Incidentally detected lung nodules: clinical predictors of adherence to Fleischner Society surveillance guidelines.

OBJECTIVE: The objective of this study was to determine adherence to incidentally detected lung nodule computed tomographic (CT) surveillance recommendations and identify demographic and clinical factors that increase the likelihood of CT surveillance. MATERIALS AND METHODS: A total of 419 patients with incidentally detected lung nodules were included. Recorded data included patient demographic, radiologic, and clinical characteristics and outcomes at a 4-year follow-up. Multivariate logistic regression models determined the factors associated with likelihood of recommended CT surveillance. RESULTS: At least 1 recommended surveillance chest CT was performed on 48% of the patients (148/310). Computed tomographic result communication to the patient (odds ratio [OR], 2.2; P = 0.006; confidence interval [CI], 1.3-4.0) or to the referring physician (OR, 2.8; P = 0.001; CI, 1.7-4.5) and recommendation of a specific surveillance time interval (OR, 1.7; P = 0.023; CI, 1.08-2.72) increased the likelihood of surveillance. Other demographic, radiologic, and clinical factors did not influence surveillance. CONCLUSIONS: Documented physician and patient result communication as well as the recommendation of a specific surveillance time interval increased the likelihood of CT surveillance of incidentally detected lung nodules.

Computed tomography angiography for suspected pulmonary embolism: comparison of 2 adaptive statistical iterative reconstruction blends to filtered back-projection alone.

OBJECTIVE: The objective of this study was to analyze pulmonary computed tomography angiography image quality and pulmonary embolism (PE) depiction comparing 2 blends of adaptive statistical iterative reconstruction (ASIR) to filtered back-projection alone. METHODS: Seventy-nine consecutive patients (49 women, 30 men; 52 ± 18 years) underwent pulmonary computed tomography angiography (120 kVp, 100-600 mA) reconstructed with filtered back-projection alone (ASIR0), 30% ASIR (ASIR30), and 50% ASIR (ASIR50) for this institutional review board-approved study. Two radiologists independently assessed PE depiction and vascular characterization, which was correlated with body mass index. RESULTS: Twelve patients (15%) had PE. No difference in PE depiction (P = 0.536), pulmonary arterial attenuation (P = 0.22-0.99), or subjective vascular characterization score (P = 0.58-.016) was observed for either blend. ASIR30 and ASIR50 achieved higher signal-to-noise ratio (P = 0.001-0.003). Body mass index inversely correlated with vascular characterization scores (P < 0.001). CONCLUSIONS: ASIR0, ASIR30, and ASIR50 accurately depict PE using the imaging parameters described. ASIR30 and ASIR50 improve objective image quality without altering subjective vascular characterization scores particularly when body mass index was less than 30 kg/m.

Thioredoxin-like 2 regulates human cancer cell growth and metastasis via redox homeostasis and NF-κB signaling.

Cancer cells have an efficient antioxidant system to counteract their increased generation of ROS. However, whether this ability to survive high levels of ROS has an important role in the growth and metastasis of tumors is not well understood. Here, we demonstrate that the redox protein thioredoxin-like 2 (TXNL2) regulates the growth and metastasis of human breast cancer cells through a redox signaling mechanism. TXNL2 was found to be overexpressed in human cancers, including breast cancers. Knockdown of TXNL2 in human breast cancer cell lines increased ROS levels and reduced NF-κB activity, resulting in inhibition of in vitro proliferation, survival, and invasion. In addition, TXNL2 knockdown inhibited tumorigenesis and metastasis of these cells upon transplantation into immunodeficient mice. Furthermore, analysis of primary breast cancer samples demonstrated that enhanced TXNL2 expression correlated with metastasis to the lung and brain and with decreased overall patient survival. Our studies provided insight into redox-based mechanisms underlying tumor growth and metastasis and suggest that TXNL2 could be a target for treatment of breast cancer.