Ali Islam E, Hattori Mariko, Sumita Yuka, Wakabayashi Noriyuki
Department of Advanced Prosthodontics, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan.
Department of Prosthodontics, Faculty of Dentistry, Mansoura University, Mansoura, Egypt.
J Prosthodont. 2025 Jun;34(5):490-499. doi: 10.1111/jopr.13994. Epub 2025 Jan 4.
This study aims to evaluate the effectiveness of a case-based reasoning (CBR) system in predicting the design of definitive obturator prostheses for maxillectomy patients.
Data from 209 maxillectomy cases, including extraoral images of obturator prostheses and occlusal images of maxillectomy defects, were collected from Institute of Science Tokyo Hospital. These cases were organized into a structured database using Python's pandas library. The CBR system was designed to match new cases with similar historical cases based on specific attributes such as aramany class, abutment details, defect extension, and oronasal connection size. The system's performance was evaluated by clinicians who assessed the accuracy of prosthesis designs generated for 33 test cases.
A correlation analysis demonstrated a significant positive relationship (ρ = 0.84, p < 0.0001) between the CBR system's confidence scores and the number of correct prosthesis designs identified by clinicians. The median precision at five cases was 0.8, indicating that the system effectively retrieved relevant designs for new cases.
The study shows that the developed CBR system effectively predicts the design of obturator prostheses for maxillectomy patients. Clinically, the system is expected to reduce clinician workload, simplify the design process, and enhance patient engagement by providing prompt insights into their final prosthetic design.
本研究旨在评估基于案例推理（CBR）系统在预测上颌骨切除患者定制闭塞器假体设计方面的有效性。
从东京科学大学医院收集了209例上颌骨切除病例的数据，包括闭塞器假体的口外图像和上颌骨切除缺损的咬合图像。使用Python的pandas库将这些病例整理成一个结构化数据库。CBR系统旨在根据特定属性（如阿拉曼尼分类、基牙细节、缺损范围和口鼻连接大小）将新病例与相似的历史病例进行匹配。临床医生对为33个测试病例生成的假体设计的准确性进行评估，以此来评价该系统的性能。
相关性分析表明，CBR系统的置信度得分与临床医生确定的正确假体设计数量之间存在显著正相关（ρ = 0.84，p < 0.0001）。五个病例时的中位精度为0.8，表明该系统有效地为新病例检索到了相关设计。
该研究表明，所开发的CBR系统能够有效地预测上颌骨切除患者的闭塞器假体设计。在临床上，该系统有望减轻临床医生的工作量，简化设计过程，并通过迅速提供有关最终假体设计的见解来提高患者的参与度。
