[Performance of Deep-learning-based Artificial Intelligence on Detection of Pulmonary Nodules in Chest CT].

Background: The detection of pulmonary nodules is a key step to achieving the early diagnosis and therapy of lung cancer. Deep learning based Artificial intelligence (AI) presents as the state of the art in the area of nodule detection, however, a validation with clinical data is necessary for further application. Therefore, the aim of this study is to evaluate the performance of AI in the detection of malignant and non-calcified nodules in chest CT.

[Growth Evaluation of Pulmonary Nodules on Chest CT].

Computed tomography (CT) follow-up of indeterminate pulmonary nodules and the quantification of growth characteristics are the commonly adopted strategy in clinical setting. The volume/mass doubling time can be used to quantify the growth velocity based on exponential growth model. Therefore, we reviewed the followed aspects on growth evaluation of pulmonary nodules on chest CT, including the growth model of lung cancer, the methods used for nodule growth quantification and the growth characteristics of different types of pulmonary nodules.

[Effect of Scanning and Reconstruction Parameters on Three Dimensional Volume and CT Value Measurement of Pulmonary Nodules: A Phantom Study].

Background: The computed tomography (CT) follow-up of indeterminate pulmonary nodules aiming to evaluate the change of the volume and CT value is the common strategy in clinic. The CT dose needs to considered on serious CT scans in addition to the measurement accuracy. The purpose of this study is to quantify the precision of pulmonary nodule volumetric measurement and CT value measurement with various tube currents and reconstruction algorithms in a phantom study with dual-energy CT.

[Three Dimensional Volumetric Analysis of Solid Pulmonary Nodules on Chest CT: Cancer Risk Assessment].

Background: The management of pulmonary nodules relies on cancer risk assessment, in which the only widely accepted criterion is diameter. The development of volumetric computed tomography (CT) and three-dimensional (3D) software enhances the clarity in displaying the nodules' characteristics. This study evaluated the values of the nodules' volume and 3D morphological characteristics (edge, shape and location) in cancer risk assessment.

[The intra-observer variability of volumetric measurement of pulmonary nodules: comparison of two-dimensional and three-dimensional method].

Background And Objective: Software oriented three-dimensional (3D) volumetric measurement of pulmonary nodules has been feasible in the follow-up of indeterminate pulmonary nodules, however, its value need a further validation. The purpose of this study is to retrospectively analyze the chest CT data of patients with pulmonary nodules to compare the intra-observer variability of 3D and two-dimensional (2D) volumetric measurement.

Methods: Eighty-six pulmonary nodules in chest CT scans of 79 subjects were retrospectively analyzed.

[Correlation of apparent diffusion coefficient with histologic type and grade of lung cancer].

Background And Objective: The histologic type and grade of lung cancer are significant in assessing the biological behaviour, prognosis and therapeutic regimen. This study investigates the correlation of apparent diffusion coefficient (ADC) with histologic type and grade of lung cancer.

Methods: A total of 115 patients pathologically diagnosed with lung cancer were enrolled in this study.