Influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer and analysis of the application value of carbon nano-tracers

Influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer and analysis of the application value of carbon nano-tracers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer and analysis of the application value of carbon nano-tracers Bingkai Xie, Guihe Lin, Zhijian Wang, Dongbo Xu, Jianxun Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4152681/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To investigate the influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer (CRC) and the application value of carbon nanoparticle tracing. A total of 120 patients with CRC who underwent minimally invasive radical surgery were included. They were divided into groups according to whether they were grouped by carbon nano-tracers, and the baseline data were matched by propensity score method. Univariate and multivariate methods were used to evaluate lymph nodes and positive lymph nodes after minimally invasive radical surgery. The number of detected independent factors. After propensity score matching, there were 37 patients in the tracer group and the non-tracer group; there was no significant difference in baseline data between the two groups; the number of positive lymph nodes detected in the tracer group was significantly higher than that in the non-tracer group. The results of univariate analysis showed that gender, lesion location, maximum tumor diameter, and whether to perform nanocarbon tracing were all related to the number of lymph nodes detected after minimally invasive radical surgery. Nanocarbon tracing was an independent influencing factor for the number of lymph nodes detected after minimally invasive radical surgery. Pathological type, T stage, histopathological grade, nerve invasion, and whether or not with cancer nodules were all related to the number of positive lymph nodes detected after minimally invasive radical surgery; multivariate analysis showed that T stage, pathological Histological grade, vascular invasion, and cancer nodules were all independent influencing factors for the number of positive lymph nodes detected after minimally invasive radical surgery. The number of lymph nodes detected in patients with CRC after minimally invasive radical surgery is closely related to the location of the lesion and whether carbon nanoparticle tracing is performed; those with T2-4 stage, histological grade 3–4, combined with vascular invasion and cancer nodules are more likely to Positive lymph nodes were detected. Colorectal cancer Detection Metastasis Lymph node Nano carbon tracer Figures Figure 1 Figure 2 1. Introduction Colorectal cancer (CRC) is one of the most common clinical malignant tumors of digestive system, and its morbidity and mortality ranks third and fifth among all malignant tumors, respectively. In recent years, with the popularization of the concept of early cancer detection/screening and the widespread development of endoscopy, the early detection rate of CRC has been increasing every year [ 1 ]. At present, it is believed that endoscopic non-curative resection, small volume, multiple primary and postoperative recurrence of CRC surgical radical resection is closely related to the accurate localization of the lesion [ 2 ]. There are many existing CRC localization methods, but the localization error rate of barium colonography, CT and colonoscopy can reach 10–35%; dye injection under colonoscopy can effectively improve the accuracy of lesion localization, but traditional methylene blue Due to the small diameter of the particles, they are easy to diffuse rapidly, leading to contamination of the surgical field, and the residence time in the tissue is short [ 3 – 4 ]. Nanocarbon is a new type of dyeing material, which has been widely used in malignant tumor surgery due to its advantages such as good histocompatibility, accurate positioning, long-lasting staining and lymph node tracing [5]. Reports have confirmed that nanocarbon tracing can increase the number of lymph nodes detected in CRC patients after surgery, but there is no clear conclusion on whether it can increase the detection of positive lymph nodes [6]. This study included a total of 120 patients with CRC who underwent minimally invasive radical surgery from October 2019 to May 2021 in the Department of Gastrointestinal Surgery, Longyan First Affiliated Hospital of Fujian Medical University.To explore the influencing factors of lymph node detection after minimally invasive radical surgery in CRC patients and the application value of carbon nano-tracers. 2. Materials and methods 2.1. General information A total of 120 patients with CRC who underwent minimally invasive radical surgery were included in the study. Inclusion criteria: 1- Histopathologically confirmed CRC; 2- Histopathological type belongs to adenocarcinoma; 3- Successfully completed laparoscopic radical resection + D3 lymph node dissection; 4- Elective surgery; 5- The same group of surgeons completed the operation. Exclusion criteria: 1- previous abdominal surgery; 2- emergency surgery; 3- CRC recurrence; 4- received neoadjuvant therapy before surgery; The study design conformed to the requirements of the Declaration of Helsinki. This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Longyan First Hospital of Fujian Province, informed consent was obtained from all subjects and/or their legal guardian(s). 2.2. Nanocarbon tracer Indications for the application of nanocarbon tracers were as follows: Imaging is difficult to locate accurately; Radical surgery is performed after non-curative endoscopic biopsy surgery; Mechanical bowel preparation was performed 1–2 days before surgery, and the electronic colonoscope was placed under the microscope. To mark the location of the lesion, we pierced the submucosa at a 45° angle, injected 0.5 mL of 0.9% sodium chloride solution to stimulate the mucosal bulge, and then injected 0.1 mL of nanocarbon stock solution (Chongqing Laimei Pharmaceutical). If the endoscope could pass through the lesion area smoothly, we injected at 1 cm on the side of the lesion and 1 cm on the side of the anus (total 4 points); Each quadrant was injected separately (4 points in total). 