Faculty Bibliography

The radiologic evaluation and management of the indeterminate solitary pulmonary nodule provide common diagnostic dilemma. With continued technologic advancements in multidetector computed tomography leading to higher spatial resolution and greater overall sensitivity of computed tomography scanners, increasing numbers of indeterminate solitary pulmonary nodules are being detected. Malignant and benign solitary pulmonary nodules have similar imaging features. Clinical management of these incidental nodules relies not only on imaging characteristics but also on malignancy risk factors, along with the risks and benefits of further investigation.

OBJECTIVE: The purpose of this study was to assess the impact of an automated program on improvement in lung nodule matching efficiency. MATERIALS AND METHODS: Four thoracic radiologists independently reviewed two serial chest CT examinations from each of 57 patients. Each radiologist performed timed manual lung nodule matching. After 6 weeks, all radiologists independently repeated the timed matching portion using an automated nodule matching program. The time required for manual and automated matching was compared. The impact of nodule size and number on matching efficiency was determined. RESULTS: An average of 325 (range, 244-413) noncalcified solid pulmonary nodules was identified. Nodule matching was significantly faster with the automated program irrespective of the interpreting radiologist (p < 0.0001 for each). The maximal time saved with automated matching was 11.4 minutes (mean, 2.3 +/- 2.0 minutes). Matching was faster in 56 of 57 cases (98.2%) for three readers and in 46 of 57 cases (80.7%) for one reader. There were no differences among readers with respect to the mean time saved per matched nodule (p > 0.5). The automated program achieved 90%, 90%, 79%, and 92% accuracy for the four readers. The improvement in efficiency for a given patient using the automated technique was proportional to the number of matched nodules (p < 0.0001) and inversely proportional to nodule size (p < 0.05). CONCLUSION: Use of the automated lung nodule matching program significantly improves diagnostic efficiency. The time saved is proportionate to the number of nodules identified and inversely proportional to nodule size. Adoption of such a program should expedite CT examination interpretation and improve report turnaround time.

OBJECTIVE: The objective of our study was to identify the significance of lung nodules reported on abdominal CT. MATERIALS AND METHODS: Abdominal CT reports from a 1-year period were reviewed for the terms "nodule," "nodular," or "mass" in reference to the lung bases. Patients with prior chest or abdominal CT examinations were excluded; the study population included patients with an initial abdominal CT study and at least one follow-up chest or abdominal CT examination. Two thoracic radiologists characterized nodules in consensus. Radiology and clinical records were reviewed for nodule growth and clinical diagnoses. RESULTS: The term "nodule," "nodular," or "mass" in reference to the lung bases was reported in 364 of 12,287 abdominal CT studies (3%). Of 125 patients with no prior CT examination, 42 had undergone follow-up chest CT, abdominal CT, or both. Common imaging indications included abdominal pain (13/42, 31%) and preexisting malignancy (n = 7, 16.7%). Regardless of the indication for imaging, 16 (38.1%) had malignancy that was known (n = 13) or newly diagnosed (n = 3) on the initial abdominal CT. Three of 42 patients (7.1%) had malignant nodules representing metastatic disease: Nodule growth was seen in one patient with preexisting colon cancer, one patient with newly diagnosed metastatic pancreatic cancer, and a third with known bladder cancer. The latter patient had suspected lung metastases that were confirmed on chest CT 1 day later. Three of the 16 patients (18.8%) with preexisting or newly diagnosed cancer had malignant nodules. No malignant nodules were identified without such history. Six patients (14.3%) had an infection. CONCLUSION: Lung nodules incidentally detected on abdominal CT were rarely malignant and were seen only in the setting of an underlying abdominal malignancy. Knowledge of such history is of critical importance to both the clinician and the radiologist. Dedicated chest CT is most useful when assessing pulmonary nodules in patients with localized malignancy.

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.

