Identification of oral cancer in OCT images based on an optical attenuation model

Yang, Zihan; Shang, Jun; Liu, Chenlu; Zhang, Jun; Liang, Yanmei

doi:10.1007/s10103-020-03025-y

Cited by 25 publications

(19 citation statements)

References 41 publications

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“…The layout of the portable SS‐OCT system and its specifications used in the hospital for intraoperative scanning has been reported in our previous articles [21,37,38]. The swept‐source with the output spectral tuning range of 87 nm, centered at 1310 nm, is used, which can provide an output power of 20 mW and a sweep rate of 100 kHz.…”

Section: Methodsmentioning

confidence: 99%

“…The model of OAC was established by matching confocal properties of the SS‐OCT system. A signal profile in depth can be described in the following equation [37,39].

I_{a} (z) = A_{1} \cdot \frac{exp (- 2 μ_{t} z)}{{(\frac{z - z_{c f}}{z_{R}})}^{2} + 1} + A_{2}

where I a ( z ) is the averaged signal profile of A‐scans in ROI, z cf is the position of the focal plane, μ t is the attenuation coefficient, and z R is the Rayleigh length.…”

Section: Methodsmentioning

confidence: 99%

“…The statistical distribution of signal intensity gradient at each transverse point was determined for quantitative analysis of dysplasia from normal control samples in histopathology and OCT images [36]. Yang et al achieved high sensitivity (97.88%) and specificity (83.77%) for the identification of oral squamous cell carcinoma based on an optical attenuation threshold [37].…”

Section: Introductionmentioning

confidence: 99%

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Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography

et al. 2021

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Background and Objectives Visual inspection is the primary diagnostic method for oral diseases, and its accuracy of diagnosis mainly depends on surgeons’ experience. Histological examination is still the golden standard, but it is invasive and time‐consuming. In order to address these issues, as a noninvasive imaging technique, optical coherence tomography (OCT) can differentiate oral tissue with advantages of real‐time, in situ, and high resolution. The aim of this study is to explore optimal quantitative parameters in OCT images to distinguish different salivary gland tumors. Study Design/Materials and Methods OCT images of four salivary gland tumors were obtained from 14 patients, including mucoepidermoid carcinoma (MC), adenoid cystic carcinoma (ACC), basal cell adenoma (BCA), and pleomorphic adenoma (PA). Two parameters of optical attenuation coefficient (OAC) and standard deviation (SD) along the depth of OCT signal were combined to create a computational model of classification, and sensitivity/specificity of classification was calculated statistically to evaluate their results. Results A total of 5,919 two‐dimensional (2D) OCT images were used for quantitative analysis. The classification sensitivities of 89.6%, 95.0%, 89.5%, 97.8%, and specificities of 97.6%, 99.0%, 98.0%, 98.2%, respectively, were obtained for MC, ACC, BCA, and PA, with the thresholds of 3.6 mm−1 based on OAC and 0.22/0.18 based on SD. Conclusion It was demonstrated that OAC and SD could be considered as important parameters in quantitative analysis of OCT images for salivary gland tissue characterization and intraoperative diagnosis. It is of great potential value in promoting the application of this method based on OCT in clinical practice. Lasers Surg. © 2020 Wiley Periodicals LLC

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Section: Methodsmentioning

confidence: 99%

“…The model of OAC was established by matching confocal properties of the SS‐OCT system. A signal profile in depth can be described in the following equation [37,39].

