ObjectiveTo explore the application value of CT-guided microcoil localization in pulmonary nodule (diameter≤15 mm) surgery.MethodsThe clinical data of 175 patients with pulmonary nodules who underwent single utility port video-assisted thoracoscopic surgery at Nanjing Drum Tower Hospital from August 2018 to December 2019 were retrospectively analyzed. According to whether CT-guided coil localization was performed before operation, they were divided into a locating group and a non-locating group. There were 84 patients (34 males, 50 females, aged 57.8±8.8 years) in the locating group and 91 patients (46 males, 45 females, aged 57.6±10.8 years) in the non-locating group. The localization success rate, localization time, incidence of complications, surgical and postoperative conditions were analyzed between the two groups.ResultsAll 84 patients in the locating group were successfully located, and localization time was 19.0±3.6 minutes. Among them, 19 (22.6%) patients had a small pneumothorax, 4 (4.8%) pulmonary hemorrhage and 2 (2.4%) coil shift; 6 (7.1%) patients had mild pain, 3 (3.6%) moderate pain and 1 (1.2%) severe pain. Sex (P=0.181), age (P=0.673), nodule location (P=0.167), nature of lesion (P=0.244), rate of conversion to thoracotomy (P=0.414), rate of disposable resection of nodules (P=0.251) and postoperative hospital stay (P=0.207) were similar between the two groups. There were significant differences in nodule size (P<0.001), nature of nodule (P<0.001), the shortest distance from nodule to pleura (P<0.001), operation time (P<0.001), lung volume by wedge resection (P=0.031), number of staplers (P<0.001) and total hospitalization costs (P<0.001) between the two groups.ConclusionCT-guided microcoil localization has the characteristics of high success rate, and is simple, practicable, effective, safe and minimally invasive. Preoperative CT-guided microcoil localization has important clinical application value for small pulmonary nodules, especially those with small size, deep location and less solid components. It can effectively shorten the operation time, reduce surgical trauma and lower hospitalization costs, which is a preoperative localization technique worthy of popularization.
ObjectiveTo investigate differential diagnosis between benign and malignant of solitary pulmonary nodules (SPN)and surgical strategies. MethodsWe retrospectively analyzed clinical and pathological data of 151 SPN patients who underwent surgical resection in Provincial Hospital Affiliated to Shandong University between November 2010 and March 2012. There were 89 male and 62 female patients with their age of 30-80 (57.99±0.86)years. Differential factors between benign and malignant SPN were analyzed. ResultsThere were 29 patients with benign SPN and 122 patients with malignant SPN. Among the 122 malignant SPN patients, there were 58 patients in stage ⅠA, 30 patients in stage ⅠB, 7 patients in stage ⅡA, 25 patients in stage ⅢA and 2 patients in stage Ⅳ. Mean diameter of malignant SPN was significantly larger than that of benign SPN (2.03 cm vs 1.77 cm, P=0.039). Malignant rate of SPN larger than 2 cm was significantly higher than that of SPN smaller than 2 cm (90.3% vs. 74.2%, P=0.013). Patients with malignant SPN was significantly older than patients with benign SPN (60.39 years vs. 47.90 years, P < 0.01). Malignant rate of patients over 45 years was significantly higher than that of patients younger than 45 years (86.4% vs. 38.9%, P < 0.01).There was no statistical difference in malignant rate between male and female, with and without clinical symptoms, smoking and nonsmo-king, smoking index≤400 and > 400 and among different lobes. Conclusions Differential factors of SPN include patients' medical history, age, diameter and shape of nodules, which should be considered comprehensively and dynamically. Gender, clinical symptoms, smoking history, smoking index and SPN location are not helpful for differential diagnosis of SPN.
