1.Assessment of indocyanine green fluorescence imaging in hepatectomy for primary liver carcinoma: short-term prognostic analysis
Wenxin HUANG ; Qining HE ; Debin Qi ; Zichao Cao ; Yanzhi JIANG
Journal of Surgery Concepts & Practice 2025;30(4):325-331
Objective To explore the efficiency of indocyanine green (ICG) fluorescence imaging-guided hepatectomy and its short-term prognosis in patients with primary liver carcinoma. Methods Retrospective analysis was conducted on 166 patients diagnosed with primary liver carcinoma and admitted to the Department of Hepatobiliary Surgery of Shanghai General Hospital affiliated to Shanghai Jiao Tong University School of Medicine from June 2018 to June 2021. Patients were categorized into ICG group (n=72) and non-ICG group (n=94) based on the utilization of ICG during surgery. Moreover, the clinical information of preoperation, intraoperation, and postoperation were collected and compared between the two groups. ICG fluorescence images of the lesions in the ICG group were recorded for analysis. Results ICG fluorescence intensity is associated with the histopathology, differentiation grade of primary liver cancer, and the presence of liver cirrhosis. Hepatocellular carcinoma lesions predominantly displayed partial fluorescence, while intrahepatic cholangiocarcinoma lesions showed circular fluorescence. Well differentiated tumors exhibited complete fluorescence (7/11), moderately differentiated tumors demonstrated partial fluorescence (28/51), and poorly differentiated tumors displayed circular fluorescence (7/10). Most patients with liver cirrhosis exhibited partial fluorescence (18/35) or complete fluorescence (13/35).Compared to the non-ICG group, the ICG group demonstrated higher serum albumin levels on the first (34.6 g/L vs. 31.4 g/L) and the third postoperative days (32.4 g/L vs. 31.2 g/L)(P<0.001). Conversely, the ICG group showed shorter operation time (170 min vs. 210 min), lower rate of intraoperative hepatic portal blockade (9.7% vs. 33.0%), less intraoperative blood loss (400 mL vs. 430 mL), shorter postoperative hospital stay (10 d vs. 14 d), and lower incidence of short-term postoperative complications (4.2% vs. 20.2%) (P<0.05) compared to the non-ICG group. Conclusions ICG fluorescence intensity is associated with the histopathology, differentiation grade of primary liver cancer, and the presence of liver cirrhosis.The judicious application of ICG fluorescence imaging technology alongside surgical techniques holds promise for improving short-term prognosis and expediting the postoperative recovery.
2.Dual-tracer PET image separation using three-dimensional depthwise separable convolution network
Dayang TANG ; Debin HU ; Hongliang QI ; Hao SUN ; Yanjiang HAN ; Hanwei LI ; Xinming ZHANG ; Zhilin PAN ; Wenjie YU ; Lijun LU ; Hongwen CHEN
Chinese Journal of Medical Physics 2025;42(2):160-166
Objective To propose a novel method based on three-dimensional depthwise separable convolution network(3D DSN)for the separation of PET images with dual tracers of 18F-FDG and 18F-FAPI.Methods A total of 120 pairs of 18F-FDG and 18F-FAPI PET images of the same patient scanned separately at different time points were collected,and the dual-tracer PET image was generated through simulation.After the image registration of PET images of two tracers for ensuring spatial position matching,the registered PET images were forward-projected to generate sinogram data,and the sinogram data of two tracers were accumulated to obtain mixed sinogram data.Subsequently,the dual-tracer PET image was reconstructed using maximum likelihood expectation maximization and input into a 3D DSN based network for image separation,thereby obtaining PET images of two single tracers.Results Compared with 3D CNN method,the proposed method increased the structure similarity index measure(SSIM)of the separated 18F-FDG images to the real 18F-FDG images by 0.87%,increased the peak signal-to-noise ratio(PSNR)by 11.8%,and reduced the normalized root mean square error(NRMSE)by 52%.The SSIM of the separated 18F-FAPI images to the real 18F-FAPI images increased by 1.1%,PSNR increased by 17.0%,and NRMSE decreased by 51%.Conclusion The proposed method can be effectively applied to simultaneous PET imaging with dual PET tracers,reducing the number of scans and costs in time and money,and providing clinical doctors more accurate and abundant diagnostic information.
