Diagnosing lung carcinomas with optical coherence tomography

Lung carcinoma diagnosis on tissue biopsy can be challenging because of insufficient tumor and lack of architectural information. Optical coherence tomography (OCT) is a high-resolution imaging modality that visualizes tissue microarchitecture in volumes orders of magnitude larger than biopsy. It has been proposed that OCT could potentially replace tissue biopsy.

We aim to determine whether OCT could replace histology in diagnosing lung carcinomas. We develop and validate OCT interpretation criteria for common primary lung carcinomas: adenocarcinoma, squamous cell carcinoma (SCC), and poorly differentiated carcinoma.

A total of 82 ex vivo tumor samples were included in a blinded assessment with 3 independent readers. Readers were trained on the OCT criteria, and applied these criteria to diagnose adenocarcinoma, SCC, or poorly differentiated carcinoma in an OCT validation dataset. After a 7-month period, the readers repeated the training and validation dataset interpretation. An independent pathologist reviewed corresponding histology.

The average accuracy achieved by the readers was 82.6% (range, 73.7-94.7%). The sensitivity and specificity for adenocarcinoma were 80.3% (65.7-91.4%) and 88.6% (80.5-97.6%), respectively. The sensitivity and specificity for SCC were 83.3% (70.0-100.0%) and 87.0% (75.0-96.5%), respectively. The sensitivity and specificity for poorly differentiated carcinoma were 85.7% (81.0-95.2%) and 97.6% (92.9-100.0%), respectively.

Although these results are encouraging, they indicate that OCT cannot replace histology in the diagnosis of lung carcinomas. However, OCT has potential to aid in diagnosing lung carcinomas as a complement to tissue biopsy, particularly when insufficient tissue is available for pathology assessment.