Facial anthropometry has profound importance in clinical diagnosis and the recognition of abnormal facial features. With the development of anthropometry, facial anthropometry has emerged as an independent research field and is widely applied in disciplines such as plastic surgery and cranio-maxillofacial surgery. This paper reviews the evolution of facial anthropometry and discusses its future trends in the context of artificial intelligence (AI). Currently, 3D facial imaging technology can accurately capture and reconstruct the three-dimensional morphology of facial soft tissues, and enhance the precision and objectivity of measurements, thus becoming the new "gold standard" for facial anthropometry. It not only provides reference for disease diagnosis and surgical planning but also plays a crucial role in evaluating cosmetic outcomes and aging research. In recent years, AI technology has developed rapidly, enabling direct recognition of abnormal facial features. Although facial recognition systems based on two-dimensional images are relatively mature, they have to struggle to fully capture facial features as they are limited by the dimensionality of information. While three-dimensional image-based recognition boasts high accuracy, it faces challenges in the recognition and classification of abnormal facial features due to limitations in the number of training samples. The integration of AI and facial anthropometry has effectively promoted automatic recognition technology for facial landmarks, thus providing more precise and interpretable methods for assessing disease-related facial features. Future research should focus on building reliable three-dimensional facial databases to further improve the accuracy of facial recognition. Additionally, developing facial recognition systems based on small sample sizes is necessary to provide robust support for the recognition of facial features associated with rare and special diseases.

Objective:To observe the effect of a new modified double-eyelid operation.Methods:From February 2018 to January 2021, modified tarsal plate-orbicularis oculi muscle-orbital septum (TMS) suture was performed in 193 double-eyelid operation in the plastic surgery department of Peking Union Medical College Hospital, including 14 males and 179 females. The patients aged from 18 to 45 years with an average of (22.3±4.2) years. The patients were followed up for 6-24 months to observe the morphology of the double eyelid fold and complications.Results:The 193 patients were included. The double eyelid lines of 173 patients were smooth, natural, durable and the scar was shallow; both doctors and patients were satisfied. There were no obvious complications after the operation. The double eyelid line became shallow or disappeared in 11 patients, and the double eyelid asymmetry occurred in 7 patients after the operation. However, the folds were symmetrical and natural after secondary operation, and both doctors and patients were satisfied.Conclusions:TMS suture not only establishes a firm adhesion, but also effectively transmits the force of the levator aponeurosis with significant advantages. After the operation, the double eyelid line is smooth, natural and stable. Both doctors and patients are highly satisfied. It is an improved double eyelid procedure worthy of clinical promotion.

Facial anthropometry has profound importance in clinical diagnosis and the recognition of abnormal facial features. With the development of anthropometry, facial anthropometry has emerged as an independent research field and is widely applied in disciplines such as plastic surgery and cranio-maxillofacial surgery. This paper reviews the evolution of facial anthropometry and discusses its future trends in the context of artificial intelligence (AI). Currently, 3D facial imaging technology can accurately capture and reconstruct the three-dimensional morphology of facial soft tissues, and enhance the precision and objectivity of measurements, thus becoming the new "gold standard" for facial anthropometry. It not only provides reference for disease diagnosis and surgical planning but also plays a crucial role in evaluating cosmetic outcomes and aging research. In recent years, AI technology has developed rapidly, enabling direct recognition of abnormal facial features. Although facial recognition systems based on two-dimensional images are relatively mature, they have to struggle to fully capture facial features as they are limited by the dimensionality of information. While three-dimensional image-based recognition boasts high accuracy, it faces challenges in the recognition and classification of abnormal facial features due to limitations in the number of training samples. The integration of AI and facial anthropometry has effectively promoted automatic recognition technology for facial landmarks, thus providing more precise and interpretable methods for assessing disease-related facial features. Future research should focus on building reliable three-dimensional facial databases to further improve the accuracy of facial recognition. Additionally, developing facial recognition systems based on small sample sizes is necessary to provide robust support for the recognition of facial features associated with rare and special diseases.