3.Dual-tracer PET image separation using three-dimensional depthwise separable convolution network
Dayang TANG ; Debin HU ; Hongliang QI ; Hao SUN ; Yanjiang HAN ; Hanwei LI ; Xinming ZHANG ; Zhilin PAN ; Wenjie YU ; Lijun LU ; Hongwen CHEN
Chinese Journal of Medical Physics 2025;42(2):160-166
Objective To propose a novel method based on three-dimensional depthwise separable convolution network(3D DSN)for the separation of PET images with dual tracers of 18F-FDG and 18F-FAPI.Methods A total of 120 pairs of 18F-FDG and 18F-FAPI PET images of the same patient scanned separately at different time points were collected,and the dual-tracer PET image was generated through simulation.After the image registration of PET images of two tracers for ensuring spatial position matching,the registered PET images were forward-projected to generate sinogram data,and the sinogram data of two tracers were accumulated to obtain mixed sinogram data.Subsequently,the dual-tracer PET image was reconstructed using maximum likelihood expectation maximization and input into a 3D DSN based network for image separation,thereby obtaining PET images of two single tracers.Results Compared with 3D CNN method,the proposed method increased the structure similarity index measure(SSIM)of the separated 18F-FDG images to the real 18F-FDG images by 0.87%,increased the peak signal-to-noise ratio(PSNR)by 11.8%,and reduced the normalized root mean square error(NRMSE)by 52%.The SSIM of the separated 18F-FAPI images to the real 18F-FAPI images increased by 1.1%,PSNR increased by 17.0%,and NRMSE decreased by 51%.Conclusion The proposed method can be effectively applied to simultaneous PET imaging with dual PET tracers,reducing the number of scans and costs in time and money,and providing clinical doctors more accurate and abundant diagnostic information.
4.LSTM-XGBoost Based RR Intervals Time Series Prediction Method in Hypertensive Patients
Wenjie YU ; Hongwen CHEN ; Hongliang QI ; Zhilin PAN ; Hanwei LI ; Debin HU
Chinese Journal of Medical Instrumentation 2024;48(4):392-395
Objective The prediction of RR intervals in hypertensive patients can help clinicians to analyze and warn patients'heart condition.Methods Using 8 patients'data as samples,the RR intervals of patients were predicted by long short-term memory network(LSTM)and gradient lift tree(XGBoost),and the prediction results of the two models were combined by the inverse variance method to overcome the disadvantage of single model prediction.Results Compared with the single model,the proposed combined model had a different degree of improvement in the prediction of RR intervals in 8 patients.Conclusion LSTM-XGBoost model provides a method for predicting RR intervals in hypertensive patients,which has potential clinical feasibility.
5.Design of a software for multimodal radiomics features mining and analysis based on artificial intelligence
Ye CHEN ; Hanwei LI ; Debin HU ; Hongliang QI ; Hongwen CHEN
Chinese Journal of Medical Physics 2024;41(12):1578-1584
Various types of software needed in radiomics studies come with the problems such as data incompatibility and hyperparameter tuning.Therefore,an artificial intelligence-based software is developed for radiomics studies,providing doctors and researchers a solution with image preprocessing,feature extraction,feature selection,modeling analysis and data visualization.The usability of the software is demonstrated using a public data set.Eight sets of feature selectors and classifiers are established for classification predication on test data set and key performance indicator output.Through hyperparameter tuning,the model is further optimized.Researchers will focus more on the research itself rather than unnecessary development efforts,and radiomics studies will become more convenient and efficient with the software addressed.
6.Design of a software for multimodal radiomics features mining and analysis based on artificial intelligence
Ye CHEN ; Hanwei LI ; Debin HU ; Hongliang QI ; Hongwen CHEN
Chinese Journal of Medical Physics 2024;41(12):1578-1584
Various types of software needed in radiomics studies come with the problems such as data incompatibility and hyperparameter tuning.Therefore,an artificial intelligence-based software is developed for radiomics studies,providing doctors and researchers a solution with image preprocessing,feature extraction,feature selection,modeling analysis and data visualization.The usability of the software is demonstrated using a public data set.Eight sets of feature selectors and classifiers are established for classification predication on test data set and key performance indicator output.Through hyperparameter tuning,the model is further optimized.Researchers will focus more on the research itself rather than unnecessary development efforts,and radiomics studies will become more convenient and efficient with the software addressed.
