Comparing true tumor volume to unidimensional and bidimensional measurements in lung cancer—A better discriminator of response?

13020 Background: Accurate evaluation of response is crucial to determine if a treatment is effective for a particular patient or if an experimental agent is effective against a specific tumor type. Current measurement techniques such as WHO and RECIST are limited by only identifying changes in size in the axial plane, and with one or two dimensions. We devised and tested a semi-automated algorithm to calculate tumor volume and other parameters on thin-section CT scans to assess response in patients with non-small cell lung cancer (NSCLC) treated with gefitinib in a clinical trial. Methods: CT scans of 15 measurable pre- and post-gefitinib-treated non-small-cell lung cancers in 15 patients were analyzed. A semi-automated three-dimensional segmentation algorithm was developed for lung cancer and applied to each tumor at baseline and follow-up. The computer automatically identified the boundaries of the tumors in three dimensions and the “true” volume and calculated the greatest diameter and the product of ...