Objective:To use three-dimensional (3D) scanning to measure the preoperative and postoperative nasal parameters of the patients received rhinoplasty with ear cartilage and silicone prosthesis, and to evaluate the clinical effect of the surgery.Methods:Sixteen female patients with an average age of 28.3 years, ranged from 21 to 35 years, received rhinoplasty with ear cartilage and silicone prosthesis in Wuhan Tongji Hospital from June 2018 to February 2019. Preoperative and postoperative 3D scanning was performed to measure nasal parameters, including linear length, angle, and proportional index.Results:All patients were satisfied with the postoperative outcomes. The postoperative nasal length, nasal height, and nasal depth increased significantly, and the postoperative nasal width and nasal tip width decreased. The postoperative nasolabial angle and nasofrontal angle were statistically improved, while the preoperative and postoperative data of columellar facial angle, nasal tip angle, and nasal column-lobular angle were not significantly different. The ratios of nasal depth and nasal width, nasal index and nasal tip protrusion were improved after surgery, while the postoperative ratios of nasal columella and nasal lobules length were not statistically improved.Conclusions:The 3D scanning allows for comprehensive and accurate measurement of the nasal parameters. The rhinoplasty with ear cartilage and silicone prosthesis is more effective in improving the overall contour of the nose, but less effective in improving the aesthetics of the nasal tip.

Objective:This study aimed to explore the use of magnetic resonance imaging (MRI) to measure breast volume and gland volume to guide reconstruction of breast reconstruction with silicone gel prothesis following nipple-sparing mastectomy (NSM).Methods:According to the inclusion criteria, the breast cancer patients admitted to Wuhan Tongji Hospital from September 2018 to June 2019 were selected to undergo breast reconstruction with prosthesis after NSM. Preoperative MRI were used to measure distance from the tumor to the nipple-areola complex and the skin, and estimate the volume of breast and mammary gland. The data of breast volume measured by MRI, gland volume measured by MRI, volume of prosthesis and specimen weight were compared. The data were analyzed using Prism 8.0 software. The paired student t-test was used to compare the difference of two groups. P< 0.05 was considered statistically significant. Linear regression models were used to obtain coefficient of determination ( R2), and R2>0.8 was considered statistically significant. Results:A total of 15 breast cancer patients, aged 28-45 years, with a mean of 35.5 years, were included. There were 13 cases unilateral and 2 cases bilateral. The clinical stages of stage 0, Ⅰ and Ⅱ were 8, 5 and 2 patients, respectively. The average distance o from tumor to nipple-areola complex was (3.1±0.8) cm. One patient suffered postoperative bleeding and was promptly reoperated through the original incision, and the patient recovered well after surgery. All patients felt sensory disturbance of the nipple and areola. There was no complication such as infection, seroma, capsular contracture, prosthesis rupture, and prosthesis shift. At 4-12 months postoperative follow-up, all breasts were basically symmetrical and no tumor recurrence or metastasis occurred, which satisfied the patients. The mean values of the volume of prosthesis, specimen weight, breast volume measured by MRI and gland volume measured by MRI were (471.10±45.60) ml, (244.60±29.14) ml, (243.60±31.16) g, (244.30±16.63) ml. There was significant difference between the breast volume measured by MRI and the specimen weight ( t=10.37, P<0.001), while no statistical difference was found between gland volume measured by MRI and specimen weight ( t=0.20, P=0.847). Similarly, there was significant difference between the breast volume measured by MRI and the volume of prosthesis ( t=5.19, P<0.001), while no statistical difference was found between gland volume measured by MRI and the volume of prosthesis ( t=1.74, P=0.104). The coefficient of determination between gland volume measured by MRI and specimen weight ( R2=0.98) was higher than that of breast volume measured by MRI ( R2=0.82). Similarly, the coefficient of determination between gland volume measured by MRI and the volume of prosthesis ( R2=0.71) was higher than that of breast volume measured by MRI ( R2=0.54). Conclusions:Preoperative MRI can provide guidance to breast reconstruction with silicone gel prothesis following nipple-sparing mastectomy in breast cancer. The gland volume measured by MRI is closer to the specimen weight and the volume of prosthesis than the breast volume measured by MRI.

