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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 | John A Engelbach | G Larry Bretthorst | Shunqiang Li | Kooresh I Shoghi | Joel R Garbow | Joseph J H Ackerman
Tomography (Ann Arbor, Mich.) | 2019

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.

Pubmed ID: 31572793

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NCI NIH HHS, United States
    Id: U24 CA209837
  • Agency: NCI NIH HHS, United States
    Id: P30 CA091842

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