to advance methods to determine the OCT attenuation coefficient and developing them toward clinical applications.

AIM

Our review provides an overview of the main models and methods, their assumptions and applicability, together with a survey of preclinical and clinical demonstrations and their translation potential.

RESULTS

The use of the attenuation coefficient, particularly when presented in the form of parametric en face images, is shown to be applicable in various medical fields. Most studies show the promise of the OCT attenuation coefficient in differentiating between tissues of clinical interest but vary widely in approach.

CONCLUSIONS

As a future step, a consensus on the model and method used for the determination of the attenuation coefficient is an important precursor to large-scale studies. With our review, we hope to provide a basis for discussion toward establishing this consensus.

Quantitative research on the interaction between cerebral edema and peripheral cerebral blood perfusion using swept-source optical coherence tomography

Background

Ischemic cerebral edema (CE) is a major leading cause of death in patients with ischemic stroke. The CE progression is closely related to the local cerebral blood perfusion (LCBP) level surrounding the edema area. Quantitative studying the interaction between the CE and peripheral LCBP may provide new inspiration for control and even treatment of CE.

Methods

Photothrombosis ischemia mouse model was established and observed for 9 hours using swept-source optical coherence tomography (SS-OCT). OCT-based angiography and OCT-based attenuation imaging techniques were used to reconstruct the angiograms reflecting the cerebral blood perfusion (CBP) level and optical attenuation coefficient (OAC) maps reflecting the edema state. The influence of edema on LCBP was analyzed by quantifying the blood perfusion in different spatial locations around the edema tissue, and the influence of LCBP on CE progression was revealed by comparing the changes of the edema area and LCBP level over time.

Results

Preliminary studies show that the effect of edema tissue on LCBP is very significant, which shows a clear spatial dependence. LCBP near the edema tissue is 15-20% lower than that far away from the edema tissue. When the LCBP drops to around 60% of the initial value, the edema area increases sharply. In addition, the level of CBP in the contralateral hemisphere also decreases with time. When the contralateral CBP drops to around 60%, there is a certain probability that contralateral edema will occur.

Conclusions

CE progression is not only related to the LCBP around the edema tissue but also related to the CBP of non-edematous regions. Controlling the CBP level of non-edematous regions may play a positive role in the treatment of CE. This work provides a new method and inspiration for exploring the mechanism of ischemic CE progression.

Robust, accurate depth-resolved attenuation characterization in optical coherence tomography

Depth-resolved optical attenuation coefficient is a valuable tissue parameter that complements the intensity-based structural information in optical coherent tomography (OCT) imaging. Herein we systematically analyzed the under- and over-estimation bias of existing depth-resolved methods when applied to real biological tissues, and then proposed a new algorithm that remedies these issues and accommodates general OCT data that contain incomplete decay and noise floor, thereby affording consistent estimation accuracy for practical biological samples of different scattering properties. Compared with other algorithms, our method demonstrates remarkably improved estimation accuracy and numerical robustness, as validated via numerical simulations and on experimental OCT data obtained from both silicone-TiO₂ phantoms and human ventral tongue leukoplakia samples.

Correlation of optical attenuation coefficient estimated using optical coherence tomography with changes in astrocytes and neurons in a chronic photothrombosis stroke model

The optical attenuation coefficient (OAC) estimated using optical coherence tomography (OAC-OCT) offers a label-free 3D mapping of tissue infarction, but the physiological origin of the OAC contrast remains unclear. For effectively suppressing OAC fluctuations, we propose a hybrid (wavelength/angle) division multiplexing (HDM) method, which improved the OAC contrast by 70.7% in tissue phantoms. To test the feasibility of OAC-based infarction detection, triphenyltetrazolium chloride (TTC) staining was performed on fresh ex vivo brain slices, and the TTC-defined infarction was used as the ground truth. Sharp OAC contrast was observed between the TTC-defined infarction (1.09 mm-1) and normal tissue (0.79 mm-1). The OAC infarction spatially matched well with the TTC-defined infarction. To further explore the physiological origin of OAC contrast in ischemic stroke at the cellular level, the dynamic changes in OAC were measured in the rat cortex in vivo over 3 weeks after photothrombosis (PT) occlusion and found significantly correlated with the changes in astrocytes and neurons acquired with ex vivo hematoxylin and eosin (HE), glial fibrillary acidic protein (GFAP), and NeuN staining. These results suggest that OAC imaging enables non-invasive infarction detection and its contrast might originate from the changes in astrocytes and neurons in the chronic PT stroke model. The cellular responses revealed by in vivo OAC imaging would be essential for evaluating treatments and even developing novel therapies.

Cerebral edema detection in vivo after middle cerebral artery occlusion using swept-source optical coherence tomography

Cerebral edema is a severe complication of ischemic cerebrovascular disease, which can lead to microcirculation compression resulting in additional ischemic damage. Real-time and continuous in vivo imaging techniques for edema detection are of great significance to basic research on cerebral edema. We attempted to monitor the cerebral edema status in rats with middle cerebral artery occlusion (MCAO) over time, using a wide field-of-view swept-source optical coherence tomography (SS-OCT) system. Optical attenuation coefficients (OACs) were calculated by an optimized depth-resolved estimation method, and en face OAC maps covering the whole cortex were obtained. Then, the tissue affected by edema was segmented from the OAC maps, and the cortical area affected by edema was estimated. Both magnetic resonance image (MRI) and brain water content measurements were used to verify the presence of cerebral edema. The results showed that the average OAC of the ischemic area gradually decreased as cerebral edema progressed, and the edema area detected by SS-OCT had high similarity in position and shape to that obtained by MRI. This work extends the application of OCT and provides an option for detecting cerebral edema in vivo after ischemic stroke.

Review of methods and applications of attenuation coefficient measurements with optical coherence tomography

The optical attenuation coefficient (AC), an important tissue parameter that measures how quickly incident light is attenuated when passing through a medium, has been shown to enable quantitative analysis of tissue properties from optical coherence tomography (OCT) signals. Successful extraction of this parameter would facilitate tissue differentiation and enhance the diagnostic value of OCT. In this review, we discuss the physical and mathematical basis of AC extraction from OCT data, including current approaches used in modeling light scattering in tissue and in AC estimation. We also report on demonstrated clinical applications of the AC, such as for atherosclerotic tissue characterization, malignant lesion detection, and brain injury visualization. With current studies showing AC analysis as a promising technique, further efforts in the development of methods to accurately extract the AC and to explore its potential use for more extensive clinical applications are desired.