Evaluation of cardiovascular pathologies in human aortas with hyperspectral imaging and optical coherence tomography

Abstract

Aortic diseases, which are among the leading causes of death worldwide, are extremely complex. These diseases, including aneurysm, atherosclerosis, and aortic stenosis, cause both morphological and chemical changes in the affected tissues. Understanding their nature, to improve diagnostics and disease progression monitoring, often presents a challenge due to the disease development over the years. Typically, CT scans with contrast agents are used for diagnosis, which are sometimes invasive for the patient providing only morphological information. Therefore, employing techniques that aid in the early diagnosis of these diseases would be of interest. In this work, ex-vivo tissue samples of 32 human aortic rings including aneurysm, atherosclerosis, aortic stenosis, aortic insufficiency, and bicuspid aortic valve diseases were obtained from surgical interventions. Healthy aortic specimens were considered as controls when excised from transplant donors undergoing non-aortic related pathologies. The aim is to co-register measurements from HSI (HyperSpectral Imaging) and OCT (Optical Coherence Tomography) imaging modalities, obtaining maps of chemical composition and morphological structure, being able track changes at each point of the tissue sample in approximately 100 cm2 of the inner aortic wall. These samples have been imaged ex-vivo using wide-field HSI, in the SWIR (1000-1700 nm) ranges, and OCT. OCT was used to generate attenuation coefficient maps of tissue specimens. Additionally, HSI was used to estimate elastin, collagen, lipid and water content of the samples. An inversely proportional relationship has been observed between the aorta's diameter and their attenuation coefficient. Furthermore, an increase in the mean squared error of the spectral fitting has been noted in pathological samples. This study underscores the potential of integrating HSI and OCT for the advanced characterization and early diagnosis of complex aortic diseases, highlighting their critical role in improving patient outcomes.