{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T17:39:49Z","timestamp":1784223589898,"version":"3.55.0"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Ministry of Higher Education, Science and Innovation, Republic of Slovenia","award":["P3-0293"],"award-info":[{"award-number":["P3-0293"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Clin Oral Invest"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Conventional plaque assessment methods, such as clinical indices and planimetry, rely on plaque-disclosing agents and may overemphasize thin biofilm areas due to plaque thickness variations. This study introduces a digital 3D method to quantify and visualize dental plaque volume from consecutive intraoral scans (IOS) and compares it with the Turesky Modification of the Quigley-Hein Plaque Index (TMQHPlI) and planimetry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>After professional supragingival debridement at baseline (T0), fifteen participants refrained from oral hygiene for four days (T4). De novo plaque formation was assessed at T4 using TMQHPlI after application of a two-tone (pink\/purple) plaque-disclosing agent. IOSs (3Shape TRIOS 4) were obtained at T0 and T4. Plaque accumulation was quantified using color-coded IOS comparisons with the Volumetric Plaque Index (VPI) and Adjusted VPI (AVPI). Machine learning (Trainable Weka Segmentation) was used to calculate the Planimetric Plaque Index (PPI).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A correlation between plaque surface area and volume was observed only for purple\/mature plaque (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.043). Early plaque growth was dominated by expansion of pink-stained, newly formed plaque. Once more than one-third of the surface was covered, further increases resulted mainly from vertical thickening rather than lateral spread.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>3D volumetric analysis offers a comprehensive, objective, and clinician-friendly method for assessing dental biofilms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical relevance<\/jats:title>\n                    <jats:p>The proposed 3D approach enables accurate monitoring of plaque accumulation and maturation, improving personalized oral hygiene assessment, patient education, and clinical decision-making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00784-025-06729-z","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T02:20:19Z","timestamp":1767579619000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Mapping dental biofilms: from plaque index through planimetry to volumetric analysis"],"prefix":"10.1007","volume":"30","author":[{"given":"Katja","family":"Pov\u0161i\u010d","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luka","family":"Fijav\u017e","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haris","family":"Munjakovi\u0107","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrian","family":"Ka\u0161aj","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rok","family":"Ga\u0161per\u0161i\u010d","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"key":"6729_CR1","doi-asserted-by":"publisher","unstructured":"Munjakovi\u0107 H, Pov\u0161i\u010d K, Poljak M, Seme K, Ga\u0161per\u0161i\u010d R, Skubic L (2025) Digital PCR outperforms quantitative real-time PCR for the detection and quantification of major periodontal pathobionts. 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