AI-aided Optical Coherence Tomography for the Detection of Basal Cell Carcinoma

Status: Recruiting
Location: See location...
Intervention Type: Diagnostic test
Study Type: Observational
SUMMARY

Basal cell carcinoma (BCC) is the most common form of cancer among the Caucasian population. A BCC diagnosis is commonly establish by means of an invasive punch biopsy (golden standard). Optical coherence tomography (OCT) is a safe non-invasive diagnostic modality which may replace biopsy if an OCT assessor is able to establish a high confidence BCC diagnosis. Hence, for clinical implementation of OCT, diagnostic certainty should be as high as possible. Artificial intelligence in the form of a clinical decision support system (CDSS) may improve the diagnostic certainty of newly trained OCT assessors by highlighting suspicious areas on OCT scans and by providing diagnostic suggestions (classification). This study will evaluate the effect of a CDSS on the diagnostic certainty and accuracy of OCT assessors.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
View:

• Patients (18+ years)

• Patient underwent OCT scan and punch biopsy for an equivocal BCC lesion

Locations
Other Locations
Netherlands
Maastricht University Medical Center+
RECRUITING
Maastricht
Time Frame
Start Date: 2023-04-10
Estimated Completion Date: 2024-12-31
Participants
Target number of participants: 124
Treatments
AI-OCT
Group of 124 patients with equivocal BCC lesions. Of these lesions, OCT scans have been obtained in the past. These scans will be evaluated with AI-assistance.
Unaided OCT
Group of 124 patients with equivocal BCC lesions (same patients as in AI-OCT group). Of these lesions, OCT scans have been obtained in the past. These scans will be evaluated without AI-assistance.
Related Therapeutic Areas
Sponsors
Leads: Maastricht University Medical Center

This content was sourced from clinicaltrials.gov