A Study on the Clinical Application of Jiang's Percutaneous Transthoracic Lung Biopsy in Pulmonary Nodules

A Study on the Clinical Application of Jiang's Percutaneous Transthoracic Lung Biopsy in Pulmonary Nodules | 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 A Study on the Clinical Application of Jiang's Percutaneous Transthoracic Lung Biopsy in Pulmonary Nodules ShiYin Jiang, Chao Li, JiaWei Long, Cheng Li, WuSheng Deng, YongLiang Jiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6390597/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 Background: Lung cancer has a high global mortality rate, and CT-guided percutaneous lung biopsy is used for lung biopsy. We invented a laser-assisted puncture system named Jiang’s percutaneous transthoracic lung biopsy to assist diagnose. Methods: Jiang's PTLB optimizes CT-guided percutaneous lung puncture via a simple homemade laser-guided puncture device with two laser devices to determine the angle and level of puncture. We recruited 34 physicians to perform a self-controlled trial of the model via two methods to evaluate its effectiveness. A total of 390 patients from January 2021 to July 2023 underwent Jiang’s method and 129 patients from March 2020 to July 2023 underwent the conventional method. Results: 1. Model experiment results: Jiang's method resulted in a higher single penetration rate (76.5% vs. 11.8%), shorter operation time (3.04±1.12 minutes vs 8.43±2.48 minutes), fewer CT scans (1.24±0.43 times vs. 3.91±1.06 times), and fewer penetrations (1.24±0.43 vs. 2.91±1.06); 2. Clinical trial results: In Jiang’s group, pneumothorax was developed in 31 patients (12.02%), bleeding occurred in 20 patients (7.75%), and 4 patients bled (1.55%). Jiang's method had a sensitivity of 94.19%, a specificity of 97.30%, a Youden index of 0.9149, a positive predictive value of 99.32%, a negative predictive value of 80.00%, a malignancy rate of 89.57%, a benign detection rate of 75.00%, and a concordance rate of 86.26%. Conclusion: Compared with the unassisted method, Jiang's method can significantly improve the puncture efficiency, reduce the incidence of complications, and increase the safety and effectiveness of the lung biopsy. COPD PTNB CT Lung nodules cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights We invented a Laser-guided system to assist thransthoracic percutaneous lung biopsy. We developed a method called Jiang's percutaneous lung biopsy to improve the efficiency of the puncture. We used a homemade puncture model to evaluate the efficiency of puncture. Introduction According to 《Cancer incidence and mortality in China, 2022》, China's lung cancer incidence and mortality rates are at the top of the list 1 . In 2022, there will be 730,000 new lung cancer deaths, which was the highest mortality rate in the world, with 1.8 million deaths due to lung cancer, accounting for 18.7% of all 2 . Therefore, it is of great importance to disseminate cancer prevention measures that focus on early detection, early diagnosis, and treatment. Among them, detection and diagnosis at an early stage is one of the most essential aspects, and how to screen for early lung cancer is of particular concern. Lung nodules may be precancerous lesions or the early manifestation of lung cancer, characterised by single or multiple soft tissue density masses on CT images in the lung field, with relatively fixed borders and increased density compared with the surrounding tissue. The diameter of the mass is usually not greater than 30 mm, encircled by the lung parenchyma, and entirely or incompletely covers the internal vascular and bronchial density masses 3 , 4 . The American College of Chest Physicians (ACCP) recognises that when a nodule is more significant than 8 mm, it is essential to be alert to the possibility of malignancy 5 . Therefore, patients with lung nodules are potential beneficiaries for early diagnosis and treatment of lung cancer. With the promotion of low-dose helical computed tomography (LDCT) 6 , the number of patients with pulmonary nodules is increasing yearly, and it has become a common disease in clinical practice. With low diagnostic efficacy based on indirect evidence alone 7 , it brings tremendous psychological pressure to patients, and how to rationally manage pulmonary nodules has aroused extensive attention. According to the 2017 Fleischner Guide 8 and NCCN Guidelines for the 2021 Edition 9 , lung biopsy is recommended to obtain diagnostic evidence in high-risk patients. Percutaneous transthoracic needle biopsy (PTNB) is most commonly used to diagnose lung cancer 10 ; documentation dates back to 1970 11 . CT-PTNB is a diagnostic technique that involves using a biopsy needle to obtain tissue or cellular specimens by percutaneous puncture into a lung nodule under the guidance of medical imaging equipment. We usually use CT or bronchoscopy to guide the biopsy. The disadvantage of bronchoscopy is that it is not available for peripheral nodules, so we choose CT instead. After years of development, many new technologies have emerged, such as IG4 electromagnetic navigation 12 , robotic assistance 13 , 3D printing technology 14 , and many other precise, expensive, and technically demanding precision aids. Such as, Min-Cheol Jeon invented a laser-assisted puncture system 15 , and some scholars have utilised more straightforward, affordable and easily replicable tools such as fences, protractors and lasers to improve CT-PTNB. However, we found that these methods have some shortcomings that need to be improved. Therefore, we developed Jiang’s Percutaneous Transthoracic Lung Biopsy, which utilizes two sets of lasers to assist in determining the angle and level of puncture. To evaluate this method's advantages, we verified its puncture efficiency and accuracy through model experiments and collected and analyzed clinical data to assess its safety, efficacy and diagnostic efficacy. Methods 1.1 Principle and procedure 3.1.1 Principle To elevate the precision of puncture, we should pay attention to four elements during operation: 1. body surface localization point; 2. puncture angle; 3. puncture depth; 4. puncture level. The body surface localization point can be located by sticking a fence on the body surface, combined with the CT laser. The depth is determined by the scale on the puncture needle. Jiang’s Percutaneous Transthoracic Lung Biopsy aims to determine the angle as well as the level of puncture. Laser-guided system (LGS): To provide precise guidance through real-time visualization during operation. It is mainly done through two homemade laser devices to guide (Fig. 1 ). It consists of a bracket and a laser goniometer mounted on it (Patent No. ZL 20222016072.3), which emits perpendicular and reference laser lights. As shown in the figure (Fig. 2 ), the laser device emits vertical and horizontal beam lines. The red lines originated from the foot end to determine the puncture angle. At the same time, another laser device placed on the opposite of the operator emits a green beam light to determine the level. Two lights cross at the predetermined puncture point. We should keep these two light beams on the coaxial needle when we insert the needle. The red laser is placed on the foot side of the patient to determine the angle of penetration; the green laser is placed on the opposite side of the operator to determine the level of penetration 3.1.2 Puncture model (Fig. 3 ): We fill argil in a simulated human thoracic skeleton model as the lung tissue, and a piece of green plasticine with a diameter of 2 cm is placed in it to simulate the lung nodules. 3.1.3 Process of model experiment Objects: We recruited 34 respiratory medicine physicians who had never been trained or finished PTNB and taught them both the Jiang’s and traditional methods to achieve biopsy on the model. Point of puncture: First, we paste the fence on the patient’s chest and then scan a CT. We can notice that there are several white dots above the chest, which represent the fence. According to this, we can determine the anatomic puncture approach. Second, we determine which fence line is the path we need, marking the line on the skin. Third, the CT scanning cursor is moved to a specific location, referring to the CT image, and then we can draw the horizontal line. Last, the intersection of these two lines is the point of puncture we need. Model experiment traditional puncture method: We insert the needle subcutaneously and do a CT scan again to predict whether the needle can reach the nodule aimed at. If the angle deviation is too large, we should adjust the angle until we can aim at that nodule. Jiang's Percutaneous Transthoracic Lung Biopsy: First, we put the red laser device on the patient's foot side and the green laser device opposite the operator. Second, we should adjust the horizontal angle of both devices to 0°; the green line should be adjusted at 90° to a horizontal surface. The red laser will guide the puncture angle, so we should adapt it to the aimed angle. Third, as marked before, the two colourful lines should be crossed on the chest's point. Last, we should ensure that the two lines are always on the needle when we puncture to achieve real-time guidance. 