Faculty Bibliography

Incidentally detected lung nodules are increasingly common in routine diagnostic computed tomography (CT) imaging. Formal management recommendations for incidental nodules, such as those outlined by the Fleischner Society, must therefore reflect a balance of malignancy risk and the clinical context in which nodules are discovered. Nodule size, attenuation, morphology, and location all influence the likelihood of malignancy and, thus, the necessity and timing of follow-up according to current Fleischner recommendations. As technological advancements in CT imaging continue, there may be greater reliance on advanced computerized analysis of lung nodule features to help determine the risk of clinically significant disease.

RATIONALE AND OBJECTIVES: This study aimed to differentiate pathologically defined lepidic predominant lesions (LPL) from more invasive adenocarcinomas (INV) using three-dimensional (3D) volumetric density and first-order texture histogram analysis of surgically excised stage 1 lung adenocarcinomas. MATERIALS AND METHODS: This retrospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant. Sixty-four cases of pathologically proven stage 1 lung adenocarcinoma surgically resected between September 2006 and October 2015, including LPL (n = 43) and INV (n = 21), were evaluated using high-resolution computed tomography. Quantitative measurements included nodule volume, percent solid volume (% solid), and first-order texture histogram analysis including skewness, kurtosis, entropy, and mean nodule attenuation within each histogram quartile. Binomial logistic regression models were used to identify the best set of parameters distinguishing LPL from INV. RESULTS: Univariate analysis of 3D volumetric density and histogram features was statistically significant between LPL and INV groups (P < .05). Accuracy of a binomial logistic model to discriminate LPL from INV based on size and % solid was 85.9%. With optimized probability cutoff, the model achieves 81% sensitivity, 76.7% specificity, and area under the receiver operating characteristic curve of 0.897 (95% confidence interval, 0.821-0.973). An additional model based on size and mean nodule attenuation of the third quartile (Hu_Q3) of the histogram achieved similar accuracy of 81.3% and area under the receiver operating characteristic curve of 0.877 (95% confidence interval, 0.790-0.964). CONCLUSIONS: Both 3D volumetric density and first-order texture analysis of stage 1 lung adenocarcinoma allow differentiation of LPL from more invasive adenocarcinoma with overall accuracy of 85.9%-81.3%, based on multivariate analyses of either size and % solid or size and Hu_Q3, respectively.

In patients with early-stage lung cancer, surgical resection is the treatment of choice. Knowledge of the expected postsurgical changes and awareness of the temporal evolution of these findings as well as potential complications are important in avoiding misinterpretation. We review the surgical techniques used for lung cancer resection, expected postoperative radiologic manifestations, as well as potential early and late postoperative complications in order to improve diagnostic interpretation and optimize patient management.

OBJECTIVE: To assess the effect of low dose computed tomography pulmonary angiography (CTPA) on radiation dose in pregnant patients. MATERIALS AND METHODS: An old CTPA protocol for pregnant patients was compared to a new protocol. Protocol changes included: decreased kVp; increased contrast injection rate; imaging after shallow inspiration. Patients undergoing CTPA before (phase 1 group) or after (phase 2 group) the protocol change, were assessed. RESULTS: Effective dose was lower in the phase 2 group (0.95 v 1.66 mSv; p<0.001). Quantitative noise was lower in the phase 1 group (p<0.001). CONCLUSION: Low dose CTPA tailored for pregnancy reduces dose in pregnant patients.

Techniques for repair of the aorta currently include open and endovascular methods, hybrid approaches, minimally-invasive techniques, and aortic branch vessel reimplantation or bypass. Collaboration among radiologists and vascular and cardiothoracic surgeons is essential. An awareness of the various surgical techniques, expected postoperative appearance, and potential complications is essential for radiologists. This review will cover the postoperative appearance of the thoracic aorta with a focus on the ascending aorta. The value of three-dimensional image evaluation will also be emphasized.

INTRODUCTION: Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in patients with COPD having emphysema. The antimicrobial effects of AZM on the lower airway microbiome are not known and may contribute to its beneficial effects. Here we tested whether AZM treatment affects the lung microbiome and bacterial metabolites that might contribute to changes in levels of inflammatory cytokines in the airways. METHODS: 20 smokers (current or ex-smokers) with emphysema were randomised to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements performed in acellular BAL fluid included 16S rRNA gene sequences and quantity; 39 cytokines, chemokines and growth factors and 119 identified metabolites. The response to lipopolysaccharide (LPS) by alveolar macrophages after ex-vivo treatment with AZM or bacterial metabolites was assessed. RESULTS: Compared with placebo, AZM did not alter bacterial burden but reduced alpha-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Compared with placebo, AZM treatment led to reduced in-vivo levels of chemokine (C-X-C) ligand 1 (CXCL1), tumour necrosis factor (TNF)-alpha, interleukin (IL)-13 and IL-12p40 in BAL, but increased bacterial metabolites including glycolic acid, indol-3-acetate and linoleic acid. Glycolic acid and indol-3-acetate, but not AZM, blunted ex-vivo LPS-induced alveolar macrophage generation of CXCL1, TNF-alpha, IL-13 and IL-12p40. CONCLUSION: AZM treatment altered both lung microbiota and metabolome, affecting anti-inflammatory bacterial metabolites that may contribute to its therapeutic effects. TRIAL REGISTRATION NUMBER: NCT02557958.

Computed tomography pulmonary angiography (CTPA) has become the primary imaging modality for evaluating the pulmonary arteries. Although pulmonary embolism is the primary indication for CTPA, various pulmonary vascular abnormalities can be detected in adults. Knowledge of these disease entities and understanding technical pitfalls that can occur when performing CTPA are essential to enable accurate diagnosis and allow timely management. This review will cover a spectrum of acquired abnormalities including pulmonary embolism due to thrombus and foreign bodies, primary and metastatic tumor involving the pulmonary arteries, pulmonary hypertension, as well as pulmonary artery aneurysms and stenoses. Additionally, methods to overcome technical pitfalls and interventional treatment options will be addressed.

Purpose To identify the ability of computer-derived three-dimensional (3D) computed tomographic (CT) segmentation techniques to help differentiate lung adenocarcinoma subtypes. Materials and Methods This study had institutional research board approval and was HIPAA compliant. Pathologically classified resected lung adenocarcinomas (n = 23) with thin-section CT data were identified. Two readers independently placed over-inclusive volumes around nodules from which automated computer measurements were generated: mass (total mass) and volume (total volume) of the nodule and of any solid portion, in addition to the solid percentage of the nodule volume (percentage solid volume) or mass (percentage solid mass). Interobserver agreement and differences in measurements among pathologic entities were evaluated by using t tests. A multinomial logistic regression model was used to differentiate the probability of three diagnoses: invasive non-lepidic-predominant adenocarcinoma (INV), lepidic-predominant adenocarcinoma (LPA), and adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). Results Mean percentage solid volume of INV was 35.4% (95% confidence interval [CI]: 26.2%, 44.5%)-higher than the 14.5% (95% CI: 10.3%, 18.7%) for LPA (P = .002). Mean percentage solid volume of AIS/MIA was 8.2% (95% CI: 2.7%, 13.7%) and had a trend toward being lower than that for LPA (P = .051). Accuracy of the model based on total volume and percentage solid volume was 73.2%; accuracy of the model based on total mass and percentage solid mass was 75.6%. Conclusion Computer-assisted 3D measurement of nodules at CT had good reproducibility and helped differentiate among subtypes of lung adenocarcinoma. (c) RSNA, 2016.