ObjectiveTo compare the effectiveness and safety of electromagnetic navigation-guided localization and CT-guided percutaneous localization for pulmonary nodules.MethodsThe literature published from the inception to January 2021 about the comparison between electromagnetic navigation-guided localization and CT-guided percutaneous localization for pulmonary nodules in the PubMed, The Cochrane Library, Web of Science, EMbase, Chinese Wanfang database and CNKI database was searched. RevMan (version 5.4) software was used for meta-analysis. Nonrandomized controlled trials were evaluated using methodological index for nonrandomized studies (MINORS).ResultsA total of six retrospective studies (567 patients) were included in this meta-analysis. MINORS scores of all studies were all 17 points and above. There were 317 patients in the CT-guided percutaneous localization group and 250 patients in the electromagnetic navigation-guided localization group. The complication rate of the CT-guided percutaneous localization group was significantly higher than that in the electromagnetic navigation-guided localization group (OR=11.08, 95%CI 3.35 to 36.65, P<0.001). There was no significant difference in the success rate of localization (OR=0.48, 95%CI 0.16 to 1.48, P=0.20), localization time (MD=0.30, 95%CI –6.16 to 6.77, P=0.93) or nodule diameter (MD=–0.07, 95%CI –0.19 to 0.06, P=0.29) between the two groups.ConclusionElectromagnetic navigation can be used as an effective preoperative positioning method for pulmonary nodules, which has the advantage of lower complication rate compared with the traditional CT positioning method.
Objective To analyze the benign-malignant outcomes of pulmonary nodules in surgical patients and their influencing factors, and provide evidence and ideas for optimizing and improving the integrated management model of pulmonary nodules. Methods From October to December 2023, a convenience sampling method was used to select patients who underwent lung surgery at West China Hospital, Sichuan University between July 2022 and June 2023 for this study. The malignancy rate of postoperative pathological results of pulmonary nodules and its influencing factors were analyzed using univariate analysis and multiple logistic regression. Results A total of 4600 surgical patients with pulmonary nodules were included, with a malignancy rate of 88.65% (4078/4600) and a benign rate of 11.35% (522/4600). Univariate analysis showed significant differences in malignancy rates among different genders, ages, methods of pulmonary nodule detection, and smoking histories (P<0.05); however, no significant difference was found regarding place of birth or family history of lung cancer (P>0.05). Multiple logistic regression analysis indicated that females [odds ratio (OR)=1.533, 95% confidence interval (CI) (1.271, 1.850)], older age groups [61-75 vs. ≤30 years: OR=1.640, 95%CI (1.021, 2.634); >75 vs. ≤30 years: OR=2.690, 95%CI (1.062, 6.814)], and pulmonary nodules detected during physical examinations [OR=1.286, 95%CI (1.064, 1.554)] were high-risk factors for malignancy, with statistical significance (P<0.05). Conclusion In the integrated management of pulmonary nodules, it is crucial not to overlook females or older patients, as they may be more significant influencing factors than smoking; furthermore, lung examinations are effective means of early detection of malignant lung tumors and are worth promoting and popularizing.
ObjectiveTo introduce the application of mixed reality technique to the preoperative and intraoperative pulmonary nodules surgery.MethodsOne 49-year female patient with multiple nodules in both lobes of the lung who finally underwent uniportal thoracoscopic resection of superior segment of left lower lobe and wedge resection of left upper lobe was taken as an example. The Mimics medical image post-processing software was used to reconstruct the patient's lung image based on the DICOM data of the patient's chest CT image before the surgery. The three-dimensional reconstructed image data was imported into the HoloLens glasses, and the preoperative discussions were conducted with the assistance of mixed reality technology to formulate the surgical methods, and the preoperative conversation with the patients was also conducted. At the same time, mixed reality technology was used to guide the surgery in real time.ResultsMixed reality technology can clearly pre-show the important anatomical structures of blood vessels, trachea, lesions and their positional relationship. With the help of mixed reality technology, the operation went smoothly. The total operation time was 49 min, the precise dorsal resection time was 27 min, and the intraoperative blood loss was about 39 mL. The patient recovered well and was discharged from hospital smoothly after surgery.ConclusionMixed reality technology has certain application value before and during the surgery for pulmonary nodules. The continuous maturity of this technology and its further application in clinics will not only bring a new direction to the development of thoracic surgery, but also provide a wide prospect.
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.