2.3. Laparoscopic radical surgery Under general anesthesia and tracheal intubation, the surgical plan was determined according to the location of the lesion, and total mesocolectomy or total mesorectal excision was used to complete laparoscopic radical resection + D3 lymph node dissection;, Complete excision of the intestinal segment, mesentery and mesangial root lymphatic and adipose tissue where the lesion was located, and dissection of the paraintestinal, middle and central lymph nodes at the same time (Fig. 1 ). 2.4. Observation indicators Review the clinicopathological data of the case records, including gender, age, height, age, lesion location, histopathological type, maximum diameter of the lesion, T stage, histological grade, vascular and nerve invasion, cancer nodule and lymph node detection, etc. 2.5. Statistical processing SPSS 24.0 software was used to analyze the data; gender, age, height, lesion location, histopathological type, maximum diameter of the lesion, T stage, histological grade, vascular and nerve invasion, cancer nodules and lymph node detection were included. A fixed-effect variable was used to calculate the propensity score; the propensity score was matched by the nearest neighbor matching method of 1:1, and the matching tolerance was 0.02; the Kolmogorov-Smirnov test was used to complete the normality evaluation, and the paired t test was used to compare the measurement data that conformed to the normal distribution., expressed as (x ± s); Mann-Whitney U test was used for comparison of measurement data that did not conform to the normal distribution, expressed as M (P25, P75); χ2 test was used for comparison of count data, expressed as rate; Poisson regression was used for multivariate analysis Multivariate model; P < 0.05 was considered statistically significant. 3. Results 3.1. Analysis of baseline data after matching Among the 120 patients, 43 underwent preoperative colonoscopy with nanocarbon tracing. During the operation, black staining of the tumor site was clearly seen (Fig. 1 ), and no complications occurred. After propensity score matching, there were 37 patients in the tracer group and the non-tracer group; there was no significant difference in baseline data between the two groups (P > 0.05) (Table 1 ). Table 1 Analysis of baseline data after matching Index Non tracer group (n = 37) Tracer group (n = 37) χ2 P Value Gender 0.48 0.42 Male 22 25 Female 15 12 Age (years old) 0.07 0.86 < 60 17 18 ≥ 60 20 19 BMI(kg/m 2 ) 0.08 0.84 < 24 16 17 ≥ 24 21 20 Lesion location 2.44 0.20 Right hemicolon 7 7 Left hemicolon 10 16 Rectum 20 14 Pathological type 1.35 0.33 Uplift type 32 27 Ulcerative type 5 10 Maximum diameter lesion (cm) 0.25 0.69 < 4 30 28 ≥ 4 7 9 T stage 1.19 0.39 Tis 6 4 T 1 12 14 T 2 10 9 T 3 7 9 T 4 2 1 Histological grading 0.23 0.71 Grade 1 ~ 2 30 32 Grade 3 ~ 4 7 5 Vascular invasion 0.05 0.90 No 33 32 Yes 4 5 Nerve invasion 0.22 0.73 No 36 34 Yes 1 3 Carcinoma nodule 0.05 0.90 No 35 34 Yes 2 3 3.2. Lymph node detection and metastasis The number of detected lymph nodes and the number of metastasis-positive lymph nodes in the observation group were significantly higher than those in the control group, and the number of lymph nodes with a diameter of less than 5 mm and the number of metastasis-positive lymph nodes were significantly higher than those in the control group (P < 0.05, Fig. 2 ). The black staining rate of lymph nodes with a diameter of less than 3 mm in the observation group was significantly higher than that of lymph nodes with a diameter of more than 3 mm (P < 0.05, Fig. 2 ). 3.3. Lymph node detection after minimally invasive radical surgery Among the 37 patients in the tracer group, 1 patient was excluded due to staining problems, and 726 lymph nodes were detected in the remaining 36 patients, and the median number of lymph nodes detected was 19 (14, 25); 38 positive lymph nodes were detected, and the median number of lymph nodes detected The number of outputs was 0 (0, 2). In the non-tracer group, 614 lymph nodes were detected, and the median number of lymph nodes was 17 (14, 20); 23 positive lymph nodes were detected, and the median number of positive lymph nodes was 0 (0, 0). The number of positive lymph nodes detected in the tracer group was significantly higher than that in the non-tracer group (P 0.05). 3.4. Analysis of influencing factors on the number of lymph nodes detected after minimally invasive radical surgery The results of univariate analysis showed that gender, age, lesion location, maximum tumor diameter, and whether nanocarbon tracing was performed were associated with the number of lymph nodes detected after minimally invasive radical surgery (P < 0.05). The results of multivariate analysis showed that the location of the lesion and whether to perform nanocarbon tracing were independent influencing factors of the number of lymph nodes detected after minimally invasive radical surgery (P < 0.05) (Table 2 – 3 ). Table 2 Univariate analysis of influencing factors on the number of lymph nodes detected after minimally invasive radical surgery Index N Number of lymph nodes [ n , M (P25, P75) ] Z P Value Gender 3.72 0.02* Male 47 17(15, 21) Female 26 19(16, 25) Age (years old) 3.22 0.03* < 60 34 19(16, 23) ≥ 60 39 17(15, 22) BMI(kg/m 2 ) 0.28 0.46 < 24 34 19(16, 23) ≥ 24 39 17(15, 21) Lesion location 4.93 0.01* Right hemicolon 13 25(17, 32) Left hemicolon 26 18(14, 21) Rectum 34 17(15, 21) Pathological type 1.09 0.45 Uplift type 59 18(15, 22) Ulcerative type 14 18(16, 25) Maximum diameter lesion (cm) 4.02 0.03* < 4 60 18(15, 22) ≥ 4 13 20(16, 25) T stage 0.85 0.58 T is 9 16(12, 20) T 1 26 18(15, 22) T 2 20 17(15, 21) T 3 16 19(16, 24) T 4 2 20(13, 27) Histological grading 1.15 0.26 Grade 1 ~ 2 62 18(16, 22) Grade 3 ~ 4 11 19(14, 22) Vascular invasion 0.57 0.56 No 64 18(15, 22) Yes 9 20(16, 27) Nerve invasion 0.93 0.33 No 70 18(15, 22) Yes 3 25(11, 30) Carcinoma nodule 1.36 0.61 No 69 18(15, 22) Yes 4 16(13, 28) Nano carbon tracer 2.9 0.03* No 37 17(14, 20) Yes 36 19(14, 25) Table 3 Multivariate analysis of influencing factors on the number of lymph nodes detected after minimally invasive radical surgery Index B SE χ2 OR 95%CI P Left hemicolon -0.45 0.07 68.54 0.77 0.50 ~ 0.96 < 0.001 Rectum -0.30 0.05 35.96 0.85 0.62 ~ 0.99 < 0.001 Nano carbon tracer 0.28 0.03 32.10 1.29 1.03 ~ 1.85 < 0.001 3.5. Analysis of influencing factors on the number of positive lymph nodes detected after minimally invasive radical surgery The results of univariate analysis showed that the pathological type, T stage, histopathological grade, vascular invasion, nerve invasion and whether it was associated with cancer nodules [no vs yes: 0 (0, 0) vs 4 (2, 9)] All