3.1.4 Clinical trial process Objects: We randomly sampled the data of patients from 258 cases who underwent Jiang’s method in our hospital (From January 2021 to July 2023) and then compared them with 129 patients’ cases data (From March 2020 to July 2023) who used the traditional method to biopsy. The data of patients with pulmonary nodules who underwent Jiang's method in our hospital (from January 2021 to July 2023), from which a sample of 258 cases was randomly selected, were compared with the data of 129 patients with nodules who underwent the traditional method in the past (from March 2020 to July 2023) according to a 2:1 ratio to compare the efficacy and safety of these two methods. Inclusion criteria: over 18 years old, pulmonary nodules in the lungs on CT imaging, patient consent to participate and signing of an informed consent form. Exclusion criteria: severe coagulation disorders, anatomical abnormalities, refusal to participate in the study, or inability to provide complete data. Preoperative evaluation: Improve assessment to exclude contraindications and avoid emphysema, interlobular fissures, large blood vessels, and abnormal enhancement foci on enhanced CT. We should fully understand the location and size of the lesion and the surrounding vascular condition through enhanced CT and determine the point and plan of penetration. The puncture point was determined as in the model experiment. Preparation for puncture: electrocardiogram monitoring of the patient's vital signs, choosing the appropriate pose according to the puncture path, instructing the patient to maintain a fixed position, preparing the puncture device, and confirming that the first aid equipment is ready. The operator wears a surgical gown, mask, cap and gloves and determines the type and model of the biopsy needle according to the lesion size. Routinely disinfects, drapes the patient, local infiltration anaesthesia, enters the needle to reach the target position by using different methods of puncture, and then performs a CT scan again to clarify the position of the needle. Clinical study of the traditional puncture: the needle is advanced vertically from the puncture point layer by layer, and the needle will stop when it reaches the expected depth. The experimental group used the same method as the model experiment for Jiang’s percutaneous transthoracic lung biopsy (Fig. 4 ). Specimen acquisition and pathological evaluation: Once the specimen was obtained, we put the specimen into formalin for fixation, withdrew the puncture needle, and pressed the wound until there was no bleeding. At the same time, we should pay attention to the patient's symptoms and whether there are any complications, such as chest tightness and bleeding. Then, we could send the patient back to the ward in a wheelchair under oxygenation. We should perform chest X-rays routinely after the operation to review the occurrence of any delayed complications. 2.2 Statistical methods Data collection: We used epi data 3.1 software to collect data and excluded incomplete data such as no preoperative and postoperative CT results, no records of relevant complications, and the data after microwave as well as radiofrequency ablation. Statistical analysis: We used SPSS 22.0 and SAS 9.4. to analyze the collected data. Continuous variables were expressed as mean ± standard deviation or median and interquartile spacing, and comparisons between groups were made using analysis of variance or Mann-Whitney U test. Nominal and categorical data were expressed as number (n) and frequency (%), and between-group comparisons were analyzed using the chi-square test or Fisher's exact test. Comparisons of baseline data were made using a two-sided test. Diagnostic efficacy, technical safety indexes, and technical success indexes were compared using one-sided tests. The value of P < 0.05 was considered statistically significant. We fitted the ROC curve to assess the diagnostic accuracy and acquire the sensitivity, specificity, predictive value, and Jordon's index. Results 4.1 Results of model experiments Jiang's method could improve the puncture efficiency (Table 1 ,Fig. 5 ). It has a significantly higher success rate of one-time achievement ratio of puncture than the unassisted method (76.5% vs 11.8%), shorter puncture time (3.04 ± 1.12 minutes vs 8.43 ± 2.48 minutes), fewer CT scans (1.24 ± 0.43 times vs 3.91 ± 1.06 times), and fewer puncture times (1.24 ± 0.43 times vs 2.91 ± 1.06 times). A significant difference was related to these indicators (P<0.05). Table 1 puncture efficiency Characteristic Jiang's Group n = 34 Traditional group n = 34 One-time achievement ratio of puncture (%) 76.5(26/34) 11.8(4/34) Puncture time(min) 3.04 ± 1.12 8.43 ± 2.48 CT scans(times) 1.24 ± 0.43 3.91 ± 1.06 Numbers of Puncture(times) 1.24 ± 0.43 2.91 ± 1.06 4.2 Results of clinical trials 1) Comparison of baseline data There was no statistical difference in the baseline information between the two methods at the population level (Table 2 ). At the clinical level, there was a statistical difference in the prevalence of diabetes mellitus (P = 0.0356 < 0.05) but no statistically significant difference in the remaining items. The baseline data is balanced. Table 2 Baseline data Parameters Jiang’s group Traditional group total P two sides n 1 = 258 n 2 = 129 N 1 = 387 Comorbidity, n(%) Hypertension 51(19.77) 37(28.68) 88(22.74) 0.0514 Diabetes 17(6.59) 17(13.18) 34(8.79) 0.0356 Coronary heart disease 16(6.20) 10(7.75) 26(6.72) 0.5699 COPD 22(8.53) 12(9.30) 34(8.79) 0.8004 Non-thoracic tumor 24(9.30) 10(7.75) 34(8.79) 0.6081 Symptom, n(%) Cough and sputum 99(38.37) 52(40.31) 151(39.02) 0.7128 Chest pain 29(11.24) 10(7.75) 39(10.08) 0.2729 Fever 5(1.94) 5(3.88) 10(2.58) 0.3114* Blood in sputum 12(4.65) 6(4.65) 18(4.65) 1.0000 Lesion localization, n(%) Right upper lobe 83(32.17) 30(23.26) 113(29.20) Right middle lobe 26(10.08) 6(4.65) 32(8.27) Right lower lobe 62(24.03) 30(23.26) 92(23.77) 0.0234 Left upper lobe 51(19.77) 33(25.58) 84(21.71) Left lower lobe 36(13.95) 30(23.26) 66(17.05) Lesion size(mm) 18.89(6.73) 19.49(7.21) 0.4255 Lung nodule density, n(%) Pure ground-glass nodule 17(6.59) 7(5.43) 24(6.20) Subsolid nodule 43(16.67) 26(20.16) 69(17.83) 0.6608 Solid nodule 198(76.74) 96(74.41) 294(75.97) Multiple nodules,n(%) Yes 163(63.18) 60(46.51) 223(57.62) 0.0018 No 95(36.82) 69(53.49) 164(42.38) Malignant sigh, n(%) Pleural identation 90(34.88) 26(20.16) 116(29.97) 0.0023 Spiculation 105(40.70) 39(30.23) 144(37.21) 0.0430 Irregular shapes 84(32.56) 10(7.75) 94(24.29) < 0.0001 Lobulation 89(34.50) 39(30.23) 128(33.07) 0.3988 Lymph node enlargement 42(16.28) 19(14.73) 61(15.76) 0.6918 Footnote: *Fisher’s exact test 2) Comparison of diagnostic effectiveness The diagnostic efficacy of the two methods was comparable (Table 3 ). The sensitivity of Jiang's group was 94.19% (146/155), the specificity was 97.30% (36/37), the positive predictive value was 99.32% (146/147), and the negative predictive value was 80.00% (36/45). The sensitivity of the traditional method was 88.52% (54/61), specificity was 96.77% (30/31), positive predictive value was 98.18% (54/55), and negative predictive value was 81.08% (30/37), none of these indicators had significant difference. The Youden index was 0.9149 for Jiang's method and 0.8529 for the traditional method. 3) Comparison of detection concordance rates The detection rate of malignant nodules by Jiang's method was 89.57% (146/163), and that of benign nodules was 75.00% (36/48), with a concordance rate of 86.26% (182/211). Jiang's method had a higher malignant detection rate than the traditional method, and the differences were statistically significant (Table 3 ). Further subgrouped according to nodule localization, the final diagnostic concordance rate of left upper lung nodules was greater in Jiang's method than in the traditional method, and the difference was statistically significant. Table 3 Comparison of diagnostic efficacy and detection concordance Parameter(%) Jiang’s group Traditional group Single − side N 2 = 192 N 3 = 92 Sensitivity 94.19 88.52 0.1683* Specificity 97.30 96.77 1.0000* Positive predictive value 99.32 98.18 0.4714* Negative predictive value 80.00 81.08 1.0000* Benign rate 89.57 79.41 0.0348 * Malignant rate 75.00 65.22 0.2087* Concordance rate 86.26 73.68 0.0045* Footnote: *Fisher’s exact test 4) Technical safety indicators comparison The complication rate of the two groups was as follows (Fig. 6 ): Jiang's group: 31 cases of pneumothorax (12.02%), 20 cases of bleeding from the needle tract (7.75%), and 4 cases of hemoptysis (1.55%). Traditional group: 37 cases of pneumothorax (28.68%), 16 cases of bleeding from the needle tract (12.40%), and 15 cases of hemoptysis (11.63%). The difference was statistically significant, and neither group had an air embolism. 5) Comparison of technical success and other indicators: Jiang's group had a higher technical success rate (Fig. 7 ), with 6 cases of insufficient sample size and an incidence rate of 2.33% (6/258). In the traditional group, a sample of 9 cases is inadequate, with an incidence rate of 6.98%, a statistically significant difference (P = 0.0264). Of the postoperative hospitalization days, the median and the interquartile spacing was three days in Jiang's group and four days in the traditional group. The unilateral Mann-Whitney U test suggested that the number of postoperative hospitalization days was less in Jiang's group than in the conventional group (P < 0.0001). Discussion With the popularity of LDCT, the detection rate of lung nodules is increasing year by year, and pathological evidence is still the gold standard. However, the traditional method of sampling lung nodules has many shortcomings, so we improved it. This paper aims to evaluate this method. Conventional unassisted puncture is inserting the needle subcutaneously by experience according to the initial CT image, then performing a CT scan again to assess the angle. If it is significantly off track, we could adjust the angle and insert it again. In the absence of other auxiliary tools, based on different personal experiences and the sense of touch of distinct operators, the standing position, as well as an ideal planar state thorax, it is difficult to predict the angle of the needle only based on the subjective judgment of an operator and to accurately replicate the simulated path of puncture to the real life as well as visualize the needle position in real-time. In the end, repeated CT scans will be required to