Statistical modeling of diabetic neuropathy: Exploring the dynamics of nerve mortality
Journal article, 2023

Diabetic neuropathy is a disorder characterized by impaired nerve function and reduction of the number of epidermal nerve fibers per epidermal surface. Additionally, as neuropathy related nerve fiber loss and regrowth progresses over time, the two-dimensional spatial arrangement of the nerves becomes more clustered. These observations suggest that with development of neuropathy, the spatial pattern of diminished skin innervation is defined by a thinning process which remains incompletely characterized. We regard samples obtained from healthy controls and subjects suffering from diabetic neuropathy as realisations of planar point processes consisting of nerve entry points and nerve endings, and propose point process models based on spatial thinning to describe the change as neuropathy advances. Initially, the hypothesis that the nerve removal occurs completely at random is tested using independent random thinning of healthy patterns. Then, a dependent parametric thinning model that favors the removal of isolated nerve trees is proposed. Approximate Bayesian computation is used to infer the distribution of the model parameters, and the goodness-of-fit of the models is evaluated using both non-spatial and spatial summary statistics. Our findings suggest that the nerve mortality process changes as neuropathy advances.

Author

Konstantinos Konstantinou

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Farnaz Ghorbanpour

Allameh Tabataba'i University

Umberto Picchini

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Adam Loavenbruck

University of Minnesota

Aila Särkkä

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Statistics in Medicine

0277-6715 (ISSN) 1097-0258 (eISSN)

Vol. 42 23 4128-4146

Deep learning and likelihood-free Bayesian inference for stochastic modelling

Chalmers AI Research Centre (CHAIR), 2020-01-01 -- 2024-12-31.

Swedish Research Council (VR) (2019-03924), 2020-01-01 -- 2023-12-31.

Subject Categories

Endocrinology and Diabetes

Ophthalmology

Probability Theory and Statistics

Neurology

DOI

10.1002/sim.9851

More information

Latest update

3/7/2024 9