CT texture analysis proves promising in identifying renal masses

Computed tomography texture analysis (CTTA) was successful in categorizing special renal masses in a study published online Sept. 16 in Academic Radiology.

A technique that characterizes heterogeneity within a region of interest based on the distribution of pixel intensities and gray-level values, CTTA  uses both unfiltered and frequency filtered images by deriving quantitative texture parameters based on attributes of the pixel values themselves and the image histogram.

Authors Siva P. Raman, MD, of John Hopkins University, and colleagues noted that this technique has been used primarily to predict patient outcomes and prognosis.

“The goal of this pilot study is to assess the efficacy of texture analysis, when combined with a robust statistical classification model, in differentiating this small group of renal masses, and thereby evaluate the promise of texture analysis as a quantitative imaging tool that might ultimately be applied to a larger number of lesion categories,” the authors wrote.

For the study, CTTA software analyzed 20 clear cell renal cell carcinomas (RCCs), 20 papillary RCCs, 20 onocytomas and 20 renal cysts.

Regions of interest were drawn around each mass on multiple slices in the arterial, venous, and delayed phases on renal mass protocol CT scans. Unfiltered images and spatial band-pass filtered images were analyzed to quantify heterogeneity.

“Random forest method was used to construct a predictive model to classify lesions using quantitative parameters. The model was externally validated on a separate set of 19 unknown cases,” the team wrote.

The results found CTTA to be an effective tool in categorizing kidney masses.

The forest model correctly categorized 89 percent of the oncocytomas, 91 percent of the clear cell RCCs, 100 percent of the cysts and 100 percent of the papillary RCCs.

“The data from this preliminary study suggest that CTTA might offer promise as a quantitative imaging tool that may someday augment a radiologist's ability to characterize lesion histology,” Raman and colleagues wrote.

The team noted the benefits of CTTA’s ability to differentiate kidney masses without the need for biopsy could impact patient management.

“Lesions strongly thought to represent either a benign entity (such as an oncocytoma) or a more indolent form of RCC (such as a papillary RCC) could theoretically be followed sequentially over time,” Raman and team wrote.

Additionally, as percutaneous biopsy of masses has become more common, CTTA could serve as a valuable adjunct, with nondiagnostic biopsies and sampling error that are relatively common with percutaneous biopsy.

“In this preliminary study, when combined with random forest statistical modeling, this technique allowed relatively accurate discrimination and characterization of a small subset of common renal masses, suggesting its future promise as a quantitative imaging tool that may augment our ability to accurately predict a lesion's histology based on its imaging appearance,” Raman and colleagues wrote.