were related to the number of positive lymph nodes detected after minimally invasive radical surgery (P < 0.05); multivariate analysis showed that T stage, histopathological grade, vascular invasion and combined cancer nodules were all positive after minimally invasive radical surgery The number of lymph nodes detected was an independent factor (P < 0.05) (Table 4 – 5 ). Table 4 Univariate analysis of influencing factors on the number of positive lymph nodes after minimally invasive radical surgery. Index N Number of lymph nodes [ n , M (P25, P75) ] Z P Value Gender 6.35 0.68 Male 47 0(0, 0) Female 26 0(0, 1) Age (years old) 5.93 0.54 < 60 34 0(0, 1) ≥ 60 39 0(0, 0) BMI(kg/m 2 ) 3.76 0.81 < 24 34 0(0, 1) ≥ 24 39 0(0, 0) Lesion location 2.90 0.55 Right hemicolon 13 0(0, 0) Left hemicolon 26 0(0, 0) Rectum 34 0(0, 1) Pathological type 0.87 0.02 Uplift type 59 0(0, 0) Ulcerative type 14 1(0, 4) Maximum diameter lesion (cm) 3.39 0.52 < 4 60 0(0, 0) ≥ 4 13 0(0, 1) T stage 1.01 0.01* T is 9 0(0, 0) T 1 26 0(0, 0) T 2 20 0(0, 1) T 3 16 0(0, 2) T 4 2 0(0, 4) Histological grading 2.93 0.03* Grade 1 ~ 2 62 0(0, 0) Grade 3 ~ 4 11 0(0, 4) Vascular invasion 2.64 0.03* No 64 0(0, 0) Yes 9 2(0, 4) Nerve invasion 5.77 0.02* No 70 0(0, 0) Yes 3 2(1, 6) Carcinoma nodule 4.47 0.01* No 69 0(0, 0) Yes 4 4(2, 9) Nano carbon tracer 0.74 0.61 No 37 0(0, 0) Yes 36 0(0, 2) Table 5 Multivariate analysis of influencing factors on the number of positive lymph nodes after minimally invasive radical surgery Index B SE χ2 OR 95%CI P Stage T 2 21.77 0.49 110.55 5.74 1.56 ~ 11.90 <0.001 Stage T 3 24.29 0.41 137.40 6.27 1.19 ~ 18.99 <0.001 Stage T 4 23.82 0.63 125.68 3.96 1.07 ~ 7.94 <0.001 Histological grade 3 ~ 4 1.69 0.36 50.47 4.82 1.42 ~ 9.98 <0.001 Vascular invasion 0.83 0.39 24.31 3.14 1.60 ~ 12.98 <0.001 Nano carbon tracer 2.04 0.30 62.14 7.59 1.33 ~ 16.81 <0.001 4. Discussion Accurate localization of lesions is the key to laparoscopic radical resection of CRC patients [ 7 ]; studies have shown [8] that additional surgical radical surgery after non-curative endoscopic resection of CRC patients can effectively prolong the overall survival time of patients. Another report confirmed [ 9 ] that the preoperative nanocarbon localization has a high accuracy rate for patients with early CRC in additional surgery, which is of great significance for improving the accuracy and safety of resection. Through the positioning of carbon nano-staining under colonoscopy 1–2 days before operation, the patient does not need to undergo mechanical bowel preparation again, which is helpful for the elimination of gas in the intestinal lumen before operation. Avoid the problem of increased difficulty in exploration due to the staining of mesangial lesions [10–11]. The results of multivariate analysis in this study showed that the location of the lesion and whether to perform nanocarbon tracing were independent influencing factors of the number of lymph nodes detected after minimally invasive radical surgery (P < 0.05). Cancer nodules were all independent influencing factors of the number of positive lymph nodes detected after minimally invasive radical surgery (P < 0.05), confirming that nanocarbon tracing can increase the total number of detected lymph nodes in CRC patients after laparoscopic radical surgery, but did not affect the number of positive lymph nodes detected. out of the situation. Nanocarbons have been confirmed to have high lymphatic system tropism, with relatively uniform particle diameters, with an average size of around 150 nm [ 12 ]. Because the hydrostatic pressure of the interstitial fluid is higher than the pressure in the lymphatic capillaries, nanocarbons can quickly enter the lymphatic channels after local injection into the human body; at the same time, they can also be phagocytosed by macrophages and migrate into the lymphatic system, staining the lymph node tissue in the tumor area. [13–14]. It has been reported that the lymph node staining rate of CRC patients after nanocarbon staining can reach 57%, which can significantly improve the detection rate of lymph nodes with a diameter of less than 5 mm compared with the past, and this result has been further confirmed by follow-up studies [ 15 ]. Pathologists mainly search for lymph nodes through a combination of direct vision and touch, and nanocarbon staining can improve the efficiency of pathologists in finding lymph nodes, increase the number of lymph nodes detected, especially those with smaller diameters, thereby maximizing the accuracy of pathological N staging. However, some scholars believe that although carbon nano-tracers can increase the operation of patients with digestive tract tumors. The total number of positive lymph nodes detected in the later period did not significantly increase the number of positive lymph nodes detected [ 16 ], which is also supported by this study. In recent years, nanocarbons have also been used for sentinel lymph node tracing in patients with CRC; a study of T1-2 stage CRC patients showed that after preoperative injection of nanocarbons under digestive endoscopy The median number of sentinel lymph nodes detected is 3, and the sensitivity and specificity for lymph node metastasis prediction can reach 91.2% and 100%, respectively [17]. However, the clinical value of sentinel lymph node tracing in CRC patients remains controversial, and whether selective lymph node dissection should be used in CRC patients remains unclear. Some scholars believe that the main purpose of sentinel lymph node detection in CRC patients is to detect lymph nodes with a higher risk of metastasis, rather than to control the extent of surgical resection [ 18 ]. This study also has certain limitations: (1) Although the baseline data was balanced by propensity score matching, the number of cases after matching was small, and it was a single-center retrospective report, so the conclusions could not completely rule out the influence of confounding factors; Follow-up studies are still needed to further analyze the impact of nanocarbon tracers on the survival of patients. 