Deep-learning-based model observer for a lung nodule detection task in computed tomography.

Task-based image quality assessment using model observers (MOs) is an effective approach to radiation dose and scanning protocol optimization in computed tomography (CT) imaging, once the correlation between MOs and radiologists can be established in well-defined clinically relevant tasks. Conventional MO studies were typically simplified to detection, classification, or localization tasks using tissue-mimicking phantoms, as traditional MOs cannot be readily used in complex anatomical background. However, anatomical variability can affect human diagnostic performance.

Efficacy of chest computed tomography prediction of the pathological TNM stage of thymic epithelial tumours.

Objectives: The aim of this study is to evaluate the efficacy of chest computed tomography (CT) to predict the pathological stage of thymic epithelial tumours (TET) using the recently introduced tumour, node and metastasis (TNM) staging with comparison to the modified Masaoka staging.

Methods: Preoperative chest CT examinations in cases of resected TET with sampled lymph nodes (2006-2016) were retrospectively reviewed by 2 thoracic radiologists and radiologically (r) staged using both staging systems. A thoracic pathologist reviewed all cases for the pathological (p) stage.

A virtual clinical trial using projection-based nodule insertion to determine radiologist reader performance in lung cancer screening CT.

Task-based image quality assessment using model observers is promising to provide an efficient, quantitative, and objective approach to CT dose optimization. Before this approach can be reliably used in practice, its correlation with radiologist performance for the same clinical task needs to be established. Determining human observer performance for a well-defined clinical task, however, has always been a challenge due to the tremendous amount of efforts needed to collect a large number of positive cases.

Effects of thyroidectomy, T4, and DITPA replacement on brain blood vessel density in adult rats.

In hypothyroid patients, altered microvascular structure and function may affect mood and cognitive function. We hypothesized that adult male hypothyroid rats will have significantly lower forebrain blood vessel densities (BVD) than euthyroid rats and that treatment with 3,5-diiothyroprionic acid (DITPA) (a thyroid hormone analog) or thyroxine (T(4)) will normalize BVDs. The euthyroid group received no thyroidectomy or treatment.