Objective:The study was to explore the nipple-areola complex(NAC) blood supply model in Chinese breasts based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to provide the blood supply knowledge for mammaplasty.Methods:Breast DCE-MRI images of breasts without masses in 245 patients from March 2012 to October 2019 in Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology were included retrospectively. The breast vessels images were obtained by image subtraction in the Siemens workstation. Axial, coronal and sagittal maximum intensity projection(MIP) images were evaluated, and all vessels supplying the nipple-areola complex were identified by 3D MIP images. Blood supply to the NAC was classified into 9 zones, and vessels of each zone were counted and analyzed. The maximum distance from the vessel to the skin surface of the breast was measured. SPSS 19.0 software was used for statistical analysis. The chi-square test was used to check for significant differences in the distribution of zones between the left breasts and the right breasts. The mean, standard deviation and 95% confidence interval of the distance between vessels and skin were calculated. Using ANOVA to compare the distance between vessels and skin of zones. P<0.05 was statistically significant. Results:There were 490 breasts in 245 DCE-MRI images, of which 97 breasts were found to have masses in 97 DCE-MRI images. The remaining 393 were normal breasts as study subjects. The patients’ ages ranged from 23 to 72 years, with a mean of 43.7 years. 637 source vessels (311 left, 326 right) were identified in 393 breasts (200 left, 193 right). Of the 637 vessels, 269 (42.2%) were in the superomedial zone and 180 (28.3%) were in the superolateral zone. The proportions of vessels in zone medial (57, 8.9%), inferior (37, 5.8%), central (30, 4.7%), inferomedial (25, 3.9%), inferolateral (25, 3.9%), superior (11, 1.7%) and lateral (3, 0.5%) were less than 10%, respectively. The chi-square test showed no significant difference in the distribution of zones ( χ2 =6.4, P=0.602) between the left breasts and the right breasts. Except for the central zone, the mean of maximum distance from the vessels to the skin surface was 0.91 cm, with a 95% confidence interval of 0.86 cm to 0.96 cm. Conclusions:DCE-MRI can clearly show the blood supply to the NAC. Superomedial or superolateral source vessels supplying the NAC were predominant, and the vessels run at a subcutaneous depth of about 1 cm.

Objective:This study aimed to explore the use of magnetic resonance imaging (MRI) to measure breast volume and gland volume to guide reconstruction of breast reconstruction with silicone gel prothesis following nipple-sparing mastectomy (NSM).Methods:According to the inclusion criteria, the breast cancer patients admitted to Wuhan Tongji Hospital from September 2018 to June 2019 were selected to undergo breast reconstruction with prosthesis after NSM. Preoperative MRI were used to measure distance from the tumor to the nipple-areola complex and the skin, and estimate the volume of breast and mammary gland. The data of breast volume measured by MRI, gland volume measured by MRI, volume of prosthesis and specimen weight were compared. The data were analyzed using Prism 8.0 software. The paired student t-test was used to compare the difference of two groups. P< 0.05 was considered statistically significant. Linear regression models were used to obtain coefficient of determination ( R2), and R2>0.8 was considered statistically significant. Results:A total of 15 breast cancer patients, aged 28-45 years, with a mean of 35.5 years, were included. There were 13 cases unilateral and 2 cases bilateral. The clinical stages of stage 0, Ⅰ and Ⅱ were 8, 5 and 2 patients, respectively. The average distance o from tumor to nipple-areola complex was (3.1±0.8) cm. One patient suffered postoperative bleeding and was promptly reoperated through the original incision, and the patient recovered well after surgery. All patients felt sensory disturbance of the nipple and areola. There was no complication such as infection, seroma, capsular contracture, prosthesis rupture, and prosthesis shift. At 4-12 months postoperative follow-up, all breasts were basically symmetrical and no tumor recurrence or