| Literature DB >> 31177622 |
Max Diem1,2, Ayşegül Ergin1, Xinying Mu1,3.
Abstract
This paper summarizes results from two large lung cancer studies comprising over 700 samples that demonstrate the ability of spectral histopathology (SHP) to distinguish cancerous tissue regions from normal tissue, to differentiate benign lesions from normal tissue and cancerous lesions, and to classify lung cancer types. Furthermore, malignancy-associated changes can be identified in cancer-adjacent normal tissue. The ability to differentiate a multitude of normal cells and tissue types allow SHP to identify tumor margins and immune cell infiltration. Finally, SHP easily distinguishes small cell lung cancer (SCLC) from non-SCLC (NSCLC) and provides a further differentiation of NSCLC into adenocarcinomas and squamous cell carcinomas with an accuracy comparable of classical histopathology combined with immunohistochemistry. Case studies are presented that demonstrates that SHP can resolve interobserver discrepancies in standard histopathology.Entities:
Keywords: cancer classification; lung cancer; spectral histo-pathology; support vector machine
Mesh:
Year: 2019 PMID: 31177622 DOI: 10.1002/jbio.201900061
Source DB: PubMed Journal: J Biophotonics ISSN: 1864-063X Impact factor: 3.207