Pancreatic Islet Viability Assessment Using Hyperspectral Imaging of Autofluorescence
Jared M. Campbell,
Stacey N. Walters,
Abbas Habibalahi,
Saabah B. Mahbub,
Ayad G. Anwer,
Shannon Handley,
Shane T. Grey,
Ewa M. Goldys
Affiliations
Jared M. Campbell
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2033, Australia
Stacey N. Walters
Garvan Institute of Medical Research, Faculty of Medicine, St Vincent’s Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
Abbas Habibalahi
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2033, Australia
Saabah B. Mahbub
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2033, Australia
Ayad G. Anwer
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2033, Australia
Shannon Handley
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2033, Australia
Shane T. Grey
Garvan Institute of Medical Research, Faculty of Medicine, St Vincent’s Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
Ewa M. Goldys
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW 2033, Australia
Islets prepared for transplantation into type 1 diabetes patients are exposed to compromising intrinsic and extrinsic factors that contribute to early graft failure, necessitating repeated islet infusions for clinical insulin independence. A lack of reliable pre-transplant measures to determine islet viability severely limits the success of islet transplantation and will limit future beta cell replacement strategies. We applied hyperspectral fluorescent microscopy to determine whether we could non-invasively detect islet damage induced by oxidative stress, hypoxia, cytokine injury, and warm ischaemia, and so predict transplant outcomes in a mouse model. In assessing islet spectral signals for NAD(P)H, flavins, collagen-I, and cytochrome-C in intact islets, we distinguished islets compromised by oxidative stress (ROS) (AUC = 1.00), hypoxia (AUC = 0.69), cytokine exposure (AUC = 0.94), and warm ischaemia (AUC = 0.94) compared to islets harvested from pristine anaesthetised heart-beating mouse donors. Significantly, with unsupervised assessment we defined an autofluorescent score for ischaemic islets that accurately predicted the restoration of glucose control in diabetic recipients following transplantation. Similar results were obtained for islet single cell suspensions, suggesting translational utility in the context of emerging beta cell replacement strategies. These data show that the pre-transplant hyperspectral imaging of islet autofluorescence has promise for predicting islet viability and transplant success.
