{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T21:43:05Z","timestamp":1791495785591,"version":"4.3.4"},"reference-count":20,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"MolecuLight Inc.","award":["NCT06682923"],"award-info":[{"award-number":["NCT06682923"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Accurate and reproducible wound measurement is essential for monitoring healing and guiding treatment decisions. Conventional ruler-based techniques are prone to geometric overestimation and operator variability. This study evaluated the accuracy and reproducibility of the MolecuLightDX wound imaging device for measuring wound surface area and depth compared with ruler-based measurements and ground truth digital photography methods. Methods: This investigation comprised two companion studies: a prospective, paired, multicenter clinical study comparing MolecuLightDX measurement with the ruler method against an image-based ground truth, and a bench and clinical validation of the AutoDepth feature against a calibrated three-dimensional optical scanner. The area of study included 17 benchtop wound models and enrolled 27 patients (33 wounds; area range: 0.56\u201323.04 cm2) across two wound care centers, and the AutoDepth study included 17 benchtop wound models and 34 clinical wounds (depth range: 0.06\u20134.13 cm). Accuracy, intra- and inter-user variability, and agreement were assessed using the mean percentage error (MPE), coefficient of variation (CV), intraclass correlation coefficients (ICC), and Bland\u2013Altman analysis. Results: The device demonstrated high accuracy and reproducibility for both wound surface area and depth measurements compared with ruler-based and ground truth digital photography methods. The MPE for surface area was &lt;10%, representing a tenfold improvement over ruler estimation (77.9%). For wound area, intra- and inter-user CVs were &lt;10%, and for depth, ICCs were \u22480.99. Conclusions: The MolecuLightDX device provides accurate and consistent wound area and depth measurements across diverse wound types, demonstrating superior accuracy and reproducibility compared with conventional ruler-based methods and supporting its integration into wound assessment workflows.<\/jats:p>","DOI":"10.3390\/diagnostics16071055","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T10:09:21Z","timestamp":1775038161000},"page":"1055","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Accuracy and Reproducibility of Digital Area and Depth Measurements of Surface Wounds: Benchtop and Clinical Validation"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3022-1157","authenticated-orcid":false,"given":"Ron","family":"Linden","sequence":"first","affiliation":[{"name":"Judy Dan Research and Treatment Centre, Toronto, ON M2R 1N5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Perry V.","family":"Mayer","sequence":"additional","affiliation":[{"name":"The Mayer Institute, Hamilton, ON L8R 2R3, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rose","family":"Raizman","sequence":"additional","affiliation":[{"name":"Scarborough Health Network, Toronto, ON M1E 4B9, Canada"},{"name":"Lawrence S. Bloomberg Facility of Nursing, University of Toronto, Toronto, ON M5T 1P8, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanna","family":"Varonina","sequence":"additional","affiliation":[{"name":"MolecuLight Inc., Toronto, ON M5G 1T6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6693-2095","authenticated-orcid":false,"given":"Laura M.","family":"Jones-Donaldson","sequence":"additional","affiliation":[{"name":"MolecuLight Inc., Toronto, ON M5G 1T6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danielle","family":"Dunham","sequence":"additional","affiliation":[{"name":"MolecuLight Inc., Toronto, ON M5G 1T6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1089\/wound.2021.0026","article-title":"Human Wound and Its Burden: Updated 2020 Compendium of Estimates","volume":"10","author":"Sen","year":"2021","journal-title":"Adv. Wound Care"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1089\/wound.2023.0150","article-title":"Human Wound and Its Burden: Updated 2022 Compendium of Estimates","volume":"12","author":"Sen","year":"2023","journal-title":"Adv. Wound Care"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s10916-025-02153-8","article-title":"Artificial Intelligence Methods for Diagnostic and Decision-Making Assistance in Chronic Wounds: A Systematic Review","volume":"49","year":"2025","journal-title":"J. Med. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"194","DOI":"10.3390\/ebj2040015","article-title":"Imaging Techniques Used for Wound Healing Assessment: A Systematic Review Part 1 Chronic Wounds","volume":"2","author":"Tan","year":"2021","journal-title":"Eur. 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