7. Study on the health literacy and related factors of the cancer prevention consciousness among urban residents in China from 2015 to 2017
Chengcheng LIU ; Chunlei SHI ; Jufang SHI ; Ayan MAO ; Huiyao HUANG ; Pei DONG ; Fangzhou BAI ; Yunsi CHEN ; Debin WANG ; Guoxiang LIU ; Xianzhen LIAO ; Yana BAI ; Xiaojie SUN ; Jiansong REN ; Li YANG ; Donghua WEI ; Bingbing SONG ; Haike LEI ; Yuqin LIU ; Yongzhen ZHANG ; Siying REN ; Jinyi ZHOU ; Jialin WANG ; Jiyong GONG ; Lianzheng YU ; Yunyong LIU ; Lin ZHU ; Lanwei GUO ; Youging WANG ; Yutong HE ; Peian LOU ; Bo CAI ; Xiaohua SUN ; Shouling WU ; Xiao QI ; Kai ZHANG ; Ni LI ; Wanghong XU ; Wuqi QIU ; Min DAI ; Wanqing CHEN
Chinese Journal of Preventive Medicine 2020;54(1):47-53
Objective:
To understand the health literacy and relevant factors of cancer prevention consciousness in Chinese urban residents from 2015 to 2017.
Methods:
A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. The self-designed questionnaire was used to collect the information of demographic characteristics and cancer prevention consciousness focusing on nine common risk factors, including smoking, alcohol, fiber food, food in hot temperature or pickled food, chewing betel nut, helicobacter pylori, moldy food, hepatitis B infection, estrogen, and exercise. The logistic regression model was adopted to identify the influencing factors.
Results:
The overall health literacy of the cancer prevention consciousness was 77.4% (24 980 participants), with 77.4% (12 018 participants), 79.9% (6 406 participants), 77.2% (1 766 participants) and 74.5% (4 709 participants) in each group (
8. Analysis on the consciousness of the cancer early detection and its influencing factors among urban residents in China from 2015 to 2017
Ayan MAO ; Jufang SHI ; Wuqi QIU ; Chengcheng LIU ; Pei DONG ; Huiyao HUANG ; Kun WANG ; Debin WANG ; Guoxiang LIU ; Xianzhen LIAO ; Yana BAI ; Xiaojie SUN ; Jiansong REN ; Li YANG ; Donghua WEI ; Bingbing SONG ; Haike LEI ; Yuqin LIU ; Yongzhen ZHANG ; Siying REN ; Jinyi ZHOU ; Jialin WANG ; Jiyong GONG ; Lianzheng YU ; Yunyong LIU ; Lin ZHU ; Lanwei GUO ; Youqing WANG ; Yutong HE ; Peian LOU ; Bo CAI ; Xiaohua SUN ; Shouling WU ; Xiao QI ; Kai ZHANG ; Ni LI ; Min DAI ; Wanqing CHEN
Chinese Journal of Preventive Medicine 2020;54(1):54-61
Objective:
To understand the consciousness of the cancer early detection among urban residents and identify the influencing factors from 2015 to 2017.
Methods:
A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. Self-designed questionnaires were used to collect population, socioeconomic indicators, self-cancer risk assessment, regular participation in physical examination and other information. The multivariate logistic regression model was used to identify the factors of people who had not regularly participated in the regular physical examination in the past five years.
