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Issue 7, 2015
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Statistical analysis of a lung cancer spectral histopathology (SHP) data set

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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

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Publication details

The article was received on 12 Oct 2014, accepted on 27 Jan 2015 and first published on 27 Jan 2015


Article type: Paper
DOI: 10.1039/C4AN01832J
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Citation: Analyst, 2015,140, 2449-2464

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    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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