Analyzing Breast Tumor Response To Neoadjuvant Therapy By Pk Models Of Dynamic-contrast Enhanced Mr
Date of Award
January 2012
Document Type
Open Access Thesis
Degree Name
Medical Doctor (MD)
Department
Medicine
First Advisor
Daniel M. Cornfeld
Subject Area(s)
Medical imaging and radiology, Medicine
Abstract
Introduction: Pharmacokinetic modeling of contrast uptake by Dynamic-‐Contrast Enhanced Magnetic Resonance Imaging studies has shown potential to predict the pathologic response to neoadjuvant therapy in breast cancer patients via several small studies. We will attempt to prospectively validate the performance of several previously published criteria in women undergoing neoadjuvant therapy with bevacizumab or trastuzumab.
Methods: 11 patients underwent dynamic contrast enhanced magnetic resonance imaging both before and after receiving one cycle of trastuzumab or bevacizumab neoadjuvant chemotherapy for a primary breast lesion of greater than two centimeters. By abstracting pharmacokinetic parameters (Ktrans) from each study, predictions for therapeutic response based on previously published criteria (Ah–See and Yu utilize a threshold for percentage change in median Ktrans; Padhani, a percentage change in Ktrans range) were compared with the response by pathology acquired after completion of neoadjuvant therapy.
Results: 7 patients were able to successfully complete imaging at the two requisite time points. All utilized criteria correctly identified 5/5 non–responders; the Ah–See and Padhani criteria were able to identify 1/2 positive responders; and the Yu criterion identified 0/2 positive responders.
Discussion: The efficacy of the Ah–See and Padhani criteria identify responders and non–responders equally well. Due to the Padhani criterion's susceptibility to noise, however, it is likely that Ah–See would outperform Padhani on a larger cohort.
Recommended Citation
Lidstrom, Matthew, "Analyzing Breast Tumor Response To Neoadjuvant Therapy By Pk Models Of Dynamic-contrast Enhanced Mr" (2012). Yale Medicine Thesis Digital Library. 1739.
https://elischolar.library.yale.edu/ymtdl/1739
This Article is Open Access
Comments
This is an Open Access Thesis.