在下重建中3D分析金策略:随机控制试点研究
Tanya Chen1, Harley H L Chan2, John de Almeida1
1Department of Otolaryngology - Head & Neck Surgery/Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
The Laryngoscope
|November 14, 2023
概括
与传统方法相比,计算机辅助下巴涂层显著提高了板材轮准确度. 这种技术增强了板与骨接触,减少了距离,优化了重建性手术的结果.
科学领域:
- 口腔和牙面部外科手术
- 生物医学工程 生物医学工程
- 医疗成像医学成像
背景情况:
- reconstruction 在实现精确的板适配方面提出了挑战.
- 传统的涂层依赖于手术内自由手曲,这可能导致不准确.
- 3D建模的进步为改善外科手术规划和执行提供了潜力.
研究的目的:
- 量化比较计算机辅助 (3D模型) 下巴贴与传统自由手曲的精度.
- 评估尺度,如板表面接触,板到骨的距离,以及合规性.
- 评估对操作时间和状头部定位的影响.
主要方法:
- 随机对照试验涉及20名接受下重建的患者.
- 在手术前的3D模型辅助板曲和手术后的自由手曲之间的比较.
- 术前和术后CT扫描的定量分析,以评估板适合和位置.
主要成果:
- 三维 (3D) 模型辅助涂层显示,表面接触的百分比明显改善 (93.9%对比78.0%,p=0.04).
- 在3D模型 (0.7mm与1.3mm相比,p=0.06) 中观察到改善板到骨距离的趋势.
- 在手术时间,状头部位置或术后并发症方面没有发现显著差异.
结论:
- 计算机辅助下巴板增强了板轮的准确性.
- 这种技术在下手术中为重建性板块提供了更精确的适应.
- 3D建模是优化下重建结果的宝贵工具.
相关概念视频
Group Design
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...
Random Sampling Method
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
Randomized Experiments
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs
Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
Methods of Medium Optimization
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...


