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Title: Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging

Abstract

Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies. Here we use dynamic thermal imaging (DTI) to demonstrate a rapid, accurate and non-invasive imaging system for detection of skin cancer. In DTI, the lesion is cooled down and the thermal recovery is recorded using infrared imaging. The thermal recovery curves of the suspected lesions are then utilized in the context of continuous-time detection theory in order to define an optimal statistical decision rule such that the sensitivity of the algorithm is guaranteed to be at a maximum for every prescribed false-alarm probability. The proposed methodology was tested in a pilot study including 140 human subjects demonstrating a sensitivity in excess of 99% for a prescribed specificity in excess of 99% for detection of skin cancer. To the best of our knowledge, this is the highest reported accuracy for any non-invasive skin cancer diagnosis method.

Authors:
 [1];  [2];  [3];  [3];  [4];  [5]
  1. Univ. of New Mexico, Albuquerque, NM (United States). Center for High Technology Materials (CHTM) and Dept. of Electrical and Computer Engineering; Univ. of Concepcion (Chile). Dept. of Electrical Engineering
  2. Univ. of New Mexico, Albuquerque, NM (United States). Center for High Technology Materials (CHTM) and Dept. of Electrical and Computer Engineering
  3. Skinfrared, LLC, Albuquerque, NM (United States)
  4. Univ. of New Mexico, Albuquerque, NM (United States). UNM Cancer Center and Dept. of Dermatology
  5. Univ. of New Mexico, Albuquerque, NM (United States). Center for High Technology Materials (CHTM) and Dept. of Electrical and Computer Engineering; Skinfrared, LLC, Albuquerque, NM (United States)
Publication Date:
Research Org.:
Univ. of New Mexico, Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1465131
Grant/Contract Number:  
NA0002494
Resource Type:
Accepted Manuscript
Journal Name:
Biomedical Optics Express
Additional Journal Information:
Journal Volume: 8; Journal Issue: 4; Journal ID: ISSN 2156-7085
Publisher:
Optical Society of America
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Godoy, Sebastián E., Hayat, Majeed M., Ramirez, David A., Myers, Stephen A., Padilla, R. Steven, and Krishna, Sanjay. Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging. United States: N. p., 2017. Web. doi:10.1364/BOE.8.002301.
Godoy, Sebastián E., Hayat, Majeed M., Ramirez, David A., Myers, Stephen A., Padilla, R. Steven, & Krishna, Sanjay. Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging. United States. https://doi.org/10.1364/BOE.8.002301
Godoy, Sebastián E., Hayat, Majeed M., Ramirez, David A., Myers, Stephen A., Padilla, R. Steven, and Krishna, Sanjay. Sun . "Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging". United States. https://doi.org/10.1364/BOE.8.002301. https://www.osti.gov/servlets/purl/1465131.
@article{osti_1465131,
title = {Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging},
author = {Godoy, Sebastián E. and Hayat, Majeed M. and Ramirez, David A. and Myers, Stephen A. and Padilla, R. Steven and Krishna, Sanjay},
abstractNote = {Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies. Here we use dynamic thermal imaging (DTI) to demonstrate a rapid, accurate and non-invasive imaging system for detection of skin cancer. In DTI, the lesion is cooled down and the thermal recovery is recorded using infrared imaging. The thermal recovery curves of the suspected lesions are then utilized in the context of continuous-time detection theory in order to define an optimal statistical decision rule such that the sensitivity of the algorithm is guaranteed to be at a maximum for every prescribed false-alarm probability. The proposed methodology was tested in a pilot study including 140 human subjects demonstrating a sensitivity in excess of 99% for a prescribed specificity in excess of 99% for detection of skin cancer. To the best of our knowledge, this is the highest reported accuracy for any non-invasive skin cancer diagnosis method.},
doi = {10.1364/BOE.8.002301},
journal = {Biomedical Optics Express},
number = 4,
volume = 8,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2017},
month = {Sun Jan 01 00:00:00 EST 2017}
}

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Works referencing / citing this record:

A novel technique to diagnose non‐melanoma skin cancer by thermal conductivity measurements: Correlations with cancer stromal factors
journal, August 2019

  • Fujimura, Taku; Okabe, Takahiro; Tanita, Kayo
  • Experimental Dermatology, Vol. 28, Issue 9
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