Artificial Intelligence-assisted Evaluation of Pigmented Skin Lesions
NNCD
Dermoscopy Evaluation of Pigmented Skin Lesions by a Neuronal Network Clinical Decision Support: an Open Prospective Non Interventional Study
1 other identifier
observational
80
1 country
1
Brief Summary
Malignant melanoma (MM) is a deadly cancer, claiming globally about 160000 new cases per year and 48000 deaths at a 1:28 lifetime incidence (2016). The golden standard, dermoscopy, enables Dermatologists to diagnose with a sensitivity of 40%, and a 8-12% specificity, approximately. Additional diagnostic abilities are restricted to devices which are either unproved or experimental. A new technology of Neuronal Network Clinical Decision Support (NNCD) was developed. It uses a dermoscopic imaging device and a camera able to capture an image. The photo is transferred to a Cloud Server and further analyzed by a trained classifier. Classifier training is aimed at a high accuracy diagnosis of Dysplastic Nevi (DN), Spitz Nevi and Malignant Melanoma detection with assistance from a Deep Neuronal Learning network (DLN). Diagnosis output is an excise or do not excise recommendation for pigmented skin lesions. A total of 80 subjects already referred to biopsy pigmented skin lesions will be examined by dermoscopy imaging in a non interventional study. Artificial Intelligence output results, as measured by 2 different dermoscopes, to be compared to ground truth biopsies, by either classifier decisions or a novel Modified Classifier Technology output decisions. Primary endpoints are sensitivity and specificity detection of the NNCD techniques. Secondary endpoints are the positive and negative prediction ratios of NNCD techniques.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started Dec 2017
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
November 27, 2017
CompletedFirst Posted
Study publicly available on registry
December 5, 2017
CompletedStudy Start
First participant enrolled
December 6, 2017
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2018
CompletedStudy Completion
Last participant's last visit for all outcomes
March 31, 2019
CompletedSeptember 13, 2018
November 1, 2017
1.1 years
November 27, 2017
September 12, 2018
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Sensitivity for Classifier results as compared to biopsy
A Sensitivity of at least 75% for Classifier results as compared to biopsy
15 months
Sensitivity for MCT results as compared to biopsy
A Sensitivity of at least 85% for Classifier results as compared to biopsy
15 months
Secondary Outcomes (2)
The positive predictive value of MCT
15 months
The negative predictive value of MCT
15 months
Study Arms (1)
Dermoscopy
Dermoscopic imaging of a lesion decided to be biopsied
Interventions
Solely after the dermatologist has decided to biopsy a lesion and sent the patient to biopsy, a dermoscopic image is captured by a camera attached to a dermoscope.
Eligibility Criteria
Subjects examined at a Dermatologic speciality clinic.
You may qualify if:
- Patient aged 18-90 years
- A pigmented lesion by dermoscopy.
- Clinical management by the examining dermatologist results in biopsy
- The diameter of the pigmented area is between 1 and 40 millimeters
- The patient has consented to participate in the study and has signed the Informed Consent Form
You may not qualify if:
- Non intact skin (ulcers, bleeding)
- The lesion is located within 1 cm of the eye
- The lesion is located on mucosal surfaces
- The lesion is on or under nails
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Maccabi Healthcare Clinic
Tel Aviv, 59485, Israel
Related Publications (8)
Eggermont AM, Spatz A, Robert C. Cutaneous melanoma. Lancet. 2014 Mar 1;383(9919):816-27. doi: 10.1016/S0140-6736(13)60802-8. Epub 2013 Sep 19.
PMID: 24054424BACKGROUNDMayer JE, Swetter SM, Fu T, Geller AC. Screening, early detection, education, and trends for melanoma: current status (2007-2013) and future directions: Part I. Epidemiology, high-risk groups, clinical strategies, and diagnostic technology. J Am Acad Dermatol. 2014 Oct;71(4):599.e1-599.e12; quiz 610, 599.e12. doi: 10.1016/j.jaad.2014.05.046.
PMID: 25219716BACKGROUNDSiegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012 Jan-Feb;62(1):10-29. doi: 10.3322/caac.20138. Epub 2012 Jan 4.
PMID: 22237781BACKGROUNDNoor O 2nd, Nanda A, Rao BK. A dermoscopy survey to assess who is using it and why it is or is not being used. Int J Dermatol. 2009 Sep;48(9):951-2. doi: 10.1111/j.1365-4632.2009.04095.x.
PMID: 19702978BACKGROUNDAmerican Academy of Dermatology Ad Hoc Task Force for the ABCDEs of Melanoma; Tsao H, Olazagasti JM, Cordoro KM, Brewer JD, Taylor SC, Bordeaux JS, Chren MM, Sober AJ, Tegeler C, Bhushan R, Begolka WS. Early detection of melanoma: reviewing the ABCDEs. J Am Acad Dermatol. 2015 Apr;72(4):717-23. doi: 10.1016/j.jaad.2015.01.025. Epub 2015 Feb 16.
PMID: 25698455BACKGROUNDCampos-do-Carmo G, Ramos-e-Silva M. Dermoscopy: basic concepts. Int J Dermatol. 2008 Jul;47(7):712-9. doi: 10.1111/j.1365-4632.2008.03556.x.
PMID: 18613881BACKGROUNDDascalu A, David EO. Skin cancer detection by deep learning and sound analysis algorithms: A prospective clinical study of an elementary dermoscope. EBioMedicine. 2019 May;43:107-113. doi: 10.1016/j.ebiom.2019.04.055. Epub 2019 May 14.
PMID: 31101596DERIVEDWalker BN, Rehg JM, Kalra A, Winters RM, Drews P, Dascalu J, David EO, Dascalu A. Dermoscopy diagnosis of cancerous lesions utilizing dual deep learning algorithms via visual and audio (sonification) outputs: Laboratory and prospective observational studies. EBioMedicine. 2019 Feb;40:176-183. doi: 10.1016/j.ebiom.2019.01.028. Epub 2019 Jan 20.
PMID: 30674442DERIVED
Biospecimen
Biopsied lesion
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Avi Dascalu, MD. Ph.D.
Bostel LLC
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- CROSS SECTIONAL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
November 27, 2017
First Posted
December 5, 2017
Study Start
December 6, 2017
Primary Completion
December 31, 2018
Study Completion
March 31, 2019
Last Updated
September 13, 2018
Record last verified: 2017-11