5. Conclusion In conclusion, the number of lymph nodes detected after minimally invasive radical surgery in CRC patients is related to the location of the lesions and whether nanocarbons are used. In addition, T2-4, histological grade 3–4, combined with vascular invasion and cancer nodules are more likely to detect positive lymph nodes. The application of nanocarbon tracer technology can help detect more lymph nodes, but its value in improving the detection of positive lymph nodes remains to be proven. Declarations Author Contribution Bingkai Xie and Guihe Lin wrote the main manuscript text, Zhijian Wang, Dongbo Xu, Jianxun Chen and Shuangming Lin collected clinical cases and performed data analyses. All authors reviewed the manuscript. Data Availability Data is provided within the manuscript or supplementary information files. References Ge W，Li Q，Liu WJ，et al. Carbon nanoparticle suspension could help get a more accurate nodal staging for patient with rectal cancer. Sci Rep，2021，11(1)：9933-9940. Li K，Chen D，Chen W，et al. A case-control study of using carbon nanoparticles to trace decision-making lymph nodes around inferior mesenteric artery in rectal cancer. Surg Endosc，2019，33(3): 904-910. Wang D，Chen M，Lv L，et al. Injection of carbon nanoparticles for lymph node detection after laparoscopic colorectal cancer surgery. J Nanosci Nanotechnol，2021，21(2): 886-894. Martín MJ，Gentili C，Lassalle V. 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(99m)Tc-labelled and pHawakened microbeads entrapping surface-modified lipid nanoparticles for the augmented effect of oxaliplatin in the therapy of colorectal cancer. J Microencapsul，2020，7(10)：1-15. Maffioli A，Danelli P. Carbon nanoparticles application during colorectal cancer surgery： updates from China. Dig Liver Dis，2020，52(12)： 1443-1444. Li J，Deng X，Wang L，et al. Clinical application of carbon nanoparticles in lymphatic mapping during colorectal cancer surgeries： a systematic review and meta-analysis. Dig Liver Dis，2020， 52(12)：1445-1454. Wang L，Xu H，Zhang X，et al. Effect of carbon nanoparticle tracer combined with laparoscopy in the treatment of colon cancer. J Nanosci Nanotechnol， 2020，20(10)：6007-6012. Liu P，Tan J，Tan Q，et al. Application of carbon nanoparticles in tracing lymph nodes and locating tumors in colorectal cancer： a concise review. Int J Nanomedicine，2020，15(12)：9671-9681. Singh R，Dumlupinar G，Andersson-Engels S，et al. Emerging applications of upconverting nanoparticles in intestinal infection and colorectal cancer. Int J Nanomedicine，2019，14(2)： 1027-1038. Lin N，Qiu J，Wu W，et al. Preoperative carbon nanoparticles and titanium clip combined labeling method for transverse colon tumor surgery. Asian J Surg，2019，42(8)：844-845. Wang R，Mo S，Liu Q，et al. The safety and effectiveness of carbon nanoparticles suspension in tracking lymph node metastases of colorectal cancer：a prospective randomized controlled trial. Jpn J Clin Oncol，2020，50(5)：535-542. Wang T，Wu Y，She J，et al. 3D nitrogen-doped carbon nanofoam arrays embedded with PdCu alloy nanoparticles： assembling on flexible microelectrode for electrochemical detection in cancer cells. Anal Chim Acta，2021，8(5)：1158-1165. Liu F，Wang XD，Du SY. Production of gold/silver doped carbon nanocomposites for effective photothermal therapy of colon cancer. Sci Rep， 2020，10(1)：7618-7625. Additional Declarations No competing interests reported. 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B) chi-square analysis of lymph node visualization based on diameter of 3 mm. C) Comparison of number of lymph nodes less than 5 mm in both groups. D) Comparison of number of metastasis-positive lymph nodes less than 5 mm in both groups.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4152681/v1/05b452068f11f8ac196ebbd1.jpg"},{"id":59260680,"identity":"4bf83d3d-76a6-431a-8a53-96277cd85265","added_by":"auto","created_at":"2024-06-28 09:36:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1132365,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4152681/v1/9c799d7d-2d29-4f5c-a227-8650e1e8be43.pdf"},{"id":54321976,"identity":"818d5d90-671f-4bc5-9ada-14b4382d262b","added_by":"auto","created_at":"2024-04-08 19:41:35","extension":"zip","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":82518,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.zip","url":"https://assets-eu.researchsquare.com/files/rs-4152681/v1/e50cc2cca222d6af55a4bd86.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer and analysis of the application value of carbon nano-tracers","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is one of the most common clinical malignant tumors of digestive system, and its morbidity and mortality ranks third and fifth among all malignant tumors, respectively. In recent years, with the popularization of the concept of early cancer detection/screening and the widespread development of endoscopy, the early detection rate of CRC has been increasing every year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. At present, it is believed that endoscopic non-curative resection, small volume, multiple primary and postoperative recurrence of CRC surgical radical resection is closely related to the accurate localization of the lesion [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. There are many existing CRC localization methods, but the localization error rate of barium colonography, CT and colonoscopy can reach 10\u0026ndash;35%; dye injection under colonoscopy can effectively improve the accuracy of lesion localization, but traditional methylene blue Due to the small diameter of the particles, they are easy to diffuse rapidly, leading to contamination of the surgical field, and the residence time in the tissue is short [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Nanocarbon is a new type of dyeing material, which has been widely used in malignant tumor surgery due to its advantages such as good histocompatibility, accurate positioning, long-lasting staining and lymph node tracing [5]. Reports have confirmed that nanocarbon tracing can increase the number of lymph nodes detected in CRC patients after surgery, but there is no clear conclusion on whether it can increase the detection of positive lymph nodes [6]. This study included a total of 120 patients with CRC who underwent minimally invasive radical surgery from October 2019 to May 2021 in the Department of Gastrointestinal Surgery, Longyan First Affiliated Hospital of Fujian Medical University.To explore the influencing factors of lymph node detection after minimally invasive radical surgery in CRC patients and the application value of carbon nano-tracers.