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Trial Title:
AI-aided Optical Coherence Tomography for the Detection of Basal Cell Carcinoma
NCT ID:
NCT05817279
Condition:
Basal Cell Carcinoma
Optical Coherence Tomography
Conditions: Official terms:
Carcinoma
Carcinoma, Basal Cell
Conditions: Keywords:
Basal cell carcinoma
BCC
Optical coherence tomography
OCT
Imaging
Artificial intelligence
Machine learning
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Retrospective
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
Optical coherence tomography
Description:
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)
Arm group label:
AI-OCT
Arm group label:
Unaided OCT
Other name:
3mm punch biopsy
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.
Detailed 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)
Criteria for eligibility:
Study pop:
Scans of patients with equivocal BCC lesions will be included. Patients previously
underwent an OCT scan and punch biopsy for their lesion. Patients signed informed consent
for the use of the OCT scans made and patient information for the sake of answering
research questions regarding OCT.
Sampling method:
Probability Sample
Criteria:
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
Gender:
All
Minimum age:
18 Years
Maximum age:
N/A
Locations:
Facility:
Name:
Maastricht University Medical Center+
Address:
City:
Maastricht
Zip:
6202AZ
Country:
Netherlands
Status:
Recruiting
Contact:
Last name:
Tom Wolswijk, MD, MSc
Phone:
+31(0)42-3877295
Email:
tom.wolswijk@mumc.nl
Start date:
April 10, 2023
Completion date:
December 31, 2024
Lead sponsor:
Agency:
Maastricht University Medical Center
Agency class:
Other
Source:
Maastricht University Medical Center
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05817279
