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Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has the ability to enhance and optimize all aspects of the PET imaging chain from patient scheduling, patient setup, protocoling, data acquisition, detector signal processing, reconstruction, image processing, and interpretation. AI poses industry-specific challenges which will need to be addressed and overcome to maximize the future potentials of AI in PET. This article provides an overview of these industry-specific challenges for the development, standardization, commercialization, and clinical adoption of AI and explores the potential enhancements to PET imaging brought on by AI in the near future. In particular, the combination of on-demand image reconstruction, AI, and custom-designed data-processing workflows may open new possibilities for innovation which would positively impact the industry and ultimately patients.

Chronic pain is associated with maladaptive reorganization of the central nervous system. Recent studies have suggested that disorganization of large-scale electrical brain activity patterns, such as neuronal network oscillations in the thalamocortical system, plays a key role in the pathophysiology of chronic pain. Yet, little is known about whether and how such network pathologies can be targeted with noninvasive brain stimulation as a nonpharmacological treatment option. We hypothesized that alpha oscillations, a prominent thalamocortical activity pattern in the human brain, are impaired in chronic pain and can be modulated with transcranial alternating current stimulation (tACS). We performed a randomized, crossover, double-blind, sham-controlled study in patients with chronic low back pain (CLBP) to investigate how alpha oscillations relate to pain symptoms for target identification and whether tACS can engage this target and thereby induce pain relief. We used high-density electroencephalography to measure alpha oscillations and found that the oscillation strength in the somatosensory region at baseline before stimulation was negatively correlated with pain symptoms. Stimulation with alpha-tACS compared to sham (placebo) stimulation significantly enhanced alpha oscillations in the somatosensory region. The stimulation-induced increase of alpha oscillations in the somatosensory region was correlated with pain relief. Given these findings of successful target identification and engagement, we propose that modulating alpha oscillations with tACS may represent a target-specific, nonpharmacological treatment approach for CLBP. This trial has been registered in ClinicalTrials.gov (NCT03243084). Perspective This study suggests that a rational design of transcranial alternating current stimulation, which is target identification, engagement, and validation, could be a nonpharmacological treatment approach for patients with CLBP.