Diagnostic Imaging Study for the Melanoma Advanced Imaging Dermatoscope (mAID)
|ClinicalTrials.gov Identifier: NCT02470273|
Recruitment Status : Active, not recruiting
First Posted : June 12, 2015
Last Update Posted : April 22, 2020
|Condition or disease|
The purpose of this study is to calculate the sensitivity and specificity of a novel imaging device and associated software algorithm in detecting early stage melanoma versus nevi of the skin. The instrument, which was invented by the PI, for the purposes of this study, will be loaned to three external (to Rockefeller) institutions and used on patients who are scheduled for biopsy of pigmented lesions. The purpose of correlating the output screening result of the novel device and the output diagnosis of the gold standard histology analysis procedure is so that these two diagnoses can be compared to generate the number of true positives, true negatives, false positives and false negatives for the novel device. The purpose of disseminating the device to the external institutions is to achieve the appropriate power such that the specificity can be evaluated at 99% sensitivity. The rationale for the power needed in the study is that in order to be clinically useful, the device needs to be extremely sensitive (i.e. 99%) because false negative diagnosis is a dangerous situation, leading to potential progression of melanoma, the most deadly form of skin cancer.
The scientific hypothesis is that the diagnostic mechanism for superficial melanoma is the light tissue interaction that occurs between the blue shifted wavelengths (i.e. blue light, ultra violet light) and the superficial epidermis while the mechanism for diagnosis of deeper melanoma (i.e. Breslow depth >0.5mm) is the light/tissue interaction that occurs between the red shifted light (i.e. red light, infrared light) and the portion of the pigmented lesion that lies within the dermis. These hypotheses were fueled by initial observations that the diagnostic sensitivity and specificity were wavelength dependent in a study that looked at only the red, green and blue wavelengths as available in traditional digital dermoscopy imaging. The initial finding was that of the multiple features analyzed, more features were statistically significant diagnostics in the blue channel but there were (a relative minority) other features that fared better in the red channel. It is hypothesized that the diagnostic features that did better in the red channel were features of deep melanin while the superficial regions, which should theoretically be atypical in ALL melanomas, were evident in the quantitative endpoint metrics generated from the blue channel.
|Study Type :||Observational|
|Estimated Enrollment :||1000 participants|
|Official Title:||Multicenter Diagnostic Imaging Study for the Melanoma Advanced Imaging Dermatoscope (mAID)|
|Study Start Date :||August 2015|
|Estimated Primary Completion Date :||July 2021|
|Estimated Study Completion Date :||July 2021|
Patients with a suspicious skin lesion indicated for biopsy
- A comparison between gold standard histopathology screening results and mAID screening results [ Time Frame: Day 1 ]A comparison between the gold standard invasive biopsy diagnostic result (melanoma or nevus) and the diagnostic result produced by automated computer image processing that operates on the mAID-produced hyperspectral image. This diagnostic result is defined as the melanoma Q-score, which is the percent likelihood that this lesion is melanoma based on a previous computer-learning algorithm that utilized 53 unique malignancy metrics.
- A comparison between gold standard histopathology screening results and analysis of the standard dermatoscope image. [ Time Frame: Day 1 ]A comparison between the gold standard invasive biopsy diagnostic result (melanoma or nevus) and the diagnostic result produced by automated computer image processing that operates on the standard dermatoscope image. This diagnostic result is defined as the melanoma Q-score, which is the percent likelihood that this lesion is melanoma based on a previous computer-learning algorithm that utilized 53 unique malignancy metrics.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02470273
|United States, California|
|Beckman Laser Institute at University of California Irvine|
|Irvine, California, United States, 92617|
|Chao Family Comprehensive Cancer Center|
|Orange, California, United States, 92868|
|The University of California (Davis)|
|Sacramento, California, United States, 95816|
|United States, Florida|
|Skin and Cancer Associates|
|Plantation, Florida, United States, 33324|
|United States, Oregon|
|Oregon Health Sciences University|
|Portland, Oregon, United States, 97239|
|Principal Investigator:||Daniel Gareau, PhD, MCR||Rockefeller University|