Automated orofacial virtual patient creation using two cohorts of MSCT vs. CBCT scans.

IF 2.4 2区医学 Q2 DENTISTRY, ORAL SURGERY & MEDICINE

Head & Face Medicine Pub Date : 2025-03-28 DOI:10.1186/s13005-025-00500-1

Thanatchaporn Jindanil, Oana-Elena Burlacu-Vatamanu, Benedetta Baldini, Joeri Meyns, Jeroen Meewis, Rocharles Cavalcante Fontenele, Maria Cadenas de Llano Perula, Reinhilde Jacobs

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引用次数: 0

Abstract

Background: Virtual simulation has advanced in dental healthcare, but the impact of different tomographic techniques on virtual patient (VP) creation remains unclear. This study primarily aimed to automatically create VP from facial scans (FS), intraoral scans (IOS), multislice (MSCT), and cone beam computed tomography (CBCT); Secondarily, to quantitatively compare artificial intelligence (AI)-driven, AI-refined and semi automatically registered (SAR) VP creation from MSCT and CBCT and to compare the effect of soft tissue on the registration with MSCT and CBCT.

Methods: A dataset of 20 FS, IOS, and (MS/CB)CT scans was imported into the Virtual Patient Creator platform to generate automated VPs. The accuracy (percentage of corrections required), consistency, and time efficiency of the AI-driven VP registration were then compared to those of the AI-refined and SAR (clinical reference) using Mimics software. The surface distance between the registered FS and the (MS/CB)CT surface rendering using SAR and AI-driven methods was measured to assess the effect of soft tissue on registration.

Results: All three registration methods achieved 100% accuracy for VP creation with both MSCT and CBCT (p > 0.999), with no significant differences between tomographic techniques either (p > 0.999). Perfect consistency (1.00) was obtained with AI-driven and AI-refined methods, and slightly lower for SAR (0.977 for MSCT and 0.895 for CBCT). Average registration times were 24.9 and 28.5 s for AI-driven and AI-refined, and 242.3 and 275.7 s for SAR with MSCT and CBCT respectively. The total time was significantly shorter for MSCT (313.7 s) compared to CBCT (850.3 s) (p < 0.001). While the average surface distance between MSCT- and CBCT-based VP showed no significant difference (p > 0.05), AI-driven resulted in a smaller surface distance than SAR (p < 0.05).

Conclusions: AI enables fast, accurate, and consistent VP creation using FS, IOS, and (MS/CB)CT data. AI-driven, AI-refined, and semi-automated methods all achieve good accuracy. Additionally, soft tissue registration shows no significant difference between MSCT and CBCT.

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使用MSCT和CBCT扫描的两个队列自动创建口面部虚拟患者。

背景：虚拟模拟在牙科保健方面取得了进展，但不同的断层成像技术对虚拟患者（VP）创建的影响尚不清楚。本研究主要旨在通过面部扫描（FS）、口内扫描（IOS）、多层扫描（MSCT）和锥形束计算机断层扫描（CBCT）自动创建VP；其次，定量比较人工智能（AI）驱动、人工智能优化和半自动注册（SAR） VP在MSCT和CBCT上的创建，并比较软组织对MSCT和CBCT注册的影响。方法：将20个FS、IOS和（MS/CB）CT扫描数据集导入Virtual Patient Creator平台以生成自动vp。然后使用Mimics软件将人工智能驱动的VP注册的准确性（所需更正的百分比），一致性和时间效率与人工智能精炼和SAR（临床参考）的注册进行比较。利用SAR和ai驱动的方法测量注册的FS和（MS/CB）CT表面绘制之间的表面距离，以评估软组织对配准的影响。结果：所有三种配准方法在MSCT和CBCT上的VP创建准确率均达到100% (p > 0.999)，层析技术之间也没有显著差异（p > 0.999）。人工智能驱动和人工智能改进的方法获得了完美的一致性（1.00），SAR略低（MSCT为0.977，CBCT为0.895）。人工智能驱动和人工智能精炼的平均配准时间分别为24.9和28.5 s， MSCT和CBCT SAR的平均配准时间分别为242.3和275.7 s。与CBCT （850.3 s）相比，MSCT的总时间（313.7 s）显著缩短（p < 0.05），人工智能驱动的表面距离比SAR小（p < 0.05）。结论：人工智能可以使用FS、IOS和（MS/CB）CT数据快速、准确和一致地创建VP。人工智能驱动、人工智能精炼和半自动化的方法都达到了很好的准确性。此外，MSCT和CBCT的软组织定位没有明显差异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Head & Face Medicine DENTISTRY, ORAL SURGERY & MEDICINE-

CiteScore

4.70

自引率

3.30%

发文量

审稿时长

>12 weeks

期刊介绍： Head & Face Medicine is a multidisciplinary open access journal that publishes basic and clinical research concerning all aspects of cranial, facial and oral conditions. The journal covers all aspects of cranial, facial and oral diseases and their management. It has been designed as a multidisciplinary journal for clinicians and researchers involved in the diagnostic and therapeutic aspects of diseases which affect the human head and face. The journal is wide-ranging, covering the development, aetiology, epidemiology and therapy of head and face diseases to the basic science that underlies these diseases. Management of head and face diseases includes all aspects of surgical and non-surgical treatments including psychopharmacological therapies.