QA procedures for multimodality preclinical tumor drug response testing

Abstract

There are growing expectations that imaging biomarkers for tumor therapeutic drug response assessment will speed up preclinical testing of anticancer drugs in rodent models. The only imaging biomarker presently approved by the U.S. Food and Drug Administration is tumor size measurement based on either World Health Organization (WHO) criteria or Response Evaluation Criteria in Solid Tumors (RECIST). Frequently, preclinical data are accumulated from multiple research centers on multiple continents using scanners from different manufacturers and sometimes even using different imaging modalities. Very expensive cancer drug response studies can be compromised by inadequate controls to assure precision and accuracy of tumor size measurements. This project was undertaken to develop standardized quality assurance (QA) procedures using a multimodality preclinical tumor response phantom to validate the accuracy of tumor size measurements based on WHO criteria, RECIST, or global tumor volume criteria for evaluation of cytostatic drugs. A tumor response phantom containing five low contrast test objects designed to simulate animal tumor models was made of tissue-mimicking materials. Imaging of the phantom was performed using three modalities in two institutions to evaluate size measurement of tumor-simulating test objects. Evaluation of tumor measurements from the three commonly used imaging devices in two different institutions for monitoring tumor size changes showed that a single phantom for multiple modalities was feasible. The tumor response phantom validated precision and accuracy of tumor response data input from ultrasound, computed tomography, and/or magnetic resonance imaging devices. Measurement results show that the standardized QA procedures using the tumor response phantom can provide a rationale check of data that excludes input from poorly maintained instruments, inadequate measurement protocols, or random operator error that frequently introduce unacceptable variability or systematic error in multiple institutions trials.