A Bayesian hierarchical model for DCE-MRI to evaluate treatment response in a phase II study in advanced squamous cell carcinoma of the head and neck

Abstract

Though the study contained a small number of subjects and no significant difference was found, the Bayesian hierarchical model provided estimates of variability from known sources in the study and confidence intervals for all estimated parameters. We believe the BHM provides a straightforward and thorough interrogation of the imaging data at the level of voxels, patients or sites in this multicenter clinical study.

Difusion-Weighted MRI: from Brownian Motion to Head and Neck Tumor Characterization

“…These imaging biomarkers may help in stratifying patients into those who would benefit from chemo-radiation therapy from those who would not. DWI studies of HNSCC have suggested that ADC can be used as a potential marker for prediction of treatment response and long-term survival [28,32,34]. These results are consistent with the hypothesis that a high pretreatment ADC value may be indicative of micronecrosis and, consequently, of hypoxia-mediated increased resistance to treatment and poor prognosis in these patients [35].…”

Mixed‐effects modeling of clinical DCE‐MRI data: Application to colorectal liver metastases treated with bevacizumab

“…A limitation of our modeling approach is that, for each patient, lesion, and DCE‐MRI visit, the information from all voxels within the tumor is summarized by one number (median K trans or median K trans · EnF = K EnF) which is then treated as a data point. More sophisticated approaches are being developed to model all voxels in all lesions of all patients in a study simultaneously but have not yet been extended to describe the time course of a DCE‐MRI response over repeated examinations.…”

Neuroconductor: an R platform for medical imaging analysis

“…In addition, some of the analysis packages have already been applied below the neck. For example, the dcemriS4 package provides estimates for the key parameters in T1w dynamic contrast-enhanced MRI (DCE-MRI) experiments for perfusion imaging commonly used to assess tissue in cancer or from inflammatory processes; such as the breast or neck (Schmid and others, 2006;Whitcher and others, 2011a). The oro.pet package provides estimates of standard uptake values (SUVs) in PET experiments, where anatomical coverage may vary from the whole body (to assess the primary cancer and/or metastatic disease) to specific anatomical regions, such as the breast, liver, or prostate (Wahl and others, 2009).…”