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Trial details imported from ClinicalTrials.gov

For full trial details, please see the original record at https://clinicaltrials.gov/ct2/show/NCT04040114




Registration number
NCT04040114
Ethics application status
Date submitted
29/07/2019
Date registered
31/07/2019
Date last updated
19/08/2021

Titles & IDs
Public title
Improving Skin Cancer Management With Artificial Intelligence (04.17 SMARTI)
Scientific title
A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management (04.17 SMARTI)
Secondary ID [1] 0 0
04.17
Universal Trial Number (UTN)
Trial acronym
SMARTI
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Skin Cancer 0 0
Melanoma (Skin) 0 0
Condition category
Condition code
Cancer 0 0 0 0
Malignant melanoma
Cancer 0 0 0 0
Non melanoma skin cancer

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Treatment: Devices - Molemap Skin Cancer Triage Artificial Intelligence Device

No Intervention: Lead-in phase - During the lead-in phase treating clinicians will not be given the Molemap artificial intelligence diagnosis in real-time (i.e. in clinic with the patient).

Active Comparator: Active phase - During the active phase treating clinicians will be given the Molemap artificial intelligence diagnosis in real-time.


Treatment: Devices: Molemap Skin Cancer Triage Artificial Intelligence Device
This device/software incorporates artificial intelligence to provide a diagnostic aide for clinicians of patients with potentially malignant skin lesions. The software is supported by the use of cameras for acquisition of images.
Intervention code [1] 0 0
Treatment: Devices
Comparator / control treatment
Control group

Outcomes
Primary outcome [1] 0 0
Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment
Timepoint [1] 0 0
12 months
Secondary outcome [1] 0 0
Diagnostic accuracy of the device when used prospectively as compared to a dermatologist assessment
Timepoint [1] 0 0
12 months
Secondary outcome [2] 0 0
Diagnostic accuracy of the device compared to teledermatologist, dermatologist and registrar using histopathology as 'gold standard' for any lesions biopsied.
Timepoint [2] 0 0
12 months
Secondary outcome [3] 0 0
Appropriate selection of lesions by registrar compared to specialist dermatologists
Timepoint [3] 0 0
12 months
Secondary outcome [4] 0 0
Appropriateness of management by registrar compared to specialist dermatologists and impact AI might have on this.
Timepoint [4] 0 0
12 months

Eligibility
Key inclusion criteria
1. Patients attending the specialist dermatology clinics for skin cancer assessment or
surveillance.

2. Patients may or may not have a lesion of concern.

3. Patients must have at least two lesions imaged during full skin examination by a
dermatologist.

4. Age greater than 18 years.

5. Participant is willing and able to undertake investigation of suspicious lesion (e.g.
skin biopsy).
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
1. Patient does not give informed consent.

2. Patient is unable or unwilling to have a full skin examination

3. Patient has a known past or current diagnosis of cognitive impairment

Study design
Purpose of the study
Diagnosis
Allocation to intervention
Non-randomised trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Masking / blinding
Blinded (masking used)
Who is / are masked / blinded?


The people assessing the outcomes
Intervention assignment
Other
Other design features
Phase
Not Applicable
Type of endpoint/s
Statistical methods / analysis

Recruitment
Recruitment status
Completed
Data analysis
Reason for early stopping/withdrawal
Other reasons
Date of first participant enrolment
Anticipated
Actual
1/10/2019
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
30/05/2021
Sample size
Target
Accrual to date
Final
200
Recruitment in Australia
Recruitment state(s)
VIC
Recruitment hospital [1] 0 0
The Alfred- Victorian Melanoma Service - Melbourne
Recruitment hospital [2] 0 0
Skin Health Institute - Melbourne
Recruitment postcode(s) [1] 0 0
3004 - Melbourne
Recruitment postcode(s) [2] 0 0
3053 - Melbourne

Funding & Sponsors
Primary sponsor type
Other
Name
Melanoma and Skin Cancer Trials Limited
Address
Country
Other collaborator category [1] 0 0
Other
Name [1] 0 0
Monash University
Address [1] 0 0
Country [1] 0 0

Ethics approval
Ethics application status

Summary
Brief summary
The study is designed to be able to prove if the Molemap Artificial Intelligence (AI)
algorithm can be used as a diagnostic aid in a clinical setting. This study will determine
whether the diagnostic accuracy of the Molemap AI algorithm is comparable to a specialist
dermatologist, teledermatologist and registrar (as a surrogate for a general practitioner).
The study patient population will be adult patients who require skin cancer assessment.

The use of AI as a diagnostic aid may assist primary care physicians who have variable skill
in skin cancer diagnosis and lead to more appropriate referrals (rapid referral for lesions
requiring treatment and fewer referrals for benign lesions), thereby improving access and
reducing waiting times for specialist care.
Trial website
https://clinicaltrials.gov/ct2/show/NCT04040114
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 0 0
Victoria Mar, A/Prof
Address 0 0
Monash University, Australia
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for public queries
Name 0 0
Address 0 0
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for scientific queries



Summary Results

For IPD and results data, please see https://clinicaltrials.gov/ct2/show/NCT04040114