Faculty Bibliography

RATIONALE AND OBJECTIVES: The aim of this study was to retrospectively evaluate an automated global scoring system for evaluating the extent and severity of disease in a known cohort of patients with documented bronchiectasis. On the basis of a combination of validated three-dimensional automated algorithms for bronchial tree extraction and quantitative airway measurements, global scoring combines the evaluation of bronchial lumen-to-artery ratios and bronchial wall-to-artery ratios, as well as the detection of mucoid-impacted airways. The result is an automatically generated global computed tomographic (CT) score designed to simplify and standardize the interpretation of scans in patients with chronic airway infections. MATERIALS AND METHODS: Twenty high-resolution CT data sets were used to evaluate an automated CT scoring method that combines algorithms for airway quantitative analysis that have been individually tested and validated. Patients with clinically documented atypical mycobacterial infections with visually assessed CT evidence of bronchiectasis varying from mild to severe were retrospectively selected. These data sets were evaluated by two independent experienced radiologists and by computer scoring, with the results compared statistically, including Spearman's rank correlation. RESULTS: Computer evaluation required 3 to 5 minutes per data set, compared to 12 to 15 minutes for manual scoring. Initial Spearman's rank tests showed positive correlations between automated and readers' global scores (r = 0.609, P = .01), extent of bronchiectasis (r = 0.69, P = .0004), and severity of bronchiectasis (r = 0.61, P = .01), while mucus plug detection showed a lesser extent of positive correlation between the scoring methods (r = 0.42, P = .07) and wall thickness a negative weak correlation (r = -0.10, P = .40). Further retrospective review of 24 lobes in which wall thickness scores showed the highest discrepancy between manual and automated methods was then performed, using electronic calipers and perpendicular cross-sections to reassess airway measurements. This resulted in an improved Spearman's rank correlation to r = 0.62 (P = .009), for a global score of r = 0.67 (P = .001). CONCLUSION: Automated computerized scoring shows considerable promise for providing a standardized, quantitative method, demonstrating overall good correlation with the results of experienced readers' evaluation of the extent and severity of bronchiectasis. It is speculated that this technique may also be applicable to a wide range of other conditions associated with chronic bronchial inflammation, as well as of potential value for monitoring response to therapy in these same populations

PURPOSE:: The objectives of this study were (1) to evaluate the potential of low-peak kilovoltage (kVp) images acquired with dual-energy computed tomography (DECT) to improve aortic attenuation and reduce contrast agent utilization and (2) to evaluate the feasibility of material-specific DECT imaging for evaluating aortic disease. MATERIALS AND METHODS:: Aortic imaging characteristics of 2 groups of patients examined with DECT were compared. In the first group, CT angiography (CTA) was performed in patients with known or suspected aortic disease (CTA group: n = 20, 100-150 mL of contrast at 4.5 mL/s). In the second group, reduced contrast volume CTA was performed in patients with 'routine' indications (RC group: n = 20, 50-60 mL at 3 mL/s followed by a saline chaser). In both groups, aortic attenuation and SD were measured at 80 and 140 kVp, and the image quality was analyzed using a 5-point scale. The use of DECT postprocessing techniques for assessing aortic pathology was also evaluated. RESULTS:: For all patients, the aortic attenuation was significantly higher at 80 kVp than at 140 kVp (P < 0.001). Image noise measured quantitatively was higher at 80 kVp (P < 0.001) but did not affect the perceived image quality (P = 0.3). Using low-peak kilovoltage allowed aortic CTA to be performed with a markedly reduced contrast volume and flow rate, with image quality similar to standard CTA (P = 0.2). In a series of cases with proved aortic disease, comparison of true precontrast and subtraction 'virtual noncontrast' images showed the potential to eliminate aortic precontrast imaging, reducing radiation exposure. CONCLUSIONS:: Single-acquisition DECT combines (1) the benefits of low-kVp vascular imaging (increased iodine conspicuity coupled with a contrast volume/rate reduction) and (2) the use of material-specific imaging techniques to uniquely characterize the aortic pathology

BACKGROUND: Sera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways. METHODS: We performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts. RESULTS: Statistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer. CONCLUSION: A pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers

