Optical imaging of tumor vasculature and angiogenesisTomanič, Tadej (Avtor) Milanič, Matija (Mentor) Markelc, Boštjan (Komentor) hyperspectral imaginglaser speckle contrast imagingoptical profilometrytumorsvasculaturemurine modelsangiogenesisbiomedical opticsAssessing human tumors and their vasculature in the head and neck region requires advanced imaging methods capable of capturing detailed physiological and morphological features. The main goal of the research presented in this thesis was to implement a multimodal optical imaging system combining hyperspectral imaging (HSI) and laser speckle contrast imaging (LSCI) into the clinical environment to assess human tumors and tumor vasculature in the head and neck region. Three fundamental research objectives were identified to achieve the main goal: 1) the development of the multimodal optical imaging system combining HSI and LSCI; 2) the implementation of the imaging system in the preclinical environment to monitor murine tumor models; 3) the translation of the imaging system into the clinical environment to human tumors. The multimodal system was first developed and characterized, integrating HSI and LSCI to enable comprehensive imaging of tumors and their vasculature. The HSI system captured the spectral signatures of tissue describing physiology, pathology, and morphology, while the LSCI system provided information about blood flow and tissue perfusion. The hyperspectral image analysis pipeline utilized an inverse adding-doubling (IAD) algorithm, which was tested for accuracy and robustness in extracting key tissue properties. Also, blood vessel segmentation algorithms and vascular metrics were employed to quantify vascular morphology. In preclinical studies, the system was employed to monitor murine tumor models, including subcutaneous solid tumors and dorsal skinfold window chamber (DSWC) models. These studies demonstrated the ability to capture tumor growth, vascular changes, and response to treatments. In subcutaneous tumor models, biological features of CT26 tumors and their vasculature were identified, while differentiation of B16-F10, MC38, MOC1, and MOC2 tumors during growth was achieved. Also, the response of MC38 tumors to radiotherapy was observed. Moreover, the DSWC model offered superior capabilities for monitoring blood vessels, providing detailed insights into blood vessel growth in B16-F10 and MC38 tumors. Also, a response of 4T1 tumors to GET treatment was studied. Ultimately, the system was adapted for clinical use to assess human skin cancer, namely basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) in the head and neck region. A portable HSI system was utilized for imaging, and a machine learning (ML) algorithm was developed to differentiate between tumor types based on their tissue properties. This thesis provides critical insights into the use of multimodal optical imaging techniques to improve tumor diagnosis and growth monitoring, as well as tumor blood vessel development. Building on the knowledge gained from preclinical studies, we translated the technology into clinical practice, bridging the gap between preclinical and clinical applications.20252025-05-16 16:09:36Doktorsko delo/naloga169196VisID: 150223COBISS_ID: 236187395sl