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

Basal Cell Carcinoma Clinical Trial

Official title:

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

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05817279
• Other study ID #: 2022-3517
• Status: Recruiting
• Start date: April 10, 2023
• Est. completion date: December 31, 2024

Study information

• Verified date: February 2024
• Source: Maastricht University Medical Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Description:

In this diagnostic case control design, OCT assessors will retrospectively evaluate OCT scans of equivocal BCC lesions twice (once with, and once without the help of the CDSS). A total of 124 scans (62 BCC/62 non-BCC) will be included in the study. Cases will be shuffled to prevent recall bias. AI-aided OCT scans and unaided OCT scans will be presented in alternating order. The assessors will express their certainty level on a 5-point confidence scale. The diagnostic certainty and diagnostic accuracy of OCT assessment with CDSS and without CDSS will be compared.

Research questions:

1. Does AI-aided OCT assessment result in an increase in high-confidence diagnoses compared to unaided OCT assessment?

2. Does AI-aided OCT assessment result in a significant increase in sensitivity for BCC detection without compromising specificity compared to unaided OCT assessment?

3. Does AI-aided OCT assessment result in more accurate BCC subtyping compared to unaided OCT assessment (explorative)

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 124
• Est. completion date: December 31, 2024
• Est. primary completion date: December 31, 2024
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients (18+ years)

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

Exclusion Criteria:

• Patient unable to sign informed consent

Related Conditions & MeSH terms

• Basal Cell Carcinoma
• Carcinoma
• Carcinoma, Basal Cell
• Optical Coherence Tomography

Intervention

Diagnostic Test:
• Optical coherence tomography
Optical coherence tomography: OCT is a non-invasive CE-certified diagnostic modality based on light interferometry. An OCT scan visualizes an area with a diameter of 6mm thereby revealing the skin and adnexal structures with a depth of approximately 1.5mm. 3mm punch biopsy: the patients included in this study underwent a 3mm punch biopsy conform regular care. The subsequent histopathological examination of the biopsy specimen serves as ground truth diagnosis of the lesions (gold standard)

Locations

Country	Name	City	State
Netherlands	Maastricht University Medical Center+	Maastricht	Limbrug

Sponsors (1)

Lead Sponsor	Collaborator
Maastricht University Medical Center

Country where clinical trial is conducted

Netherlands, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Proportion of high-confidence diagnoses	The difference in percentage of high-confidence diagnoses will be evaluated between AI-OCT and unaided OCT.	31-12-2023
Secondary	Diagnostic accuracy of high-confidence diagnoses	Diagnostic parameters (sensitivity, specificity, positive predictive value, negative predicted value, diagnostic odds ratio) will be estimated for high-confidence diagnoses made by AI-OCT and unaided OCT.	31-12-2023
Secondary	Diagnostic parameters for BCC subtyping	Differences in diagnostic parameters for BCC subtyping (sBCC/nBCC/iBCC) will be evaluated (explorative)	31-12-2023