臨床上在進行All-on-4®全口速訂植牙前，會針對患者的口腔狀況進行完整的植牙方案評估，其中就包含咬合平面位置的制定，而咬合平面的決定在整個流程中尤為重要，因為其直接影響到患者的面部美觀、牙齒排列與咀嚼系統的生物力學性能。在文獻回顧中，常見的咬合平面定義方式為Camper’s line主要是透過連線鼻翼下緣與耳珠上緣、中緣、下緣完成咬合平面的定義，然而Camper’s line作為最廣泛運用咬合平面定義方式，但卻容易受到顱面解剖位置或是軟組織差異的影響，而無法確定參考點的正確性。在進行全口速定植牙的電腦輔助設計時，需要導入患者口腔之數位醫學影像檔案，但在影像檔案中經常不包含建構咬合平面所需的軟組織特徵，因此本研究之目的是開發基於顱顏面硬組織的咬合平面定義方法。
納入30位患者作為研究數據，並將30位患者依照下顎缺牙程度與下顎角度進行分類，患者的數位影像檔案會經過立體化處裡並於於顱顏面硬組織中標記12個特徵點，分別是GO 1 (Gonion)、GO 2 (Gonion)、ME (Menton)、ANS (Anterior Nasal Spine)、PNS (Posterior Nasal Spine)、PNS 1、PNS 2、SM (Supramental), SS (Subspinale), OCC 1, OCC 2, OCC 3，OCC 2與OCC 3為下顎左右兩側第二臼齒頰側遠心端尖點，OCC 1為下顎門牙切齒，這些特徵點形成對應的點、線、面，並生成出ATC軸與P&P軸，以下顎基準平面繞ATC軸與P&P軸得出ATC平面與P&P平面，利用平面法向量的方式比較以上兩個平面與患者自然咬合平面角度差異值，以導航角的方式分解平面法向量，將法向量拆解成翻滾角及俯仰角，藉此觀察造成差異的旋轉方向，同時導入統計學的概念，以成對樣本T檢定的方式分析出平面之間的顯著性，評估兩種咬合平面是否與自然咬合平面存在顯著差異，最後利用有限元素分析驗證平面之間的差異對於力學性能上的影響。
平面角度差值的結果落在平均4.50°至4.60°，最小誤差值為0.95°，最大誤差值不超過10.0°，導航角的拆分不呈現了在各個角度之間的差異，明顯的看出造成差異較大的方向，也因為法向量的拆分有助於統計學進一步的分析，統計學在多數組別中皆顯示無顯著差異，部分組別因樣本數據不平均的問題造成統計學結果出現顯差異，而有限元素分析的結果證明了P&P平面與自然咬合平面在6.06°的角度差異值情況下，力學性能的表現幾乎相同，僅左側遠心端的皮質骨周圍出現略大於自然咬合平面9.4%的應力表現。
本研究使用不同的分析方式驗證兩種平面與自然咬合平面的差異，結果顯示在不同的分析方式中與自然咬合平面都有相近的效果，這表示本研究之方法針對不同的分類對象時皆表現出良好的泛用性，但此方法在建立每位患者對應的咬合平面時仍存在構造、前處理、模型製作等問題，此些問題衍伸出患者顱顏面構造、模型前處理、Inter & Intra差異、有限元素模型以及應用範圍上的挑戰與限制，尤其在應用範圍的部分，雖然對於完整有牙、部分缺牙及嚴重缺牙的患者皆評估出了良好的結果，但是對於全口無牙的患者仍然缺乏足夠的數據證明本研究之方法的可行性，因此未來需要納入更多元的患者進行相關的研究。
本研究提供臨床一全新的咬合平面定義方式，咬合平面的制定不需要倚靠任何輔助儀器，僅須透過簡單的提取特徵點及計算即可完成制定，此方法提供不完整之數位醫學影像建立出對應的咬合平面，更是首次以力學的角度評估咬合平面差異在All-on-4®治療方案下，對下顎骨植體周圍的應力影響。

The study aimed to develop a method for defining the occlusal plane in All-on-4® full-mouth reconstructions using digital medical images and focusing on hard tissue features of the craniofacial region. Traditional methods like Camper's line were noted for their susceptibility to soft tissue and craniofacial anatomical variations. Instead, the study proposed using specific hard tissue landmarks such as Gonion, Menton, Anterior Nasal Spine, and Supramental points to establish the occlusal plane. Thirty patients were categorized based on mandibular edentulism and angle, with their digital images stereotaxically processed and labeled for 12 craniofacial features.
The study generated occlusal planes (ATC and P&P) from these images and compared them to each patient’s natural occlusal plane using statistical methods and finite element analysis. Statistical analysis, primarily paired T-tests, generally indicated insignificant differences between the proposed planes and the natural occlusal plane, suggesting their similarity. Finite element analysis further supported this finding by demonstrating comparable mechanical performance between the P&P plane and the natural occlusal plane, with minor variations in stress distribution.
The research highlights the potential of using digital imaging and hard tissue characteristics to accurately define occlusal planes without additional devices, though it acknowledges challenges in patient-specific craniofacial modeling, particularly in fully edentulous cases. Further studies are recommended to validate and refine this method across broader patient populations.

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