adjust the direction of the puncture, which could increase radiation exposure and operation time. To sum up, the uncertainty of unassisted punctures is high, and individual success cannot be replicated because the experience and feel of punctures cannot be developed in a short time. As a result, many puncture assistive devices have been designed to improve puncture efficiency further. Laser-assisted puncture device was invented by Min-Cheol Jeon in Korea 15 . Other scholars have invented the double fence positioning angle gauge, long-distance laser, double-needle CT-guided percutaneous lung biopsy, and many other different ways. However, there are still some shortcomings, such as a cumbersome adjustment process, lack of flexibility, contaminating the operation area easily, increasing the number of punctures as well as CT scan times, and accuracy needs to be improved. Therefore, we invented Jiang's method to improve it further. There are four elements in lung puncture: surface localization, puncture level, angle, and depth. A combination of fence and collimated laser light from the CT determines surface localization. The scale on the needle determines the depth of the puncture. To improve puncture accuracy, Jiang's method mainly uses a red light to determine the puncture angle and a green light to locate the puncture needle in the transverse plane. It guides the needle in real-time throughout the puncture process to prevent it from deviating. In addition, long-distance laser guidance can reduce infection; it also has good manoeuvrability, easy to use and cheap. In conjunction with this method applied in practice, we can draw the following conclusions. First, Jiang's method can improve puncture efficiency and reduce the complication rate. Repeated puncture increases the chance of passing through interlobar fissures, pulmonary blisters, and injury to the thick bronchi. Also, the prolonged retention of the puncture needle in the lung tissue, coupled with the effects of respiratory motion, will continuously cut into the lung tissue and increase the risk of complications 16 . Reducing the number and duration of punctures significantly reduces puncture complications such as bleeding, hemoptysis, and pneumothorax 17 – 19 . The results of the model experiment suggested that Jiang's method could considerably reduce the number of needle adjustments and shorten the puncture time. The clinical control study showed that the complication rate of the traditional group was significantly higher than that of Jiang’s group, which was in line with previous studies in the literature. To avoid Air embolism 20 , 21 , the coaxial needle should not be left exposed to air for long periods during the operation, and we should keep the core in the needle at all times when we penetrate. Fewer complications can shorten postoperative hospitalization days and benefit the patient economically. Second, Jiang's method can improve the diagnostic efficacy. Tumors, infections, inflammation, autoimmunity, and other [22] pathological conditions could also manifest as pulmonary nodules. Thus, it is vital to accurately determine their benign and malignant nature and then appropriately intervene. Synthesizing the results of studies from multiple centres at home and abroad [23–26], the sensitivity of PTNB was 72.34%-95.7%, and the specificity was 95.7%-100%, we can notice that the efficacy of Jiang's method was consistent with the trend. There were differences in the distribution of lesion localization and the percentage of malignant signs between the two groups in the baseline data, which may be related to different teams' assessment of lung nodules. Further analysis of the relationship between the concordance rate of the two methods and the localization of lung nodules suggested that Jiang's method was superior to the traditional method in the diagnostic rate of the left upper lung lobes. No statistical difference was found for other lung lobes; it may be because further categorization according to nodule localization resulted in a smaller sample size, leading to a decrease in test efficacy. We can explain it by expanding the sample size in the future. Signs of malignancy are more common in Jiang’s method than in the traditional method, which may lead to exaggerating the malignant detection rate. However, by analyzing the distribution of the final diagnosis, there was no statistically significant difference between the two groups' final benign and malignant ratios, which indicates that it does not lead to exaggerated diagnostic efficacy. With a balanced baseline, Jiang's group did not show statistically significant differences in sensitivity, specificity and predictive value from the traditional method. It is probably because our study was a single-centre retrospective analysis; the pathology results relied on pathologists from the same centre to read the CT images and were not blinded beforehand. In addition, the pathologists accessed the patient's information from the medical record system. They made a final diagnosis interpretation of the non-specific pathology specimens consistent with the clinical situation. As a result, it will increase diagnostic scepticism bias. By the way, the traditional method has limited sample size, non-randomization, and is not included in a time gradient; thereby, it would produce a selection bias to cover the differences in diagnosis efficacy. In addition, due to the limitation of the indicator definition, the formula only calculated the patients who obtained both final diagnosis and puncture results and did not include the patients who had not been diagnosed. It may ignore the impact of sampling failure and obtain non-specific lesions outside of the target tissues on the diagnosis in the actual situation. In conclusion, comparing the two methods, although Jiang's method improved the malignant detection rate and diagnostic concordance rate, the sensitivity, specificity, and predictive value were not significant compared with the traditional method. Our study is a single-centre, retrospective historical cohort study with limited extrapolation of findings and limited proof strength in two independent samples due to unknown confounders. Further paired studies in vivo animals could be conducted for a supplement. The traditional method’s sample size is limited, and the occurrence of false positives, false negatives and complications may be incompletely revealed. In addition, the retrospective study was not blinded for pathologic diagnosis, and the pathologists could reference the patient's clinical information to diagnose nonspecific specimens, which could bias the results, resulting in no statistically significant difference in sensitivity and specificity between the two methods of comparative study. In conclusion, Jiang's method can improve puncture efficiency and reduce the incidence of complications. It is also significantly better than the traditional unassisted method in terms of technical safety and success. Abbreviations CT：Computed Tomography PTLB：Percutaneous Transthoracic Lung Biopsy PTNB：Percutaneous Transthoracic Needle Biopsy LDCT：Low Dose Computed Tomography LGS：Laser-guided system ACCP：American College of Clinical Pharmacy NCCN：National Comprehensive Cancer Network SPSS：Statistical Product and Service Solutions SAS：Statistical Analysis System ROC：Receiver Operating Characteristic Curve Declarations Ethical Approval: This study was approved by the Medical Ethics Committee of Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) (No.:[2024]-289), the date of registration is 18/07/2024. Because this was a retrospective study, written informed consent was waived, all methods were performed in accordance with the relevant guidelines and regulations. We hereby confirm that our study strictly adheres to the principles outlined in the Declaration of Helsinki. Consent for public: Written consent for publication has been obtained from all participants. Available of data and materials: All data generated or analysed during this study are included in this published article, . Competing interests: The authors have no conflicts of interest to disclose. Funding: This work was supported by the grant from by National Natural Science Foundation of China (82400050,82070057),and the Natural Science Foundation of Hunan (2021JJ30400,2024JJ6270,2023SK2110-2),and the Natural Science Foundation of Changsha(kq2014191),and the Young Doctor Foundation of Hunan Provincial People's Hospital(BSJJ202215). Author contributions: S.Y.J. is responsible for the article，including the content of the manuscript, reference list’s accuracy and appropriateness, S.Y. J. contributed to protocol design, patient enrollment, data curation and interpretation, drafting of manuscript and preparation of figures and tables. C. 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Can Association Radiol J = J l'Association canadienne des radiologistes. 2024;8465371241242758. https://doi.org/10.1177/08465371241242758 . E H, et al. Three-dimensionally printed navigational template: a promising guiding approach for lung biopsy. Translational lung cancer Res. 2022;11:393–403. https://doi.org/10.21037/tlcr-22-172 . Jeon MC, et al. CT-Guided Percutaneous Transthoracic Needle Biopsy Using the Additional Laser Guidance System by a Pulmonologist with 2 Years of Experience in CT-Guided Percutaneous Transthoracic Needle Biopsy. Tuberc Respir Dis. 2018;81:330–8. https://doi.org/10.4046/trd.2017.0123 . He C, et al. Incidence and risk factors for pulmonary hemorrhage after percutaneous CT-guided pulmonary nodule biopsy: an observational study. Sci Rep. 2024;14:7348. https://doi.org/10.1038/s41598-024-58045-3 . Çakir Ö, Çam I, Koç U, Çiftçi E. Evaluation of major complications associated with percutaneous CT-guided biopsy of lung nodules below 3 cm. Turk J Med Sci. 2020;50:369–74. https://doi.org/10.3906/sag-1908-73 . Ruud EA, et al. Predictors of pneumothorax and chest drainage after percutaneous CT-guided lung biopsy: A prospective study. Eur Radiol. 