Objective:To construct a whole course management and follow-up platform, named Care Plan, for patients undergoing breast reconstruction surgery, and to evaluate its initial clinical applications.Methods:From June 2023 to January 2024, patients who underwent breast reconstruction surgery at Peking Union Medical College Hospital were selected as the study subjects and enrolled in the Care Plan platform for whole course management. The platform comprised five modules: patient education, self-assessment, medical assessment, medical follow-up, and doctor-patient dialogue, each with corresponding sub-modules and specific components. Each patient was assigned to a case manager who provided one-on-one assessment, sent patient education materials, and conducted follow-ups. The preliminary application of the Care Plan platform was evaluated based on the completeness of patient data, patient education material reading status, doctor-patient dialogue topics, and follow-up responses. At 3 months postoperatively, patients were followed up and further divided into patient education group(reading at least an article on patient educational materials) and control group based on their reading status of educational materials. Patients rated their satisfaction with the surgery using a 5-point questionnaire, including five indicators: expected breast reconstruction outcome, expected surgical type, completeness of information acquisition, breast symmetry, and breast softness. Statistical analysis was performed using SPSS 27.0.1 software, with count data expressed as frequencies and (or) percentages, normally distributed measurement data expressed as Mean±SD, intergroup comparisons conducted using t-test, and P<0.05 indicating statistical significance. Results:A total of 147 female patients aged 16 to 63 years with a body mass index of 16.6 to 31.3 kg/m 2 were ultimately included. All 147 patients completed the content of the self-assessment and medical assessment modules, with relatively complete data. Of the 133 patients who received patient education materials sent through the platform, 38 (28.6%) read the materials, with the sub-module on the introduction and choices of the reconstruction surgery (37.3%, 94/252 ) being the most frequently viewed. A total of 24 patients (16.3%, 24/147 ) raised 45 questions using the doctor-patient dialogue module, with the highest proportion related to consultation issues and complications, each accounting for 22.2% (10/45). Twenty-three patients completed the 3-month follow-up, with 12 in the patient education group and 11 in the control group. The patient education group scored higher than the control group in terms of completeness of information acquisition [(4.58±0.51) points vs. (3.91±0.70) points, t=-2.65, P=0.015], while scoring lower in breast symmetry [(3.92±0.79) points vs. (4.63±0.67) points, t=2.33, P=0.030]. There was no significant difference between the two groups in terms of expected breast reconstruction outcome, expected surgical type, and breast softness scores ( P>0.05 for all). Conclusion:The Care Plan platform for whole course management and follow-up of breast reconstruction can assist medical staff in formulating patient-centered management plans, improve patients’ understanding of surgical information, and aid patients in making decisions regarding breast reconstruction methods.

Objective:To construct a whole course management and follow-up platform, named Care Plan, for patients undergoing breast reconstruction surgery, and to evaluate its initial clinical applications.Methods:From June 2023 to January 2024, patients who underwent breast reconstruction surgery at Peking Union Medical College Hospital were selected as the study subjects and enrolled in the Care Plan platform for whole course management. The platform comprised five modules: patient education, self-assessment, medical assessment, medical follow-up, and doctor-patient dialogue, each with corresponding sub-modules and specific components. Each patient was assigned to a case manager who provided one-on-one assessment, sent patient education materials, and conducted follow-ups. The preliminary application of the Care Plan platform was evaluated based on the completeness of patient data, patient education material reading status, doctor-patient dialogue topics, and follow-up responses. At 3 months postoperatively, patients were followed up and further divided into patient education group(reading at least an article on patient educational materials) and control group based on their reading status of educational materials. Patients rated their satisfaction with the surgery using a 5-point questionnaire, including five indicators: expected breast reconstruction outcome, expected surgical type, completeness of information acquisition, breast symmetry, and breast softness. Statistical analysis was performed using SPSS 27.0.1 software, with count data expressed as frequencies and (or) percentages, normally distributed measurement data expressed as Mean±SD, intergroup comparisons conducted using t-test, and P<0.05 indicating statistical significance. Results:A total of 147 female patients aged 16 to 63 years with a body mass index of 16.6 to 31.3 kg/m 2 were ultimately included. All 147 patients completed the content of the self-assessment and medical assessment modules, with relatively complete data. Of the 133 patients who received patient education materials sent through the platform, 38 (28.6%) read the materials, with the sub-module on the introduction and choices of the reconstruction surgery (37.3%, 94/252 ) being the most frequently viewed. A total of 24 patients (16.3%, 24/147 ) raised 45 questions using the doctor-patient dialogue module, with the highest proportion related to consultation issues and complications, each accounting for 22.2% (10/45). Twenty-three patients completed the 3-month follow-up, with 12 in the patient education group and 11 in the control group. The patient education group scored higher than the control group in terms of completeness of information acquisition [(4.58±0.51) points vs. (3.91±0.70) points, t=-2.65, P=0.015], while scoring lower in breast symmetry [(3.92±0.79) points vs. (4.63±0.67) points, t=2.33, P=0.030]. There was no significant difference between the two groups in terms of expected breast reconstruction outcome, expected surgical type, and breast softness scores ( P>0.05 for all). Conclusion:The Care Plan platform for whole course management and follow-up of breast reconstruction can assist medical staff in formulating patient-centered management plans, improve patients’ understanding of surgical information, and aid patients in making decisions regarding breast reconstruction methods.