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. General information\u003c/h2\u003e \u003cp\u003eA total of 120 patients with CRC who underwent minimally invasive radical surgery were included in the study. Inclusion criteria: 1- Histopathologically confirmed CRC; 2- Histopathological type belongs to adenocarcinoma; 3- Successfully completed laparoscopic radical resection\u0026thinsp;+\u0026thinsp;D3 lymph node dissection; 4- Elective surgery; 5- The same group of surgeons completed the operation. Exclusion criteria: 1- previous abdominal surgery; 2- emergency surgery; 3- CRC recurrence; 4- received neoadjuvant therapy before surgery; The study design conformed to the requirements of the Declaration of Helsinki. This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Longyan First Hospital of Fujian Province, informed consent was obtained from all subjects and/or their legal guardian(s).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Nanocarbon tracer\u003c/h2\u003e \u003cp\u003eIndications for the application of nanocarbon tracers were as follows: Imaging is difficult to locate accurately; Radical surgery is performed after non-curative endoscopic biopsy surgery; Mechanical bowel preparation was performed 1\u0026ndash;2 days before surgery, and the electronic colonoscope was placed under the microscope. To mark the location of the lesion, we pierced the submucosa at a 45\u0026deg; angle, injected 0.5 mL of 0.9% sodium chloride solution to stimulate the mucosal bulge, and then injected 0.1 mL of nanocarbon stock solution (Chongqing Laimei Pharmaceutical). If the endoscope could pass through the lesion area smoothly, we injected at 1 cm on the side of the lesion and 1 cm on the side of the anus (total 4 points); Each quadrant was injected separately (4 points in total).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Laparoscopic radical surgery\u003c/h2\u003e \u003cp\u003eUnder general anesthesia and tracheal intubation, the surgical plan was determined according to the location of the lesion, and total mesocolectomy or total mesorectal excision was used to complete laparoscopic radical resection\u0026thinsp;+\u0026thinsp;D3 lymph node dissection;, Complete excision of the intestinal segment, mesentery and mesangial root lymphatic and adipose tissue where the lesion was located, and dissection of the paraintestinal, middle and central lymph nodes at the same time (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Observation indicators\u003c/h2\u003e \u003cp\u003eReview the clinicopathological data of the case records, including gender, age, height, age, lesion location, histopathological type, maximum diameter of the lesion, T stage, histological grade, vascular and nerve invasion, cancer nodule and lymph node detection, etc.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical processing\u003c/h2\u003e \u003cp\u003eSPSS 24.0 software was used to analyze the data; gender, age, height, lesion location, histopathological type, maximum diameter of the lesion, T stage, histological grade, vascular and nerve invasion, cancer nodules and lymph node detection were included. A fixed-effect variable was used to calculate the propensity score; the propensity score was matched by the nearest neighbor matching method of 1:1, and the matching tolerance was 0.02; the Kolmogorov-Smirnov test was used to complete the normality evaluation, and the paired t test was used to compare the measurement data that conformed to the normal distribution., expressed as (x\u0026thinsp;\u0026plusmn;\u0026thinsp;s); Mann-Whitney U test was used for comparison of measurement data that did not conform to the normal distribution, expressed as M (P25, P75); χ2 test was used for comparison of count data, expressed as rate; Poisson regression was used for multivariate analysis Multivariate model; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Analysis of baseline data after matching\u003c/h2\u003e\n \u003cp\u003eAmong the 120 patients, 43 underwent preoperative colonoscopy with nanocarbon tracing. During the operation, black staining of the tumor site was clearly seen (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), and no complications occurred. After propensity score matching, there were 37 patients in the tracer group and the non-tracer group; there was no significant difference in baseline data between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of baseline data after matching\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon tracer group\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTracer group\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathological type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUplift type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUlcerative type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaximum diameter lesion (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistological grading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 1\u0026thinsp;~\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 3\u0026thinsp;~\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarcinoma nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Lymph node detection and metastasis\u003c/h2\u003e\n \u003cp\u003eThe number of detected lymph nodes and the number of metastasis-positive lymph nodes in the observation group were significantly higher than those in the control group, and the number of lymph nodes with a diameter of less than 5 mm and the number of metastasis-positive lymph nodes were significantly higher than those in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The black staining rate of lymph nodes with a diameter of less than 3 mm in the observation group was significantly higher than that of lymph nodes with a diameter of more than 3 mm (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Lymph node detection after minimally invasive radical surgery\u003c/h2\u003e\n \u003cp\u003eAmong the 37 patients in the tracer group, 1 patient was excluded due to staining problems, and 726 lymph nodes were detected in the remaining 36 patients, and the median number of lymph nodes detected was 19 (14, 25); 38 positive lymph nodes were detected, and the median number of lymph nodes detected The number of outputs was 0 (0, 2). In the non-tracer group, 614 lymph nodes were detected, and the median number of lymph nodes was 17 (14, 20); 23 positive lymph nodes were detected, and the median number of positive lymph nodes was 0 (0, 0). The number of positive lymph nodes detected in the tracer group was significantly higher than that in the non-tracer group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); there was no significant difference in the number