Respiratory Musculature Evaluated by Computed Tomography in the Setting of Prolonged Mechanical Ventilation.

BACKGROUND: Diaphragm atrophy has been observed in subjects who undergo invasive mechanical ventilation. We propose a new method to assess for respiratory muscle (RM) changes in subjects who undergo invasive mechanical ventilation by assessing for changes in respiratory muscles through computed tomography (CT). METHODS: A retrospective case series study was conducted on subjects who underwent invasive mechanical ventilation and received at least 2 chest CT scans during admission. Exclusion criteria included history of chronic mechanical ventilation dependence and neuromuscular disease. Respiratory muscle cross-sectional area (CSA) was measured at the T6 vertebrae. RESULTS: Fourteen subjects were included: mean (± SD) age, BMI, and admission APACHE II scores were 54.0 y (± 14.9), 32.6 kg/m2 (± 10.9), and 23.5 (± 6.0), respectively. Ten (71%) subjects were male. Mean length of time between CT chest scans was 7.5 d (± 3.3). Mean duration of invasive mechanical ventilation was 4.5 d (± 3.4). The percentage change in TM CSA among those who underwent invasive mechanical ventilation was 10.5% (± 6.1). CONCLUSIONS: We demonstrated that serial analysis of respiratory muscle CSA through CT chest scans can be a method to assess for respiratory muscle atrophy in subjects undergoing mechanical ventilation. Future prospective studies involving larger populations are needed to better understand how this method can be used to predict outcomes in mechanically ventilated patients.

Augmenting the National Institutes of Health Chest Radiograph Dataset with Expert Annotations of Possible Pneumonia.

This dataset is intended to be used for machine learning and is composed of annotations with bounding boxes for pulmonary opacity on chest radiographs which may represent pneumonia in the appropriate clinical setting.

Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer: A Primer for Radiologists.

The past 2 decades have seen a rapid growth in use of stereotactic body radiation therapy (SBRT) for the management of non-small cell lung cancer (NSCLC). Not only is SBRT the reference standard for treatment of early-stage node-negative NSCLC in medically inoperable patients, it is also currently challenging the role of surgery for early-stage operable disease. SBRT is also used to treat recurrent disease and has a role in the management of multiple synchronous lung cancers. Imaging changes after SBRT differ from the changes after conventional radiation therapy in many ways, the knowledge of which is pertinent for accurate image interpretation. Posttreatment response assessment and detection of recurrent disease are heavily reliant on radiologic assessment, and often the decision to treat recurrent disease is based on the imaging findings themselves. This article provides a comprehensive review of the concepts of SBRT and the current indications for its use in the treatment of early-stage NSCLC, as well as a discussion of the CT findings seen after SBRT compared with the changes after conventional radiation therapy. Radiologic findings that are suggestive of recurrent disease and the imaging pitfalls are also highlighted. Finally, the rare complications after SBRT are described. SBRT is a major component of the changing treatment paradigms for early- and late-stage NSCLC. The imaging findings after SBRT often determine the next steps in a patient's clinical management. Therefore, radiologists must be familiar with the uses of this therapy and its radiologic appearance to be able to effectively contribute to the care of patients with NSCLC. ©RSNA, 2018.

Development and validation of a plasma biomarker panel for discerning clinical significance of indeterminate pulmonary nodules.

INTRODUCTION: The recent findings of the National Lung Screening Trial showed 24.2% of individuals at high risk for lung cancer having one or more indeterminate nodules detected by low-dose computed tomography-based screening, 96.4% of which were eventually confirmed as false positives. These positive scans necessitate additional diagnostic procedures to establish a definitive diagnosis that adds cost and risk to the paradigm. A plasma test able to assign benign versus malignant pathology in high-risk patients would be an invaluable tool to complement low-dose computed tomography-based screening and promote its rapid implementation. METHODS: We evaluated 17 biomarkers, previously shown to have value in detecting lung cancer, against a discovery cohort, comprising benign (n = 67) cases and lung cancer (n = 69) cases. A Random Forest method based analysis was used to identify the optimal biomarker panel for assigning disease status, which was then validated against a cohort from the Mayo Clinic, comprising patients with benign (n = 61) or malignant (n = 20) indeterminate lung nodules. RESULTS: Our discovery efforts produced a seven-analyte plasma biomarker panel consisting of interleukin 6 (IL-6), IL-10, IL-1ra, sIL-2Rα, stromal cell-derived factor-1α+ß, tumor necrosis factor α, and macrophage inflammatory protein 1 α. The sensitivity and specificity of our panel in our validation cohort is 95.0% and 23.3%, respectively. The validated negative predictive value of our panel was 93.8%. CONCLUSION: We developed a seven-analyte plasma biomarker panel able to identify benign nodules, otherwise deemed indeterminate, with a high degree of accuracy. This panel may have clinical utility in risk-stratifying screen-detected lung nodules, decrease unnecessary follow-up imaging or invasive procedures, and potentially avoid unnecessary morbidity, mortality, and health care costs.