NCT03362138

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

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
80

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Dec 2017

Geographic Reach
1 country

1 active site

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

November 27, 2017

Completed
8 days until next milestone

First Posted

Study publicly available on registry

December 5, 2017

Completed
1 day until next milestone

Study Start

First participant enrolled

December 6, 2017

Completed
1.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2018

Completed
3 months until next milestone

Study Completion

Last participant's last visit for all outcomes

March 31, 2019

Completed
Last Updated

September 13, 2018

Status Verified

November 1, 2017

Enrollment Period

1.1 years

First QC Date

November 27, 2017

Last Update Submit

September 12, 2018

Conditions

Keywords

melanomadysplastic nevusartificial intelligenceearly diagnosis

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

Device: dermoscopy

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.

Dermoscopy

Eligibility Criteria

Age18 Years - 90 Years
Sexall
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

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

RECRUITING

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: 24054424BACKGROUND
  • Mayer 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: 25219716BACKGROUND
  • Siegel 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: 22237781BACKGROUND
  • Noor 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: 19702978BACKGROUND
  • American 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: 25698455BACKGROUND
  • Campos-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: 18613881BACKGROUND
  • Dascalu 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.

  • Walker 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.

Biospecimen

Retention: SAMPLES WITHOUT DNA

Biopsied lesion

MeSH Terms

Conditions

MelanomaDysplastic Nevus SyndromeDisease

Interventions

Dermoscopy

Condition Hierarchy (Ancestors)

Neuroendocrine TumorsNeuroectodermal TumorsNeoplasms, Germ Cell and EmbryonalNeoplasms by Histologic TypeNeoplasmsNeoplasms, Nerve TissueNevi and MelanomasSkin NeoplasmsNeoplasms by SiteSkin DiseasesSkin and Connective Tissue DiseasesNevusNeoplastic Syndromes, HereditaryGenetic Diseases, InbornCongenital, Hereditary, and Neonatal Diseases and AbnormalitiesPathologic ProcessesPathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Intravital MicroscopyMicroscopyDiagnostic ImagingDiagnostic Techniques and ProceduresDiagnosisInvestigative Techniques

Study Officials

  • Avi Dascalu, MD. Ph.D.

    Bostel LLC

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Avi Dascalu, MD, Ph.D.

CONTACT

Robert Raleigh, MBA

CONTACT

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

Locations