I_{a} (z) = A_{1} \cdot \frac{exp (- 2 μ_{t} z)}{{(\frac{z - z_{c f}}{z_{R}})}^{2} + 1} + A_{2}

where I a ( z ) is the averaged signal profile of A‐scans in ROI, z cf is the position of the focal plane, μ t is the attenuation coefficient, and z R is the Rayleigh length.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography

et al. 2021

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“…According to Beer's law, a OCT signal in depth can be described in the following formula. 26,44,45 ( )…”

Section: Quantitative Analysis Based On Optical Attenuation Modelmentioning

confidence: 99%

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography

et al. 2021

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Background and Objectives: Distinguishing cancer from precancerous lesions is critical and challenging in oral medicine. As a noninvasive method, optical coherence tomography (OCT) has the advantages of real-time, in vivo, and large-depth imaging. Texture information hidden in OCT images can provide an important auxiliary effect for improving diagnostic accuracy. The aim of this study is to explore a reliable and accurate OCT-based method for the screening and diagnosis of human oral diseases, especially oral cancer. Materials and Methods: Fresh ex vivo oral tissues including normal mucosa, leukoplakia with epithelial hyperplasia (LEH), and oral squamous cell carcinoma (OSCC) were imaged intraoperatively by a homemade OCT system, and 58 texture features were extracted to create computational models of these tissues. A principal component analysis algorithm was employed to optimize the combination of texture feature vectors. The identification based on artificial neural network (ANN) was proposed and the sensitivity/specificity was calculated statistically to evaluate the classification performance. Results: A total of 71 sites of three types of oral tissues were measured, and 5176 OCT images of three types of oral tissues were used in this study. The superior classification result based on ANN was obtained with an average accuracy of 98.17%. The sensitivity and specificity of normal mucosa, LEH, and OSCC are 98.17% / 98.38%, 93.81% / 98.54%, and 98.11% / 99.04%, respectively. Conclusion: It is demonstrated from the high accuracies, sensitivities, and specificities that texture-based analysis can be used to identify oral precancerous and cancerous tissue in OCT images, and it has the potential to help surgeons in diseases screening and diagnosis effectively.

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“…Furthermore, tissue optical properties can be altered with the presence of disease. For example, Yang et al have shown that tissue samples with oral squamous cell carcinoma, a type of cancerous lesion, has a lower extinction coe cient compared to that of normal tissue (Yang et al, 2020) . The increased cell density in cancerous tissue meanwhile increases the overall refractive index of the lesion (Khan et al, 2021) .…”

Section: Working Principles Of Td-octmentioning

confidence: 99%

Time-Domain Optical Coherence Tomography System for Determining The Extinction Coefficient and Group Refractive Index of Gelatin-based Skin Phantoms

Galvez

Vallar

Shiina

et al. 2021

Sci. Technol. Indones

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Optical Coherence Tomography (OCT) is a non-invasive, non-destructive optical imaging technique that uses a low coherence interferometer to obtain real-time cross-sectional images of samples. OCT is notably used in biomedical applications including ophthalmology and dermatology. Aside from generating cross-sectional images, axial scans can also provide additional information about its optical properties such as extinction coefficient and refractive index. This study determines the extinction coefficients and group refractive indices of gelatin-based skin phantoms using a portable time-domain (TD) – OCT system. The gelatin-based skin phantoms were fabricated with varying concentrations of titanium dioxide (TiO2), while keeping the amount of both gelatin and water constant. By changing the proportion of the gelatin powder and TiO2, skin phantoms can then be fabricated to mimic various skin conditions, both pathologic and non-pathologic. Results of the study found a positive correlation of extinction coefficient and refractive index with TiO2 concentration. Thus, increasing TiO2 concentration also increases both extinction coefficient and group refractive index. The median extinction coefficient values of the phantoms ranged from 4.29 mm−1 to 8.48 mm−1. Literature showed that the epidermis can have extinction coefficients of 1.64-7.3 mm−1. For refractive indices of the fabricated phantoms, values ranged from 1.32 to 1.48, while studies on human participants showed that human skin has refractive index values of 1.34-1.56. Based on these properties, it is feasible to fabricate phantoms simulating the optical properties of human skin.

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Identification of oral cancer in OCT images based on an optical attenuation model

Cited by 25 publications

References 41 publications

Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography

Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography

Time-Domain Optical Coherence Tomography System for Determining The Extinction Coefficient and Group Refractive Index of Gelatin-based Skin Phantoms

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