## Protocol Section
### Identification Module
**NCT ID:** NCT05817279

**Brief Title:** AI-aided Optical Coherence Tomography for the Detection of Basal Cell Carcinoma

**Official Title:** AI-aided Optical Coherence Tomography for the Detection of Basal Cell Carcinoma

#### Organization Study ID Info
**ID:** 2022-3517
#### Organization
**Class:** OTHER
**Full Name:** Maastricht University Medical Center
### Status Module
#### Completion Date
**Date:** 2024-12-31

**Type:** ESTIMATED

#### Expanded Access Info
#### Last Update Post Date
**Date:** 2024-02-16

**Type:** ACTUAL

**Last Update Submit Date:** 2024-02-15

**Overall Status:** RECRUITING

#### Primary Completion Date
**Date:** 2024-12-31

**Type:** ESTIMATED

#### Start Date
**Date:** 2023-04-10

**Type:** ACTUAL

**Status Verified Date:** 2024-02

#### Study First Post Date
**Date:** 2023-04-18
**Type:** ACTUAL
**Study First Submit Date:** 2023-04-04
**Study First Submit QC Date:** 2023-04-04
### Sponsor Collaborators Module

#### Lead Sponsor

**Class:** OTHER

**Name:** Maastricht University Medical Center

#### Responsible Party

**Type:** SPONSOR

### Oversight Module

**Is FDA Regulated Device:** False

**Is FDA Regulated Drug:** False

**Oversight Has DMC:** False

### Description Module

**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)

### Conditions Module

**Conditions:**

- Basal Cell Carcinoma

- Optical Coherence Tomography

**Keywords:**

- Basal cell carcinoma

- BCC

- Optical coherence tomography

- OCT

- Imaging

- Artificial intelligence

- Machine learning

### Design Module

#### Design Info

**Observational Model:** CASE_CONTROL

**Time Perspective:** RETROSPECTIVE

#### Enrollment Info

**Count:** 124

**Type:** ESTIMATED

**Study Type:** OBSERVATIONAL

### Arms Interventions Module

#### Arm Group 1

**Description:** 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.

**Intervention Names:**

- Diagnostic Test: Optical coherence tomography

**Label:** AI-OCT

#### Arm Group 2

**Description:** 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.

**Intervention Names:**

- Diagnostic Test: Optical coherence tomography

**Label:** Unaided OCT

### Interventions

#### Intervention 1

**Arm Group Labels:**

- AI-OCT

- Unaided OCT

**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)

**Name:** Optical coherence tomography

**Other Names:**

- 3mm punch biopsy

**Type:** DIAGNOSTIC_TEST

### Outcomes Module

#### Primary Outcomes

**Description:** The difference in percentage of high-confidence diagnoses will be evaluated between AI-OCT and unaided OCT.

**Measure:** Proportion of high-confidence diagnoses

**Time Frame:** 31-12-2023

#### Secondary Outcomes

**Description:** 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.

**Measure:** Diagnostic accuracy of high-confidence diagnoses

**Time Frame:** 31-12-2023

**Description:** Differences in diagnostic parameters for BCC subtyping (sBCC/nBCC/iBCC) will be evaluated (explorative)

**Measure:** Diagnostic parameters for BCC subtyping

**Time Frame:** 31-12-2023

### Eligibility Module

**Eligibility 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

**Minimum Age:** 18 Years

**Sampling Method:** PROBABILITY_SAMPLE

**Sex:** ALL

**Standard Ages:**

- ADULT

- OLDER_ADULT

**Study Population:** 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.

### Contacts Locations Module

#### Locations

**Location 1:**

**City:** Maastricht

**Contacts:**

***Contact 1:***

- **Email:** tom.wolswijk@mumc.nl

- **Name:** Tom Wolswijk, MD, MSc

- **Phone:** +31(0)42-3877295

- **Role:** CONTACT

**Country:** Netherlands

**Facility:** Maastricht University Medical Center+

**State:** Limbrug

**Status:** RECRUITING

**Zip:** 6202AZ

### IPD Sharing Statement Module

**IPD Sharing:** UNDECIDED

## Derived Section

### Condition Browse Module - Ancestors

- ID: D000009375

- Term: Neoplasms, Glandular and Epithelial

- ID: D000009370

- Term: Neoplasms by Histologic Type

- ID: D000009369

- Term: Neoplasms

- ID: D000018295

- Term: Neoplasms, Basal Cell

### Condition Browse Module - Browse Branches

- Abbrev: BC04

- Name: Neoplasms

- Abbrev: All

- Name: All Conditions

### Condition Browse Module - Browse Leaves

- ID: M5534

- Name: Carcinoma

- Relevance: HIGH

- As Found: Carcinoma

- ID: M5537

- Name: Carcinoma, Basal Cell

- Relevance: HIGH

- As Found: Basal Cell Carcinoma

- ID: M12320

- Name: Neoplasms, Glandular and Epithelial

- Relevance: LOW

- As Found: Unknown

- ID: M12315

- Name: Neoplasms by Histologic Type

- Relevance: LOW

- As Found: Unknown

- ID: M20439

- Name: Neoplasms, Basal Cell

- Relevance: LOW

- As Found: Unknown

### Condition Browse Module - Meshes

- ID: D000002277

- Term: Carcinoma

- ID: D000002280

- Term: Carcinoma, Basal Cell

### Misc Info Module

- Version Holder: 2024-05-24
