1.Virtual surgery for choledocholithiasis
Chihua FANG ; Yunqiang TANG ; Yanpeng HUANG ; Fengping PENG ; Jiahui PAN ; Susu BAO
Chinese Journal of Digestive Surgery 2009;8(5):367-369
Objective To study the image segmentation, three-dimensional (3D) reconstruction and simulation operation of choledocholithotomy and T-tube drainage based on the computed tomagraphy (CT) data of patient with choledocholithiasis. Methods Patient with choledocholithiasis underwent 64-slice spiral CT imaging. The images segmentation and 3D reconstruction were performed by Medical Image Process System (MIPS) to construct the 3D model of the hepatobiliary system. The model was modified by FreeForm Modeling System. The virtual surgical instruments were developed by GHOST SDK software, and were imported to the virtual surgery. Results The data of plain, arterial phase, venous phase and portal venous phase scanning were collected, and the data stored in DICOM format were transformed to BMP format. A model of the hepatobiliary system was constructed after the data was segmented by MIPS, and then the model was exported in the STL format. The data in STL format were imported to FreeForm Modeling System for smoothing the model. Different structures were assigned different colors to make the model more vivid. The self-developed virtual surgical instruments were imported to the system, and the virtual surgery for choledocholithiasis was performed with PHANToM. Conclusions With the help of MIPS, the image segmentation and 3D reconstruction of the model are finished rapidly and effectively. After the virtual surgical instruments are developed in FreeForm Modeling System, the virtual surgery can be achieved in the 3D model with the assistance of PHANToM.
2.An extensive DeBakey type IIIb aortic dissection with massive right pleural effusion presenting as abdominal pain and acute anemia:particular case report
Huichun YU ; Zhenqing WANG ; Yuanyuan HAO ; Fengping AN ; Yuchuan HU ; Ruibing DENG ; Peng YU ; Guangbin CUI ; He LI
Journal of Geriatric Cardiology 2015;(3):319-322
We describe the case of a 79-year-old male presented with sudden onset of abdominal pain and mild breathlessness, and complicated acute progressive anemia with haemoglobin which declined from 120 g/L to 70 g/L within five days. An urgent computed tomography an-giography showed acute thoracic aortic dissection, DeBakey type IIIb, a dissecting aneurysm in the proximal descending thoracic aorta start-ing immediately after the origin of the left subclavian artery and extending distally below the renal arteries with evidence of rupture into the right pleural cavity for massive pleural effusion. Plasma D-dimer, brain natriuretic peptide and C reactive protein level were elevated. Our case showed that D-dimer can be used as a‘rule-out’ test in patients with suspected aortic dissection. A raised BNP may exert a protective role through anti-inflammatory endothelial actions in the systemic circulation.
3.The bone turnover markers of myeloma bone disease.
Chinese Journal of Hematology 2014;35(11):1030-1033
4.Construction of digital three-dimensional models of renal stones and virtual surgery simulation.
Yuanbo CHEN ; Hulin LI ; Chunxiao LIU ; Kai XU ; Yangyan LIN ; Susu BAO ; Fengping PENG ; Jiahui PAN
Journal of Southern Medical University 2013;33(2):267-270
OBJECTIVETo construct three-dimensional (3D) models of renal stones and perform percutaneous nephrolithotomy (PCNL) virtual surgery simulation. Methods CT images were obtained from 8 patients with renal stones. Images segmentation and reconstruction were performed using MIMICS 10.0 software to construct the 3D model of the renal stones, which provided the anatomical relationships between the kidney and the adjacent organs. The optimal PCNL virtual surgery simulation for each individual case was performed using FreeForm Modeling System on the basis of the 3D model.
RESULTSEight 3D models of renal stone were constructed. The 3D model of the renal stones represented the interrelationships of the stones, intrarenal vessel, and the collecting system with the adjacent anatomical structures. Individualized PCNL virtual surgery simulations including percutaneous puncture, dilatation and pneumatic lithotripsy were performed successfully in all the 8 3D models.
CONCLUSIONDigital 3D model of renal stone provides the reliable and comprehensive imaging information for surgical design, and PCNL virtual surgery simulation has important clinical significance to improve the stone clearance rate and reduce the surgical complications.