metastasis occurred, which satisfied the patients. The mean values of the volume of prosthesis, specimen weight, breast volume measured by MRI and gland volume measured by MRI were (471.10±45.60) ml, (244.60±29.14) ml, (243.60±31.16) g, (244.30±16.63) ml. There was significant difference between the breast volume measured by MRI and the specimen weight ( t=10.37, P<0.001), while no statistical difference was found between gland volume measured by MRI and specimen weight ( t=0.20, P=0.847). Similarly, there was significant difference between the breast volume measured by MRI and the volume of prosthesis ( t=5.19, P<0.001), while no statistical difference was found between gland volume measured by MRI and the volume of prosthesis ( t=1.74, P=0.104). The coefficient of determination between gland volume measured by MRI and specimen weight ( R2=0.98) was higher than that of breast volume measured by MRI ( R2=0.82). Similarly, the coefficient of determination between gland volume measured by MRI and the volume of prosthesis ( R2=0.71) was higher than that of breast volume measured by MRI ( R2=0.54). Conclusions:Preoperative MRI can provide guidance to breast reconstruction with silicone gel prothesis following nipple-sparing mastectomy in breast cancer. The gland volume measured by MRI is closer to the specimen weight and the volume of prosthesis than the breast volume measured by MRI.

Objective:The study was to explore the nipple-areola complex(NAC) blood supply model in Chinese breasts based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to provide the blood supply knowledge for mammaplasty.Methods:Breast DCE-MRI images of breasts without masses in 245 patients from March 2012 to October 2019 in Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology were included retrospectively. The breast vessels images were obtained by image subtraction in the Siemens workstation. Axial, coronal and sagittal maximum intensity projection(MIP) images were evaluated, and all vessels supplying the nipple-areola complex were identified by 3D MIP images. Blood supply to the NAC was classified into 9 zones, and vessels of each zone were counted and analyzed. The maximum distance from the vessel to the skin surface of the breast was measured. SPSS 19.0 software was used for statistical analysis. The chi-square test was used to check for significant differences in the distribution of zones between the left breasts and the right breasts. The mean, standard deviation and 95% confidence interval of the distance between vessels and skin were calculated. Using ANOVA to compare the distance between vessels and skin of zones. P<0.05 was statistically significant. Results:There were 490 breasts in 245 DCE-MRI images, of which 97 breasts were found to have masses in 97 DCE-MRI images. The remaining 393 were normal breasts as study subjects. The patients’ ages ranged from 23 to 72 years, with a mean of 43.7 years. 637 source vessels (311 left, 326 right) were identified in 393 breasts (200 left, 193 right). Of the 637 vessels, 269 (42.2%) were in the superomedial zone and 180 (28.3%) were in the superolateral zone. The proportions of vessels in zone medial (57, 8.9%), inferior (37, 5.8%), central (30, 4.7%), inferomedial (25, 3.9%), inferolateral (25, 3.9%), superior (11, 1.7%) and lateral (3, 0.5%) were less than 10%, respectively. The chi-square test showed no significant difference in the distribution of zones ( χ2 =6.4, P=0.602) between the left breasts and the right breasts. Except for the central zone, the mean of maximum distance from the vessels to the skin surface was 0.91 cm, with a 95% confidence interval of 0.86 cm to 0.96 cm. Conclusions:DCE-MRI can clearly show the blood supply to the NAC. Superomedial or superolateral source vessels supplying the NAC were predominant, and the vessels run at a subcutaneous depth of about 1 cm.

Schizophrenia(SZ)is a serious mental illness,and traditional diagnostic methods are prone to missed and misdiagnosis.Using machine learning(ML)algorithms can extract SZ relative features from functional MRI(fMRI)data,hence being helpful for diagnosing and predicting treatment response of SZ.The research progresses of ML based on fMRI for diagnosis and treatment of SZ were reviewed in this article.

