Spectroscopic optical coherence tomography for classification of colorectal cancer in a mouse model.
Wesley Y KendallJulianna BordasSeyedbabak MirminachiAbel JosephJatin RoperAdam WaxPublished in: Journal of biophotonics (2022)
Noninvasive diagnosis of the malignant potential of colon polyps can improve prevention of colorectal cancer without the need for time-consuming and expensive biopsies. This study examines the use of spectroscopic optical coherence tomography (OCT) to classify tissue from genetically engineered mouse models of early-stage adenoma (APC) and advanced adenocarcinoma (AKP) in which tumors are induced in the distal colon. The optical tissue properties of scattering power and scattering attenuation coefficient are evaluated by analyzing the imaging data collected from tissues. Classifications are generated using 2D linear discriminant analysis with high levels of discrimination obtained. The overall classification accuracy obtained was 91.5%, with 100% sensitivity and 96.7% specificity in separating tumors from benign tissue, and 77.8% sensitivity and 99.4% specificity in separating adenocarcinoma from nonmalignant tissue. Thus, this study demonstrates the clinical potential of using spectroscopic OCT for rapid detection of colon adenoma and colorectal cancer.
Keyphrases
- optical coherence tomography
- mouse model
- early stage
- molecular docking
- diabetic retinopathy
- machine learning
- high resolution
- deep learning
- gene expression
- big data
- human health
- drug induced
- climate change
- molecular dynamics simulations
- risk assessment
- lymph node
- electronic health record
- locally advanced
- artificial intelligence
- radiation therapy
- mass spectrometry
- rectal cancer
- neoadjuvant chemotherapy