2021;31:4243–52. https://doi.org/10.1007/s00330-020-07449-6 . Hajjar WM, et al. Complications and Risk Factors of Patients Undergoing Computed Tomography-Guided Core Needle Lung Biopsy: A Single-Center Experience. Cureus. 2021;13:e16907. https://doi.org/10.7759/cureus.16907 . Liu SH, et al. A retrospective analysis of the risk factors associated with systemic air embolism following percutaneous lung biopsy. Experimental therapeutic Med. 2020;19:347–52. https://doi.org/10.3892/etm.2019.8208 . Tey AJ, Wong JJJ, Lim NF, Ho S. Systemic Air Embolism after Image-guided Percutaneous Biopsy of the Lung. Am J Respir Crit Care Med. 2024;210:e1–2. https://doi.org/10.1164/rccm.202308-1496IM . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6390597","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":453475208,"identity":"46d2c6a7-5c0f-4f4d-b3d4-d0a09dbb5124","order_by":0,"name":"ShiYin Jiang","email":"","orcid":"","institution":"Hunan Provincial People's Hospital(The first-affiliated hospital of Hunan normal university)","correspondingAuthor":false,"prefix":"","firstName":"ShiYin","middleName":"","lastName":"Jiang","suffix":""},{"id":453475209,"identity":"99f9a6e2-48f8-4c6b-bcee-b90764592c35","order_by":1,"name":"Chao Li","email":"","orcid":"","institution":"Hunan Provincial People's Hospital(The first-affiliated hospital of Hunan normal university)","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Li","suffix":""},{"id":453475210,"identity":"55890d1b-75eb-42f4-8c56-f2e047c4a755","order_by":2,"name":"JiaWei Long","email":"","orcid":"","institution":"Hunan Provincial People's Hospital(The first-affiliated hospital of Hunan normal university)","correspondingAuthor":false,"prefix":"","firstName":"JiaWei","middleName":"","lastName":"Long","suffix":""},{"id":453475211,"identity":"118ac10b-5670-464d-84e7-f8b030826f41","order_by":3,"name":"Cheng Li","email":"","orcid":"","institution":"Hunan Provincial People's Hospital(The first-affiliated hospital of Hunan normal university)","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Li","suffix":""},{"id":453475212,"identity":"fb8c6df4-baec-468e-9d2f-5fe4765587ad","order_by":4,"name":"WuSheng Deng","email":"","orcid":"","institution":"Hunan Provincial People's Hospital(The first-affiliated hospital of Hunan normal university)","correspondingAuthor":false,"prefix":"","firstName":"WuSheng","middleName":"","lastName":"Deng","suffix":""},{"id":453475213,"identity":"1b6a621a-9034-4de9-b341-3745bdcfad23","order_by":5,"name":"YongLiang Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIie3QsQrCMBCA4SuBuMR2vS61jxAolA59E5cEoZsuLg5FCh1cCr6K4AsUDtpF6OqYR9Cto3ZzS0aH/NtBvoMLgM/3lwUG1IxJxBgZR8Ik6K7I4guvpDsBftJyEik6AfncBcYIVBkJkFCXWxfCpCrwkNO6NzBU+8ZKHtOASuAxp1DJoCEXQqtZcdT3Vkh0I2PLYSE35krisWWoO8yQvp+sXG4JiQXveT4n0ZXIvOrSTtL+d1K250sb61Kfz+fzfQB/UT17LYR1WgAAAABJRU5ErkJggg==","orcid":"","institution":"Hunan Provincial People's Hospital(The first-affiliated hospital of Hunan normal university)","correspondingAuthor":true,"prefix":"","firstName":"YongLiang","middleName":"","lastName":"Jiang","suffix":""}],"badges":[],"createdAt":"2025-04-07 06:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6390597/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6390597/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82356358,"identity":"cd5837d2-5cc4-4bed-a5bb-5ac150e87da5","added_by":"auto","created_at":"2025-05-09 11:17:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69338,"visible":true,"origin":"","legend":"\u003cp\u003eLaser-guided system principle colorful chart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/3b4d8a86266cde65e9452bcf.png"},{"id":82356361,"identity":"57d0c4a5-8e78-4331-8ae0-8cd34d16b48f","added_by":"auto","created_at":"2025-05-09 11:17:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83597,"visible":true,"origin":"","legend":"\u003cp\u003ePuncture schematic\u003c/p\u003e\n\u003cp\u003eA: Scalloped columns represent the patient's chest, irregular circle-like shapes represent pulmonary nodules, and the red line represents the red laser, which defines the angle； B： The green laser determines the level of puncture to guide the needle insertion； C： The red and green plane define a line.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/02638d69468eae297c3707eb.png"},{"id":82356362,"identity":"3eb64f14-924d-49d4-b33a-86f4da2cd013","added_by":"auto","created_at":"2025-05-09 11:17:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":784907,"visible":true,"origin":"","legend":"\u003cp\u003ePuncture model\u003c/p\u003e\n\u003cp\u003eA： Human skeleton model filled with argil to simulate lung tissue； B： Green plasticine of about 2 cm in diameter was placed to simulate lung nodule\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/c7715eb7b589c1bac2750503.png"},{"id":82356369,"identity":"b8ed9c45-1fac-4ed9-bffd-15f1d59059d1","added_by":"auto","created_at":"2025-05-09 11:17:58","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":209678,"visible":true,"origin":"","legend":"\u003cp\u003eOperation procedure\u003c/p\u003e\n\u003cp\u003eA: Paste the homemade fence on the patient’s chest; B: Preoperative CT scan to plan the needle path; C: Adjusting CT slices to the puncture transverse plane; D: Adjust the angle of the red laser device to a particular value that consistent with the plan; E: Mark body surface puncture point; F: Put the devices to appropriate location; G: Ensure two lights crossed on the puncture point; H: Operator insert the coaxial needle at the guidance of two lights real-timely; I: Conduct a CT scan again to prevent complication; J: Acquire the lung tissue and put it in the formalin quickly.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/2f7d1ba7ab2022600ba29f05.jpg"},{"id":82356360,"identity":"61a80208-1abe-4ddf-8c09-f3682ae49463","added_by":"auto","created_at":"2025-05-09 11:17:58","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":87655,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of puncture efficiency graph\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/4042f9785c8f26850a4f03c2.jpg"},{"id":82356363,"identity":"a7e811ab-c937-4dd7-8264-cca5aad1434c","added_by":"auto","created_at":"2025-05-09 11:17:58","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":152339,"visible":true,"origin":"","legend":"\u003cp\u003ePie chart of complication rates\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/162cb6a814ad532dacf52f62.jpg"},{"id":82359855,"identity":"c001864c-1f99-4b3c-8f4b-d84f169308f2","added_by":"auto","created_at":"2025-05-09 11:33:58","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":48471,"visible":true,"origin":"","legend":"\u003cp\u003eTechnical Success Pie Charts\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/96a11fbe945ed1c1422dd233.jpg"},{"id":103049457,"identity":"6c79c86b-f55c-4d52-8bca-be3d669f08cb","added_by":"auto","created_at":"2026-02-20 07:41:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2114723,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6390597/v1/019b1d3a-75f2-46c3-a5fa-20e1339fa966.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Study on the Clinical Application of Jiang's Percutaneous Transthoracic Lung Biopsy in Pulmonary Nodules","fulltext":[{"header":"Highlights","content":"\u003cp\u003eWe invented a Laser-guided system to assist thransthoracic percutaneous lung biopsy.\u003c/p\u003e\n\u003cp\u003eWe developed a method called Jiang\u0026apos;s percutaneous lung biopsy to improve the efficiency of the puncture.\u003c/p\u003e\n\u003cp\u003eWe used a homemade puncture model to evaluate the efficiency of puncture.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eAccording to 《Cancer incidence and mortality in China, 2022》, China's lung cancer incidence and mortality rates are at the top of the list \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In 2022, there will be 730,000 new lung cancer deaths, which was the highest mortality rate in the world, with 1.8\u0026nbsp;million deaths due to lung cancer, accounting for 18.7% of all\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Therefore, it is of great importance to disseminate cancer prevention measures that focus on early detection, early diagnosis, and treatment. Among them, detection and diagnosis at an early stage is one of the most essential aspects, and how to screen for early lung cancer is of particular concern.\u003c/p\u003e \u003cp\u003eLung nodules may be precancerous lesions or the early manifestation of lung cancer, characterised by single or multiple soft tissue density masses on CT images in the lung field, with relatively fixed borders and increased density compared with the surrounding tissue. The diameter of the mass is usually not greater than 30 mm, encircled by the lung parenchyma, and entirely or incompletely covers the internal vascular and bronchial density masses\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The American College of Chest Physicians (ACCP) recognises that when a nodule is more significant than 8 mm, it is essential to be alert to the possibility of malignancy \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Therefore, patients with lung nodules are potential beneficiaries for early diagnosis and treatment of lung cancer. With the promotion of low-dose helical computed tomography (LDCT) \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, the number of patients with pulmonary nodules is increasing yearly, and it has become a common disease in clinical practice. With low diagnostic efficacy based on indirect evidence alone \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, it brings tremendous psychological pressure to patients, and how to rationally manage pulmonary nodules has aroused extensive attention. According to the 2017 Fleischner Guide \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and NCCN Guidelines for the 2021 Edition \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, lung biopsy is recommended to obtain diagnostic evidence in high-risk patients.