With the endorsement of low-dose CT (LDCT) screening for lung cancer in high-risk individuals by the United States Preventive Services Task Force, as well as the decision by the Centers for Medicare and Medicaid Services to approve Medicare coverage of the test, it is clear that LDCT lung cancer screening will become widespread.

With that in mind, an article in the April issue of the Journal of the American College of Radiology—“Role of the Quantitative Imaging Biomarker Alliance in Optimizing CT for the Evaluation of Lung Cancer Screen-Detected Nodules”—pointed out that as screening extends more widely into clinical practice, greater care “must be taken to ensure that its effectiveness and safety are optimized.”

According to the authors, led by James L. Mulshine, MD, of Rush University in Chicago, effectiveness depends on diagnosing and treating lung cancers as early as possible, while enhancing safety means avoiding potential harms related to unnecessary diagnostic procedures. “In practice,” the authors wrote, “this requires the early detection of small, noncalcified lung nodules and prompt differentiation of the few that are malignant from the many that are benign, through predominantly noninvasive means.” 

Screening and surveillance for lung cancer in clinical practice should ensure that the classification of lung cancer nodules detected by screening—as well as recommendations for their management—is done consistently across screening sites. An optimal way of accomplishing this is with quantitative imaging.

Nodule as biomarker

The Quantitative Imaging Biomakers Alliance (QIBA) is an initiative—organized by the Radiological Society of North America in 2007—to advance quantitative imaging and the use of imaging biomarkers in clinical practice by engaging researchers, healthcare professionals and industry stakeholders. Size is currently the basis of risk stratification of noncalcified lung nodules detected at screening; because solid and part-solid nodules <6 mm are rarely malignant, such nodules act as biomarkers followed over time.

"The use of imaging to assess lung nodule size is a clear example of how using quantitative imaging in a precise, reproducible fashion to guide the clinical management of lung cancer screening is a biomarker," Mulshine and his colleagues wrote.

Validating a quantitative imaging biomarker requires the identification and characterization of the sources of errors that effect measurements.  The factors that affect imaging measurements of lung nodules include:

• Imaging equipment-related factors—depending on the imaging modality—include things such as signal-to-noise ratio, spatial resolution, slice thickness, and image reconstruction algorithms.
• Environmental factors include the position of the lesion within the body and blocking or attenuation of the signal due to bone mass or other anatomic or pathologic features, as relevant in the defined clinical setting.
• Lesion- or feature-specific factors for CT volumetry in lung cancer, include the size of the nodule, its shape, and interaction with slice thickness; and biologic phenomena that are not necessarily part of the lesion but affect the detected signal.
• Observer- and software algorithm–related factors that Influence the robustness and accuracy of implementing an algorithm in a defined use context.

One of the QIBA strategies is to get stakeholders to collaborate to identify barriers to developing “consistent, reliable, valid, and achievable” quantitative imaging results across imaging platforms and clinical sites, and to expedite the development of hardware and software necessary to achieve these results. The eventual goal, that authors wrote, is for medical imaging devices to be manufactured as measuring devices akin to something like a blood pressure cuff, which will give accurate measurements no matter who makes the device.

This is being accomplished via experimentation, literature review and the assembly of expert opinion to provide the “strongest evidence” needed to define how best to implement each step in imaging acquisition and evaluation. The initiative involves the efforts of many stakeholders in lung cancer screening, professional societies (ACR, the American Association of Physicists in Medicine) and collaborative and advocacy groups including the International Early Lung Cancer Action Project, the Prevent Cancer Foundation and the Lung Cancer Alliance.

“This systematic approach to implementing a quantitative imaging biomarker with standardized specifications for image acquisition and postprocessing for a specific quantitative measurement of a pulmonary nodule results in consistent performance characteristics of the measurement,” the authors wrote. “Implementation of the QIBA small nodule profile may allow more efficient and effective clinical management of the diagnostic workup of individuals found to have suspicious pulmonary nodules in the course of lung cancer screening evaluation.”

According to the authors, a profile for small nodule CT volumetry in the lung cancer screening setting is nearly complete and will be posted for public comment in 2015.