{"doi":"10.1002/jper.23-0370","title":"Ultrasound‐based jawbone surface quality evaluation after alveolar ridge preservation","abstract":"BACKGROUND: Bone readiness for implant placement is typically evaluated by bone quality/density on 2-dimensional radiographs and cone beam computed tomography at an arbitrary time between 3 and 6 months after tooth extraction and alveolar ridge preservation (ARP). The aim of this study is to investigate if high-frequency ultrasound (US) can classify bone readiness in humans, using micro-CT as a reference standard to obtain bone mineral density (BMD) and bone volume fraction (BVTV) of healed sockets receiving ARP in humans. METHODS: A total of 27 bone cores were harvested during the implant surgery from 24 patients who received prior extraction with ARP. US images were taken immediately before the implant surgery at a site co-registered with the tissue biopsy collection location, made possible with a specially designed guide, and then classified into 3 tiers using B-mode image criteria (1) favorable, (2) questionable, and (3) unfavorable. Bone mineral density (hydroxyapatite) and BVTV were obtained from micro-CT as the gold standard. RESULTS: ). The present US B-mode classification inversely scales with BMD. Regression analysis showed a significant relation between US classification and BMD as well as BVTV. T-test analysis demonstrated a significant correlation between US reader scores and the gold standard. When comparing Tier 1 with the combination of Tier 2 and 3, US achieved a significant group differentiation relative to mean BMD (p = 0.004, true positive 66.7%, false positive 0%, true negative 100%, false negative 33.3%, specificity 100%, sensitivity 66.7%, receiver operating characteristics area under the curve 0.86). Similar results were found between US-derived tiers and BVTV. CONCLUSION: Preliminary data suggest US could classify jawbone surface quality that correlates with BMD/BVTV and serve as the basis for future development of US-based socket healing evaluation after ARP.","journal":"Journal of Periodontology","year":2024,"id":476776,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9603,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":366611,"name":"Oliver D. Kripfgans","orcid":"0000-0003-2905-1496","position":1,"is_corresponding":false},{"id":361207,"name":"Kenneth M. Kozloff","orcid":"0000-0002-1108-7258","position":2,"is_corresponding":false},{"id":1029433,"name":"Ankita Samal","orcid":"0000-0001-9304-9724","position":3,"is_corresponding":false},{"id":1084555,"name":"Jae‐Man Woo","orcid":"0000-0001-7209-186X","position":4,"is_corresponding":false},{"id":692593,"name":"Mostafa Shehabeldin","orcid":"0000-0002-2122-4105","position":5,"is_corresponding":false},{"id":644790,"name":"Hsun‐Liang Chan","orcid":"0000-0001-5952-0447","position":6,"is_corresponding":false},{"id":1029432,"name":"Amanda Rodriguez Betancourt","orcid":"0000-0001-6011-6708","position":0,"is_corresponding":true}],"reference_count":62,"raw_metadata":null,"created_at":"2026-07-19T02:06:29.605760Z","pmid":"38742564","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}