\u003c/p\u003e \u003cp\u003ePercutaneous transthoracic needle biopsy (PTNB) is most commonly used to diagnose lung cancer \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e; documentation dates back to 1970 \u003csup\u003e11\u003c/sup\u003e. CT-PTNB is a diagnostic technique that involves using a biopsy needle to obtain tissue or cellular specimens by percutaneous puncture into a lung nodule under the guidance of medical imaging equipment.\u003c/p\u003e \u003cp\u003eWe usually use CT or bronchoscopy to guide the biopsy. The disadvantage of bronchoscopy is that it is not available for peripheral nodules, so we choose CT instead. After years of development, many new technologies have emerged, such as IG4 electromagnetic navigation \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, robotic assistance \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, 3D printing technology\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, and many other precise, expensive, and technically demanding precision aids. Such as, Min-Cheol Jeon invented a laser-assisted puncture system\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, and some scholars have utilised more straightforward, affordable and easily replicable tools such as fences, protractors and lasers to improve CT-PTNB. However, we found that these methods have some shortcomings that need to be improved.\u003c/p\u003e \u003cp\u003eTherefore, we developed Jiang\u0026rsquo;s Percutaneous Transthoracic Lung Biopsy, which utilizes two sets of lasers to assist in determining the angle and level of puncture. To evaluate this method's advantages, we verified its puncture efficiency and accuracy through model experiments and collected and analyzed clinical data to assess its safety, efficacy and diagnostic efficacy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003e1.1 Principle and procedure\u003c/h2\u003e\n\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\n\u003ch2\u003e3.1.1 Principle\u003c/h2\u003e\n\u003cp\u003eTo elevate the precision of puncture, we should pay attention to four elements during operation: 1. body surface localization point; 2. puncture angle; 3. puncture depth; 4. puncture level. The body surface localization point can be located by sticking a fence on the body surface, combined with the CT laser. The depth is determined by the scale on the puncture needle. Jiang\u0026rsquo;s Percutaneous Transthoracic Lung Biopsy aims to determine the angle as well as the level of puncture.\u003c/p\u003e\n\u003cp\u003eLaser-guided system (LGS): To provide precise guidance through real-time visualization during operation. It is mainly done through two homemade laser devices to guide (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). It consists of a bracket and a laser goniometer mounted on it (Patent No. ZL 20222016072.3), which emits perpendicular and reference laser lights. As shown in the figure (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), the laser device emits vertical and horizontal beam lines. The red lines originated from the foot end to determine the puncture angle. At the same time, another laser device placed on the opposite of the operator emits a green beam light to determine the level. Two lights cross at the predetermined puncture point. We should keep these two light beams on the coaxial needle when we insert the needle.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe red laser is placed on the foot side of the patient to determine the angle of penetration; the green laser is placed on the opposite side of the operator to determine the level of penetration\u003c/p\u003e\n\n\u003cp\u003e3.1.2 Puncture model (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e): We fill argil in a simulated human thoracic skeleton model as the lung tissue, and a piece of green plasticine with a diameter of 2 cm is placed in it to simulate the lung nodules.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n\u003ch2\u003e3.1.3 Process of model experiment\u003c/h2\u003e\n\u003cp\u003eObjects: We recruited 34 respiratory medicine physicians who had never been trained or finished PTNB and taught them both the Jiang\u0026rsquo;s and traditional methods to achieve biopsy on the model.\u003c/p\u003e\n\u003cp\u003ePoint of puncture: First, we paste the fence on the patient\u0026rsquo;s chest and then scan a CT. We can notice that there are several white dots above the chest, which represent the fence. According to this, we can determine the anatomic puncture approach. Second, we determine which fence line is the path we need, marking the line on the skin. Third, the CT scanning cursor is moved to a specific location, referring to the CT image, and then we can draw the horizontal line. Last, the intersection of these two lines is the point of puncture we need.\u003c/p\u003e\n\u003cp\u003eModel experiment traditional puncture method: We insert the needle subcutaneously and do a CT scan again to predict whether the needle can reach the nodule aimed at. If the angle deviation is too large, we should adjust the angle until we can aim at that nodule.\u003c/p\u003e\n\u003cp\u003eJiang's Percutaneous Transthoracic Lung Biopsy: First, we put the red laser device on the patient's foot side and the green laser device opposite the operator. Second, we should adjust the horizontal angle of both devices to 0\u0026deg;; the green line should be adjusted at 90\u0026deg; to a horizontal surface. The red laser will guide the puncture angle, so we should adapt it to the aimed angle. Third, as marked before, the two colourful lines should be crossed on the chest's point. Last, we should ensure that the two lines are always on the needle when we puncture to achieve real-time guidance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n\u003ch2\u003e3.1.4 Clinical trial process\u003c/h2\u003e\n\u003cp\u003eObjects: We randomly sampled the data of patients from 258 cases who underwent Jiang\u0026rsquo;s method in our hospital (From January 2021 to July 2023) and then compared them with 129 patients\u0026rsquo; cases data (From March 2020 to July 2023) who used the traditional method to biopsy.\u003c/p\u003e\n\u003cp\u003eThe data of patients with pulmonary nodules who underwent Jiang's method in our hospital (from January 2021 to July 2023), from which a sample of 258 cases was randomly selected, were compared with the data of 129 patients with nodules who underwent the traditional method in the past (from March 2020 to July 2023) according to a 2:1 ratio to compare the efficacy and safety of these two methods.\u003c/p\u003e\n\u003cp\u003eInclusion criteria: over 18 years old, pulmonary nodules in the lungs on CT imaging, patient consent to participate and signing of an informed consent form.\u003c/p\u003e\n\u003cp\u003eExclusion criteria: severe coagulation disorders, anatomical abnormalities, refusal to participate in the study, or inability to provide complete data.\u003c/p\u003e\n\u003cp\u003ePreoperative evaluation: Improve assessment to exclude contraindications and avoid emphysema, interlobular fissures, large blood vessels, and abnormal enhancement foci on enhanced CT. We should fully understand the location and size of the lesion and the surrounding vascular condition through enhanced CT and determine the point and plan of penetration. The puncture point was determined as in the model experiment.\u003c/p\u003e\n\u003cp\u003ePreparation for puncture: electrocardiogram monitoring of the patient's vital signs, choosing the appropriate pose according to the puncture path, instructing the patient to maintain a fixed position, preparing the puncture device, and confirming that the first aid equipment is ready. The operator wears a surgical gown, mask, cap and gloves and determines the type and model of the biopsy needle according to the lesion size. Routinely disinfects, drapes the patient, local infiltration anaesthesia, enters the needle to reach the target position by using different methods of puncture, and then performs a CT scan again to clarify the position of the needle.\u003c/p\u003e\n\u003cp\u003eClinical study of the traditional puncture: the needle is advanced vertically from the puncture point layer by layer, and the needle will stop when it reaches the expected depth.\u003c/p\u003e\n\u003cp\u003eThe experimental group used the same method as the model experiment for Jiang\u0026rsquo;s percutaneous transthoracic lung biopsy (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSpecimen acquisition and pathological evaluation: Once the specimen was obtained, we put the specimen into formalin for fixation, withdrew the puncture needle, and pressed the wound until there was no bleeding. At the same time, we should pay attention to the patient's symptoms and whether there are any complications, such as chest tightness and bleeding. Then, we could send the patient back to the ward in a wheelchair under oxygenation. We should perform chest X-rays routinely after the operation to review the occurrence of any delayed complications.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 Statistical methods\u003c/h2\u003e\n\u003cp\u003eData collection: We used epi data 3.1 software to collect data and excluded incomplete data such as no preoperative and postoperative CT results, no records of relevant complications, and the data after microwave as well as radiofrequency ablation.\u003c/p\u003e\n\u003cp\u003eStatistical analysis: We used SPSS 22.0 and SAS 9.4. to analyze the collected data. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median and interquartile spacing, and comparisons between groups were made using analysis of variance or Mann-Whitney U test. Nominal and categorical data were expressed as number (n) and frequency (%), and between-group comparisons were analyzed using the chi-square test or Fisher's exact test. Comparisons of baseline data were made using a two-sided test. Diagnostic efficacy, technical safety indexes, and technical success indexes were compared using one-sided tests. The value of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. We fitted the ROC curve to assess the diagnostic accuracy and acquire the sensitivity, specificity, predictive value, and Jordon's index.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 Results of model experiments\u003c/h2\u003e\n \u003cp\u003eJiang\u0026apos;s method could improve the puncture efficiency (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e,Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). It has a significantly higher success rate of one-time achievement ratio of puncture than the unassisted method (76.5% vs 11.8%), shorter puncture time (3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 minutes vs 8.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48 minutes), fewer CT scans (1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43 times vs 3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06 times), and fewer puncture times (1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43 times vs 2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06 times). A significant difference was related to these indicators (P\u0026lt;0.05).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\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\u003epuncture efficiency\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJiang\u0026apos;s Group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;34\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTraditional group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;34\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\u003eOne-time achievement ratio of puncture (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76.5(26/34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.8(4/34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePuncture time(min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCT scans(times)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumbers of Puncture(times)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\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\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cbr\u003e\u003c/h2\u003e\n \u003ch2\u003e4.2 Results of clinical trials\u003c/h2\u003e\n\u003c/div\u003e\n\u003cp\u003e1) Comparison of baseline data\u003c/p\u003e\n\u003cp\u003eThere was no statistical difference in the baseline information between the two methods at the population level (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). At the clinical level, there was a statistical difference in the prevalence of diabetes mellitus (P\u0026thinsp;=\u0026thinsp;0.0356\u0026thinsp;\u0026lt;\u0026thinsp;0.05) but no statistically significant difference in the remaining items. The baseline data is balanced.\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\u003eBaseline data\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\" rowspan=\"2\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJiang\u0026rsquo;s\u003c/p\u003e\n \u003cp\u003egroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTraditional group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP\u003csub\u003etwo sides\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;258\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;129\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;387\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\u003eComorbidity, n(%)\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=\"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\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51(19.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(28.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88(22.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0514\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(6.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(13.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34(8.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0356\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCoronary heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(6.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(7.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(6.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5699\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(8.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(9.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34(8.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-thoracic tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24(9.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(7.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34(8.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSymptom, n(%)\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=\"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\u003eCough and sputum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99(38.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52(40.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e151(39.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChest pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(11.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(7.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(10.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(3.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(2.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3114*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood in sputum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion localization, n(%)\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=\"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\u003eRight upper lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83(32.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(23.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113(29.20)\u003c/p\u003e\n \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\u003eRight middle lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(10.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(8.27)\u003c/p\u003e\n \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\u003eRight lower lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62(24.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(23.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92(23.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0234\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft upper lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51(19.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33(25.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84(21.71)\u003c/p\u003e\n \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 lower lobe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36(13.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(23.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66(17.05)\u003c/p\u003e\n \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 size(mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.89(6.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.49(7.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung nodule density, n(%)\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=\"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\u003ePure ground-glass nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(6.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(5.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24(6.20)\u003c/p\u003e\n \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\u003eSubsolid nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43(16.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(20.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(17.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSolid nodule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e198(76.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96(74.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e294(75.97)\u003c/p\u003e\n \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\u003eMultiple nodules,n(%)\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=\"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\u003e163(63.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60(46.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e223(57.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0018\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\u003e95(36.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(53.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e164(42.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalignant sigh, n(%)\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=\"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\u003ePleural identation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90(34.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(20.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116(29.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpiculation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105(40.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(30.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e144(37.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0430\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrregular shapes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84(32.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(7.