[Feasibility analysis and nail planning ofS2 iliac crest screw placement in children].

OBJECTIVE: To evaluate the feasibility of S2 alar iliac screw insertion in Chinese children using computerized three-dimension reconstruction and simulated screw placement technique, and to optimize the measurement of screw parameters. METHODS: A total of 83 pelvic CT data of children who underwent pelvic CT scan December 2018 to December 2020 were retrospectively analyzed, excluding fractures, deformities, and tumors. There were 44 boys and 39 girls, with an average age of (10.66±3.52) years, and were divided into 4 groups based on age (group A:5 to 7 years old;group B:8 to 10 years old;group C:11-13 years old;group D:14 to 16 years old). The original CT data obtained were imported into Mimics software, and the bony structure of the pelvis was reconstructed, and the maximum and minimum cranial angles of the screws were simulated in the three-dimensional view with the placement of 6.5 mm diameter S2 alar iliac screws. Subsequently, the coronal angle, sagittal angle, transverse angle, total length of the screw, length of the screw in the sacrum, width of the iliac, and distance of the entry point from the skin were measured in 3-Matic software at the maximum and minimum head tilt angles, respectively. The differences among the screw parameters of S2 alar iliac screws in children of different ages and the differences between gender and side were compared and analyzed. RESULTS: In all 83 children, 6.5 mm diameter S2 iliac screws could be placed. There was no significant difference between the side of each screw placement parameter. The 5 to 7 years old children had a significantly smaller screw coronal angle than other age groups, but in the screw sagittal angle, the difference was more mixed. The 5 to 7 years old children could obtain a larger angle at the maximum head tilt angle of the screw, but at the minimum cranial angle, the larger angle was obtained in the age group of 11 to 13 years old. There were no significant differences among the age groups. The coronal angle and sagittal angle under maximum cephalic angle and minimum cranial angle of 5 to 7 years old male were (40.91±2.91)° and (51.85±3.75)° respectively, which were significantly greater than in female. The coronal angle under minimum cranial angle was significantly greater in girls aged 8-10 years old than in boys. For the remaining screw placement angle parameters, there were no significant differences between gender. The differences in the minimum iliac width, the screw length, and the length of the sacral screws showed an increasing trend with age in all age groups. The distance from the screw entry point to the skin in boys were significantly smaller than that of girls. The minimum width of the iliac in boys at 14 to 16 years of age were significantly wider than that in girls at the same stage. In contrast, in girls aged 5 to 7 years and 11 to 13 years, the screw length was significantly longer than that of boys at the same stage. CONCLUSION: The pelvis of children aged 5 to 16 years can safely accommodate the placement of 6.5 mm diameter S2 alar iliac screws, but the bony structures of the pelvis are developing and growing in children, precise assessment is needed to plan a reasonable screw trajectory and select the appropriate screw length.

AI-predicted mpMRI image features for the prediction of clinically significant prostate cancer.

