AI-Assisted In Situ Detection of Human Glioma Infiltration Using a Novel Computational Method for Optical Coherence Tomography.
Ronald M Juarez-ChambiCarmen KutJose J Rico-JimenezKaisorn L ChaichanaJiefeng XiDaniel Ulises Campos-DelgadoFausto J RodriguezAlfredo Quinones-HinojosaXingde LiJavier A JoPublished in: Clinical cancer research : an official journal of the American Association for Cancer Research (2019)
Previous methods for OCT-based detection of glioma-infiltrated brain tissue rely on estimating the tissue optical attenuation coefficient from the OCT signal, which requires sacrificing spatial resolution to increase signal quality, and performing systematic calibration procedures using tissue phantoms. By overcoming these major challenges, our AI-assisted method will enable implementing practical OCT-guided surgical tools for continuous, real-time, and accurate intraoperative detection of glioma-infiltrated brain tissue, facilitating maximal glioma resection and superior surgical outcomes for patients with glioma.
Keyphrases
- optical coherence tomography
- diabetic retinopathy
- loop mediated isothermal amplification
- real time pcr
- endothelial cells
- artificial intelligence
- high resolution
- label free
- white matter
- resting state
- patients undergoing
- computed tomography
- blood pressure
- heart rate
- mass spectrometry
- machine learning
- single molecule
- subarachnoid hemorrhage