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Fan W, Yang L, Li J, Dong B. Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:6914157. [PMID: 35096134 PMCID: PMC8791740 DOI: 10.1155/2022/6914157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/13/2021] [Accepted: 12/21/2021] [Indexed: 01/22/2023]
Abstract
This study was aimed at investigating the location of gastric cancer by using a gastroscope image based on an artificial intelligence algorithm for gastric cancer and the effect of ultrasonic-guided nerve block combined with general anesthesia on patients undergoing gastric cancer surgery. A total of 160 patients who were undergoing gastric cancer surgery from March 2019 to March 2021 were collected as the research objects, and the convolutional neural network (CNN) algorithm was used to segment the gastroscope image of gastric cancer. The patients were randomly divided into a simple general anesthesia group of 80 cases and a transversus abdominis plane block combined with rectus abdominis sheath block combined with the general anesthesia group of 80 cases. Then, compare the systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) at the four time points T0, T1, T2, and T3. The times of analgesic drug use within 48 hours after operation and postoperative adverse reactions were recorded. The visual analog scale (VAS) scores were also recorded at 4 h, 12 h, 24 h, and 48 h. The results show that the image quality after segmentation is good: the accuracy of tumor location is 75.67%, which is similar to that of professional endoscopists. Compared with the general anesthesia group, the transversus abdominis plane block combined with the rectus sheath block combined with the general anesthesia group had fewer anesthetics, and the difference was statistically significant (P < 0.05). Compared with the general anesthesia group, SBP, DBP, and HR were significantly reduced at T1, T2, and T3 in the transverse abdominis plane block combined with rectus sheath block and general anesthesia group (P < 0.05). Compared with the simple general anesthesia group, the VAS scores of the transversus abdominis plane block combined with rectus sheath block combined with the general anesthesia group decreased at 4 h, 12 h, and 24 h after surgery, and the difference was statistically significant (P < 0.05). The number of analgesics used in transversus abdominis plane block combined with the rectus sheath block combined with the general anesthesia group within 48 hours after operation was significantly less than that in the general anesthesia group, and the difference was statistically significant (P < 0.05). The average incidence of adverse reactions in the nerve block combined with the general anesthesia group was 2.5%, which was lower than the average incidence of 3.75% in the general anesthesia group. In summary, the CNN algorithm can accurately segment the lesions in the ultrasonic images of gastric cancer, which was convenient for doctors to make a more accurate judgment on the lesions, and provided a basis for the preoperative examination of radical gastrectomy for gastric cancer. Ultrasonic-guided nerve block combined with general anesthesia can effectively improve the analgesic effect of radical gastrectomy for gastric cancer, reduced intraoperative and postoperative adverse reactions and analgesic drug dosage, and had a good effect on postoperative recovery of patients. The combined application of these two methods can further improve the precision treatment of gastric cancer patients and accelerate postoperative recovery.
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Affiliation(s)
- Wanqiu Fan
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000 Sichuan, China
| | - Liuyingzi Yang
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000 Sichuan, China
- Maternal and Child Health Hospital of Shifang, Deyang, 618400 Sichuan, China
| | - Jing Li
- Department of Anesthesiology, People's Hospital of Yilong County, Nanchong, 636000 Sichuan, China
| | - Biqian Dong
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000 Sichuan, China
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Mendis S, Gill S. Cautious optimism-the current role of immunotherapy in gastrointestinal cancers. Curr Oncol 2020; 27:S59-S68. [PMID: 32368175 PMCID: PMC7193996 DOI: 10.3747/co.27.5095] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Immunotherapy has been described as the "fourth pillar" of oncology treatment, in conjunction with surgery, chemotherapy, and radiotherapy. However, the role of immunotherapy in gastrointestinal tumours is still evolving. Data for checkpoint inhibition in esophagogastric, hepatocellular, colorectal, and anal squamous cell carcinomas are expanding. In phase iii trials in the second-line setting, PD-1 inhibitors have demonstrated positive results for the subset of esophageal cancers that are positive for PD-L1 at a combined positive score of 10 or more. Based on results of phase ii trials, PD-1 inhibitors were approved in North America for use in PD-L1-positive chemorefractory gastric cancers, in hepatocellular carcinoma after sorafenib exposure, and in treatment-refractory deficient mismatch repair (dmmr) or high microsatellite instability (msi-h) tumours, regardless of tissue site. Combination use of PD-1 and ctla-4 inhibitors has been approved by the U.S. Food and Drug Administration for chemorefractory dmmr or msi-h colorectal cancer. Responses to checkpoint inhibition are durable, particularly in the dmmr or msi-h colorectal cancer cohort. As trials of combination immunotherapy, immunotherapy in combination with other systemic therapies, and immunotherapy in combination with other treatment modalities move forward in multiple tumour sites, cautious optimism is called for. The treatment landscape is continually changing, and expanded indications are likely to be just around the corner.
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Affiliation(s)
- S Mendis
- Medical Oncology, BC Cancer, Vancouver, BC
| | - S Gill
- Medical Oncology, BC Cancer, Vancouver, BC
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Shi S, Ye S, Mao J, Ru Y, Lu Y, Wu X, Xu M, Zhu T, Wang Y, Chen Y, Tang X, Xi Y. CMA1 is potent prognostic marker and associates with immune infiltration in gastric cancer. Autoimmunity 2020; 53:210-217. [PMID: 32129682 DOI: 10.1080/08916934.2020.1735371] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Background: Chymase 1 (CMA1), a gene known to be expressed in mast cells (MCs), is largely linked to immunity. However, the relationship between CMA1 and prognosis of multiple tumours and tumour-infiltrating lymphocytes (TILs) remains elusive.Methods: The differential expressions of CMA1 in different tumours and their corresponding normal tissues were evaluated via exploring Tumour Immune Estimation Resource (TIMER) and Oncomine database; the correlation within expression level of CMA1 and outcome of cancer patients was evaluated via Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA) database; the correlation between CMA1 and tumour immune cell infiltration was further investigated by TIMER; additionally, the correlation between CMA1 and gene signature pattern of immune infiltration were checked using TIMER and GEPIA.Results: There were significant differences in CMA1 expression levels between gastric cancer (GC) tissues and adjacent normal tissues. The high expression of CMA1 was closed related to poor overall survival (OS) and progression-free survival (PFS) in patients with GC (OS HR = 1.50, p = .00015; PFS HR = 1.33, p = .016). Especially, in GC patients at N1, N2 and N3 stages, high CMA1 expression was correlated with poor OS and PFS, but not with NO (p = .15, .09). The expression of CMA1 was positively associated with the levels of infiltrated CD4+, CD8+ T cells, neutrophils, macrophages, and dendritic cells (DCs) in GC. Whereas, CMA1 expression was considerably associated with various immune markers.Conclusion: CMA1 is a key gene whose expression level is significantly correlated with GC prognosis and infiltration levels of CD8+, CD4+ T cells, neutrophils, macrophages, and DCs in GC. In addition, the expression of CMA1 may be involved in regulating tumour-associated macrophages (TAMs), dendritic cells, exhausted T cells and regulatory T cells in GC. It suggests that CMA1 could be utilized as a prognostic marker and a sign of immune infiltration in GC.
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Affiliation(s)
- Shanping Shi
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Shazhou Ye
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Jianmei Mao
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Yuqing Ru
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Yicong Lu
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Xiaoyue Wu
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Mingjun Xu
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Tingwei Zhu
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Yibo Wang
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Yuanming Chen
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Xiaoli Tang
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
| | - Yang Xi
- Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo, China
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