of positive lymph nodes detected between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.4. Analysis of influencing factors on the number of lymph nodes detected after minimally invasive radical surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe results of univariate analysis showed that gender, age, lesion location, maximum tumor diameter, and whether nanocarbon tracing was performed were associated with the number of lymph nodes detected after minimally invasive radical surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The results of multivariate analysis showed that the location of the lesion and whether to perform nanocarbon tracing were independent influencing factors of the number of lymph nodes detected after minimally invasive radical surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate analysis of influencing factors on the number of lymph nodes detected after minimally invasive radical surgery\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of lymph nodes\u003c/p\u003e\n \u003cp\u003e[\u003cem\u003en\u003c/em\u003e, M (P25, P75) ]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(15, 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(16, 25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(16, 23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(16, 23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(15, 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25(17, 32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(14, 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(15, 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathological type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.45\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUplift type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUlcerative type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(16, 25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaximum diameter lesion (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(16, 25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003eis\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(12, 20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(15, 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(16, 24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(13, 27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistological grading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 1\u0026thinsp;~\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(16, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 3\u0026thinsp;~\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(14, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(16, 27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25(11, 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarcinoma nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18(15, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(13, 28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNano carbon tracer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17(14, 20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(14, 25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate analysis of influencing factors on the number of lymph nodes detected after minimally invasive radical surgery\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.50\u0026thinsp;~\u0026thinsp;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.62\u0026thinsp;~\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNano carbon tracer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.03\u0026thinsp;~\u0026thinsp;1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.5. Analysis of influencing factors on the number of positive lymph nodes detected after minimally invasive radical surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe results of univariate analysis showed that the pathological type, T stage, histopathological grade, vascular invasion, nerve invasion and whether it was associated with cancer nodules [no vs yes: 0 (0, 0) vs 4 (2, 9)] All were related to the number of positive lymph nodes detected after minimally invasive radical surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); multivariate analysis showed that T stage, histopathological grade, vascular invasion and combined cancer nodules were all positive after minimally invasive radical surgery The number of lymph nodes detected was an independent factor (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate analysis of influencing factors on the number of positive lymph nodes after minimally invasive radical surgery.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of lymph nodes\u003c/p\u003e\n \u003cp\u003e[\u003cem\u003en\u003c/em\u003e, M (P25, P75) ]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft hemicolon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRectum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePathological type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUplift type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUlcerative type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(0, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaximum diameter lesion (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003eis\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistological grading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 1\u0026thinsp;~\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 3\u0026thinsp;~\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(0, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(1, 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarcinoma nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(2, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNano carbon tracer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate analysis of influencing factors on the number of positive lymph nodes after minimally invasive radical surgery\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage T\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.56\u0026thinsp;~\u0026thinsp;11.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage T\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e137.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.19\u0026thinsp;~\u0026thinsp;18.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage T\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e125.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.07\u0026thinsp;~\u0026thinsp;7.