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94(24.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLobulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89(34.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(30.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e128(33.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymph node enlargement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42(16.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(14.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61(15.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eFootnote: *Fisher\u0026rsquo;s exact test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e2) Comparison of diagnostic effectiveness\u003c/p\u003e\n\u003cp\u003eThe diagnostic efficacy of the two methods was comparable (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The sensitivity of Jiang\u0026apos;s group was 94.19% (146/155), the specificity was 97.30% (36/37), the positive predictive value was 99.32% (146/147), and the negative predictive value was 80.00% (36/45). The sensitivity of the traditional method was 88.52% (54/61), specificity was 96.77% (30/31), positive predictive value was 98.18% (54/55), and negative predictive value was 81.08% (30/37), none of these indicators had significant difference. The Youden index was 0.9149 for Jiang\u0026apos;s method and 0.8529 for the traditional method.\u003c/p\u003e\n\u003cp\u003e3) Comparison of detection concordance rates\u003c/p\u003e\n\u003cp\u003eThe detection rate of malignant nodules by Jiang\u0026apos;s method was 89.57% (146/163), and that of benign nodules was 75.00% (36/48), with a concordance rate of 86.26% (182/211). Jiang\u0026apos;s method had a higher malignant detection rate than the traditional method, and the differences were statistically significant (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Further subgrouped according to nodule localization, the final diagnostic concordance rate of left upper lung nodules was greater in Jiang\u0026apos;s method than in the traditional method, and the difference was statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\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\u003eComparison of diagnostic efficacy and detection concordance\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJiang\u0026rsquo;s group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTraditional group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSingle\u003csub\u003e\u0026minus;\u0026thinsp;side\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;192\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;92\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\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1683*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive predictive value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e99.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4714*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative predictive value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBenign rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0348\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalignant rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2087*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConcordance rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0045*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eFootnote: *Fisher\u0026rsquo;s exact test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e4) Technical safety indicators comparison\u003c/p\u003e\n\u003cp\u003eThe complication rate of the two groups was as follows (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e): Jiang\u0026apos;s group: 31 cases of pneumothorax (12.02%), 20 cases of bleeding from the needle tract (7.75%), and 4 cases of hemoptysis (1.55%). Traditional group: 37 cases of pneumothorax (28.68%), 16 cases of bleeding from the needle tract (12.40%), and 15 cases of hemoptysis (11.63%). The difference was statistically significant, and neither group had an air embolism.\u003c/p\u003e\n\u003cp\u003e5) Comparison of technical success and other indicators:\u003c/p\u003e\n\u003cp\u003eJiang\u0026apos;s group had a higher technical success rate (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e), with 6 cases of insufficient sample size and an incidence rate of 2.33% (6/258). In the traditional group, a sample of 9 cases is inadequate, with an incidence rate of 6.98%, a statistically significant difference (P\u0026thinsp;=\u0026thinsp;0.0264). Of the postoperative hospitalization days, the median and the interquartile spacing was three days in Jiang\u0026apos;s group and four days in the traditional group. The unilateral Mann-Whitney U test suggested that the number of postoperative hospitalization days was less in Jiang\u0026apos;s group than in the conventional group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith the popularity of LDCT, the detection rate of lung nodules is increasing year by year, and pathological evidence is still the gold standard. However, the traditional method of sampling lung nodules has many shortcomings, so we improved it. This paper aims to evaluate this method.\u003c/p\u003e \u003cp\u003eConventional unassisted puncture is inserting the needle subcutaneously by experience according to the initial CT image, then performing a CT scan again to assess the angle. If it is significantly off track, we could adjust the angle and insert it again. In the absence of other auxiliary tools, based on different personal experiences and the sense of touch of distinct operators, the standing position, as well as an ideal planar state thorax, it is difficult to predict the angle of the needle only based on the subjective judgment of an operator and to accurately replicate the simulated path of puncture to the real life as well as visualize the needle position in real-time. In the end, repeated CT scans will be required to adjust the direction of the puncture, which could increase radiation exposure and operation time.\u003c/p\u003e \u003cp\u003eTo sum up, the uncertainty of unassisted punctures is high, and individual success cannot be replicated because the experience and feel of punctures cannot be developed in a short time. As a result, many puncture assistive devices have been designed to improve puncture efficiency further. Laser-assisted puncture device was invented by Min-Cheol Jeon in Korea \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Other scholars have invented the double fence positioning angle gauge, long-distance laser, double-needle CT-guided percutaneous lung biopsy, and many other different ways. However, there are still some shortcomings, such as a cumbersome adjustment process, lack of flexibility, contaminating the operation area easily, increasing the number of punctures as well as CT scan times, and accuracy needs to be improved. Therefore, we invented Jiang's method to improve it further.\u003c/p\u003e \u003cp\u003eThere are four elements in lung puncture: surface localization, puncture level, angle, and depth. A combination of fence and collimated laser light from the CT determines surface localization. The scale on the needle determines the depth of the puncture. To improve puncture accuracy, Jiang's method mainly uses a red light to determine the puncture angle and a green light to locate the puncture needle in the transverse plane. It guides the needle in real-time throughout the puncture process to prevent it from deviating. In addition, long-distance laser guidance can reduce infection; it also has good manoeuvrability, easy to use and cheap. In conjunction with this method applied in practice, we can draw the following conclusions.\u003c/p\u003e \u003cp\u003eFirst, Jiang's method can improve puncture efficiency and reduce the complication rate. Repeated puncture increases the chance of passing through interlobar fissures, pulmonary blisters, and injury to the thick bronchi. Also, the prolonged retention of the puncture needle in the lung tissue, coupled with the effects of respiratory motion, will continuously cut into the lung tissue and increase the risk of complications \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Reducing the number and duration of punctures significantly reduces puncture complications such as bleeding, hemoptysis, and pneumothorax \u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The results of the model experiment suggested that Jiang's method could considerably reduce the number of needle adjustments and shorten the puncture time. The clinical control study showed that the complication rate of the traditional group was significantly higher than that of Jiang\u0026rsquo;s group, which was in line with previous studies in the literature. To avoid Air embolism \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, the coaxial needle should not be left exposed to air for long periods during the operation, and we should keep the core in the needle at all times when we penetrate. Fewer complications can shorten postoperative hospitalization days and benefit the patient economically. Second, Jiang's method can improve the diagnostic efficacy. Tumors, infections, inflammation, autoimmunity, and other [22] pathological conditions could also manifest as pulmonary nodules. Thus, it is vital to accurately determine their benign and malignant nature and then appropriately intervene. Synthesizing the results of studies from multiple centres at home and abroad [23\u0026ndash;26], the sensitivity of PTNB was 72.34%-95.7%, and the specificity was 95.7%-100%, we can notice that the efficacy of Jiang's method was consistent with the trend. There were differences in the distribution of lesion localization and the percentage of malignant signs between the two groups in the baseline data, which may be related to different teams' assessment of lung nodules. Further analysis of the relationship between the concordance rate of the two methods and the localization of lung nodules suggested that Jiang's method was superior to the traditional method in the diagnostic rate of the left upper lung lobes. No statistical difference was found for other lung lobes; it may be because further categorization according to nodule localization resulted in a smaller sample size, leading to a decrease in test efficacy. We can explain it by expanding the sample size in the future.