PURPOSE: To evaluate the feasibility of using mpMRI image features predicted by AI algorithms in the prediction of clinically significant prostate cancer (csPCa). MATERIALS AND METHODS: This study analyzed patients who underwent prostate mpMRI and radical prostatectomy (RP) at the Affiliated Hospital of Jiaxing University between November 2017 and December 2022. The clinical data collected included age, serum prostate-specific antigen (PSA), and biopsy pathology. The reference standard was the prostatectomy pathology, and a Gleason Score (GS) of 3 + 3 = 6 was considered non-clinically significant prostate cancer (non-csPCa), while a GS ≥ 3 + 4 was considered csPCa. A pre-trained AI algorithm was used to extract the lesion on mpMRI, and the image features of the lesion and the prostate gland were analyzed. Two logistic regression models were developed to predict csPCa: an MR model and a combined model. The MR model used age, PSA, PSA density (PSAD), and the AI-predicted MR image features as predictor variables. The combined model used biopsy pathology and the aforementioned variables as predictor variables. The model's effectiveness was evaluated by comparing it to biopsy pathology using the area under the curve (AUC) of receiver operation characteristic (ROC) analysis. RESULTS: A total of 315 eligible patients were enrolled with an average age of 70.8 ± 5.9. Based on RP pathology, 18 had non-csPCa, and 297 had csPCa. PSA, PSAD, biopsy pathology, and ADC value of the prostate outside the lesion (ADCprostate) varied significantly across different ISUP grade groups of RP pathology (P < 0.001). Other clinical variables and image features did not vary significantly across different ISUP grade groups (P > 0.05). The MR model included PSAD, the ratio of ADC value between the lesion and the prostate outside the lesion (ADClesion/prostate), the signal intensity ratio of DWI between the lesion and the prostate outside the lesion (DWIlesion/prostate), and the ratio of DWIlesion/prostate to ADClesion/prostate. The combined model included biopsy pathology, ADClesion/prostate, mean signal intensity of the lesion on DWI (DWIlesion), DWI signal intensity of the prostate outside the lesion (DWIprostate), and signal intensity ratio of DWI between the lesion and the prostate outside the lesion (DWIlesion/prostate). The AUC of the MR model (0.830, 95% CI 0.743, 0.916) was not significantly different from that of biopsy pathology (0.820, 95% CI 0.728, 0.912, P = 0.884). The AUC of the combined model (0.915, 95% CI 0.849, 0.980) was higher than that of the biopsy pathology (P = 0.042) and MR model (P = 0.031). CONCLUSION: The aggressiveness of prostate cancer can be effectively predicted using AI-extracted image features from mpMRI images, similar to biopsy pathology. The prediction accuracy was improved by combining the AI-extracted mpMRI image features with biopsy pathology, surpassing the performance of biopsy pathology alone.

Green extraction and purification of chondroitin sulfate from jumbo squid cartilage by a novel procedure combined with enzyme, ultrasound and hollow fiber dialysis.

Chondroitin sulfate (ChS) from marine sources is gaining attention. The purpose of this study was to extract ChS from jumbo squid cartilage (Dosidicus gigas) using ultrasound-assisted enzymatic extraction (UAEE). An ultrasound with protease assistance, including either alcalase, papain or Protin NY100 was used to extract ChS. The results showed that alcalase had the best extraction efficiency. The response surface methodology was employed to evaluate the relationship between extraction conditions and extraction yield of ChS. The ridge max analysis revealed a maximum extraction yield of 11.9 mg ml- 1 with an extraction temperature of 59.40 °C, an extraction time of 24.01 min, a pH of 8.25, and an alcalase concentration of 3.60%. Compared to ethanol precipitation, purification using a hollow fiber dialyzer (HFD) had a higher extraction yield of 62.72% and purity of 85.96%. The structure characteristics of ChS were identified using FTIR, 1 H-NMR, and 13 C-NMR to confirm that the purified ChS structure was present in the form of chondroitin-4-sulfate and chondroitin-6-sulfate. The results of this study provide a green and efficient process for extraction and purification of ChS and are essential for the use of ChS for the development and production of nutrient food products or pharmaceuticals. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-023-05701-7.

Cervical Cancer Mortality Trends in China, 1991-2013, and Predictions for the Future.

BACKGROUND: To analyze cervical cancer mortality trends in China from 1991-2013 and forecast the mortality distribution in future five years (2014-2018), and provide clues for prevention and treatment. MATERIALS AND METHODS: Mortality data for cervical cancer in China from 1991 to 2013 were used to describe the epidemiological characteristics and distribution, including the trend of the standardized mortality rate, urban-rural differences, and age variation. Trend-surface analysis was used to analyze the geographical distribution of mortality. Curve estimation, time series, gray modeling, and joinpoint regression were performed to predict and forecast mortality trends. RESULTS: In recent years, the mortality rate of cervical cancer has increased, and there is also a steady increase in the incidence from 2003 to 2013 in China. Mortality rates in rural areas are higher than in urban areas. The mortality dramatically increases in the 40+ yr age group, reaching a peak in the >85 yr age group. In addition, geographical analysis showed that the cervical cancer mortality increased from the southwest to west-central and from the southeast to northeast of the country. CONCLUSIONS: The incidence rate and the mortality rate are increasing from 1991 to 2013, and the predictions show this will continue in the future. Thus, implementation of prevention and management programs for cervical cancer are necessary in China, especially for rural areas, young women in urban areas, and high risk regions (the west-central).

