Biomedical hyperspectral imaging of murine tumors in the preclinical environment
Abstract
Biomedical hyperspectral imaging (HSI) is an emerging non-invasive optical imaging technique that captures spatial and spectral information of the imaged biological tissue. In recent years, HSI has been widely used to image human and animal tumors in the brain, breast, colon, prostate, and skin. This talk will cover the recent advancements in hyperspectral imaging for biomedical applications, mainly skin, in our lab at the Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia. The talk will introduce the basics of HSI and various implementations, followed by presenting tissue models and algorithms needed to extract tissue properties from hyperspectral images, focusing on the inverse adding-doubling (IAD) algorithm and advanced machine learning (ML) techniques. Moreover, the application of HSI to monitor the growth of different murine tumor models in the preclinical setting will be presented, and the possibility of combining HSI with other optical techniques, such as laser speckle contrast imaging, will be demonstrated. Ultimately, the capabilities of HSI for early detection of murine tumors will be exhibited.
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One significant finding is that lipid turnover decreases faster in aged female Drosophila compared to males. Additionally, dietary restrictions, downregulation of the insulin/IGF-1 signaling (IIS) pathway, and AMPK activation significantly alter lipid metabolism in aged or Alzheimer’s-affected brains. The introduction of APoD and PRM algorithms has enhanced our current multimodal metabolic nanoscopy to deliver superresolution with hyperspectral volumetric imaging capabilities. By using deuterated molecules—including glucose, amino acids, fatty acids, and water molecules—as bioorthogonal probes, this technology provides insights into the metabolic heterogeneity of organs such as the brain, adipose tissue, liver, muscle, retina, and kidneys.
Biography
Tadej Tomanic, MSc, is a young researcher and teaching assistant at the Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia. He received his BSc and MSc degrees in Physics and Medical Physics from the University of Ljubljana in 2017 and 2020, respectively. As part of his Master’s research, he collaborated with the Department of Neurology, University Medical Centre Ljubljana, to analyze brain FDG PET images of patients with Alzheimer’s disease. He also interned at Cosylab as a software engineer to work on developing a treatment planning system for patients with cancer treated with radiotherapy. He is currently pursuing his PhD in Physics at the University of Ljubljana under the supervision of Assoc. Prof. Matija Milanic, PhD. His research interests include early tumor detection, monitoring, treatment, and tumor vasculature development in vivo. He develops and applies various optical imaging methods in preclinical and clinical environments, focusing on hyperspectral imaging, laser speckle contrast imaging, optical coherence tomography, and optical profilometry. He is expected to graduate by January 2025.
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