Lung cancer is the leading type of cancer death, and most patients with lung cancer are diagnosed at an advanced stage and have a very poor prognosis. Although low-dose computed tomography (LDCT) has entered the clinic as a screening tool for lung cancer, its false-positive rate is more than 90%. As one of the epigenetic modifications of research hotspots, DNA methylation plays a key role in a variety of diseases, including cancer.Hypermethylation of tumor suppressor genes and hypomethylation of proto-oncogenes are important events in tumorigenesis and development. Therefore, DNA methylation analysis can provide some useful information for the early screening, diagnosis, treatment and prognosis of lung cancer. Although invasive methods such as tissue biopsy remain the gold standard for tumor diagnosis and monitoring, they also have limitations such as inconvenience in sampling. In recent years, there has been a rapid development of liquid biopsy, which can detect primary or metastatic malignancies and reflect the heterogeneity of tumors. In addition, the blood sample can be collected in a minimally invasive or non-invasive format and is well tolerated in older and frail patients. This article explores some of the emerging technologies for DNA methylation analysis and provides an overview of the application of DNA methylation in the diagnosis and treatment of lung cancer.

Objective To investigate the effect of long?term exposure to environmental cadmium on eight mineral element's metabolic balance of human body. Methods To choose a high cadmium area polluted by smelting and mining north of Guangdong province and a cadmium?free area with a similar economic level, and living and eating habit of residents as a contrast from April 2011 to August 2012. Stratified random sampling and clustered sampling method were adopted to choose the non?occupationally cadmium?exposed respondents who have lived in local area for more than 15 years, older than 40 years, having local rice and vegetable as the main dietary source, with simple and relatively stable diet, and without diabetes, kidney disease, thyroid disease, liver disease or other history of chronic disease. This study included 298 respondents, of whom 155 were in cadmium exposure group and 143 in control group. Questionnaires was used to acquire their health status and their morning urine samples were collected. Electrolytically coupled plasma mass spectrometry (ICP?MS) was used to test the concentrations of sodium (Na), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), copper (Cu), zinc (Zn) and iodine (I). The Mann?Whitney U test method was used to compare the differences of concentrations of urinary cadmium, Na, Mg, P, K, Ca, Cu, Zn, I, and the ratio of Na to K (Na/K), Ca to P (Ca/P) between exposed group and control group.χ2 test was used to compare the abnormal rate of urinary cadmium between exposed group and control group. Pearson correlation and multiple regression method were used to investigate the relationship between urinary cadmium levels, gender, age, smoking, passive smoking, and minerals. Results The urinary cadmium level P50 (P25-P75) in exposed group was 5.45 (2.62-10.68)μg/g·cr, which was higher than that of the control group, which was 1.69 (1.22-2.36)μg/g · cr (Z=-10.49, P<0.001). The abnormal rate of urinary cadmium was 51.6%(80/155), which was higher than that of the control group (2.8%(4/143)) (χ2=87.56,P<0.001). The urinary Ca, Cu, Zn, and I level P50 (P25-P75) of exposed group were 173.80 (114.40-251.70), 20.55 (14.95-28.44), 520.23 (390.25-647.15), and 246.94 (203.65-342.97)μg/g · cr, which were higher than those in control group (142.42 (96.87-179.11), 15.44 (12.26-20.98), 430.09 (309.85-568.78) and 213.85 (156.70-281.63) μg/g · cr, respectively) (Z values were-4.33,-5.04,-3.47 and-4.24, all P values<0.001). The urinary P, K level P50 (P25-P75) of exposed group were 582.50 (463.20-742.8), 890.10 (666.00-1 305.40) μg/g · cr, which were lower than control group (694.50 (546.20-851.17), 1 098.58 (904.53-1 479.18) μg/g · cr) (Z values were-3.36,-4.02, all P values <0.001). on Based the results of Pearson correlation analysis, urinary cadmium was positively correlated with urinary Ca, Cu, Zn, and I, and the correlation coefficients were 0.31, 0.61, 0.38, and 0.25, respectively(all P values<0.05). Based on the results of multiple regression analysis, urinary cadmium levels contributed most to the metabolic balance of urinary Ca, Cu, Zn and I. The standardized regression coefficients were 0.31, 0.59, 0.39, and 0.24, respectively (all P values<0.001). Conclusion Long?term environmental exposure to cadmium affected the metabolic balance of Ca, Cu, Zn and I in human body.