ObjectiveTo explore the independent risk factors for benign and malignant subsolid pulmonary nodules and establish a malignant probability prediction model.MethodsA retrospective analysis was performed in 443 patients with subsolid pulmonary nodules admitted to Subei People's Hospital of Jiangsu Province from 2014 to 2018 with definite pathological findings. The patients were randomly divided into a modeling group and a validation group. There were 296 patients in the modeling group, including 125 males and 171 females, with an average age of 55.9±11.1 years. There were 147 patients in the verification group, including 68 males and 79 females, with an average age of 56.9±11.6 years. Univariate and multivariate analysis was used to screen the independent risk factors for benign and malignant lesions of subsolid pulmonary nodules, and then a prediction model was established. Based on the validation data, the model of this study was compared and validated with Mayo, VA, Brock and PKUPH models.ResultsUnivariate and multivariate analysis showed that gender, consolidation/tumor ratio (CTR), boundary, spiculation, lobulation and carcinoembryonic antigen (CEA) were independent risk factors for the diagnosis of benign and malignant subsolid pulmonary nodules. The prediction model formula for malignant probability was: P=ex/(1+ex). X=0.018+(1.436×gender)+(2.068×CTR)+(−1.976×boundary)+ (2.082×spiculation)+(1.277×lobulation)+(2.296×CEA). In this study, the area under the curve was 0.856, the sensitivity was 81.6%, the specificity was 75.6%, the positive predictive value was 95.4%, and the negative predictive value was 39.8%. Compared with the traditional model, the predictive value of this model was significantly better than that of Mayo, VA, Brock and PKUPH models.ConclusionCompared with Mayo, VA, Brock and PKUPH models, the predictive value of the model is more ideal and has greater clinical application value, which can be used for early screening of subsolid nodules.
ObjectiveAnalyze the clinical features of epilepsy induced by tuberous sclerosis complex (TSC) to improve diagnosis and treatment level of this disease, and improve the prognosis. MethodsThe clinical data of 54 patients with epilepsy induced by TSC from May, 2012 to May, 2015 were analyzed together with the physical data, clinical presentations, EEG, imaging findings, treatment, prognosis and follow-up. Summarizing the clinical features of epilepsy induced by TSC. ResultsPatients with different epilepsy onset age, whether or not combined spasm, differences in intelligence status were statistically significant (P < 0.05); Patients with different gender, skin lesions, types of seizures, differences in intelligence status were no statistical significance (P > 0.05); Patients with different gender, epilepsy onset age, differences in patients with spasm were statistically significant (P < 0.05); Patients with different family history, skin lesions, types of seizures, differences in patients with spasm were not statistically significant (P > 0.05). Patients with different intelligence status, difference of medication quantity was statistically significant (P < 0.05); Patients with different gender, onset age, family history, skin lesions, whether or not combined spasm, types of seizures, difference of medication quantity was not statistically significant (P > 0.05). ConclusionsEpilepsy is the most common neurological manifestations in TSC, mostly onset in early childhood. Seizure types are different from one to another. Patients can be combined with skin damage and mental retardation. Positive rate of EEG and head imaging examination are high, seizure control rate is low. Patients need long-term follow-up and timely adjustment of treatment. Intelligence status is related to epilepsy onset age, spasm. Patients with spasm are related to different gender, epilepsy onset age. Medication quantity is related to intelligence status.
Objective To explore the efficiency of Vigabatrin for epilepsy in children with Tuberous Sclerosis Complex, and to further research the risk factors related to the outcome after adjunctive use of Vigabatrin. Methods 25 children with TSC and epilepsy treated with Vigabatrin at Children′s Hospital of Fudan University between 2013 and 2015 were included. Clinical characteristics and the effectiveness of other antiepileptic drugs were extracted from the follow-up data. The prevalence of visual field defect was analyzed among the cases. And correlations were made between the responses to Vigabatrin in groups. Results 25 cases, 15 male (60%). 18 cases had response to VGB-adjuvant therapy. Children with epilepsy onset at greater than six months of age were most likely to demonstrateagood response to VGB treatment. And the poorly response of cases showed that 4 had TSC1 mutation. And among the 25 cases, one child had the visual filed defect. Conclusions Vigabatrin as adjunctive therapy showed certain effect in controlling epilepsy in TSC cases, especially infantile spasms and some partial epilepsy. But the side effect of visual filed defect should be cautious. Age-appropriate visual field testing is recommended at baseline and then repeated at intervals in patients exposed to long term Vigabatrin therapy.
Accurate segmentation of pulmonary nodules is an important basis for doctors to determine lung cancer. Aiming at the problem of incorrect segmentation of pulmonary nodules, especially the problem that it is difficult to separate adhesive pulmonary nodules connected with chest wall or blood vessels, an improved random walk method is proposed to segment difficult pulmonary nodules accurately in this paper. The innovation of this paper is to introduce geodesic distance to redefine the weights in random walk combining the coordinates of the nodes and seed points in the image with the space distance. The improved algorithm is used to achieve the accurate segmentation of pulmonary nodules. The computed tomography (CT) images of 17 patients with different types of pulmonary nodules were selected for segmentation experiments. The experimental results are compared with the traditional random walk method and those of several literatures. Experiments show that the proposed method has good accuracy in the segmentation of pulmonary nodule, and the accuracy can reach more than 88% with segmentation time is less than 4 seconds. The results could be used to assist doctors in the diagnosis of benign and malignant pulmonary nodules and improve clinical efficiency.