Search

Background: Fluoroscopy-guided PTNB for fluoroscopy-identifiable lung lesions has been suggested as a useful method for the pathological diagnosis of lung lesions; however, it is lacking in accuracy and safety compared to CT-guided PTNB. Thus, we aimed to investigate the diagnostic accuracy and complications of fluoroscopy-guided percutaneous transthoracic needle biopsy (PTNB) with the aid of pre-procedural planning cone-beam computed tomography (CBCT) in order to take advantage of their respective strengths. Methods: A total of 255 fluoroscopy-guided PTNBs with the aid of planning CBCT were performed. Pre-procedural planning CBCT was conducted to calculate the shortest length from the skin puncture site to the margin of the target lesion for the needle trajectory. No intra-procedural CBCT was performed. The diagnostic performance of fluoroscopy-guided PTNB with the aid of planning CBCT was calculated. The prognostic factors for diagnostic failures and complications were evaluated using logistic regression analysis. Results: The accuracy, sensitivity, specificity, PPV, and NPV were 97.3%, 88.0%, 90.9%, 100%, and 62.5%, respectively. There were 29 diagnostic failures (11.8%), and the multivariable analysis showed that a longer lesion depth on CBCT and a shorter specimen length were each associated with diagnostic failure (p = 0.010 and 0.012, respectively). Complications occurred in 34 PTNBs (13.3%). The multivariable analysis showed that an increased total number of biopsies per lesion, a longer length of lung aeration via needle insertion, a smaller lesion size on CT imaging (≤20 mm), and the presence of an air bronchogram were associated with the occurrence of complications (p = 0.027, <0.001, 0.003, and 0.020, respectively). Conclusions: Excellent diagnostic accuracy was obtained by fluoroscopy-guided PTNB with the aid of planning CBCT. Compared to that of CT- or CBCT-guided PTNB, the procedure-related complication rate was acceptably low, but the radiation dose to patients could be potentially reduced. [ABSTRACT FROM AUTHOR]

Purpose: To develop models to predict programmed death ligand 1 (PD-L1) expression in pulmonary squamous cell carcinoma (SCC) using CT., Materials and Methods: A total of 97 patients diagnosed with SCC who underwent PD-L1 expression assay were included in this study. We performed a CT analysis of the tumors using pretreatment CT images. Multiple logistic regression models were constructed to predict PD-L1 positivity in the total patient group and in the 40 advanced-stage (≥ stage IIIB) patients. The area under the receiver operating characteristic curve (AUC) was calculated for each model., Results: For the total patient group, the AUC of the 'total significant features model' (tumor stage, tumor size, pleural nodularity, and lung metastasis) was 0.652, and that of the 'selected feature model' (pleural nodularity) was 0.556. For advanced-stage patients, the AUC of the 'selected feature model' (tumor size, pleural nodularity, pulmonary oligometastases, and absence of interstitial lung disease) was 0.897. Among these factors, pleural nodularity and pulmonary oligometastases had the highest odds ratios (8.78 and 16.35, respectively)., Conclusion: Our model could predict PD-L1 expression in patients with lung SCC, and pleural nodularity and pulmonary oligometastases were notable predictive CT features of PD-L1., Competing Interests: Conflicts of Interest: The authors have no potential conflicts of interest to disclose., (Copyrights © 2024 The Korean Society of Radiology.)

Purpose: Our study aimed to evaluate the association between automated quantified body composition on CT and pulmonary function or quantitative lung features in patients with chronic obstructive pulmonary disease (COPD)., Materials and Methods: A total of 290 patients with COPD were enrolled in this study. The volume of muscle and subcutaneous fat, area of muscle and subcutaneous fat at T12, and bone attenuation at T12 were obtained from chest CT using a deep learning-based body segmentation algorithm. Parametric response mapping-derived emphysema (PRM emph ), PRM-derived functional small airway disease (PRM fSAD ), and airway wall thickness (AWT)-Pi10 were quantitatively assessed. The association between body composition and outcomes was evaluated using Pearson's correlation analysis., Results: The volume and area of muscle and subcutaneous fat were negatively associated with PRM emph and PRM fSAD ( p < 0.05). Bone density at T12 was negatively associated with PRM emph ( r = -0.1828, p = 0.002). The volume and area of subcutaneous fat and bone density at T12 were positively correlated with AWT-Pi10 ( r = 0.1287, p = 0.030; r = 0.1668, p = 0.005; r = 0.1279, p = 0.031). However, muscle volume was negatively correlated with the AWT-Pi10 ( r = -0.1966, p = 0.001). Muscle volume was significantly associated with pulmonary function ( p < 0.001)., Conclusion: Body composition, automatically assessed using chest CT, is associated with the phenotype and severity of COPD., Competing Interests: Conflicts of Interest: The authors have no potential conflicts of interest to disclose., (Copyrights © 2023 The Korean Society of Radiology.)

Thoracic foreign bodies (FBs) are serious and relatively frequent in emergency departments. Thoracic FBs may occur in association with aspiration, ingestion, trauma, or iatrogenic causes. Imaging plays an important role in the identification of FBs and their dimensions, structures, and locations, before the initiation of interventional treatment. To guide proper clinical management, radiologists should be aware of the radiologic presentations and the consequences of thoracic FBs. In this pictorial essay, we reviewed the optimal imaging settings to identify FBs in the thorax, classified thoracic FBs into four types according to their etiology, and reviewed the characteristic imaging features and the possible complications., Competing Interests: Conflicts of Interest: The authors have no potential conflicts of interest to disclose., (Copyrights © 2022 The Korean Society of Radiology.)