Objective To investigate dynamic change of cadmium body burden and renal dysfunction among residents living in cadmium?polluted areas. Methods From April to July of 2011, the cadmium?polluted areas of northern Guangdong province in China was chosen as the study site. Based on the levels of cadmium pollution in soil and rice, the survey areas were divided into low exposed group (average concentration of cadmium was 0.15-0.40 mg/kg, 0.5-1.0 mg/kg in rice and soil, respectively) and high exposed group (average concentration of cadmium was >0.40 mg/kg, >1.0 mg/kg in rice and soil, respectively). Stratified random sampling and cluster sampling method of epidemiological investigations were carried out among 414 local residents who lived in cadmium exposure areas for more than 15 years, aged above 40, and without occupational cadmium exposure, including 168 and 246 residents in low and high exposed group, respectively. From March to June of 2014, 305 respondents of those who participated in 2011 were successfully traced, including 116 and 189 respondents in low and high exposed group, respectively. We used health questionnaires to acquire their health status. Home?harvested rice and vegetable samples were collected using quartering method for detection of cadmium level, including 190 rice samples, 161 vegetable samples in 2011 and 190 rice samples, 153 vegetable samples in 2014. Urine specimens of residents were collected for the detection of urinary cadmium and creatinine as well as renal dysfunction biomarkers, namely, N?acetyl?beta?D?glucosamidase (NAG) andβ2?microglobulin (β2?MG), respectively. In 2011 and 2014, Chi?square test was used to investigate the differences of abnormality of cadmium concentration in rice, vegetables and urinary cadmium,β2?MG,and NAG that were expressed as odds ratio (OR) and 95%confidence intervals (95%CI). Results In 2011 and 2014, cadmium concentration P50 (P25-P75) in rice was 0.43 (0.17-1.10) mg/kg,and 0.42 (0.20-1.14) mg/kg, respectively (Z=-0.77, P=0.440). In 2011 and 2014, cadmium concentrations P50 (P25-P75) in vegetables were 0.13 (0.07-0.34) mg/kg,and 0.25 (0.12-0.59) mg/kg, respectively, with abnormal rates of 38.5%(62/161) and 60.8%(93/153), respectively. In 2014, both average concentration and abnormal rate of cadmium in vegetables were higher than those in 2011 (Z=-4.69,P<0.001 andχ2=15.58, P<0.001). Concentrations of urinary cadmium P50 (P25-P75) in high exposed group were 7.90 (3.96-14.91)μg/g creatinine, 8.64 (4.56-17.60)μg/g creatinine in 2011 and 2014, respectively. Contrary to that in 2011, urinary cadmium of high exposed group was significantly increased in 2014 (Z=-2.80 ,P=0.005). In 2011 and 2014, concentrations of β2?MG, NAG P50 (P25-P75) were 0.15 (0.07-0.29)μg/g creatinine, 0.15 (0.07-0.45)μg/g creatinine,and 7.12 (5.05-10.65) U/g creatinine, 13.55 (9.1-19.84) U/g creatinine, respectively, with abnormal rates of 7.5% (23/305), 15.1% (46/305) ,8.2%(25/305) , and 33.8% (103/305), respectively. Compared with baseline in 2011, average concentrations ofβ2?MG, NAG significantly increased in 2014 (Z=-2.263,P=0.024 and Z=-12.52,P<0.001), and abnormal rates ofβ2?MG, NAG were also higher in 2014 (χ2=15.61,P<0.001 andχ2=64.72,P<0.001), with odds ratio (OR) of 2.00 (95%CI:1.23-3.24) and 4.12 (95%CI:2.87-5.92). Conclusion Environmental cadmium pollution of crops such as rice and vegetables in survey areas continued to remain high. Body burden of cadmium might kept at sustainably high levels and renal dysfunction was worsened after continuous, long?term cadmium exposure. Our results suggested that NAG might be more sensitive than β2?MG to serve as an indicator for an individual's future tubular function.