Results:
The self-assessment results of 32 357 residents showed that there were 27.54% (8 882) of total study population with self-reported cancer risk, 45.48% (14 671) without cancer risk and 26.98% (8 704) with unclear judgement on their own cancer risk. Among population with cancer risk, 79.84% (7 091) considered physical examination accounted. In the past five years, there were 21 105 (65.43%) residents participated in regular physical examination and 11 148 (34.56%) participated in non-scheduled one, respectively. The multivariate logistic regression analysis showed that compared with unmarried and western region residents, divorced, middle and eastern region residents had a stronger consciousness to participate in the regular physical examination (
9. Analysis on the consciousness of the early cancer diagnosis and its related factors among urban residents in China from 2015 to 2017
Xuan CHENG ; Pei DONG ; Jufang SHI ; Wuqi QIU ; Chengcheng LIU ; Kun WANG ; Huiyao HUANG ; Yana BAI ; Xiaojie SUN ; Debin WANG ; Guoxiang LIU ; Xianzhen LIAO ; Li YANG ; Donghua WEI ; Bingbing SONG ; Haike LEI ; Yuqin LIU ; Yongzhen ZHANG ; Siying REN ; Jinyi ZHOU ; Jialin WANG ; Jiyong GONG ; Lianzheng YU ; Yunyong LIU ; Lin ZHU ; Lanwei GUO ; Youqing WANG ; Yutong HE ; Peian LOU ; Bo CAI ; Xiaohua SUN ; Shouling WU ; Xiao QI ; Kai ZHANG ; Ni LI ; Jiansong REN ; Wanqing CHEN ; Min DAI ; Ayan MAO
Chinese Journal of Preventive Medicine 2020;54(1):62-68
Objective:
To understand the consciousness of the cancer early diagnosis among urban residents and identify the related factors from 2015 to 2017.
Methods:
A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. The general demographic characteristics, the consciousness of the cancer early diagnosis (whether people would have a willingness or encourage their relatives/friends to confirm the abnormal results once which were detected from the physical examination) and other information were collected by using the self-designed questionnaire. The non-conditional logistic regression model was used to identify the relateol factors related to the consciousness of the cancer early diagnosis.
Results:
As for residents with abnormal result from the physical examination, 89.29% (28 802) of residents would choose to seek medical treatment for further diagnosis. If their relatives/friends had abnormal results from the physical examination, 89.55% (28 886) of residents would encourage their relatives/friends to confirm the diagnosis in time. The non-conditional logistic regression model analysis showed that compared with the public institution staff/civil servants, annual household income less than 20 000 CNY, the western region and the cancer risk assessment/screening intervention population, the company staff, annual household income about 40 000 CNY and more, and the residents from the middle and eastern region had a stronger consciousness to seek further diagnosis; while the unemployed residents and community residents were less likely to seek further diagnosis (
10. Analysis on the consciousness of the early cancer treatment and its influencing factors among urban residents in China from 2015 to 2017
Huichao LI ; Kun WANG ; Yannan YUAN ; Ayan MAO ; Chengcheng LIU ; Shuo LIU ; Lei YANG ; Huiyao HUANG ; Pei DONG ; Debin WANG ; Guoxiang LIU ; Xianzhen LIAO ; Yana BAI ; Xiaojie SUN ; Jiansong REN ; Li YANG ; Donghua WEI ; Bingbing SONG ; Haike LEI ; Yuqin LIU ; Yongzhen ZHANG ; Siying REN ; Jinyi ZHOU ; Jialin WANG ; Jiyong GONG ; Lianzheng YU ; Yunyong LIU ; Lin ZHU ; Lanwei GUO ; Youqing WANG ; Yutong HE ; Peian LOU ; Bo CAI ; Xiaohua SUN ; Shouling WU ; Xiao QI ; Kai ZHANG ; Ni LI ; Min DAI ; Wanqing CHEN ; Ning WANG ; Wuqi QIU ; Jufang SHI
Chinese Journal of Preventive Medicine 2020;54(1):69-75
Objective:
To understand the consciousness of the cancer early treatment and its demographic and socioeconomic factors.
Methods:
A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China (CanSPUC) from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. The questionnaire collected personal information, the consciousness of the cancer early treatment and relevant factors. The Chi square test was used to compare the difference between the consciousness of the cancer early treatment and relevant factors among the four groups. The logistic regression model was used to analyze the influencing factors related to the consciousness of the cancer early treatment.
Results:
With the assumption of being diagnosed as precancer or cancer, 89.97% of community residents, 91.84% of cancer risk assessment/screening population, 93.00% of cancer patients and 91.52% of occupational population would accept active treatments (

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