Abstract
Lung cancer is the most common cause of cancer-related deaths worldwide. Early detection improves outcomes, however, existing sampling techniques are associated with suboptimal diagnostic yield and procedure-related complications. Autofluorescence-based fluorescence-lifetime imaging microscopy (FLIM), a technique which measures endogenous fluorophore decay rates, may aid identification of optimal biopsy sites in suspected lung cancer. Our fibre-based fluorescence-lifetime imaging system, utilising 488 nm excitation, which is deliverable via existing diagnostic platforms, enables real-time visualisation and lifetime analysis of distal alveolar lung structure. We evaluated the diagnostic accuracy of the fibre-based fluorescence-lifetime imaging system to detect changes in fluorescence lifetime in freshly resected ex vivo lung cancer and adjacent healthy tissue as a first step towards future translation. The study compares paired non-small cell lung cancer (NSCLC) and non-cancerous tissues with gold standard diagnostic pathology to assess the performance of the technique. Paired NSCLC and non-cancerous lung tissues were obtained from thoracic resection patients (N=21). A clinically compatible 488 nm fluorescence-lifetime endomicroscopy platform was used to acquire simultaneous fluorescence intensity and lifetime images. Fluorescence lifetimes were calculated using a computationally-lightweight, rapid lifetime determination method. Fluorescence lifetime was significantly reduced in ex vivo lung cancer, compared with non-cancerous lung tissue [mean ± standard deviation (SD), 1.79±0.40 vs. 2.15±0.26 ns, P<0.0001], and fluorescence intensity images demonstrated distortion of alveolar elastin autofluorescence structure. Fibre-based fluorescence-lifetime imaging demonstrated good performance characteristics for distinguishing lung cancer, from adjacent noncancerous tissue, with 81.0% sensitivity and 71.4% specificity. Our novel fibre-based fluorescence-lifetime imaging system, which enables label-free imaging and quantitative lifetime analysis, discriminates ex vivo lung cancer from adjacent healthy tissue. This minimally invasive technique has potential to be translated as a real-time biopsy guidance tool, capable of optimising diagnostic accuracy in lung cancer.
Original language | English |
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Pages (from-to) | 355-361 |
Number of pages | 7 |
Journal | Translational Lung Cancer Research |
Volume | 13 |
Issue number | 2 |
Early online date | 1 Feb 2024 |
DOIs | |
Publication status | Published - 1 Feb 2024 |
Funding
This work was supported by Medical Research Council (grant No. MR/R017794/1 to S.F.); Engineering and Physical Sciences Research Council (grants Nos. EP/ K03197X/1 and EP/S025987/1 to K.D.).
Funders | Funder number |
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The Wellcome Trust | |
Medical Research Council | MR/R017794/1 |
Engineering and Physical Sciences Research Council | EP/ K03197X/1, EP/S025987/1 |
Keywords
- diagnostic imaging
- fibre-optics
- interventional pulmonology
- Lung cancer
- optical imaging
ASJC Scopus subject areas
- Oncology