ArticleClinical physiology and functional imaging2022
PET/CT imaging of spinal inflammation and microcalcification in patients with low back pain: A pilot study on the quantification by artificial intelligence-based segmentation.
Article in Clinical physiology and functional imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Potential applications of artificial intelligence in pain management: a scoping review.Frontiers in pain research (Lausanne, Switzerland) · 2026Pooled it
- [ 18 F]fluorodeoxyglucose PET/MRI for nononcological musculoskeletal indications: reference uptake values in the asymptomatic lumbar spine and example comparison to a low back pain patient.Nuclear medicine communications · 2026Article
- Automated joint segmentation enables quantitative molecular imaging of degeneration with [¹⁸F]FDG and [¹⁸F]NaF PET/CT.European journal of nuclear medicine and molecular imaging · 2026Article
- What a pain in the back: etiology, diagnosis and future treatment directions for discogenic low back pain.Bone research · 2025Review
- [Brain sciences · 2025Article
- Automated segmentation of the sacro-iliac joints, posterior spinal joints and discovertebral units on low-dose computed tomography for Na[EJNMMI physics · 2025Article
- A deep neural network for MRI spinal inflammation in axial spondyloarthritis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024Article
- Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine.Cyborg and bionic systems (Washington, D.C.) · 2024Review
- Review
- PET/CT imaging of spinal inflammation and microcalcification in patients with low back pain: A pilot study on the quantification by artificial intelligence-based segmentation.Clinical physiology and functional imaging · 2022Article
- Role of magnetic resonance imaging and 18-fluorodeoxyglucose positron emission tomography-computed tomography in identifying pain generators in patients with chronic low back pain.Journal of craniovertebral junction & spineArticle
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundCurrent imaging modalities are often incapable of identifying nociceptive sources of low back pain (LBP). We aimed to characterize these by means of positron emission tomography/computed tomography (PET/CT) of the lumbar spine region applying tracers
methodsUsing artificial intelligence (AI)-based quantification, we compared PET findings in two sex- and age-matched groups, a case group of seven males and five females, mean age 45 ± 14 years, with ongoing LBP and a similar control group of 12 pain-free individuals. PET/CT scans were segmented into three distinct volumes of interest (VOIs): lumbar vertebral bodies, facet joints and intervertebral discs. Maximum, mean and total standardized uptake values (SUVmax, SUVmean and SUVtotal) for FDG and NaF uptake in the 3 VOIs were measured and compared between groups. Holm-Bonferroni correction was applied to adjust for multiple testing.
resultsFDG uptake was slightly higher in most locations of the LBP group including higher SUVmean in the intervertebral discs (0.96 ± 0.34 vs. 0.69 ± 0.15). All NaF uptake values were higher in cases, including higher SUVmax in the intervertebral discs (11.63 ± 3.29 vs. 9.45 ± 1.32) and facet joints (14.98 ± 6.55 vs. 10.60 ± 2.97).
conclusionObserved intergroup differences suggest acute inflammation and microcalcification as possible nociceptive causes of LBP. AI-based quantification of relevant lumbar VOIs in PET/CT scans of LBP patients and controls appears to be feasible. These promising, early findings warrant further investigation and confirmation.
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