Early Detection of Diabetic Peripheral Neuropathy by fMRI: An Evidence-Based Review

Abstract

With the significant rise in the prevalence of diabetes worldwide, diabetic peripheral neuropathy (DPN) remains the most common complication among type 1 and 2 diabetics. The adverse sequelae of DPN, which include neuropathic pain, diabetic foot ulcers and lower-limb amputations, significantly impact quality of life and are major contributors to the biopsychosocial and economic burden of diabetes at the individual, societal and health system levels. Because DPN is often diagnosed in the late stages of disease progression by electromyography (EMG), and neuropathic pain as a result of DPN is difficult to treat, the need for earlier detection is crucial to better ascertain and manage the condition. Among the various modalities available to aid in the early detection of DPN, functional magnetic resonance imaging (fMRI) has emerged as a practical tool in DPN imaging due to its noninvasive radiation-free nature and its ability to relate real-time functional changes reflecting the local oxygen consumption of regions of the CNS due to external stimuli. This review aims to summarize the current body of knowledge regarding the utility of fMRI in detecting DPN by observing central nervous system (CNS) activity changes among individuals with DPN when compared to controls. The evidence to date points toward a tendency for increased activity in various central neuroanatomical structures that can be detected by fMRI and positively correlates with diabetic neuropathic pain.

Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes

“…However, a novel operator-independent system, which connects a VPT sensor to an ML algorithm, is currently being developed. 71 Besides quantitative data, anatomical data such as magnetic resonance imaging scans, are collected as biomarkers to diagnose painful DPN based on functional connectivity 75 and blood flow 76 in the central nervous system. Similarly, ultrasound images of the peripheral nerves can be utilized as anatomical inputs to a convolutional neural network capable of identifying peripheral nerve patterns indicative of DPN.…”

Simultaneous cortical, subcortical, and brainstem mapping of sensory activation

“…The spinocerebellar tracts, parallel pathways also involved in proprioception, carry stretch-related signals from muscles via the spinal cord to the cerebellum. Tactile sensory processing throughout the sensory network is affected in a wide variety of conditions, including stroke, diabetes, autism spectrum disorders, Parkinson’s disease and by normal aging (Carey et al 2011; Brodoehl et al 2013; He et al 2021; Lorenzini et al 2021; Chitneni et al 2022; Croosu et al 2023; Ma et al 2023). The changes in tactile detection and discrimination experienced in these conditions can affect mobility, self-care, and in the case of autism spectrum disorders, make it difficult to engage in social activities like childhood play (Welmer et al 2007; He et al 2021).…”

Improving Effects of Peripheral Nerve Decompression Microsurgery of Lower Limbs in Patients with Diabetic Peripheral Neuropathy

“…Diabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes, with an incidence rate of as high as 50–60% [ 1 , 2 ]. It is also the main cause of foot ulcers, infections, and amputations [ 3 , 4 ].…”