Issue 7, 2015

Statistical analysis of a lung cancer spectral histopathology (SHP) data set

Abstract

We report results on a statistical analysis of an infrared spectral dataset comprising a total of 388 lung biopsies from 374 patients. The method of correlating classical and spectral results and analyzing the resulting data has been referred to as spectral histopathology (SHP) in the past. Here, we show that standard bio-statistical procedures, such as strict separation of training and blinded test sets, result in a balanced accuracy of better than 95% for the distinction of normal, necrotic and cancerous tissues, and better than 90% balanced accuracy for the classification of small cell, squamous cell and adenocarcinomas. Preliminary results indicate that further sub-classification of adenocarcinomas should be feasible with similar accuracy once sufficiently large datasets have been collected.

Graphical abstract: Statistical analysis of a lung cancer spectral histopathology (SHP) data set

Article information

Article type
Paper
Submitted
12 oct. 2014
Accepted
27 ene. 2015
First published
27 ene. 2015

Analyst, 2015,140, 2449-2464

Author version available

Statistical analysis of a lung cancer spectral histopathology (SHP) data set

X. Mu, M. Kon, A. Ergin, S. Remiszewski, A. Akalin, C. M. Thompson and M. Diem, Analyst, 2015, 140, 2449 DOI: 10.1039/C4AN01832J

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