Delineating nonmelanoma skin cancer margins using terahertz and optical imaging

Anna N. Yaroslavsky (Login required)
Department of Physics and Applied Physics, University of Massachusetts, Lowell, MA, USA
Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA

Cecil Joseph
Department of Physics and Applied Physics, University of Massachusetts, Lowell, MA, USA

Rakesh Patel
Department of Physics and Applied Physics, University of Massachusetts, Lowell, MA, USA

Alona Muzikansky
MGH Biostatistics Center, Massachusetts General Hospital, Boston, MA, USA

Victor A. Neel
Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA

Robert H. Giles
Department of Physics and Applied Physics, University of Massachusetts, Lowell, MA, USA

Paper #3170 received 8 Mar 2017; revised manuscript received 24 Mar 2017; accepted for publication 25 Mar 2017; published online 29 Mar 2017.

DOI: 10.18287/JBPE17.03.010301


We evaluated terahertz reflectance imaging and a combination of terahertz and optical techniques for delineating nonmelanoma skin cancers. After imaging, each terahertz pixel of each specimen was classified as cancerous or normal using a previously determined threshold. Subsequently, cancerous terahertz pixels were re-evaluated with polarization-sensitive optical technique. This additional information enabled us to re-classify each cancerous terahertz pixel using morphological appearance of the structures in the optical images. If the structures in the terahertz pixel appeared normal, the pixel was considered normal. The generalized linear mixture model was implemented to determine the sensitivity and specificity of each method. The model tested the probability of each terahertz pixel being diagnosed as a match with histology. For terahertz imaging alone, the sensitivity and specificity were 82% and 94%, respectively. For multimodal imaging, the sensitivity and specificity increased to 96 % and 99%, respectively. Multimodal terahertz-optical imaging has potential for the intraoperative assessment of tumor margins.


imaging; cancer

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