Objective: To observe the safety and efficiency of face-lift combined with fat grafting in facial rejuvenation. Methods: We performed a retrospective study, which included 23 patients. SMAS suspension and multi-site suspension were combined to correct the nasolabial fold, mid-cheek aging and malar mounds. Structural fat grafting was performed to treat the volume loss in mid-face. Results: All patients demonstrated a significant improvement in midfacial appearance. No infection or nerve injury were found in this study. Only three patients did not get primary healing in temple region, which led to temporal hair loss from secondary healing. Conclusions This study demonstrates that fat grafting and multiple layers face-lift are efficient method for facial rejuvenation. These approaches appear to be very promising for facial anti-aging techniques.

Objective: To observe the outcome of breast reconstruction with autologous fat grafting in the patients following treatment for breast cancer. Methods: The clinical data of 22 patients after breast cancer modified radical mastectomy with fat grafting for breast reconstruction from January 2012 to March 2015 at Department of Body Contouring and Liposuction Center of Plastic Surgery, Hospital of Peking Union Medical College were analyzed retrospectively. The age of 22 patients (all female) was 28 to 54 years. Fifteen patients were performed breast modified radical mastectomy 5 to 16 year ago without radiotherapy, 7 patients were performed breast modified radical mastectomy following regular radiotherapy 2 years ago. Low negative pressure liposuction technical was applied to harvest fat tissue for 400 to 800 ml which was filtrated and purified by cotton pad method in low temperature environment. Fat grafting was performed with multi-level and multi-tunnel and in multi-point injection ways. All patients were followed up by regular imaging evaluation with MRI or ultrasonography after operation every 3 months. Results: All breast reconstruction were successfully performed in 22 patients, no severe complications occurred. Among 15 patients without radiotherapy, 12 patients were performed with autologous fat grafting for breast reconstruction, 3 patients with prosthetic implantation for breast augmentation after autologous fat grafting. Among 7 patients with radiotherapy, 6 patients were performed with autologous fat grafting for breast reconstruction, 1 patient with prosthetic implantation for breast augmentation after autologous fat grafting. The volume of fat grafting was 104 to 380 ml. It took 2.5 hours to finish the operation including 1.0 to 1.5 hours for liposuction and 40 minutes for fat grafting. Next fat grafting were performed after 3 months. The fat of the breast were survived well detecting by MRI, only 1 patient had a cystic nodule which had been resected during nipple reconstruction. Ultrasonography screened several cystic nodules with the major axis of 0.1 to 0.2 cm in the breast, which couldn′t be found by palpating in 18 patients. The patients were followed up for 18 to 36 months, the outcome were satisfactory. Conclusion Autologous fat grafting for breast reconstruction simplifies the operation program with satisfied results and avoids the complications of breast reconstruction with skin flap.

Objective:To report our clinical experience in simultaneous implant exchange with fat (SIEF) for breast augmentation and reshaping.Methods:The medical records of 26 patients who received SIEF in our department from January 2013 to June 2019 were reviewed. All patients were female, aged (35.2±8.3) years. The prosthesis was removed through axillary approach, inframammary approach or radial incision at the junction of lateral breast and chest wall. Capsulectomy was not performed after implant removal. Fat was harvested using a blunt liposuction cannulas with the diameter of 2.5 mm and 3 side holes, with a negative pressure of -60 kPa. After washing with 4 degree physiological saline, the fat was processed with the cotton pad filtering technique, then a diameter 2.5 mm, 1-hole blunt cannula was used to place the fat. The evaluation of postoperative improvements included breast size, incidence of complications. Patient satisfaction and physician satisfaction were assessed by two independent surgeons (the full score ranged from 4 to 20).Results:All patients completed the study. The volume of implants in the left breast was (216.2±54.6) ml and that in the right breast was (217.9±53.1) ml. Grafted fat volume for the left breast was (256.8±55.8) ml each time and that for the right breast was (258.1±55.7) ml. The mean follow-up time was (13.5±5.7) months. Small nonpalpable nodules were detected in two patients (7.7%) by ultrasound. No other complications were documented during the study period. The average chest circumference was decreased by (1.1±0.8) cm which was less than one cup according to Chinese Industrial Standards. Patient satisfaction and physician satisfaction were (16.8±2.0) and (16.4±1.6), respectively.Conclusions:SIEF is an effective and safe method to restore breast volume after implant removal.