Mortality Characteristic and Prediction of Nasopharyngeal Carcinoma in China from 1991 to 2013.

BACKGROUND: To analyze the mortality distribution of nasopharyngeal carcinoma in China from 1991 to 2013, to predict the mortality in the ensuing five years, and to provide evidence for prevention and treatment of nasopharyngeal carcinoma. MATERIALS AND METHODS: Mortality data for Nasopharyngeal Carcinoma in China from 1991 to 2013 were used to describe its epidemiological characteristics, such as the change of the standardized mortality rate, sex and age differences, urban-rural differences. Trend-surface analysis was used to study the geographical distribution of the mortality. Curve estimation, time series, gray modeling, and joinpoint regression were used to predict the mortality for the ensuing five years in the future. RESULTS: In China, the standardized mortality rate of Nasopharyngeal Carcinoma increased with time from 1996, reaching the peak values of 1.45 /105 at the year of 2002, and decreased gradually afterwards. With males being 1.51 times higher than females, and the city had a higher rate than the rural during the past two decades. The mortality rate increased from age 40. Geographical analysis showed the mortality rate increased from middle to southern China. CONCLUSIONS: The standardized mortality rate of Nasopharyngeal Carcinoma is falling. The regional disease control for Nasopharyngeal Carcinoma should be focused on Guangdong province of China, and the key targets for prevention and treatment are rural men, especially after the age of 40. The mortality of Nasopharyngeal Carcinoma will decrease in the next five years.

Liver cancer mortality characteristics and trends in China from 1991 to 2012.

PURPOSE: To investigate the distribution of liver cancer mortality as well as its developing trend from l991 to 2012, forecast the future five-year trend, and provide a basis for the comprehensive prevention and management. MATERIALS AND METHODS: Mortality data for liver cancer in China from 1991 to 2012 were used to describe characteristics and distribution of liver cancer mortality. Trend surface analysis was used to study the geographical distribution of liver cancer mortality. Curve estimation, time series modeling, gray modeling (GM) and joinpoint regression were used to predict and forecast future trends. RESULTS: The mortality rate of liver cancer has constantly increased in China since 1991. Rates in rural areas are higher than in urban areas, and in males are higher than in females. In addition, our data predicted that the trend will continue to increase in the next 5 years. The age-specific mortality of liver cancer increases with age and peaks in the group of 80-84 years old. Geographical analysis showed the liver mortality rate was higher in the southeast provinces, such as Jiangsu, Zhejiang and Guangdong, and southwest regions like Guangxi Province. CONCLUSIONS: The standardized mortality rate of liver cancer in China has consistently increased from 1991 to 2012, and the upward trend is predicted to continue in the future. Much better prevention and management of liver cancer is needed in high mortality areas (the southwestern and southeastern parts of China) and high mortality age groups (80- to 84-year-olds), especially in rural areas.

Epidemiological characteristics and prediction of esophageal cancer mortality in China from 1991 to 2012.

BACKGROUND: To analyze the mortality distribution of esophageal cancer in China from 1991 to 2012, to forecast the mortality in the future five years, and to provide evidence for prevention and treatment of esophageal cancer. MATERIALS AND METHODS: Mortality data for esophageal cancer in China from 1991 to 2012 were used to describe its epidemiological characteristics, such as the change of the standardized mortality rate, urban-rural differences, sex and age differences. Trend-surface analysis was used to study the geographical distribution of the mortality. Curve estimation, time series, gray modeling, and joinpoint regression were used to predict the mortality for the next five years in the future. RESULTS: In China, the incidence rate of esophageal cancer from 2007 and the mortality rate of esophageal cancer from 2008 increased yearly, with males at 8.72/105 being higher than females, and the countryside at 15.5/105 being higher than in the city. The mortality rate increased from age 45. Geographical analysis showed the mortality rate increased from southern to eastern China, and from northeast to central China. CONCLUSIONS: The incidence rate and the standardized mortality rate of esophageal cancer are rising. The regional disease control for esophageal cancer should be focused on eastern, central and northern regions China, and the key targets for prevention and treatment are rural men more than 45 years old. The mortality of esophageal cancer will rise in the next five years.