Surgeons need to understand the effects of the nasal cartilage on facial morphology, the function of both soft tissues and hard tissues and nasal function when performing nasal surgery. In nasal cartilage-related surgery, the main goals for clinical research should include clarification of surgical goals, rationalization of surgical methods, precision and personalization of surgical design and preparation and improved convenience of doctor-patient communication. Computational technology has become an effective way to achieve these goals. Advances in three-dimensional (3D) imaging technology will promote nasal cartilage-related applications, including research on computational modelling technology, computational simulation technology, virtual surgery planning and 3D printing technology. These technologies are destined to revolutionize nasal surgery further. In this review, we summarize the advantages, latest findings and application progress of various computational technologies used in clinical nasal cartilage-related work and research. The application prospects of each technique are also discussed.
Computer Simulation ; Face ; Humans ; Models, Anatomic ; Nasal Cartilages ; Nasal Septum ; surgery ; Nose ; surgery ; Printing, Three-Dimensional ; Rhinoplasty ; trends

Objective This study aims to test the reliability and validity of the Chinese version of the Asher-McDade aesthetic index and clarify its feasibility for the postoperative outcome evaluation of cleft lip in China.Methods The Chinese version of the Asher-McDade aesthetic index was established through translation,back translation,debugging,and pre-survey.Eighty postoperative photographs of patients with cleft lip admitted to the West China Hospital of Stoma-tology,Sichuan University were included.Ten healthcare professionals,including surgeons,nurses,and students,in the department of cleft lip and palate surgery finished the index to test its reliability and validity.Results The Cronbach's alpha coefficient and retest reliability of this index are 0.804 and 0.895,respectively.The item-level content validity in-dex(I-CVI)and scale-level content validity index ave-rage(S-CVI/ave)of the index are 1.000 and 0.95,respec-tively.For this index,the Kaiser-Meyer-Olkin(KMO)test score is 0.706,the χ2 value of Bartlett's test for the consistency of the index is 962.260(P<0.01),and the cu-mulative variance contribution rate is 63.095%.Conclu-sion The Chinese version of the Asher-McDade aesthe-tic index has good reliability and validity and is applica-ble to the professional evaluation of the effect of postoperative photographs in Chinese patients with cleft lip.

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact various fields. This paper mainly discusses the future applications of LLMs in dentistry. We introduce two primary LLM deployment methods in dentistry, including automated dental diagnosis and cross-modal dental diagnosis, and examine their potential applications. Especially, equipped with a cross-modal encoder, a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations. We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application. While LLMs offer significant potential benefits, the challenges, such as data privacy, data quality, and model bias, need further study. Overall, LLMs have the potential to revolutionize dental diagnosis and treatment, which indicates a promising avenue for clinical application and research in dentistry.
Dentistry ; Artificial Intelligence