Jane P. Ko

Pulmonary Nodule Detection, Characterization, and Management With Multidetector Computed Tomography

Pulmonary nodule detection and characterization continue to improve with technological advancements. The noninvasive methods available for assisting in nodule detection and for characterizing nodules as benign, malignant, or indeterminate will be discussed. Evidence-based guidelines will be reviewed to help guide the appropriate management of pulmonary nodules.

Lung nodule detection and characterization with multislice CT

The ability to identify and characterize pulmonary nodules has been dramatically increased by the introduction of multislice CT (MSCT) technology. Using high-resolution sections, MSCT allows considerable improvement in assessing nodule morphology, enhancement patterns, and growth. MSCT also has facilitated the development and potential of clinical application of computer-assisted diagnosis.

Lung pathologic findings in a local residential and working community exposed to World Trade Center dust, gas, and fumes.

Objective: To describe pathologic findings in symptomatic World Trade Center–exposed local workers, residents, and cleanup workers enrolled in a treatment program. Methods: Twelve patients underwent surgical lung biopsy for suspected interstitial lung disease (group 1, n = 6) or abnormal pulmonary function tests (group 2, n = 6). High-resolution computed axial tomography and pathologic findings were coded. Scanning electron microscopy with energy-dispersive x-ray spectroscopy was performed. Results: High-resolution computed axial tomography showed reticular findings (group 1) or normal or airway-related findings (group 2). Pulmonary function tests were predominantly restrictive. Interstitial fibrosis, emphysematous change, and small airway abnormalities were seen. All cases had opaque and birefringent particles within macrophages, and examined particles contained silica, aluminum silicates, titanium dioxide, talc, and metals. Conclusions: In symptomatic World Trade Center–exposed individuals, pathologic findings suggest a common exposure resulting in alveolar loss and a diverse response to injury.

Pulmonary nodules: detection, assessment, and CAD.

OBJECTIVE The imaging of pulmonary nodules is an evolving and dynamic field. In this review, we discuss the detection and multitechnique characterization of pulmonary nodules, emphasizing the impact of technological advances on both noninvasive and invasive evaluation and surveillance. The potential contribution of MRI, evolving imaging-guided techniques, and computer applications are also discussed. CONCLUSION Advances in MDCT and PET and the potential contribution of fast-imaging MRI sequences and computer applications should continue to improve our evaluation of the solitary pulmonary nodule.

Pulmonary Nodules: Growth Rate Assessment in Patients by Using Serial CT and Three-dimensional Volumetry

PURPOSE To determine the precision of a three-dimensional (3D) method for measuring the growth rate of solid and subsolid nodules and its ability to detect abnormal growth rates. MATERIALS AND METHODS This study was approved by the Institutional Research Board and was HIPAA compliant. Informed consent was waived. The growth rates of 123 lung nodules in 59 patients who had undergone lung cancer screening computed tomography (CT) were measured by using a 3D semiautomated computer-assisted volume method. Clinical stability was established with long-term CT follow-up (mean, 6.4 years±1.9 [standard deviation]; range, 2.0-8.5 years). A mean of 4.1 CT examinations per patient±1.2 (range, two to seven CT examinations per patient) was analyzed during 2.4 years±0.5 after baseline CT. Nodule morphology, attenuation, and location were characterized. The analysis of standard deviation of growth rate in relation to time between scans yielded a normative model for detecting abnormal growth. RESULTS Growth rate precision increased with greater time between scans. Overall estimate for standard deviation of growth rate, on the basis of 939 growth rate determinations in clinically stable nodules, was 36.5% per year. Peripheral location (P=.01; 37.1% per year vs 25.6% per year) and adjacency to pleural surface (P=.05; 38.9% per year vs 34.0% per year) significantly increased standard deviation of growth rate. All eight malignant nodules had an abnormally high growth rate detected. By using 3D volumetry, growth rate-based diagnosis of malignancy was made at a mean of 183 days±158, compared with radiologic or clinical diagnosis at 344 days±284. CONCLUSION A normative model derived from the variability of growth rates of nodules that were stable for an average of 6.4 years may enable identification of lung cancer.

Dual-energy computed tomography: concepts, performance, and thoracic applications.

