Clinical trial · Observational
Dual-Channel Near-Infrared Autofluorescence Imaging and AI Analysis to Locate Parathyroid Glands (PTFinder)
A Multicenter Prospective Paired Observational Study Evaluating the Performance of the PTFinder Dual-Channel Near-Infrared and White-Light Imaging System With AI-Assisted Analysis for Rapid Identification of Parathyroid Glands in Surgical Specimens
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study tests PTFinder, a dual-camera system that makes parathyroid glands glow on screen by capturing their natural near-infrared autofluorescence. After a thyroid or parathyroid operation, the removed tissue is scanned with PTFinder and then checked again under normal white light. We will measure how fast (seconds) and how accurately the device finds real glands, confirmed by frozen pathology or a rapid PTH strip. About 180 adult patients at three Chinese hospitals will join. The imaging adds only a few minutes and does not change any part of the surgery. We will also record blood calcium and PTH at 1 h, 24 h, and 7 d after surgery to see whether better gland recovery lowers low-calcium risk.Collected images will also be used to train and test a deep-learning model for fully automated parathyroid recognition; model performance metrics constitute secondary outcomes.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Hyperparathyroidism | — | UNRESOLVED | — |
| Parathyroid Gland | — | UNRESOLVED | — |
| Thyroid Neoplasms | Thyroid Gland Neoplasm | ALIAS | 0.90 |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Offline Machine-Learning Algorithm (PTFinder-AI Beta) | Other | — | UNRESOLVED |
| PTFinder Dual-Channel NIR Autofluorescence Imaging System | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Surgical Specimen Cohort
- description
- Adults (≥18 y) undergoing thyroid or parathyroid surgery; their excised specimens will be imaged ex vivo with the PTFinder device for parathyroid-gland identification.
- interventionNames
- Device: PTFinder Dual-Channel NIR Autofluorescence Imaging System
- Other: Offline Machine-Learning Algorithm (PTFinder-AI Beta)
Primary outcomes (1)
- measure
- Detection Rate of Pathology-Confirmed Parathyroid Glands per Specimen (PTFinder)
- timeFrame
- Intra-operative imaging session (0-5 minutes)
- description
- Proportion of parathyroid glands correctly located by PTFinder divided by the total number of glands confirmed on frozen section or rapid PTH strip. Unit = % (higher = better).
Secondary outcomes (6)
- measure
- Time to First Parathyroid Gland Identification (PTFinder)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Age ≥18 years. * Scheduled for elective total thyroidectomy, hemithyroidectomy, or parathyroidectomy with removal of thyroid/parathyroid tissue. * Able and willing to provide written informed consent for participation and specimen imaging. Exclusion Criteria: * History of neck irradiation or prior neck surgery that may distort parathyroid anatomy. * Pregnancy or breastfeeding. * Confirmed or suspected parathyroid carcinoma, or thyroid carcinoma requiring en-bloc parathyroid resection. * Inability to understand the study procedures or to comply with follow-up.
References
Publications (1)
- BACKGROUNDWang B, Zhou CP, Ao W, Cai SJ, Ge ZW, Wang J, Huang WY, Yu JF, Wu SB, Yan SY, Zhang LY, Wang SS, Wang ZH, Hua S, Abdelhamid Ahmed AH, Randolph GW, Zhao WX. Exploring near-infrared autofluorescence properties in parathyroid tissue: an analysis of fresh and paraffin-embedded thyroidectomy specimens. J Biomed Opt. 2025 Jan;30(Suppl 1):S13702. doi: 10.1117/1.JBO.30.S1.S13702. Epub 2024 Jul 18. PMID 39034960