Adult ; Female ; Humans ; Imaging, Three-Dimensional ; Kidney Calculi ; diagnostic imaging ; surgery ; Male ; Middle Aged ; Nephrostomy, Percutaneous ; methods ; Software ; Tomography, Spiral Computed ; User-Computer Interface
5.Therapeutic effect and prognosis of linalutide in diabetic nephropathy
Chenglong ZHANG ; Dongmei CHEN ; Qing PENG ; Wen MENG ; Fengping WANG
Chinese Journal of Postgraduates of Medicine 2023;46(10):890-895
Objective:To investigate the effect of linalutide on adipocytokine, blood glucose and renal function in diabetic nephropathy (DN) patients.Methods:One hundred DN patients diagnosed and treated by Chengdu Second People′s Hospital and Chunxi Community Health Service Center of Jinjiang District and Shuyuan Community Health Service Center of Jinjiang District from January 2018 to June 2019 were selected and divided into metformin group (48 cases) and combined group (52 cases) according to different treatment regimens. Metformin group was treated with metformin, the combined group was treated with linalutide on the basis of metformin group, and both groups were treated for 12 weeks. The therapeutic efficacy, adipocytokine index adiponectin (ADPN), secretory-type curl-related proteins-5(SFRP5), omentin-1; blood glucose index fasting blood glucose (FBG), 2 h postprandial blood glucose (2hPBG), glycosylated hemoglobin (HbA 1c), fasting insulin (FINS), insulin resistance index(HOMA-IR), and renal function index urinary albumin excretion rate (UAER), albumin creatinine ratio(ACR), liver-type fatty acid binding protein(L-FABP) were compared between the two groups and the prognosis was analyzed. Results:The total effective rate in the combined group at 4, 8 and 12 weeks were higher than those in the metformin group and the longer treatment, the higher total effective, there were statistical differences ( χ2 group = 4.61, χ2 time point = 78.57, P<0.05). Before treatment, there were no significant differences in serum FBG, 2hPBG, HbA 1c, FINS, HOMA-IR, ADPN, SFRP5, omentin-1, urine UAER, ACR and L-FABP between the two groups ( P>0.05). After treatment, the levels of serum FBG, 2hPBG, HbA 1c, FINS, HOMA-IR, urine UAER, ACR and L-FABP in the combined group were lower than those in the metformin group: (7.17 ± 1.62) mmol/L vs. (8.75 ± 2.11) mmol/L, (5.54 ± 1.11)mmol/L vs. (6.56 ± 1.08) mmol/L, (6.63 ± 0.92)% vs. (7.95 ± 0.89)%, (7.12 ± 1.17) mU/L vs. (8.72 ± 1.58)mU/L, 3.52 ± 0.88 vs. 4.04 ± 0.70, (28.65 ± 3.22) mg/24 h vs. (65.42 ± 6.85) mg/24 h, (56.24 ± 7.68) μg/mg vs. (92.68 ± 9.29) μg/mg, (8.62 ± 1.08) μg/(g·Cr) vs. (14.62 ± 1.85) μg/(g·Cr); the levels of ADPN, SFRP5 and omentin-1 were higher than those in the metformin group: (14.53 ± 2.43) mg/L vs. (10.21 ± 2.12) mg/L, (12.81 ± 2.31) μg/L vs. (8.75 ± 2.18) μg/L, (48.49 ± 5.28) μg/L vs. (36.57 ± 4.32) μg/L, there were statistical differences ( P<0.05). After treatment, the incidence of end-point events in the combined group was 7.69% (4/52), which was lower than that in the metformin group 22.92% (11/48), and there was statistical differences ( χ2 = 4.57, P<0.05). The survival analysis showed that the survival time and median survival time after treatment in the combined group were higher than those in the metformin group ( P<0.05). Conclusions:Linalutid can effectively improve blood glucose level and renal function in DN patients, and has obvious effect on adipocykine secretion, which is conducive to improve prognosis.
6.A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies.
Xiaoya ZHANG ; Xiaohong PENG ; Chengsheng HAN ; Wenzhen ZHU ; Lisi WEI ; Yulin ZHANG ; Yi WANG ; Xiuqin ZHANG ; Hao TANG ; Jianshe ZHANG ; Xiaojun XU ; Fengping FENG ; Yanhong XUE ; Erlin YAO ; Guangming TAN ; Tao XU ; Liangyi CHEN
Protein & Cell 2019;10(4):306-311