A Summary of Pain Locations and Neuropathic Patterns Extracted Automatically from Patient Self-Reported Sensation Drawings
<b>Background</b> Chronic low-back pain (LBP) is the largest contributor to disability worldwide, yet many assessments still reduce a complex, spatially distributed condition to a single 0-10 score. Body-map drawings capture location and extent of pain, but manual digitization is too slow and inconsistent for large studies or real-time telehealth. <b>Methods</b> Paper pain drawings from 332 adults in the multicenter COMEBACK study (four University of California sites, March 2021-June 2023) were scanned to PDFs. A Python pipeline automatically (i) rasterized PDF pages with <i>pdf2image</i> v1.17.0; (ii) resized each scan and delineated anterior/posterior regions of interest; (iii) registered patient silhouettes to a canonical high-resolution template using ORB key-points, Brute-Force Hamming matching, RANSAC inlier selection, and 3 × 3 projective homography implemented in OpenCV; (iv) removed template outlines via adaptive Gaussian thresholding, Canny edge detection, and 3 × 3 dilation, leaving only patient-drawn strokes; (v) produced binary masks for pain, numbness, and pins-and-needles, then stacked these across subjects to create pixel-frequency matrices; and (vi) normalized matrices with min-max scaling and rendered heat maps. RGB composites assigned distinct channels to each sensation, enabling intuitive visualization of overlapping symptom distributions and for future data analyses. <b>Results</b> Cohort-level maps replicated classic low-back pain hotspots over lumbar paraspinals, gluteal fold, and posterior thighs, while exposing less-recognized clusters along the lateral hip and lower abdomen. Neuropathic-leaning drawings displayed broader leg involvement than purely nociceptive patterns. <b>Conclusions</b> Our automated workflow converts pen-on-paper pain drawings into machine-readable digitized images and heat maps at the population scale, laying practical groundwork for spatially informed, precision management of chronic LBP.
Authors
- Thomas A. Peterson (ORCID: https://orcid.org/0000-0002-2562-6574)
- Jeffrey C. Lotz
- Jeannie F. Bailey (ORCID: https://orcid.org/0000-0003-4618-7512)
- Abel Torres‐Espín (ORCID: https://orcid.org/0000-0002-9787-8738)
- Trisha F. Hue (ORCID: https://orcid.org/0000-0001-5922-5755)
- Andrew Bishara (ORCID: https://orcid.org/0000-0002-5427-482X)
- Jennifer E. Cummings
- Elisabetta de Rinaldis
Institutions
- University of Waterloo (CA)
- Università Campus Bio-Medico (IT)
- University of California, San Francisco (US)
Publication Details
- Journal
- International Journal of Environmental Research and Public Health
- Published
- 2025-09-19
- DOI
- https://doi.org/10.3390/ijerph22091456
- Primary Topic
- Musculoskeletal pain and rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- University of California, San Francisco