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHistological grade 3\u0026thinsp;~\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.42\u0026thinsp;~\u0026thinsp;9.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.60\u0026thinsp;~\u0026thinsp;12.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNano carbon tracer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.33\u0026thinsp;~\u0026thinsp;16.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAccurate localization of lesions is the key to laparoscopic radical resection of CRC patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e7\u003c/span\u003e]; studies have shown [8] that additional surgical radical surgery after non-curative endoscopic resection of CRC patients can effectively prolong the overall survival time of patients. Another report confirmed [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e9\u003c/span\u003e] that the preoperative nanocarbon localization has a high accuracy rate for patients with early CRC in additional surgery, which is of great significance for improving the accuracy and safety of resection. Through the positioning of carbon nano-staining under colonoscopy 1\u0026ndash;2 days before operation, the patient does not need to undergo mechanical bowel preparation again, which is helpful for the elimination of gas in the intestinal lumen before operation. Avoid the problem of increased difficulty in exploration due to the staining of mesangial lesions [10\u0026ndash;11].\u003c/p\u003e \u003cp\u003eThe results of multivariate analysis in this study showed that the location of the lesion and whether to perform nanocarbon tracing were independent influencing factors of the number of lymph nodes detected after minimally invasive radical surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Cancer nodules were all independent influencing factors of the number of positive lymph nodes detected after minimally invasive radical surgery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), confirming that nanocarbon tracing can increase the total number of detected lymph nodes in CRC patients after laparoscopic radical surgery, but did not affect the number of positive lymph nodes detected. out of the situation. Nanocarbons have been confirmed to have high lymphatic system tropism, with relatively uniform particle diameters, with an average size of around 150 nm [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Because the hydrostatic pressure of the interstitial fluid is higher than the pressure in the lymphatic capillaries, nanocarbons can quickly enter the lymphatic channels after local injection into the human body; at the same time, they can also be phagocytosed by macrophages and migrate into the lymphatic system, staining the lymph node tissue in the tumor area. [13\u0026ndash;14]. It has been reported that the lymph node staining rate of CRC patients after nanocarbon staining can reach 57%, which can significantly improve the detection rate of lymph nodes with a diameter of less than 5 mm compared with the past, and this result has been further confirmed by follow-up studies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Pathologists mainly search for lymph nodes through a combination of direct vision and touch, and nanocarbon staining can improve the efficiency of pathologists in finding lymph nodes, increase the number of lymph nodes detected, especially those with smaller diameters, thereby maximizing the accuracy of pathological N staging. However, some scholars believe that although carbon nano-tracers can increase the operation of patients with digestive tract tumors. The total number of positive lymph nodes detected in the later period did not significantly increase the number of positive lymph nodes detected [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which is also supported by this study.\u003c/p\u003e \u003cp\u003eIn recent years, nanocarbons have also been used for sentinel lymph node tracing in patients with CRC; a study of T1-2 stage CRC patients showed that after preoperative injection of nanocarbons under digestive endoscopy\u003c/p\u003e \u003cp\u003eThe median number of sentinel lymph nodes detected is 3, and the sensitivity and specificity for lymph node metastasis prediction can reach 91.2% and 100%, respectively [17]. However, the clinical value of sentinel lymph node tracing in CRC patients remains controversial, and whether selective lymph node dissection should be used in CRC patients remains unclear. Some scholars believe that the main purpose of sentinel lymph node detection in CRC patients is to detect lymph nodes with a higher risk of metastasis, rather than to control the extent of surgical resection [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study also has certain limitations: (1) Although the baseline data was balanced by propensity score matching, the number of cases after matching was small, and it was a single-center retrospective report, so the conclusions could not completely rule out the influence of confounding factors; Follow-up studies are still needed to further analyze the impact of nanocarbon tracers on the survival of patients.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, the number of lymph nodes detected after minimally invasive radical surgery in CRC patients is related to the location of the lesions and whether nanocarbons are used. In addition, T2-4, histological grade 3\u0026ndash;4, combined with vascular invasion and cancer nodules are more likely to detect positive lymph nodes. The application of nanocarbon tracer technology can help detect more lymph nodes, but its value in improving the detection of positive lymph nodes remains to be proven.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eBingkai Xie and Guihe Lin wrote the main manuscript text, Zhijian Wang, Dongbo Xu, Jianxun Chen and Shuangming Lin collected clinical cases and performed data analyses. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGe W，Li Q，Liu WJ，et al. Carbon nanoparticle suspension could help get a more accurate nodal staging for patient with rectal cancer. Sci Rep，2021，11(1)：9933-9940.\u003c/li\u003e\n\u003cli\u003eLi K，Chen D，Chen W，et al. A case-control study of using carbon nanoparticles to trace decision-making lymph nodes around inferior mesenteric artery in rectal cancer. Surg Endosc，2019，33(3): 904-910.