title: Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data.
abstract: Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.
authors.affiliation: Imaging Science and Biomedical Engineering, School of Cancer and Imaging Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: G A
authors.initials: GA
authors.lastname: Buonaccorsi
authors.forename: C J
authors.initials: CJ
authors.lastname: Rose
authors.forename: J P B
authors.initials: JP
authors.lastname: O'Connor
authors.forename: C
authors.initials: C
authors.lastname: Roberts
authors.forename: Y
authors.initials: Y
authors.lastname: Watson
authors.forename: A
authors.initials: A
authors.lastname: Jackson
authors.forename: G C
authors.initials: GC
authors.lastname: Jayson
authors.forename: G J M
authors.initials: GJ
authors.lastname: Parker
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000627:therapeutic use; D016477:Artifacts; D003287:Contrast Media; D019786:Gadolinium DTPA; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008113:Liver Neoplasms / Q000188:drug therapy / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D016896:Treatment Outcome
chemical_list: D000970:Antineoplastic Agents; D003287:Contrast Media; C064925:gadodiamide; D019786:Gadolinium DTPA