Abstract： Objective To explore the approach of clinical diagnosis and treatment strategy for patients with small pulmonary nodules （SPN）≤ 1.0 cm in size on CT. Methods We retrospectively analyzed the clinical records of 39 patients with SPN less than 1.0 cm in size who underwent lung resection at Nanjing Drum Tower Hospital from January 2005 to June 2011. There were 23 males and 16 females. Their age ranged from 31-74 （51.0±7.4） years. Nine patients had cough and sputum and other patients had no symptom. All the patients were found to have SPN less than 1.0（0.8±0.1）cm in size but not associated with hilum and mediastinal lymphadenectasis in chest CT and X-ray. The results of their sputum cytology and electronic bronchoscope were all negative. All the patients had no histologic evidence and underwent pulmonary function test prior to operation. Eleven patients had positron emission tomography/computer tomography （PET/CT）or single-photon emission computed tomography （SPECT）which was all negative. Thirteen patients underwent video-assisted minithoracotomy（VAMT） and 26 patients underwent video-assisted thoracoscopic surgery （VATS）. Results The average operation time was 121.0±48.0 min. Patients after partial lung resection were discharged 4～5 d postoperatively, and patients after lobectomy were discharged 7 d postoperatively. All the patients had no postoperative complications. Twenty one patients were identified as lung malignancy by postoperative pathology, including 9 patients with adenocarcinoma, 7 patients with bronchioloalveolar carcinoma, 1 patient with small cell lung carcinoma, and 4 patients with pulmonary metastasis. Eighteen patients had benign lesions including 4 patients with sclerosing hemangioma, 4 patients with inflammatory pseudotumor, 2 patients with pneumonia, 3 patients with granuloma, 2 patients with tuberculosis, and 3 patients with pulmonary lymph node hyperplasia. The SPN were located in left upper lobe in 11 patients, left lower lobe in 6 patients, right upper lobe in 14 patients, right middle lobe in 1 patient, and right lower lobe in 7 patients. Conclusion The diagnosis of SPN ≤1.0 cm in size on CT should consider malignance in the first step to avoid treatment delay. Patients may have a 3-month observation period to receive selective antibiotic treatment, chest CT and X-ray review after 2 to 4 weeks. CT- guided hook-wire fixation is useful to help in precise lesion localization for surgical resection. VATS and VAMT are common and effective methods for the diagnosis and treatment for SPN.
Objective To investigate the risk factors, diagnosis and treatment of solitary pulmonary nodule （diameter≤3cm）. Methods From Jan. 2001 to Dec. 2002, the clinical data of 297 patients with solitary pulmonary nodule were reviewed. Chi-square or t-test were used in univariate analysis of age, gender, symptom, smoking history, the size, location and radiological characteristics of nodule, and logistic regression in multivariate analysis. Results Univariate analysis revealed that malignancy was significantly associated with age （P=0. 000）, smoking history （P=0. 001）, the size （P=0. 000） and radiological characteristics （P=0. 000） of nodule. In multivariate analysis （logistic regression）, it was significantly associated with age （OR = 1. 096）, the size （OR = 2. 329） and radiological characteristics （OR=0. 167） of nodule. Conclusion Age and the size of nodule could be risk factors. Radiological findings could help distinguish from malignant nodules.
Objective To evaluate the diagnostic value and utility of flexible bronchoscopy in the preoperative assessment in patients with solitary pulmonary nodules (SPNs). Methods A total of 111 patients with SPNs of unknown origin treated between January and June 2016 were retrospectively enrolled. The clinical characteristics, bronchoscopy findings and surgical strategies were collected. Results In the total 111 cases, malignant and benign SPNs were 79 and 32 cases, respectively. The mean diameter of malignant SPNs was larger than that of benign SPNs [(2.04±0.58) vs. (1.70±0.75) cm, P<0.05]. Bronchoscopy identified 9 cases (8.1%) unsuspected findings. Surgeries were modified or cancelled in 3 patients (2.7%) because of bronchoscopy findings. Transbronchoscopy biopsies were performed in 26 patients, 9 of whom were diagnosed lung cancer preoperatively, with a sensitivity of 45% (9/20) and a specificity of 100% (6/6). Conclusions Flexible bronchoscopy can be contributed to diagnosis of SPN before surgery and determination of surgical strategies. It is suggested that flexible bronchoscopy could be included in the routine preoperative work-up of SPN.
In order to optimize the postoperative rehabilitation path of patients undergoing fourth-level day surgery, West China Hospital of Sichuan University has learned from the abroad “recovery hotel” mode and innovatively regarded the primary rehabilitation institution as an extended service carrier for thoracoscopic lung nodule day surgery. This extended rehabilitation mode based on primary rehabilitation institutions is not only beneficial for shortening the hospitalization period and reducing medical costs, but also ensures medical safety through a standardized postoperative monitoring system, providing innovative solutions for the full process management of day surgeries. This article will introduce the specific implementation methods and preliminary practical results of the extended rehabilitation mode mentioned above.
ObjectiveTo establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. MethodsPatients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. ResultsA total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. ConclusionFor patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.
