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Research Papers

LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool

[+] Author and Article Information
Tyler D. Wortman

Department of Mechanical Engineering,
Massachusetts Institute of Technology,
77 Massachusetts Avenue,
Cambridge, MA 02139
e-mail: wortman@mit.edu

Jay D. Carlson

Department of Electrical Engineering,
University of Nebraska-Lincoln,
209N SEC, 844 N. 16th Street,
Lincoln, NE 68588
e-mail: jcarlson@unl.edu

Edward Perez

Dermatology Laser Center,
1605 Redwood Road,
San Marcos, TX 78666
e-mail: epperez_md@yahoo.com

Alexander H. Slocum

Fellow ASME
Department of Mechanical Engineering,
Massachusetts Institute of Technology,
77 Massachusetts Avenue,
Cambridge, MA 02139
e-mail: slocum@mit.edu

Manuscript received March 15, 2017; final manuscript received January 19, 2018; published online March 5, 2018. Assoc. Editor: Chris Rylander.

J. Med. Devices 12(2), 021001 (Mar 05, 2018) (6 pages) Paper No: MED-17-1054; doi: 10.1115/1.4039209 History: Received March 15, 2017; Revised January 19, 2018

Current techniques for diagnosing skin cancer lack specificity and sensitivity, resulting in unnecessary biopsies and missed diagnoses. Automating tissue palpation and morphology quantification will result in a repeatable, objective process. LesionAir is a low-cost skin cancer diagnostic tool that measures the full-field compliance of tissue by applying a vacuum force and measuring the precise deflection using structured light three-dimensional (3D) reconstruction. The technology was tested in a benchtop setting on phantom skin and in a small clinical study. LesionAir has been shown to measure deflection with a 0.085 mm root-mean-square (RMS) error and measured the stiffness of phantom tissue to within 20% of finite element analysis (FEA) predictions. After biopsy and analysis, a dermatopathologist confirmed the diagnosis of skin cancer in tissue that LesionAir identified as noticeably stiffer and the regions of this stiffer tissue aligned with the bounds of the lesion. A longitudinal, full-scale study is required to determine the clinical efficacy of the device. This technology shows initial promise as a low-cost tool that could rapidly identify and diagnose skin cancer.

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Figures

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Fig. 1

LesionAir device fabricated to demonstrate the proposed methodology

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Fig. 2

Measured error heat map of a billiard ball for the presented structured light system

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Fig. 3

Cumulative distribution function of measured error of a billiard ball for the presented structured light system

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Fig. 4

A clinical image (a) of the pilot study patient's stage 3 malignant melanoma can be qualitatively compared to the normalized stiffness map (b). An increase in stiffness relative to surrounding tissue maps to the extents of the visible lesion (c).

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Fig. 5

Calculated ABCD results for the pilot study patient

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