{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T18:52:51Z","timestamp":1773773571013,"version":"3.50.1"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T00:00:00Z","timestamp":1762128000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Previous cross-sectional studies suggest nonlinear facial skeletal aging patterns, but longitudinal evidence quantifying acceleration of change is lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>The aim of the authors of this study is to quantify acceleration in facial skeletal aging by analyzing 3-dimensional computed tomography (CT) scans at 3 time points over \u223c2 decades.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Twenty-one patients (11 males, 10 females) underwent standardized CT imaging at 3 time points: T1 (mean age 45.5\u2005years), T2 (mean age 56.3\u2005years), and T3 (mean age 65.4\u2005years). Twenty-one anthropometric measurements across 4 facial regions were obtained. Acceleration was calculated as the difference in rate of change between T1 \u2192 T2 and T2 \u2192 T3 intervals. Mixed-effects models tested for significant acceleration with \u03b1 = .05.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The authors reported that 8 of the 21 parameters (38.1%) demonstrated statistically significant acceleration (P &amp;lt; .05). Orbital aperture area showed the greatest acceleration (10.65\u2005mm2\/year2, P &amp;lt; .001), followed by mandibular angle (0.64\u00b0\/year2, P = .008). Ramus height demonstrated significant negative acceleration (\u22120.33\u2005mm\/year2, P &amp;lt; .001), shifting from minimal change to rapid decline. Sex-specific patterns emerged: males showed greater orbital aperture expansion (+177.0\u2005mm\u00b2 vs +119.5\u2005mm\u00b2 from T2 \u2192 T3), whereas females demonstrated greater ramus height decline (\u22124.6\u2005mm vs \u22122.8\u2005mm). The pyriform angle showed subtle biphasic reversal (0.23\u00b0\/year2, P = .018).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Facial skeletal aging accelerates nonlinearly, with region-specific patterns emerging after the sixth decade. These findings challenge linear aging assumptions and provide quantitative evidence for optimizing the timing of facial rejuvenation interventions. The identification of acceleration phases enables predictive rather than reactive approaches to facial aging management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Level of Evidence: 4 (Therapeutic)<\/jats:title>\n                    <jats:p\/>\n                  <\/jats:sec>","DOI":"10.1093\/asj\/sjaf221","type":"journal-article","created":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T13:09:32Z","timestamp":1761916172000},"page":"415-427","source":"Crossref","is-referenced-by-count":0,"title":["Twenty Years of Facial Skeletal Aging: Regional Rate Changes Through Longitudinal 3-Dimensional Computed Tomography Analysis"],"prefix":"10.1093","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6227-8740","authenticated-orcid":false,"given":"Melih 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