Test-Retest Performance of a 1-Hour Multiparametric MR Image Acquisition Pipeline With Orthotopic Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts.

Xia Ge,James D Quirk,Joseph J H Ackerman,John A Engelbach,G Larry Bretthorst,Kooresh I Shoghi,Joel R Garbow,Shunqiang Li

doi:10.18383/j.tom.2019.00012

Abstract

Preclinical imaging is critical in the development of translational strategies to detect diseases and monitor response to therapy. The National Cancer Institute Co-Clinical Imaging Resource Program was launched, in part, to develop best practices in preclinical imaging. In this context, the objective of this work was to develop a 1-hour, multiparametric magnetic resonance image-acquisition pipeline with triple-negative breast cancer patient-derived xenografts (PDXs). The 1-hour, image-acquisition pipeline includes T1- and T2-weighted scans, quantitative T1, T2, and apparent diffusion coefficient (ADC) parameter maps, and dynamic contrast-enhanced (DCE) time-course images. Quality-control measures used phantoms. The triple-negative breast cancer PDXs used for this study averaged 174 ± 73 μL in volume, with region of interest–averaged T1, T2, and ADC values of 1.9 ± 0.2 seconds, 62 ± 3 milliseconds, and 0.71 ± 0.06 μm2/ms (mean ± SD), respectively. Specific focus was on assessing the within-subject test–retest coefficient-of-variation (CVWS) for each of the magnetic resonance imaging metrics. Determination of PDX volume via manually drawn regions of interest is highly robust, with ∼1% CVWS. Determination of T2 is also robust with a ∼3% CVWS. Measurements of T1 and ADC are less robust with CVWS values in the 6%–11% range. Preliminary DCE test–retest time-course determinations, as quantified by area under the curve and Ktrans from 2-compartment exchange (extended Tofts) modeling, suggest that DCE is the least robust protocol, with ∼30%–40% CVWS.

Highlights

The triple-negative breast cancer patient-derived xenografts (PDXs) used for this study averaged 174 Ϯ 73 ␮L in volume, with region of interest–averaged T1, T2, and apparent diffusion coefficient (ADC) values of 1.9 Ϯ 0.2 seconds, 62 Ϯ 3 milliseconds, and 0.71 Ϯ 0.06 ␮m2/ms, respectively
Triple-negative breast cancer (TNBC) is an aggressive tumor characterized by poor outcomes and higher relapse rates compared with other subtypes of breast cancer
Significant progress has been made in advancing such quantitative imaging (QI) approaches, preclinical imaging remains a critical component in the translational pipeline of validating advanced QI methods for applications in drug discovery and assessment of response to therapy

Summary

Introduction

Triple-negative breast cancer (TNBC) is an aggressive tumor characterized by poor outcomes and higher relapse rates compared with other subtypes of breast cancer. Toward that end, advanced quantitative imaging (QI) strategies have been developed and evaluated for predicting or assessing response to therapy in breast cancer. Significant progress has been made in advancing such QI approaches, preclinical imaging remains a critical component in the translational pipeline of validating advanced QI methods for applications in drug discovery and assessment of response to therapy. Patient-derived tumor xenografts (PDXs) are considered to provide more faithful tumor models than traditional orthotopic implantation of established tumor cell lines. There are challenges in developing optimal quantitative pipelines to assess response to therapy in a preclinical setting. Most preclinical (small-animal) magnetic resonance imaging (MRI) studies of cancer models involve tumor-cell implantation into the brain or leg (thigh) of the subject

Objectives

Methods

Results

Discussion

Conclusion