Could microcomputed tomography be a new method to distinguish between metastatic and non-metastatic lymph nodes in patients with non-small cell lung cancer as a decision support tool for pathological examination? A pilot study for method validation

Abstract

AbstractBackground:Patients with non-small cell lung cancer (NSCLC) wihtout lymph node (LN) metastases (pN0) have different survival rates even when the T status is similar. This may be because excised mediastinal and bronchial LNs are currently examined using a 2D method. Because, despite the rules of 2D pathological examination, unfortunately, not all of the removed LN can be sampled, and there may be metastatic foci in these remaining and unsampled LN tissues. Whereas, evaluation with micro-computed tomography (micro-CT) provides detailed information on internal structures of all these LNs as a whole and and without damaging the sample. We used quantitative micro-CT parameters to evaluate the metastasis status of LNs embedded in paraffin blocks.MethodsTwelve paraffin blocks and the corresponding whole slide images from eight NSCLC patients with pathological mediastinal LN metastases were used. The formalin-fixed paraffin-embedded (FFPE) LN blocks were subjected to micro-CT. Forty-seven regions of interest (ROIs) (17 metastatic foci, 11 normal lymphoid tissues, 10 adipose tissues, and 9 anthracofibrotic areas) were marked. Quantitative structural variables obtained via micro-CT analysis from tumoral and non-tumoral ROIs were analyzed.ResultsLinear density, connectivity, connectivity density, and closed porosity all differed significantly between tumoral and non-tumoral ROIs (kappa coefficients: 1, 0.90, 1, and 1, respectively). Receiver operating characteristic analysis showed that tumoral and non-tumoral ROIs differed in terms of thickness, linear density, connectivity, connectivity density, and percentage of closed porosity.ConclusionsQuantitative micro-CT parameters can distinguish between tumoral and non-tumoral areas in FFPE blocks of mediastinal LNs. These quantitative micro-CT parameters may facilitate the development of an artificial intelligence algorithm that can detect metastatic foci in the LN in FFPE LN blocks .