Basal Cell Carcinoma, Optical Coherence Tomography
Conditions
Keywords
Basal cell carcinoma, BCC, Optical coherence tomography, OCT, Imaging, Artificial intelligence, Machine learning
Brief 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)
Interventions
DIAGNOSTIC_TESTOptical 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)
Sponsors
Maastricht University Medical Center
Study design
Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proportion of high-confidence diagnoses | 31-12-2023 | The difference in percentage of high-confidence diagnoses will be evaluated between AI-OCT and unaided OCT. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic accuracy of high-confidence diagnoses | 31-12-2023 | 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. |
| Diagnostic parameters for BCC subtyping | 31-12-2023 | Differences in diagnostic parameters for BCC subtyping (sBCC/nBCC/iBCC) will be evaluated (explorative) |
Countries
Netherlands
Outcome results
None listed