ObjectiveTo explore the efficacy of artificial intelligence (AI) detection on pulmonary nodule compared with multidisciplinary team (MDT) in regional medical center.MethodsWe retrospectively analyzed the clinical data of 102 patients with lung nodules in the Xiamen Fifth Hospital from April to December 2020. There were 57 males and 45 females at age of 36-90 (48.8±11.6) years. The preoperative chest CT was imported into AI system to record the detected lung nodules. The detection rate of pulmonary nodules by AI system was calculated, and the sensitivity, specificity of AI in the different diagnosis of benign and malignant pulmonary was calculated and compared with manual film reading by MDT.ResultsA total of 322 nodules were detected by AI software system, and 305 nodules were manually detected by physicians (P<0.05). Among them, 113 pulmonary nodules were diagnosed by pathologist. Thirty-eight of 40 lung cancer nodules were AI high-risk nodules, the sensitivity was 95.0%, and 25 of 73 benign nodules were AI high-risk nodules, the specificity was 65.8%. Lung cancer nodules were correctly diagnosed by MDT, but benign nodules were still considered as lung cancer at the first diagnosis in 10 patients.ConclusionAI assisted diagnosis system has strong performance in the detection of pulmonary nodules, but it can not content itself with clinical needs in the differentiation of benign and malignant pulmonary nodules. The artificial intelligence system can be used as an auxiliary tool for MDT to detect pulmonary nodules in regional medical center.
The coming out of electromagnetic navigation bronchoscopy gives exciting solution for diagnosis and even treatment of peripheral pulmonary nodules. It breaks the barriers of traditional bronchoscopy, and gives live visible imaging guidance for operators during biopsy of peripheral pulmonary nodules. The electromagnetic navigation bronchoscopy system can intelligently recognize and reconstruct the bronchial tree of the patients, and generate visible data and virtual guidance for the operators. It can perceive real-time magnetic localization of the signal, so as to precisely guide the navigational or biopsy tools. This review introduced the artificial intelligence configuration of the electromagnetic navigation bronchoscopy system based on the Veran system, and gave some improvement advices based on the defects of the system. In this way, we hope to promote the development and better clinical application of electromagnetic navigation bronchoscopy system.
Objective To analyze risk factors of malignancy in patients with small pulmonary nodules （diameter ≤2 cm） using univariate analysis and multivariate logistic regression，and establish a mathematical prediction model to estimatethe probability of malignancy. Methods Clinical data of 147 patients with small pulmonary nodules who underwentsurgical resection with definite postoperative pathological diagnosis from January 2005 to September 2012 in the 161st Central Hospital of PLA were retrospectively analyzed. There were 84 male and 63 female patients with their age of 31-78（56.2±10.1） years. Univariate analysis using Chi-square test or t test was performed to analyze risk factors including patientage，gender，symptoms，history and quantity of smoking，history of heavy drinking，history of tumor，tumor site，diameter，lobulation，spiculation，pleural indentation，ground-glass opacity，cavity，enlarged hilar and mediastinal lymph nodes.Independent predictors of malignancy were screened with multivariate logistic regression analysis. A mathematical predictionmodel was built to estimate the probability of malignancy and then examined. Results Univariate analysis showed that there was statistical difference in patient age（t=7.146，P＜0.001），heavy smoking history（χ2=6.169，P=0.013），nodule diameter（t=3.375，P=0.001），spiculation（χ2=5.609，P=0.018），lobulation（χ2=5.675，P=0.017），and pleural indentation（χ2=12.994，P＜0.001）between benign and malignant small pulmonary nodule groups. Multivariate logistic regression analysis showed that patient age （OR=1.110，P=0.000），nodule diameter （OR=2.050，P=0.029），lobulation （OR=1.672，P=0.045），spiculation（OR=2.054，P=0.032） and pleural indentation（OR=4.090，P=0.024）were independent predictors of malignancy in patients with small pulmonary nodules （P＜0.05） . The mathematical prediction model to estimate the probability of malignancy was：Logit （P） =ez/ （1 ＋ ez），Z=-6.657 ＋ （0.104×age） ＋ （0.718×diameter） ＋ （0.720×spiculation） ＋（0.514×lobulation） ＋ （1.409×pleural indentation），and e was natural logarithm. Both Hosmer-Lemeshow test （χ2=1.802，P=0.986） and maximum likelihood ratio test （Cox-Snell R2=0.310，Nagelkerke R2=0.443） showed satisfactory goodness of fit. The diagnostic accuracy was 85.71%，sensitivity was 87.50%，specificity was 81.40%，positive predictive value was 91.92%，and negative predictive value was 72.92% when the cut-off value was 0.58. Conclusions Patient age，nodule diameter，spiculation，lobulation and pleural indentation are independent predictors of malignancy in patients with small pulmonary nodules. The mathematical prediction model can accurately estimate the probability of malignancy for patients with small pulmonary nodules.