Detection of Oral Dysplastic and Early Cancerous Lesions by Polarization-Sensitive Optical Coherence Tomography.
Ping-Hsien ChenHung-Yi LeeYi-Fen ChenYi-Chen YehKuo-Wei ChangMing-Chih HouWen-Chuan KuoPublished in: Cancers (2020)
Detection of oral dysplastic and early-stage cancerous lesions is difficult with the current tools. Half of oral cancers are diagnosed in a late stage. Detection of early stromal change to predict malignant transformation is a new direction in the diagnosis of early-stage oral cancer. The application of new optical tools to image stroma in vivo is under investigation, and polarization-sensitive optical coherence tomography (PS-OCT) is potentially one of those tools. This is a preliminary study to sequentially image oral stromal changes from normal, hyperplasia, and dysplasia to early-stage cancer by PS-OCT in vivo. We used 4-Nitroquinoline-1-oxide drinking water to induce dysplasia and early-stage oral cancer in 19 K14-EGFP-miR-211-GFP transgenic mice. A total of 8 normal, 12 hyperplastic, 11 dysplastic, and 4 early-stage cancerous lesions were enrolled. A new analytic process of PS-OCT imaging was proposed, called an en-face birefringence map. From the birefringence map, the sensitivity, specificity, positive predictive value, and negative predictive values to detect dysplasia and early-stage cancer were 100.00%, 95.00%, 93.75%, and 100.00%, respectively, and the kappa value of these images between two investigators was 0.942. The mean size of malignant lesions detected in this study is 1.66 ± 0.93 mm. This pilot animal study validates the use of PS-OCT to detect small and early-stage oral malignancy with high accuracy and consistency.
Keyphrases
- early stage
- optical coherence tomography
- drinking water
- diabetic retinopathy
- sentinel lymph node
- deep learning
- papillary thyroid
- high resolution
- optic nerve
- cell proliferation
- loop mediated isothermal amplification
- bone marrow
- squamous cell carcinoma
- long non coding rna
- immune response
- randomized controlled trial
- nuclear factor
- study protocol
- label free
- machine learning
- quantum dots
- childhood cancer
- lymph node metastasis
- heavy metals
- health risk assessment