A pilot study of volume measurement as a method of tumor response evaluation to aid biomarker development

Abstract

Purpose: Tissue biomarker discovery is potentially limited by conventional tumor measurement techniques, which have an uncertain ability to accurately distinguish sensitive and resistant tumors. Semiautomated volumetric measurement of computed tomography imaging has the potential to more accurately capture tumor growth dynamics, allowing for more exact separation of sensitive and resistant tumors and a more accurate comparison of tissue characteristics.

Experimental design: Forty-eight patients with early stage non-small cell lung cancer and clinical characteristics of sensitivity to gefitinib were studied. High-resolution computed tomography was done at baseline and after 3 weeks of gefitinib. Tumors were then resected and molecularly profiled. Unidimensional and volumetric measurements were done using a semiautomated algorithm. Measurement changes were evaluated for their ability to differentiate tumors with and without sensitizing mutations.

Results: Forty-four percent of tumors had epidermal growth factor receptor-sensitizing mutations. Receiver operating characteristic curve analysis showed that volumetric measurement had a higher area under the curve than unidimensional measurement for identifying tumors harboring sensitizing mutations (P = 0.009). Tumor volume decrease of >24.9% was the imaging criteria best able to classify tumors with and without sensitizing mutations (sensitivity, 90%; specificity, 89%).

Conclusions: Volumetric tumor measurement was better than unidimensional tumor measurement at distinguishing tumors based on presence or absence of a sensitizing mutation. Use of volume-based response assessment for the development of tissue biomarkers could reduce contamination between sensitive and resistant tumor populations, improving our ability to identify meaningful predictors of sensitivity.

Trial registration: ClinicalTrials.gov NCT00588445.

Figure 1

Plots of unidimensional and volumetric measurement changes, grouped by absence (blue) or presence (green) of EGFR sensitizing mutation. There is a statistically significant difference between the molecular subtypes using both unidimensional (p=0.002) and volumetric (p<0.001) measurement, as is expected biologically. Note there is overlap between the interquartile ranges using unidimensional measurement, while there is better separation of groups using the volumetric measurement.

Figure 2

ROC curves for the ability of each measurement method to distinguish tumors based on presence or absence of a sensitizing mutation. For each possible percent measurement change, a specificity and sensitivity for predicting presence of a sensitizing mutation is calculated, and these are plotted on the X and Y axes. Volumetric measurement change is shown to have better diagnostic accuracy when the area under the curve (AUC) is compared (p=0.009).

Figure 3

Detection of tumor change on CT, comparing volumetric and unidimensional measurement, for an EGFR mutant tumor at baseline (A) and at 20-day follow-up (B). Computer delineated tumor contours and diameter lines are superimposed on one image from each study date. Three-dimensional (3D) view of each segmented tumor is displayed at upper-left corner of the each panel. For this case, a significant change is detected using volume measurement (−52.4%), but not using unidimensional measurement (−4.4%).