Skin CancerSMARTINCT04040114
Improving Skin Cancer Management With Artificial Intelligence (04.17 SMARTI)
A study testing Molemap Skin Cancer Triage Artificial Intelligence Device in people with Skin Cancer and Melanoma (Skin), run by Melanoma and Skin Cancer Trials Limited at 2 sites in Australia.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Skin Cancer, Melanoma (Skin)
- What is being tested?
- Molemap Skin Cancer Triage Artificial Intelligence Device
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 200 participants
- Where
- 2 sitesAustralia
- Study dates
- 1 Oct 2019to 30 May 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Patients attending the specialist dermatology clinics for skin cancer assessment or surveillance.
- Patients may or may not have a lesion of concern.
- Patients must have at least two lesions imaged during full skin examination by a dermatologist.
- Age greater than 18 years.
- Participant is willing and able to undertake investigation of suspicious lesion (e.g. skin biopsy).
Who cannot join
- Patient does not give informed consent.
- Patient is unable or unwilling to have a full skin examination
- Patient has a known past or current diagnosis of cognitive impairment
Trial locations and contacts
2 sites in 1 country.
Australia2 sites
The Alfred- Victorian Melanoma Service
Melbourne, Victoria, 3004
Skin Health Institute
Melbourne, Victoria, 3053
About this study
Official title: A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management (04.17 SMARTI)
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.
Read the detailed description
This is a pilot study which aims to establish whether artificial intelligence can be used as a diagnostic aid to improve diagnostic accuracy and outcomes in the specialist setting prior to conducting a much larger trial of the intervention in primary care.
Objectives:
- To establish whether the diagnostic accuracy of an artificial intelligence system is on par with teledermatologists' clinical assessment.
- To establish the safety and feasibility of offering artificial intelligence as a diagnostic aid prior to conducting a large trial of the intervention in primary care.
Hypotheses:
- The AI algorithm will have diagnostic accuracy comparable with a teledermatologists' assessment.
- The AI algorithm will have a diagnostic accuracy more conservative (i.e. more false positives) than dermatologists in the clinical setting.
- The AI algorithm will have greater diagnostic accuracy than the registrar.
- The AI algorithm will lead to a reduction in the number of biopsies performed by the registrar the likely impact of which will be reduced cost to patients and the healthcare system.
Trial Design:
The pilot study will take place in specialist dermatology and melanoma clinics in Victoria, Australia. Potential participants will be identified and screened at the general dermatology and melanoma clinics by the clinic doctors who deem the participant meet the inclusion and exclusion criteria.
Intervention:
Photography of lesions using a MoleMap camera device with automated artificial intelligence providing an assessment of the lesion in real time.
This pilot study will be a before and after intervention trial design. For the initial 'lead-in' phase, no AI diagnosis will be provided back to the treating clinicians. This phase will be used for prospective data collection.
For the intervention phase, an AI diagnosis will be provided to the dermatology registrar (who is used in this pilot study as a surrogate for the GP) and dermatologist after they have both assessed the patient clinically. Management of the lesion will be determined by the dermatologist and recorded.
The safety of the device will be determined by its use in the setting of specialist dermatology clinics to ensure that patients are receiving the highest standard of care with a dermatologist providing a clinical diagnosis and management for all lesions tested.
It is anticipated that the full trial will expand to include multiple sites across Australia and New Zealand.
- Conditions
- Skin Cancer, Melanoma (Skin)
- Being tested
- Molemap Skin Cancer Triage Artificial Intelligence Device
- Keywords
- Artificial Intelligence, Surveillance, Melanoma, Skin Cancer, photography
- Medical subject headings
- Skin Neoplasms, Melanoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Molemap Skin Cancer Triage Artificial Intelligence DeviceDevice
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.
| Study group | Role | What they receive |
|---|---|---|
| Lead-in phase | No intervention | 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 phase | Active comparator | During the active phase treating clinicians will be given the Molemap artificial intelligence diagnosis in real-time. Receives: Device: Molemap Skin Cancer Triage Artificial Intelligence Device |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment
Sensitivity and specificity of the algorithm compared to the teledermatologist.
Measured: 12 months
Secondary outcomes (4)
Diagnostic accuracy of the device when used prospectively as compared to a dermatologist assessment
Sensitivity and specificity of the algorithm compared to the dermatologist.
Measured: 12 months
Diagnostic accuracy of the device compared to teledermatologist, dermatologist and registrar using histopathology as 'gold standard' for any lesions biopsied.
Sensitivity and specificity of the algorithm compared to histopathology of any lesions biopsied.
Measured: 12 months
Appropriate selection of lesions by registrar compared to specialist dermatologists
This will be assessed by comparing the lesions selected for review by the registrar with the lesions selected by the dermatologist.
Measured: 12 months
Appropriateness of management by registrar compared to specialist dermatologists and impact AI might have on this.
This will be assessed by comparing the registrars clinical assessment with the dermatologists clinical assessment and if providing the AI assessment in real time has an impact.
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Jul 2019
- Study start1 Oct 2019
- Primary completion19 May 2021
- Study completion30 May 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Skin CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Sequential
- Model description
- Controlled before-and-after intervention study
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 200 participants (actual)
Sponsor and investigators
- Lead sponsor
- Melanoma and Skin Cancer Trials Limited
- Sponsor type
- University, hospital or other
- Collaborators
- Monash University
- Responsible party
- Sponsor
- Investigators
- Victoria Mar, A/Prof, Study chair, Monash University, Australia
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04040114
- Sponsor's protocol ID
- 04.17
- Acronym
- SMARTI
- Status last verified
- Jul 2021
- First submitted
- 29 Jul 2019
- Last updated
- 19 Aug 2021
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Felmingham C, MacNamara S, Cranwell W, Williams N, Wada M, Adler NR, Ge Z, Sharfe A, Bowling A, Haskett M, Wolfe R, Mar V. Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting. BMJ Open. 2022 Jan 4;12(1):e050203. doi: 10.1136/bmjopen-2021-050203.
