title: Reproducibility of magnetic resonance perfusion imaging.
abstract: Dynamic MR biomarkers (T2*-weighted or susceptibility-based and T1-weighted or relaxivity-enhanced) have been applied to assess tumor perfusion and its response to therapies. A significant challenge in the development of reliable biomarkers is a rigorous assessment and optimization of reproducibility. The purpose of this study was to determine the measurement reproducibility of T1-weighted dynamic contrast-enhanced (DCE)-MRI and T2*-weighted dynamic susceptibility contrast (DSC)-MRI with two contrast agents (CA) of different molecular weight (MW): gadopentetate (Gd-DTPA, 0.5 kDa) and Gadomelitol (P792, 6.5 kDa). Each contrast agent was tested with eight mice that had subcutaneous MDA-MB-231 breast xenograft tumors. Each mouse was imaged with a combined DSC-DCE protocol three times within one week to achieve measures of reproducibility. DSC-MRI results were evaluated with a contrast to noise ratio (CNR) efficiency threshold. There was a clear signal drop (>95% probability threshold) in the DSC of normal tissue, while signal changes were minimal or non-existent (<95% probability threshold) in tumors. Mean within-subject coefficient of variation (wCV) of relative blood volume (rBV) in normal tissue was 11.78% for Gd-DTPA and 6.64% for P792. The intra-class correlation coefficient (ICC) of rBV in normal tissue was 0.940 for Gd-DTPA and 0.978 for P792. The inter-subject correlation coefficient was 0.092. Calculated K(trans) from DCE-MRI showed comparable reproducibility (mean wCV, 5.13% for Gd-DTPA, 8.06% for P792). ICC of K(trans) showed high intra-subject reproducibility (ICC = 0.999/0.995) and inter-subject heterogeneity (ICC = 0.774). Histograms of K(trans) distributions for three measurements had high degrees of overlap (sum of difference of the normalized histograms <0.01). These results represent homogeneous intra-subject measurement and heterogeneous inter-subject character of biological population, suggesting that perfusion MRI could be an imaging biomarker to monitor or predict response of disease.
authors.affiliation: Biomedical Engineering Graduate Interdisciplinary Program, University of Arizona, Tucson, Arizona, United States of America ; H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
authors.forename: Xiaomeng
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Biomedical Engineering Graduate Interdisciplinary Program, University of Arizona, Tucson, Arizona, United States of America ; Department of Chemistry and Biochemistry, University of Arizona, Tucson, Arizona, United States of America ; University of Arizona Cancer Center, University of Arizona, Tucson, Arizona, United States of America.
authors.forename: Mark D
authors.initials: MD
authors.lastname: Pagel
authors.affiliation: University of Arizona Cancer Center, University of Arizona, Tucson, Arizona, United States of America ; Hematology/Oncology Section, College of Medicine, University of Arizona, Tucson, Arizona, United States of America.
authors.forename: Amanda F
authors.initials: AF
authors.lastname: Baker
authors.affiliation: H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Gillies
mesh_terms: D000818:Animals; D019540:Area Under Curve; D001943:Breast Neoplasms / Q000473:pathology*; D045744:Cell Line, Tumor; D003287:Contrast Media / Q000737:chemistry* / Q000493:pharmacokinetics; D005260:Female; D006801:Humans; D018810:Magnetic Resonance Angiography / Q000379:methods* / Q000592:standards*; D051379:Mice; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media