BACKGROUND: The accuracy of gadolinium-enhanced magnetic resonance pulmonary angiography and magnetic resonance venography for diagnosing pulmonary embolism has not been determined conclusively. OBJECTIVE: To investigate performance characteristics of magnetic resonance angiography, with or without magnetic resonance venography, for diagnosing pulmonary embolism. DESIGN: Prospective, multicenter study from 10 April 2006 to 30 September 2008. SETTING: 7 hospitals and their emergency services. PATIENTS: 371 adults with diagnosed or excluded pulmonary embolism. MEASUREMENTS: Sensitivity, specificity, and likelihood ratios were measured by comparing independently read magnetic resonance imaging with the reference standard for diagnosing pulmonary embolism. Reference standard diagnosis or exclusion was made by using various tests, including computed tomographic angiography and venography, ventilation-perfusion lung scan, venous ultrasonography, d-dimer assay, and clinical assessment. RESULTS: Magnetic resonance angiography, averaged across centers, was technically inadequate in 25% of patients (92 of 371). The proportion of technically inadequate images ranged from 11% to 52% at various centers. Including patients with technically inadequate images, magnetic resonance angiography identified 57% (59 of 104) with pulmonary embolism. Technically adequate magnetic resonance angiography had a sensitivity of 78% and a specificity of 99%. Technically adequate magnetic resonance angiography and venography had a sensitivity of 92% and a specificity of 96%, but 52% of patients (194 of 370) had technically inadequate results. LIMITATION: A high proportion of patients with suspected embolism was not eligible or declined to participate. CONCLUSION: Magnetic resonance pulmonary angiography should be considered only at centers that routinely perform it well and only for patients for whom standard tests are contraindicated. Magnetic resonance pulmonary angiography and magnetic resonance venography combined have a higher sensitivity than magnetic resonance pulmonary angiography alone in patients with technically adequate images, but it is more difficult to obtain technically adequate images with the 2 procedures.

Bronchiolar disorders are generally difficult to diagnose because most patients present with nonspecific respiratory symptoms of variable duration and severity. A detailed clinical history may point toward a specific diagnosis. Pertinent clinical questions include history of smoking, collagen vascular disease, inhalational injury, medication usage, and organ transplant. It is important also to evaluate possible systemic and pulmonary signs of infection, evidence of air trapping, and high-pitched expiratory wheezing, which may suggest small airways involvement. In this context, pulmonary function tests and plain chest radiographs may demonstrate abnormalities; however, they rarely prove sufficiently specific to obviate bronchoscopic or surgical biopsy. Given these limitations, in our experience, high-resolution CT (HRCT) scanning of the chest often proves to be the most important diagnostic tool to guide diagnosis in these difficult cases, because different subtypes of bronchiolar disorders may present with characteristic image findings. Three distinct HRCT patterns in particular are of value in assisting differential diagnosis. A tree-in-bud pattern of well-defined nodules is seen primarily as a result of infectious processes. Ill-defined centrilobular ground-glass nodules point toward respiratory bronchiolitis when localized in upper lobes in smokers or subacute hypersensitivity pneumonitis when more diffuse. Finally, a pattern of mosaic attenuation, especially when seen on expiratory images, is consistent with air-trapping characteristic of bronchiolitis obliterans or constrictive bronchiolitis. Based on an appreciation of the critical role played by HRCT scanning, this article provides clinicians with a practical algorithmic approach to the diagnosis of bronchiolar disorders

OBJECTIVE: The diagnostic performance of radiologists using incremental CAD assistance for lung nodule detection on CT and their temporal variation in performance during CAD evaluation was assessed. METHODS: CAD was applied to 20 chest multidetector-row computed tomography (MDCT) scans containing 190 non-calcified > or =3-mm nodules. After free search, three radiologists independently evaluated a maximum of up to 50 CAD detections/patient. Multiple free-response ROC curves were generated for free search and successive CAD evaluation, by incrementally adding CAD detections one at a time to the radiologists' performance. RESULTS: The sensitivity for free search was 53% (range, 44%-59%) at 1.15 false positives (FP)/patient and increased with CAD to 69% (range, 59-82%) at 1.45 FP/patient. CAD evaluation initially resulted in a sharp rise in sensitivity of 14% with a minimal increase in FP over a time period of 100 s, followed by flattening of the sensitivity increase to only 2%. This transition resulted from a greater prevalence of true positive (TP) versus FP detections at early CAD evaluation and not by a temporal change in readers' performance. The time spent for TP (9.5 s +/- 4.5 s) and false negative (FN) (8.4 s +/- 6.7 s) detections was similar; FP decisions took two- to three-times longer (14.4 s +/- 8.7 s) than true negative (TN) decisions (4.7 s +/- 1.3 s). CONCLUSIONS: When CAD output is ordered by CAD score, an initial period of rapid performance improvement slows significantly over time because of non-uniformity in the distribution of TP CAD output and not to a changing reader performance over time.