June 5, 2019, a 36-year-old female was diagnosed with septic shock caused by Streptococcus dysgalactiae infection eight hours after liposuction and fat grafting in Plastic Surgery Hospital, Chinese Academy of Medical Sciences. As the symptoms were identified early, the patient received immediate treatment and was transferred to Peking Union Medical College Hospital. After multi-disciplinary coordination of departments of emergency, plastic surgery, and ICU, the septic status was finally resolved and the patient was discharged after a 103-day hospital stay. The authors reviewed the course of the treatment in detail and our experience in dealing with the special kind of toxic septic shock.

Objective:This study aims to compare the application value of Autoregressive Integrated Moving Average model (ARIMA ) and deep learning model inprediction and analysis of liposuction operation data.Methods:The patients who met inclusion criteria and underwent liposuction surgery in the Plastic Surgery Hospital of Chinese Academy of Medical Sciences from January 2019 to September 2019 were enrolled in this study. For each patient, 250~400 s operation data including kinematics and mechanical data were collected by a senior plastic surgeon, usingthe liposuction operation recording system which consists of optical tracking and force sensing equipment. After pretreatment, the collected data were divided into one liposuction reciprocating cycle as one set of data. ARIMA model and deep learning model were used to analyze the collected datafor establishing prediction models of liposuction operation. Using Matlab2017, 30 couplesofliposuction data setwereextractedby simple random sampling, andthe DTW valueofeachcoupleofdatasetswascalculated as test standard. Then, the DTW values between 30 sets of predicted data and actual data based on the ARIMA model and the deep learning model were calculated respectively and compared with the test standard to verify the prediction result of the two models. Matlab2017 was used for statistical analysis. Independent sample t-test was used to compare the two groups, and P<0. 05 indicates that the difference is statistically significant.Results:18 patients were enrolled. All patients were females at 23-49 years old, with the mean age of 36. 6 years old. Liposuction was performed in the abdomen, thighs, and waist. A total of 16 800 sets of liposuction cycle data were obtained. The mean DTW value of test standard was 0. 048±0. 028. The meanDTW value between the ARIMA model predicted data and the actual data was 0. 660±0. 577, which was statistically significant compared with the test standard ( P< 0. 05) . The meanDTW value between the deep learning model predicted data and the actual data was 0. 052±0. 030, which was no significant difference compared with the test standard ( P> 0. 05 ). Conclusions:Compared with ARIMA model, deep learning model can predict liposuction operation data more accurately, and has better adaptability and real-time performance.

Objective:This study aims to compare the applicability value of autoregressive integrated moving average model(ARIMA) and deep learning model inprediction and analysis of liposuction operation data.Methods:The patients who met inclusion criteria and underwent liposuction surgery in the Plastic Surgery Hospital of Chinese Academy of Medical Sciences from January 2019 to September 2019 were enrolled in this study. For each patient, 250-400 s operation data including kinematics and mechanical data were collected by a senior plastic surgeon, using the liposuction operation recording system which consists of optical tracking and force sensing equipment. After pretreatment, the collected data were divided into one liposuction reciprocating cycle as one set of data. ARIMA model and deep learning model were used to analyze the collected data for establishing prediction models of liposuction operation. Using Matlab 2017, 30 couples of liposuction data set were extracted by simple random sampling, and the dynamic time warping (DTW) value of each couple of data sets was calculated as test standard. Then, the DTW values between 30 sets of predicted data and actual data based on the ARIMA model and the deep learning model were calculated respectively and compared with the test standard to verify the prediction results of the two models. Matlab 2017 was used for statistical analysis. Independent sample t-test was used to compare the two groups, and P<0.05 indicated statistically significant difference. Results:Eighteen patients were enrolled. All patients were females at 23-49 years old, with the mean age of 36.6 years old. Liposuction was performed in the abdomen, thighs, and waist. A total of 16 800 sets of liposuction cycle data were obtained. The mean DTW value of test standard was 0.048±0.028. The mean DTW value between the ARIMA model predicted data and the actual data was 0.660±0.577, which was statistically significant compared with the test standard ( P<0.05). The mean DTW value between the deep learning model predicted data and the actual data was 0.052±0.030, which was not significantly different compared to the test standard ( P>0.05). Conclusions:Compared with ARIMA model, deep learning model can predict liposuction operation data more accurately, and has better adaptability and real-time performance.

