Percutaneous lung needle biopsies : utility and complications in various chest lesions : a single-institution experience

Purpose: It is crucial to obtain a specific diagnosis before treatment of chest pathology is initiated. The purpose of the study is to present the utility of percutaneous biopsies, core and fine-needle aspiration, in various thoracic lesions, and related complications. Material and methods: A total of 593 transthoracic biopsies were performed in the Department of Radiology between 2013 and 2016. Fine-needle aspiration biopsy (FNAB) and core biopsy (CB) were implemented. The procedures were divided into four groups according to the location of the pathology: lung lesions (LL - 540), mediastinal masses (MM - 25), chest wall tumours (CWT - 13), and pleural lesions (PL - 15). The lung lesion group was divided into two subgroups: lung nodules and lung infiltrations. All groups were analysed in respect of diagnostic accuracy, pathological findings, and complication rate. Results: Pathological diagnosis was confirmed in 447 cases after all 593 procedures. The sensitivity of malignancy diagnosis in the group of lung tumours was 75% for FNAB and 89% for CB. The sensitivity in other groups, where CB was a preferable technique, was counted for lung infiltration, mediastinal masses, chest wall tumours, and pleural lesions and amounted to 83.3%, 90.9%, 100%, and 85.7%, respectively. In the group of lung tumours malignancy was confirmed most commonly (79%), while in the lung infiltration group benign processes dominated (83%). There was no statistical difference between the pneumothorax rate after CB and FNAB. Haemoptysis appeared more often after CB. Conclusions: FNAB and CB are useful, safe, and sensitive tools in the diagnostic work-up. They can both be used to diagnose almost all chest pathologies

BRONCO: Automated modelling of the bronchovascular bundle using the Computed Tomography Images

Segmentation of the bronchovascular bundle within the lung parenchyma is a key step for the proper analysis and planning of many pulmonary diseases. It might also be considered the preprocessing step when the goal is to segment the nodules from the lung parenchyma. We propose a segmentation pipeline for the bronchovascular bundle based on the Computed Tomography images, returning either binary or labelled masks of vessels and bronchi situated in the lung parenchyma. The method consists of two modules, modeling of the bronchial tree and vessels. The core revolves around a similar pipeline, the determination of the initial perimeter by the GMM method, skeletonization, and hierarchical analysis of the created graph. We tested our method on both low-dose CT and standard-dose CT, with various pathologies, reconstructed with various slice thicknesses, and acquired from various machines. We conclude that the method is invariant with respect to the origin and parameters of the CT series. Our pipeline is best suited for studies with healthy patients, patients with lung nodules, and patients with emphysema