Structural and spectral morphometry and diagnosis of lung tumors

Abstract

Visualization of multi-dimensional (3D) pathological information of lung specimens can provide better understanding for the diagnosis of lung cancers. Phase-sensitive computed tomography has been employed to investigate non-destructive 3D histology and morphometry of soft tissues in the last decade. However, it’s insufficient to make an accurate diagnosis by only using the microstructural morphology of tumor specimens linked to clinical data. Synchrotron-based micro-structural and infrared spectroscopic techniques was employed to improve the level of diagnosing lung tumor (LT) with combination of traditional medical examination. The synchrotron X-ray phase-contrast microtomography can provide the elucidation of correlated cross-scale morphometry of LT, including biological boundary, 3D histologic features, and quantitative volumetric lesion statistics. Compared to conventional histopathological sections, it facilitated the time-efficient scouting for regions of interest related to LT. The Fourier transform infrared micro-spectroscopy successfully revealed the IR spectral correlations and differences between normal and tumor tissues, partially confirmed by conventional biochemical examinations. Especially, lacking the peak of 1733 cm−1 could be considered as an important indicator for malignant LT. The dual-modality imaging fusion of LT samples was capable of better explanation of LT biomolecular and microenvironmental evolution. We demonstrated the multi-dimensional imaging protocol for LT-related diagnosis has a good potential in early lung cancer screening and clinical assessment.