Liposuction is generally a safe aesthetic procedure, but it can lead to dangerous and even fatal complications. Based on the literature review, this article reviewed the causes, diagnosis, risk factors and other relevant knowledge of serious complications caused by liposuction, and expounded the prevention and treatment measures combined with personal experience.

Objective:To assess the safety and efficacy of mammaplasty with autologous fat grafting(AFG).Methods:A retrospective analysis was conducted to review cases of mammaplasty with AFG from December 2010 to December 2020 in Department of Body Contouring and Fat Grafting Center, Plastic Surgery Hospital, Chinese Academy of Medical Sciences. Liposuction was performed using low negative pressure (-60 kPa) by liposuction machine. After lipoaspirate was washed with normal saline, cotton pad or low-speed centrifugation method was utilized to process fat. A blunt cannula with a diameter of 2.5 mm was used for multi-layer injection into the breast. The efficacy of surgery was evaluated from routine breast examinations, ultrasound examinations, third-party evaluations of pre- and post-operative photos, and patient’s scoring on breast appearance and the quality of life. The score interval is 0-100 points, and the higher the score, the better the effect. The Mann-Whitney U test was applied to compare the differences between groups, and the paired t-test was used to compare the difference of chest circumferences before and after surgery and the doctors’ scores. P<0.05 indicates statistically significant difference. Results:449 patients with 829 breasts were enrolled, aged (37.6±9.4) years old with a body mass index of (21.4±2.8) kg/m 2, including 372 patients with breast dysplasia, 42 patients underwent total mastectomy due to breast cancer, 8 patients with breast deformity after breast-conserving surgery, and 27 cases with breast implants for augmentation. Of the 449 cases, 37 cases used Brava before surgery, including 25 patients with breast dysplasia and 12 patients who underwent total mastectomy. All patients successfully completed the operation. Patients with breast dysplasia required (2.0±0.7) times of AFG for breast augmentation, with a unilateral injection volume of (244.4±58.1) ml per session. Patients who underwent total mastectomy required (2.9±1.1) times of AFG, with a unilateral injection volume of (223.2±62.4) ml per session. Patients with breast deformity after breast-conserving surgery required (1.5±0.5) times of AFG, with a unilateral injection volume of (204.0±29.5) ml per session. And for patients with breast implants for augmentation, it takes (2.2±0.8) times of AFG after removal of implants. The postoperative follow-up time was (14.0±6.8) months. Cystic nodules and benign calcifications with a diameter of 0.1-0.3 cm was found in 34 patients in ultrasound, 5 patients had palpable nodules and 3 patients had intramammary infections. No serious complications occurred. The breast circumference of 353 patients with bilateral breast dysplasia increased by (4.8±1.0) cm ( P<0.01) compared with that before operation. Breast circumference of the 27 patients who underwent implant removal and AFG for augmentation reduced by (1.2±1.7) cm ( P<0.01) after operation. The scores of third-party after operation in each group were significantly higher than those before operation ( P<0.05). The doctor’s score of patients with breast reconstruction after total mastectomy for breast cancer increased the most, which was 15.4±4.9 points ( P<0.01). In this group, the scores of patients who underwent radiotherapy increased by (19.3±2.3) points, which was higher than those without radiotherapy 13.4±5.5 points ( P<0.01). Patients with breast reconstruction after total mastectomy for breast cancer had the lowest breast satisfaction and quality of life scores, which were 84.6±2.9 and 84.7±3.2 points respectively, while those with breast deformity correction after breast conserving surgery had the highest scores, 88.8±4.0 and 90.6±3.7 points respectively. Conclusions:The application of AFG to mammaplasty is both safe and effective, with fewer complications, and high satisfaction rate.

With the popularity of soft tissue fillers, more and more complications have been reported. Inflammatory nodule is one of the complications that has long been considered to be an allergic reaction or response to the filler material as a foreign body. But it is attributed to bacterial biofilms infection in recent years. This paper described the nature of biofilms and the evidences that biofilms were involved in inflammatory nodules after injection, and summarized the research progress on the diagnosis, treatment and prevention.