ArticleIEEE transactions on bio-medical engineering2023
Anatomy-Specific Classification Model Using Label-Free FLIm to Aid Intraoperative Surgical Guidance of Head and Neck Cancer.
Article in IEEE transactions on bio-medical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Flexible intraoperative detectors for robotic and laparoscopic image-guided surgery: a systematic review.European journal of nuclear medicine and molecular imaging · 2026Pooled it
- Effects of surgical resection on tissue autofluorescence lifetime signatures in head and neck cancer: implications for intraoperative tumor margin assessment.Journal of biomedical optics · 2026Article
- Article
- Label-free fluorescence lifetime imaging can distinguish cancer from healthy tissue in spontaneously occurring canine oral tumors.Scientific reports · 2026Article
- Article
- Optical diagnostics of liver tumors using an autofluorescence lifetime probe.Biomedical optics express · 2025Article
- Data-Centric Learning Framework for Real-Time Detection of Aiming Beam in Fluorescence Lifetime Imaging Guided Surgery.IEEE transactions on bio-medical engineering · 2025Article
- Artificial Intelligence Assurance in Head and Neck Surgery: Now and Next.Proceedings. IEEE International Symposium on Computer-Based Medical Systems · 2025Article
- Label-free optical microscopy with artificial intelligence: a new paradigm in pathology.Biophotonics discovery · 2025Review
- Perspective on the use of fluorescence molecular imaging for peripheral and deepJournal of biomedical optics · 2025Review
- Early Detection of Lymph Node Metastasis Using Primary Head and Neck Cancer Computed Tomography and Fluorescence Lifetime Imaging.Diagnostics (Basel, Switzerland) · 2024Article
- Illuminating the future of precision cancer surgery with fluorescence imaging and artificial intelligence convergence.NPJ precision oncology · 2024Review
- FLIm-Based in Vivo Classification of Residual Cancer in the Surgical Cavity During Transoral Robotic Surgery.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
Intraoperative identification of head and neck cancer tissue is essential to achieve complete tumor resection and mitigate tumor recurrence. Mesoscopic fluorescence lifetime imaging (FLIm) of intrinsic tissue fluorophores emission has demonstrated the potential to demarcate the extent of the tumor in patients undergoing surgical procedures of the oral cavity and the oropharynx. Here, we report FLIm-based classification methods using standard machine learning models that account for the diverse anatomical and biochemical composition across the head and neck anatomy to improve tumor region identification. Three anatomy-specific binary classification models were developed (i.e., "base of tongue," "palatine tonsil," and "oral tongue"). FLIm data from patients (N = 85) undergoing upper aerodigestive oncologic surgery were used to train and validate the classification models using a leave-one-patient-out cross-validation method. These models were evaluated for two classification tasks: (1) to discriminate between healthy and cancer tissue, and (2) to apply the binary classification model trained on healthy and cancer to discriminate dysplasia through transfer learning. This approach achieved superior classification performance compared to models that are anatomy-agnostic; specifically, a ROC-AUC of 0.94 was for the first task and 0.92 for the second. Furthermore, the model demonstrated detection of dysplasia, highlighting the generalization of the FLIm-based classifier. Current findings demonstrate that a classifier that accounts for tumor location can improve the ability to accurately identify surgical margins and underscore FLIm's potential as a tool for surgical guidance in head and neck cancer patients, including those subjects of robotic surgery.
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