Valdes-Hernandez, Pedro A;
Laffitte Nodarse, Chavier;
Johnson, Alisa J;
Montesino-Goicolea, Soamy;
Bashyam, Vishnu;
Davatzikos, Christos;
Peraza, Julio A;
... Cruz-Almeida, Yenisel; + view all
(2023)
Brain-predicted age difference estimated using DeepBrainNet is significantly associated with pain and function—a multi-institutional and multiscanner study.
Pain
, 164
(12)
pp. 2822-2838.
10.1097/j.pain.0000000000002984.
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Abstract
Brain age predicted differences (brain-PAD: predicted brain age minus chronological age) have been reported to be significantly larger for individuals with chronic pain compared with those without. However, a debate remains after one article showed no significant differences. Using Gaussian Process Regression, an article provides evidence that these negative results might owe to the use of mixed samples by reporting a differential effect of chronic pain on brain-PAD across pain types. However, some remaining methodological issues regarding training sample size and sex-specific effects should be tackled before settling this controversy. Here, we explored differences in brain-PAD between musculoskeletal pain types and controls using a novel convolutional neural network for predicting brain-PADs, ie, DeepBrainNet. Based on a very large, multi-institutional, and heterogeneous training sample and requiring less magnetic resonance imaging preprocessing than other methods for brain age prediction, DeepBrainNet offers robust and reproducible brain-PADs, possibly highly sensitive to neuropathology. Controlling for scanner-related variability, we used a large sample (n = 660) with different scanners, ages (19-83 years), and musculoskeletal pain types (chronic low back [CBP] and osteoarthritis [OA] pain). Irrespective of sex, brain-PAD of OA pain participants was ∼3 to 4.7 years higher than that of CBP and controls, whereas brain-PAD did not significantly differ among controls and CBP. Moreover, brain-PAD was significantly related to multiple variables underlying the multidimensional pain experience. This comprehensive work adds evidence of pain type-specific effects of chronic pain on brain age. This could help in the clarification of the debate around possible relationships between brain aging mechanisms and pain.
| Type: | Article |
|---|---|
| Title: | Brain-predicted age difference estimated using DeepBrainNet is significantly associated with pain and function—a multi-institutional and multiscanner study |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1097/j.pain.0000000000002984 |
| Publisher version: | http://doi.org/10.1097/j.pain.0000000000002984 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10176704 |
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