LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool
Author(s)Carlson, Jay D.; Perez, Edward; Wortman, Tyler D.; Slocum Jr., Alexander H
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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 0.085mm 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.
DepartmentMassachusetts Institute of Technology. Department of Mechanical Engineering
Journal of Medical Devices
Wortman, Tyler D., Jay D. Carlson, Edward Perez, and Alexander H. Slocum. “LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool.” Journal of Medical Devices 12, no. 2 (March 5, 2018): 021001. © 2018 by ASME
Final published version