Exploration of CT imaging features of cystic pulmonary nodules and establishment of a prediction model for benign and malignant pulmonary nodules / 中国胸心血管外科临床杂志

@#Objective To explore the CT imaging features and independent risk factors for cystic pulmonary nodules and establish a malignant probability prediction model. Methods The patients with cystic pulmonary nodules admitted to the Department of Thoracic Surgery of the First People's Hospital of Neijiang from January 2017 to February 2022 were retrospectively enrolled. They were divided into a malignant group and a benign group according to the pathological results. The clinical data and preoperative chest CT imaging features of the two groups were collected, and the independent risk factors for malignant cystic pulmonary nodules were screened out by logistic regression analysis, so as to establish a prediction model for benign and malignant cystic pulmonary nodules. Results A total of 107 patients were enrolled. There were 76 patients in the malignant group, including 36 males and 40 females, with an average age of 59.65±11.74 years. There were 31 patients in the benign group, including 16 males and 15 females, with an average age of 58.96±13.91 years. Multivariate logistic analysis showed that the special CT imaging features such as cystic wall nodules [OR=3.538, 95%CI (1.231, 10.164), P=0.019], short burrs [OR=4.106, 95%CI (1.454, 11.598), P=0.008], cystic wall morphology [OR=6.978, 95%CI (2.374, 20.505), P<0.001], and the number of cysts [OR=4.179, 95%CI (1.438, 12.146), P=0.009] were independent risk factors for cystic lung cancer. A prediction model was established: P=ex/(1+ex), X=–2.453+1.264×cystic wall nodules+1.412×short burrs+1.943×cystic wall morphology+1.430×the number of cysts. The area under the receiver operating charateristic curve was 0.830, the sensitivity was 82.9%, and the specificity was 74.2%. Conclusion Cystic wall nodules, short burrs, cystic wall morphology, and the number of cysts are the independent risk factors for cystic lung cancer, and the established prediction model can be used as a screening method for cystic pulmonary nodules.

Establishment and verification of a mathematical prediction model for benignancy and malignancy in subsolid pulmonary nodules / 中国胸心血管外科临床杂志

@#Objective    To explore the independent risk factors for benign and malignant subsolid pulmonary nodules and establish a malignant probability prediction model. Methods    A 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. Results    Univariate 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. Conclusion    Compared 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.

Accuracy of closed pleural biopsy in the diagnosis of malignant pleural effusion / Exactitud de la biopsia pleural cerrada para el diagnóstico de derrame pleural maligno

ABSTRACT Objective: Previous studies have demonstrated that closed pleural biopsy (CPB) has a sensitivity of less than 60% for diagnosing malignancy. Therefore, controversy has recently emerged regarding the value of CPB as a diagnostic test. Our objective was to assess the accuracy of CPB in diagnosing malignancy in patients with pleural effusion. Methods: This was a prospective 8-year study of individuals who underwent CPB to establish the etiology of pleural effusion. Information on each patient was obtained from anatomopathological reports and medical records. When CPB findings showed malignancy or tuberculosis, the biopsy was considered diagnostic, and that was the definitive diagnosis. In cases in which biopsy histopathological findings were nonspecific, a definitive diagnosis was established on the basis of other diagnostic procedures, such as thoracoscopy, thoracotomy, fiberoptic bronchoscopy, biochemical and cellular measurements in pleural fluid, and/or microbiological tests. The accuracy of CPB was determined with 2 × 2 contingency tables. Results: A total of 1034 biopsies from patients with pleural effusion were studied. Of those, 171 (16.54%) were excluded from the accuracy analysis either because of inadequate samples or insufficient information. The results of the accuracy analysis were as follows: sensitivity, 77%; specificity, 98%; positive predictive value, 99%; negative predictive value, 66%; positive likelihood ratio, 38.5; negative likelihood ratio, 0.23; pre-test probability, 2.13; and post-test probability, 82. Conclusions: CPB is useful in clinical practice as a diagnostic test, because there is an important change from pre-test to post-test probability.