PubMed 34983756
Study at a glance
From the registry record, last updated by the sponsor on 19 Aug 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management (04.17 SMARTI)
- ClinicalTrials.gov ID
- NCT04040114
- Acronym / sponsor ID
- SMARTI / 04.17
- Conditions
- Skin Cancer, Melanoma (Skin)
- Keywords
- Artificial Intelligence, Surveillance, Melanoma, Skin Cancer, photography
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 200 participants (actual)
- Lead sponsor
- Melanoma and Skin Cancer Trials LimitedUniversity, hospital or other
- Collaborators
- Monash University
- Study start
- 1 Oct 2019 (actual)
- Primary completion
- 19 May 2021 (actual)
- Study completion
- 30 May 2021 (actual)
- First posted
- 31 Jul 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This is a pilot study which aims to establish whether artificial intelligence can be used as a diagnostic aid to improve diagnostic accuracy and outcomes in the specialist setting prior to conducting a much larger trial of the intervention in primary care.
Objectives:
- To establish whether the diagnostic accuracy of an artificial intelligence system is on par with teledermatologists' clinical assessment.
- To establish the safety and feasibility of offering artificial intelligence as a diagnostic aid prior to conducting a large trial of the intervention in primary care.
Hypotheses:
- The AI algorithm will have diagnostic accuracy comparable with a teledermatologists' assessment.
- The AI algorithm will have a diagnostic accuracy more conservative (i.e. more false positives) than dermatologists in the clinical setting.
- The AI algorithm will have greater diagnostic accuracy than the registrar.
- The AI algorithm will lead to a reduction in the number of biopsies performed by the registrar the likely impact of which will be reduced cost to patients and the healthcare system.
Trial Design:
The pilot study will take place in specialist dermatology and melanoma clinics in Victoria, Australia. Potential participants will be identified and screened at the general dermatology and melanoma clinics by the clinic doctors who deem the participant meet the inclusion and exclusion criteria.
Intervention:
Photography of lesions using a MoleMap camera device with automated artificial intelligence providing an assessment of the lesion in real time.
This pilot study will be a before and after intervention trial design. For the initial 'lead-in' phase, no AI diagnosis will be provided back to the treating clinicians. This phase will be used for prospective data collection.
For the intervention phase, an AI diagnosis will be provided to the dermatology registrar (who is used in this pilot study as a surrogate for the GP) and dermatologist after they have both assessed the patient clinically. Management of the lesion will be determined by the dermatologist and recorded.
The safety of the device will be determined by its use in the setting of specialist dermatology clinics to ensure that patients are receiving the highest standard of care with a dermatologist providing a clinical diagnosis and management for all lesions tested.
It is anticipated that the full trial will expand to include multiple sites across Australia and New Zealand.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Sequential
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- Controlled before-and-after intervention study
| Arm | Type | Receives |
|---|---|---|
| Lead-in phase | No intervention | –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 phase | Active comparator | Device: Molemap Skin Cancer Triage Artificial Intelligence DeviceDuring the active phase treating clinicians will be given the Molemap artificial intelligence diagnosis in real-time. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Patients attending the specialist dermatology clinics for skin cancer assessment or surveillance.
- Patients may or may not have a lesion of concern.
- Patients must have at least two lesions imaged during full skin examination by a dermatologist.
- Age greater than 18 years.
- Participant is willing and able to undertake investigation of suspicious lesion (e.g. skin biopsy).
Key exclusion criteria (3 listed)
- Patient does not give informed consent.
- Patient is unable or unwilling to have a full skin examination
- Patient has a known past or current diagnosis of cognitive impairment
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Molemap Skin Cancer Triage Artificial Intelligence DeviceThis 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. | Device | Active phase |
Primary outcome
Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment
Time frame: 12 months
Sensitivity and specificity of the algorithm compared to the teledermatologist.
4 secondary outcomes
Diagnostic accuracy of the device when used prospectively as compared to a dermatologist assessment
Time frame: 12 months
Diagnostic accuracy of the device compared to teledermatologist, dermatologist and registrar using histopathology as 'gold standard' for any lesions biopsied.
Time frame: 12 months
Appropriate selection of lesions by registrar compared to specialist dermatologists
Time frame: 12 months
Appropriateness of management by registrar compared to specialist dermatologists and impact AI might have on this.
Time frame: 12 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Aug 2021.
- Derived from this study: PubMed 34983756Felmingham C, MacNamara S, Cranwell W, Williams N, Wada M, Adler NR, Ge Z, Sharfe A, Bowling A, Haskett M, Wolfe R, Mar V. Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting. BMJ Open. 2022 Jan 4;12(1):e050203. doi: 10.1136/bmjopen-2021-050203.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Victoria Mar, A/Prof study chair
Monash University, Australia
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Molemap Skin Cancer Triage Artificial Intelligence Device in people with Skin Cancer and Melanoma (Skin), run by Melanoma and Skin Cancer Trials Limited at 2 sites in Australia.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 19 Aug 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Australia. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic accuracy of the device when compared prospectively to a teledermatologist assesment (time frame: 12 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04040114, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Aug 2021.