Advances in multidetector technology have made dual-energy computed tomography (CT) imaging possible. Dual-energy CT imaging enables tissue characterization in addition to morphologic evaluation of imaged regions. This article reviews current and potential CT technology, technical and workflow considerations when performing dual-energy CT, and clinical applications in the thorax, with an emphasis on the knowledge gained so far.

CT manifestations of respiratory syncytial virus infection in lung transplant recipients.

PURPOSE The purpose of our study was to evaluate CT findings during respiratory syncytial virus (RSV) infection in lung transplant recipients and to identify sequelae. METHOD Thirty-nine CT scans prior to, during, and following acute infection in 10 lung transplant recipients were reviewed. Abnormalities that were new from baseline observations and occurred within 4 weeks of diagnosis were defined as acute. Chronic findings were defined as those present >4 weeks after diagnosis. RESULTS Findings in nine patients were ground-glass (seven), air-space (five), and tree-in-bud (four) opacities and acute bronchial dilatation (four) and wall thickening (four). Patients lacked pleural effusions or lymph node enlargement. Five of seven patients with follow-up exams had new air trapping (three), persistent bronchial dilatation (three), and thickening (two). Three and 2 of the 10 patients developed bronchiolitis obliterans syndrome and obliterative bronchiolitis, respectively. CONCLUSION During acute infection, patients commonly had ground-glass opacities but lacked pleural effusions and lymph node enlargement. There can be chronic sequelae after infection.

Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT

OBJECTIVE The objective of our study was to evaluate the impact of computer-aided detection (CAD) on the identification of subsolid and solid lung nodules on thin- and thick-section CT. MATERIALS AND METHODS For 46 chest CT examinations with ground-glass opacity (GGO) nodules, CAD marks computed using thin data were evaluated in two phases. First, four chest radiologists reviewed thin sections (reader(thin)) for nodules and subsequently CAD marks (reader(thin) + CAD(thin)). After 4 months, the same cases were reviewed on thick sections (reader(thick)) and subsequently with CAD marks (reader(thick) + CAD(thick)). Sensitivities were evaluated. Additionally, reader(thick) sensitivity with assessment of CAD marks on thin sections was estimated (reader(thick) + CAD(thin)). RESULTS For 155 nodules (mean, 5.5 mm; range, 4.0-27.5 mm)-74 solid nodules, 22 part-solid (part-solid nodules), and 59 GGO nodules-CAD stand-alone sensitivity was 80%, 95%, and 71%, respectively, with three false-positives on average (0-12) per CT study. Reader(thin) + CAD(thin) sensitivities were higher than reader(thin) for solid nodules (82% vs 57%, p < 0.001), part-solid nodules (97% vs 81%, p = 0.0027), and GGO nodules (82% vs 69%, p < 0.001) for all readers (p < 0.001). Respective sensitivities for reader(thick), reader(thick) + CAD(thick), reader(thick) + CAD(thin) were 40%, 58% (p < 0.001), and 77% (p < 0.001) for solid nodules; 72%, 73% (p = 0.322), and 94% (p < 0.001) for part-solid nodules; and 53%, 58% (p = 0.008), and 79% (p < 0.001) for GGO nodules. For reader(thin), false-positives increased from 0.64 per case to 0.90 with CAD(thin) (p < 0.001) but not for reader(thick); false-positive rates were 1.17, 1.19, and 1.26 per case for reader(thick), reader(thick) + CAD(thick), and reader(thick) + CAD(thin), respectively. CONCLUSION Detection of GGO nodules and solid nodules is significantly improved with CAD. When interpretation is performed on thick sections, the benefit is greater when CAD marks are reviewed on thin rather than thick sections.

Lung Adenocarcinoma: Correlation of Quantitative CT Findings with Pathologic Findings

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 = 41) 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. (©) RSNA, 2016.

Multidetector CT of Solitary Pulmonary Nodules

With the increasing use of multidetector CT, small nodules are being detected more often. Although most incidentally discovered nodules are benign, usually the sequelae of pulmonary infection and malignancy, either primary or secondary, remains an important consideration in the differential diagnosis of solitary pulmonary nodules. This article reviews the role of imaging in the detection and characterization of solitary pulmonary nodules. Strategies for evaluating and managing solitary pulmonary nodules are also discussed.