Evaluation of superficial xenograft volume estimation by ultrasound and caliper against MRI in a longitudinal pre-clinical radiotherapeutic setting.

Abstract

Accurate tumor volume estimation is important for evaluating the response to radionuclide therapy and external beam radiotherapy as well as to other pharmaceuticals. A common method for monitoring the growth of subcutaneous tumors in pre-clinical models and assessing the treatment response is to measure the tumor length and width by external calipers to estimate its volume. This procedure relies on an assumption of a spheroidal tumor shape wherein the tumor depth equals the width and can yield considerably inaccuracies. Ultrasound imaging is a non-invasive technique that can measure all three axes of the tumor and might be an alternative to caliper measurement with potentially greater accuracy and comparable ease-of-use and throughput. Both 2D and 3D ultrasound imaging are possible, the former offering short scan times without the need for anesthesia and heating-valuable factors for longitudinal studies in large animal cohorts. Nevertheless, tumor volume estimation accuracy by 2D ultrasound imaging has seen limited investigation. In this study we have evaluated the accuracy of tumor volume estimation by caliper and 2D ultrasound with comparisons to reference measurements by magnetic resonance imaging (MRI) in a pre-clinical model of prostate cancer treated with either external beam radiotherapy, radionuclide therapy, or no treatment. Tumor volumes were measured longitudinally in 29 mice by caliper, ultrasound, and MRI before and after external beam radiotherapy, [177Lu]Lu-PSMA-617 radionuclide therapy, or no treatment. Caliper measurements had a marked bias, overestimating the tumor volumes by a median of 150% compared to MRI. Ultrasound measurements were markedly more accurate, with a median bias of -21% compared to MRI. Ultrasound imaging is a reliable and accurate method for tumor volume estimation in pre-clinical models of radiotherapy, whereas caliper measurements are prone to overestimation.