An Update of CT Screening for Lung Cancer

The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program

We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in Lancet 1999 showed that CT screening could identify a high proportion of early, curable lung cancers. This stimulated large national screening studies to be quickly started. The ELCAP design, which provided evidence about screening in the context of a clinical program, was able to rapidly expand to a 12-institution study in New York State (NY-ELCAP) and to many international institutions (International-ELCAP), ultimately working with 82 institutions, all using the common I-ELCAP protocol. This expansion was possible because the investigators had developed the ELCAP Management System for screening, capturing data and CT images, and providing for quality assurance. This advanced registry and its rapid accumulation of data and images allowed continual assessment and updating of the regimen of screening as advances in knowledge and new technology emerged. For example, in the initial ELCAP study, introduction of helical CT scanners had allowed imaging of the entire lungs in a single breath, but the images were obtained in 10 mm increments resulting in about 30 images per person. Today, images are obtained in submillimeter slice thickness, resulting in around 700 images per person, which are viewed on high-resolution monitors. The regimen provides the imaging acquisition parameters, imaging interpretation, definition of positive result, and the recommendations for further workup, which now include identification of emphysema and coronary artery calcifications. Continual updating is critical to maximize the benefit of screening and to minimize potential harms. Insights were gained about the natural history of lung cancers, identification and management of nodule subtypes, increased understanding of nodule imaging and pathologic features, and measurement variability inherent in CT scanners. The registry also provides the foundation for assessment of new statistical techniques, including artificial intelligence, and integration of effective genomic and blood-based biomarkers, as they are developed.

The importance of the regimen of screening in maximizing the benefit and minimizing the harms

BACKGROUND

In CT screening for lung cancer, the regimen of screening is critical in diagnosing lung cancer early while limiting unnecessary tests and invasive procedures. The International Early Lung Cancer Action Program (I-ELCAP) has developed a regimen based on evidence collected in the I-ELCAP cohort of more than 70,000 participants.

METHODS

Important in the development of the regimen is the recognition of the profound difference between the first, baseline round of screening and all subsequent rounds of repeat screening. For each person undergoing screening, the baseline round happens only once while repeat rounds will be performed annually for many years. This difference needs to be clearly recognized as it is these annual rounds which allow for identification of small, early, yet aggressive, lung cancers which have high cure rates despite their aggressiveness. The importance of nodule consistency and size are key factors in the regimen. The regimen needs to be continuously updated by incorporating advances in technology and knowledge.

RESULTS

The use of the I-ELCAP regimen reduces the workup of participants in the screening program to less than 10% in the baseline round and less than 6% in the annual repeat rounds. By use of this regimen, estimated cure rate of lung cancers diagnosed under screening is 80% or higher in both baseline and annual repeat rounds.

CONCLUSIONS

The I-ELCAP collaboration provides a new paradigm that answers the 2002 NCI call for multiple approaches to address relevant questions about screening and the Institute of Medicine (IOM) Roundtable on Evidence-based Medicine from the National Academy of Science's call for a "new clinical research paradigm that takes better advantage of data generated in the course of healthcare delivery would speed and improve the development of evidence for real-world decision making".

Small Pulmonary Nodules: Effect of Two Computer-aided Detection Systems on Radiologist Performance

PURPOSE

To prospectively compare the effects of two computer-aided detection (CAD) systems on the detection of small pulmonary nodules at multi-detector row computed tomography (CT) by using a consensus panel decision as the reference standard.

MATERIALS AND METHODS

Institutional review board approval and informed consent were obtained. Multi-detector row CT scans were randomly chosen and prospectively evaluated in 25 patients. Two dedicated CAD systems-ImageChecker CT (R2 Technologies, Sunnyvale, Calif) and Nodule Enhanced Viewing (NEV) (Siemens Medical Solutions, Forchheim, Germany)-were used. Results were interpreted by three radiologists with 1, 3, and 6 years of experience. Images were evaluated without and with CAD software. The reference standard was assessed by a consensus panel consisting of all three radiologists and an adjudicator with 8 years of experience.

RESULTS

A total of 116 pulmonary nodules (average diameter, 3.4 mm; average volume, 32.05 mm3) were found in all data sets during consensus interpretation, which included findings from the CAD software and all radiologists. Overall sensitivity was 73% with ImageChecker CT and 75% with NEV. Overall sensitivity without CAD was 68% for radiologist 1, 78% for radiologist 2, and 82% for radiologist 3. With ImageChecker CT, sensitivity increased to 79% for radiologist 1, 90% for radiologist 2, and 84% for radiologist 3. With NEV, sensitivity increased to 79% for radiologist 1, 90% for radiologist 2, and 86% for radiologist 3. The average number of false-positive findings was six (range, 0-14) with ImageChecker CT and eight (range, 0-22) with NEV.

CONCLUSION

Radiologist performance in the interpretation of multi-detector row CT scans can be improved by using CAD systems, with a reduction in the number of false-negative diagnoses. No statistically significant difference in sensitivity was found between the two CAD systems.