\u003c/li\u003e\n\u003cli\u003eWang D，Chen M，Lv L，et al. Injection of carbon nanoparticles for lymph node detection after laparoscopic colorectal cancer surgery. J Nanosci Nanotechnol，2021，21(2): 886-894.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;n MJ，Gentili C，Lassalle V. In vitro biological tests as the first tools to validate magnetic nanotheranostics for colorectal cancer models. Chem Med Chem，2020，15(12)：1003-1017.\u003c/li\u003e\n\u003cli\u003e\u0026Uuml;nal S，Akta \u0026ccedil; Y，Benito JM，et al. Cyclodextrin nanoparticle bound oral camptothecin for colo- rectal cancer： formulation development and optimization. Int J Pharm，2020，584(6)：119468.\u003c/li\u003e\n\u003cli\u003eLi J，Deng X，Wang L，et al. Clinical application of carbon nanoparticles in lymphatic mapping during colorectal cancer surgeries： a systematic review and meta -analysis. Dig Liver Dis ，2020，7(7)：1590-1597.\u003c/li\u003e\n\u003cli\u003eBhattarai DP，Kim BS. NIR-triggered hyperthermal effect of polythiophene nanoparticles synthesized by surfactant-free oxidative polymerization method on colorectal carcinoma cells. Cells，2020，9(9)：E2122.\u003c/li\u003e\n\u003cli\u003eJin KT，Yao JY，Ying XJ，et al. Nanomedicine and early cancer diagnosis： molecular imaging using fluorescence nanoparticles. L Curr Top Med Chem，2020，22(9)：1124-1129.\u003c/li\u003e\n\u003cli\u003eRajpoot K，Jain SK. (99m)Tc-labelled and pHawakened microbeads entrapping surface-modified lipid nanoparticles for the augmented effect of oxaliplatin in the therapy of colorectal cancer. J Microencapsul，2020，7(10)：1-15.\u003c/li\u003e\n\u003cli\u003eMaffioli A，Danelli P. Carbon nanoparticles application during colorectal cancer surgery： updates from China. Dig Liver Dis，2020，52(12)： 1443-1444.\u003c/li\u003e\n\u003cli\u003eLi J，Deng X，Wang L，et al. Clinical application of carbon nanoparticles in lymphatic mapping during colorectal cancer surgeries： a systematic review and meta-analysis. Dig Liver Dis，2020， 52(12)：1445-1454.\u003c/li\u003e\n\u003cli\u003eWang L，Xu H，Zhang X，et al. Effect of carbon nanoparticle tracer combined with laparoscopy in the treatment of colon cancer. J Nanosci Nanotechnol， 2020，20(10)：6007-6012.\u003c/li\u003e\n\u003cli\u003eLiu P，Tan J，Tan Q，et al. Application of carbon nanoparticles in tracing lymph nodes and locating tumors in colorectal cancer： a concise review. Int J Nanomedicine，2020，15(12)：9671-9681.\u003c/li\u003e\n\u003cli\u003eSingh R，Dumlupinar G，Andersson-Engels S，et al. Emerging applications of upconverting nanoparticles in intestinal infection and colorectal cancer. Int J Nanomedicine，2019，14(2)： 1027-1038.\u003c/li\u003e\n\u003cli\u003eLin N，Qiu J，Wu W，et al. Preoperative carbon nanoparticles and titanium clip combined labeling method for transverse colon tumor surgery. Asian J Surg，2019，42(8)：844-845.\u003c/li\u003e\n\u003cli\u003eWang R，Mo S，Liu Q，et al. The safety and effectiveness of carbon nanoparticles suspension in tracking lymph node metastases of colorectal cancer：a prospective randomized controlled trial. Jpn J Clin Oncol，2020，50(5)：535-542.\u003c/li\u003e\n\u003cli\u003eWang T，Wu Y，She J，et al. 3D nitrogen-doped carbon nanofoam arrays embedded with PdCu alloy nanoparticles： assembling on flexible microelectrode for electrochemical detection in cancer cells. Anal Chim Acta，2021，8(5)：1158-1165.\u003c/li\u003e\n\u003cli\u003eLiu F，Wang XD，Du SY. Production of gold/silver doped carbon nanocomposites for effective photothermal therapy of colon cancer. Sci Rep， 2020，10(1)：7618-7625.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Colorectal cancer, Detection, Metastasis, Lymph node, Nano carbon tracer","lastPublishedDoi":"10.21203/rs.3.rs-4152681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4152681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo investigate the influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer (CRC) and the application value of carbon nanoparticle tracing. A total of 120 patients with CRC who underwent minimally invasive radical surgery were included. They were divided into groups according to whether they were grouped by carbon nano-tracers, and the baseline data were matched by propensity score method. Univariate and multivariate methods were used to evaluate lymph nodes and positive lymph nodes after minimally invasive radical surgery. The number of detected independent factors. After propensity score matching, there were 37 patients in the tracer group and the non-tracer group; there was no significant difference in baseline data between the two groups; the number of positive lymph nodes detected in the tracer group was significantly higher than that in the non-tracer group. The results of univariate analysis showed that gender, lesion location, maximum tumor diameter, and whether to perform nanocarbon tracing were all related to the number of lymph nodes detected after minimally invasive radical surgery. Nanocarbon tracing was an independent influencing factor for the number of lymph nodes detected after minimally invasive radical surgery. Pathological type, T stage, histopathological grade, nerve invasion, and whether or not with cancer nodules were all related to the number of positive lymph nodes detected after minimally invasive radical surgery; multivariate analysis showed that T stage, pathological Histological grade, vascular invasion, and cancer nodules were all independent influencing factors for the number of positive lymph nodes detected after minimally invasive radical surgery. The number of lymph nodes detected in patients with CRC after minimally invasive radical surgery is closely related to the location of the lesion and whether carbon nanoparticle tracing is performed; those with T2-4 stage, histological grade 3\u0026ndash;4, combined with vascular invasion and cancer nodules are more likely to Positive lymph nodes were detected.\u003c/p\u003e","manuscriptTitle":"Influencing factors of lymph node detection after minimally invasive radical surgery in patients with colorectal cancer and analysis of the application value of carbon nano-tracers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 19:41:30","doi":"10.21203/rs.3.rs-4152681/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a4b46dd-be25-49a5-b27b-9724afc2f409","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-28T09:36:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 19:41:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4152681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4152681","identity":"rs-4152681","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}