BACKGROUND AND PURPOSE: To determine the optimal method of targeting breast and regional nodes in selected breast cancer patients after axillary dissection, we compared the results of IMRT versus no IMRT, and CT-informed versus clinically-placed fields, in supine and prone positions. MATERIALS AND METHODS: Twelve consecutive breast cancer patients simulated both prone and supine provided the images for this study. Four techniques were used to target breast, level III axilla, and supraclavicular fossa in either position: a traditional three-field three-dimensional conformal radiotherapy (3DCRT) plan, a four-field 3DCRT plan using a posterior axillary boost field, and two techniques using a CT-informed target volume consisting of an optimized 3DCRT plan (CT-planned 3D) and an intensity-modulated radiotherapy (IMRT) plan. The prescribed dose was 50Gy in 25 fractions. RESULTS: CT-planned 3D and IMRT techniques improved nodal PTV coverage. Supine, mean nodal PTV V50 was 50% (3-field), 59% (4-field), 92% (CT-planned 3D), and 94% (IMRT). Prone, V50 was 29% (3-field), 42% (4-field), 97% (CT-planned 3D), and 95% (IMRT). Prone positioning, compared to supine, and IMRT technique, compared to 3D, lowered ipsilateral lung V20. CONCLUSIONS: Traditional 3DCRT plans provide inadequate nodal coverage. Prone IMRT technique resulted in optimal target coverage and reduced ipsilateral lung V20

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

Purpose: Many potential lung cancers start out as small pulmonary nodules showing up as incidental findings on chest radiograph or computed tomography (CT) scans. Diagnosis is confirmed via biopsy, usually involving broncoscopy or CT-guided biopsy. However, these are invasive procedures that expose patients to additional risks. An alternative mode of tumor detection lies in administering successive chest CT scans. This has the advantage of avoiding those risks associated with biopsy. Overall, there is growing evidence for the effectiveness of low-dose CT for lung cancer screening. Morphology is an important indicator of malignant potential for lung nodules detected at CT. Automated methods for morphology assessment have previously been described for breast cancer visualized on mammography [1]. The most common measure of nodule shape is area-to-perimeter-length ratio (APR), low APR values being associated with spiculated or lobulated shape. APR is a static measure and thus highly susceptible to alterations by random noise and artifacts in image acquisition. We introduce and analyze the self-overlap (SO) method as a dynamic automated morphological detection scheme. SO measures the rate of change of nodule masks as a function of the radius of the blurring kernel. In other words, SO measures the degree to which a nodule's shape changes or stays intact upon successive pixel averaging that blurs the original image. Irregularities at the surface mean that a significant number of high-attenuation pixels (representing solid nodular tissue) are surrounded by low-attenuation pixels (representing air). Averaging each pixel with its neighboring pixels thus serves to trim back lobulations and spiculations from a nodule image. Hence, comparedto smooth nodules, lobulated and spiculated nodules are subject to more of this trimming upon successive averaging, so that their shape changes more, resulting in lower SO values. Due to its dynamical nature, we hypothesized that SO is more resilient to random image noise than APR. Methods: In experiment 1 we compare our algorithm with APR for nodules simulated using a spherical harmonic model (degree = 0-7) rasterized and contaminated with random noise. In experiment 2 we compare the new measure with a consensus of two expert morphology ratings of 119 nodules from clinical CT exams. Results: Experiment 1 shows that both methods display the desired trend in that APR and SO both decrease with increasing spherical harmonic degree-meaning more lobulations. As such both methods serve as measures of surface smoothness. However, SO displays significantly greater robustness to CT image noise; for both methods, we calculate variability as standard deviation over mean. We find that APR's variability in the face of random noise is on the order of ten times that of SO. This finding suggests that SO is much more robust than APR to the effects of random noise. Using a logistic regression model, in experiment 2 we achieved 89.9% agreement with the consensus assessment of two expert radiologists, versus 87.4% for APR. Conclusion: Simulation nodules show that both our dynamic method (SO) and a representative static method (APR) for automated lung nodule surface morphology determination yield clear trends as functions of surface smoothness. Hence both methods can, with proper fitting and cutoff selection, yield faithful predictions that have over 80% agreement with expert assessment. However, when the simulation nodules are subjected to random noise, SO yields much more consistent and reproducible results than APR. Overall, we conclude that our method, due to its robustness to the random noise and CT artifacts that can plague nodule images, is well suited for clinical application

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