RESUMEN Objetivo: Estudios previos demuestran que la biopsia pleural cerrada (BPC) para diagnóstico de malignidad tiene una sensibilidad menor al 60%, por lo que recientemente ha despertado controversia su valor como prueba diagnóstica. Nuestro objetivo fue evaluar la exactitud de la BPC para diagnóstico de malignidad en pacientes con derrame pleural. Métodos: Estudio prospectivo de 8 años en individuos que se sometieron a la realización de BPC para establecer la etiología del derrame. La información de cada paciente se tomó de los registros de anatomopatología y del expediente clínico. Cuando el resultado de la BPC demostró malignidad o tuberculosis, esto se tomó como biopsia diagnóstica y quedó éste como diagnóstico definitivo. En los casos en que el resultado del estudio histopatológico de la biopsia resultó inespecífico, el diagnóstico definitivo se estableció en base a otros procedimientos diagnósticos, como toracoscopia, toracotomía, fibrobroncoscopia, estudio bioquímico y celular del líquido pleural y/o pruebas microbiológicas. Mediante una tabla de contingencia de 2 × 2 se midieron los indicadores para una prueba diagnóstica. Resultados: Se estudiaron 1034 biopsias de pacientes con derrame pleural, de las cuales se excluyeron 171 (16.54%) por muestra inadecuada o información insuficiente. El desempeño para malignidad fue: sensibilidad, 77%; especificidad, 98%; valores predictivos positivo y negativo, 99% y 66%, respectivamente; índices de probabilidad positivo y negativo, 38.5 y 0.23, respectivamente; probabilidad antes y después de la prueba, 2.13 y 82, respectivamente. Conclusión: La BPC es útil como prueba diagnóstica en la práctica clínica, debido a que produce un cambio importante de la probabilidad antes de la prueba a la probabilidad después de la prueba.

Thoracic metastasis in advanced ovarian cancer: comparison between computed tomography and video-assisted thoracic surgery / 부인종양

OBJECTIVE: To determine which computed tomography (CT) imaging features predict pleural malignancy in patients with advanced epithelial ovarian carcinoma (EOC) using video-assisted thoracic surgery (VATS), pathology, and cytology findings as the reference standard. METHODS: This retrospective study included 44 patients with International Federation of Obstetrics and Gynecology (FIGO) stage III or IV primary or recurrent EOC who had chest CT < or =30 days before VATS. Two radiologists independently reviewed the CT studies and recorded the presence and size of pleural effusions and of ascites; pleural nodules, thickening, enhancement, subdiaphragmatic tumour deposits and supradiaphragmatic, mediastinal, hilar, and retroperitoneal adenopathy; and peritoneal seeding. VATS, pathology, and cytology findings constituted the reference standard. RESULTS: In 26/44 (59%) patients, pleural biopsies were malignant. Only the size of left-sided pleural effusion (reader 1: rho=-0.39, p=0.01; reader 2: rho=-0.37, p=0.01) and presence of ascites (reader 1: rho=-0.33, p=0.03; reader 2: rho=-0.35, p=0.03) were significantly associated with solid pleural metastasis. Pleural fluid cytology was malignant in 26/35 (74%) patients. Only the presence (p=0.03 for both readers) and size (reader 1: rho=0.34, p=0.04; reader 2: rho=0.33, p=0.06) of right-sided pleural effusion were associated with malignant pleural effusion. Interobserver agreement was substantial (kappa=0.78) for effusion size and moderate (kappa=0.46) for presence of solid pleural disease. No other CT features were associated with malignancy at biopsy or cytology. CONCLUSION: In patients with advanced EOC, ascites and left-sided pleural effusion size were associated with solid pleural metastasis, while the presence and size of right-sided effusion were associated with malignant pleural effusion. No other CT features evaluated were associated with pleural malignancy.