\u003c/p\u003e \u003cp\u003eSigns of malignancy are more common in Jiang\u0026rsquo;s method than in the traditional method, which may lead to exaggerating the malignant detection rate. However, by analyzing the distribution of the final diagnosis, there was no statistically significant difference between the two groups' final benign and malignant ratios, which indicates that it does not lead to exaggerated diagnostic efficacy. With a balanced baseline, Jiang's group did not show statistically significant differences in sensitivity, specificity and predictive value from the traditional method. It is probably because our study was a single-centre retrospective analysis; the pathology results relied on pathologists from the same centre to read the CT images and were not blinded beforehand. In addition, the pathologists accessed the patient's information from the medical record system. They made a final diagnosis interpretation of the non-specific pathology specimens consistent with the clinical situation. As a result, it will increase diagnostic scepticism bias. By the way, the traditional method has limited sample size, non-randomization, and is not included in a time gradient; thereby, it would produce a selection bias to cover the differences in diagnosis efficacy. In addition, due to the limitation of the indicator definition, the formula only calculated the patients who obtained both final diagnosis and puncture results and did not include the patients who had not been diagnosed. It may ignore the impact of sampling failure and obtain non-specific lesions outside of the target tissues on the diagnosis in the actual situation. In conclusion, comparing the two methods, although Jiang's method improved the malignant detection rate and diagnostic concordance rate, the sensitivity, specificity, and predictive value were not significant compared with the traditional method.\u003c/p\u003e \u003cp\u003eOur study is a single-centre, retrospective historical cohort study with limited extrapolation of findings and limited proof strength in two independent samples due to unknown confounders. Further paired studies in vivo animals could be conducted for a supplement. The traditional method\u0026rsquo;s sample size is limited, and the occurrence of false positives, false negatives and complications may be incompletely revealed. In addition, the retrospective study was not blinded for pathologic diagnosis, and the pathologists could reference the patient's clinical information to diagnose nonspecific specimens, which could bias the results, resulting in no statistically significant difference in sensitivity and specificity between the two methods of comparative study.\u003c/p\u003e \u003cp\u003eIn conclusion, Jiang's method can improve puncture efficiency and reduce the incidence of complications. It is also significantly better than the traditional unassisted method in terms of technical safety and success.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCT：Computed Tomography\u003c/p\u003e\n\u003cp\u003ePTLB：Percutaneous Transthoracic Lung Biopsy\u003c/p\u003e\n\u003cp\u003ePTNB：Percutaneous Transthoracic Needle Biopsy\u003c/p\u003e\n\u003cp\u003eLDCT：Low Dose Computed Tomography\u003c/p\u003e\n\u003cp\u003eLGS：Laser-guided system\u003c/p\u003e\n\u003cp\u003eACCP：American College of Clinical Pharmacy\u003c/p\u003e\n\u003cp\u003eNCCN：National Comprehensive Cancer Network\u003c/p\u003e\n\u003cp\u003eSPSS：Statistical Product and Service Solutions\u003c/p\u003e\n\u003cp\u003eSAS：Statistical Analysis System\u003c/p\u003e\n\u003cp\u003eROC：Receiver Operating Characteristic Curve\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical Approval: This study was approved by the Medical Ethics Committee of Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) (No.:[2024]-289), the date of registration is 18/07/2024. Because this was a retrospective study, written informed consent was waived, all methods were performed in accordance with the relevant guidelines and regulations. We hereby confirm that our study strictly adheres to the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eConsent for public: Written consent for publication has been obtained from all participants.\u003c/p\u003e\n\u003cp\u003eAvailable of data and materials: All data generated or analysed during this study are included in this published article, .\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003eFunding: This work was supported by the grant from by National Natural Science Foundation of China (82400050,82070057),and the Natural Science Foundation of Hunan (2021JJ30400,2024JJ6270,2023SK2110-2),and the Natural Science Foundation of Changsha(kq2014191),and the Young Doctor Foundation of Hunan Provincial People's Hospital(BSJJ202215).\u003c/p\u003e\n\u003cp\u003eAuthor contributions: S.Y.J. is responsible for the article，including the content of the manuscript, reference list’s accuracy and appropriateness, S.Y. J. contributed to protocol design, patient enrollment, data curation and interpretation, drafting of manuscript and preparation of figures and tables. C. L. conceptualized the study, contributed to editing manuscript, supervised the study. J.W.L. contributed to patient enrollment, data analysis and acquisition, preparation of figures and tables. C. L. contributed to preparation of figures, data collection, patient enrollment, supervised the study. W.S.D. contributed to preparation of video, patient enrollment and data collection. All authors critically revised the manuscript and approved the final version to submit for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHan B et al. 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Cureus. 2021;13:e16907. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7759/cureus.16907\u003c/span\u003e\u003cspan address=\"10.7759/cureus.16907\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu SH, et al. A retrospective analysis of the risk factors associated with systemic air embolism following percutaneous lung biopsy. Experimental therapeutic Med. 2020;19:347\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3892/etm.2019.8208\u003c/span\u003e\u003cspan address=\"10.3892/etm.2019.8208\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTey AJ, Wong JJJ, Lim NF, Ho S. Systemic Air Embolism after Image-guided Percutaneous Biopsy of the Lung. Am J Respir Crit Care Med. 2024;210:e1\u0026ndash;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/rccm.202308-1496IM\u003c/span\u003e\u003cspan address=\"10.1164/rccm.202308-1496IM\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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":"COPD, PTNB, CT, Lung nodules, cancer","lastPublishedDoi":"10.21203/rs.3.rs-6390597/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6390597/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Lung cancer has a high global mortality rate, and CT-guided percutaneous lung biopsy is used for lung biopsy. We invented a laser-assisted puncture system named Jiang’s percutaneous transthoracic lung biopsy to assist diagnose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Jiang's PTLB optimizes CT-guided percutaneous lung puncture via a simple homemade laser-guided puncture device with two laser devices to determine the angle and level of puncture. We recruited 34 physicians to perform a self-controlled trial of the model via two methods to evaluate its effectiveness. A total of 390 patients from January 2021 to July 2023 underwent Jiang’s method and 129 patients from March 2020 to July 2023 underwent the conventional method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e 1. Model experiment results: Jiang's method resulted in a higher single penetration rate (76.5% vs. 11.8%), shorter operation time (3.04±1.12 minutes vs 8.43±2.48 minutes), fewer CT scans (1.24±0.43 times vs. 3.91±1.06 times), and fewer penetrations (1.24±0.43 vs. 2.91±1.06); 2. Clinical trial results: In Jiang’s group, pneumothorax was developed in 31 patients (12.02%), bleeding occurred in 20 patients (7.75%), and 4 patients bled (1.55%). Jiang's method had a sensitivity of \u0026nbsp;94.19%, a specificity of \u0026nbsp;97.30%, \u0026nbsp;a Youden index of \u0026nbsp;0.9149, a positive predictive value of \u0026nbsp;99.32%, a negative predictive value of 80.00%, a malignancy rate of 89.57%, a benign detection rate of 75.00%, and a concordance rate of 86.26%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Compared with the unassisted method, Jiang's method can significantly improve the puncture efficiency, reduce the incidence of complications, and increase the safety and effectiveness of the lung biopsy.\u003c/p\u003e","manuscriptTitle":"A Study on the Clinical Application of Jiang's Percutaneous Transthoracic Lung Biopsy in Pulmonary Nodules","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 11:17:54","doi":"10.21203/rs.3.rs-6390597/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":"8291e282-cc7c-45db-875a-df9db6a03a68","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-18T08:57:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 11:17:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6390597","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6390597","identity":"rs-6390597","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}