Objective To investigate the effect of long?term exposure to environmental cadmium on eight mineral element's metabolic balance of human body. Methods To choose a high cadmium area polluted by smelting and mining north of Guangdong province and a cadmium?free area with a similar economic level, and living and eating habit of residents as a contrast from April 2011 to August 2012. Stratified random sampling and clustered sampling method were adopted to choose the non?occupationally cadmium?exposed respondents who have lived in local area for more than 15 years, older than 40 years, having local rice and vegetable as the main dietary source, with simple and relatively stable diet, and without diabetes, kidney disease, thyroid disease, liver disease or other history of chronic disease. This study included 298 respondents, of whom 155 were in cadmium exposure group and 143 in control group. Questionnaires was used to acquire their health status and their morning urine samples were collected. Electrolytically coupled plasma mass spectrometry (ICP?MS) was used to test the concentrations of sodium (Na), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), copper (Cu), zinc (Zn) and iodine (I). The Mann?Whitney U test method was used to compare the differences of concentrations of urinary cadmium, Na, Mg, P, K, Ca, Cu, Zn, I, and the ratio of Na to K (Na/K), Ca to P (Ca/P) between exposed group and control group.χ2 test was used to compare the abnormal rate of urinary cadmium between exposed group and control group. Pearson correlation and multiple regression method were used to investigate the relationship between urinary cadmium levels, gender, age, smoking, passive smoking, and minerals. Results The urinary cadmium level P50 (P25-P75) in exposed group was 5.45 (2.62-10.68)μg/g·cr, which was higher than that of the control group, which was 1.69 (1.22-2.36)μg/g · cr (Z=-10.49, P<0.001). The abnormal rate of urinary cadmium was 51.6%(80/155), which was higher than that of the control group (2.8%(4/143)) (χ2=87.56,P<0.001). The urinary Ca, Cu, Zn, and I level P50 (P25-P75) of exposed group were 173.80 (114.40-251.70), 20.55 (14.95-28.44), 520.23 (390.25-647.15), and 246.94 (203.65-342.97)μg/g · cr, which were higher than those in control group (142.42 (96.87-179.11), 15.44 (12.26-20.98), 430.09 (309.85-568.78) and 213.85 (156.70-281.63) μg/g · cr, respectively) (Z values were-4.33,-5.04,-3.47 and-4.24, all P values<0.001). The urinary P, K level P50 (P25-P75) of exposed group were 582.50 (463.20-742.8), 890.10 (666.00-1 305.40) μg/g · cr, which were lower than control group (694.50 (546.20-851.17), 1 098.58 (904.53-1 479.18) μg/g · cr) (Z values were-3.36,-4.02, all P values <0.001). on Based the results of Pearson correlation analysis, urinary cadmium was positively correlated with urinary Ca, Cu, Zn, and I, and the correlation coefficients were 0.31, 0.61, 0.38, and 0.25, respectively(all P values<0.05). Based on the results of multiple regression analysis, urinary cadmium levels contributed most to the metabolic balance of urinary Ca, Cu, Zn and I. The standardized regression coefficients were 0.31, 0.59, 0.39, and 0.24, respectively (all P values<0.001). Conclusion Long?term environmental exposure to cadmium affected the metabolic balance of Ca, Cu, Zn and I in human body.