Diffusion MRI with Semi-Automated Segmentation Can Serve as a Restricted Predictive Biomarker of the Therapeutic Response of Liver Metastasis

Renu M. Stephen, Abhinav K. Jha, Denise J. Roe, Theodore P. Trouard, Jean Philippe Galons, Matthew A. Kupinski, Georgette Frey, Haiyan Cui, Scott Squire, Mark "Marty" Pagel, Jeffrey J. Rodriguez, Robert J. Gillies, Alison T Stopeck

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8 Scopus citations

Abstract

Purpose: To assess the value of semi-automated segmentation applied to diffusion MRI for predicting the therapeutic response of liver metastasis. Methods: Conventional diffusion weighted magnetic resonance imaging (MRI) was performed using b-values of 0, 150, 300 and 450s/mm2 at baseline and days 4, 11 and 39 following initiation of a new chemotherapy regimen in a pilot study with 18 women with 37 liver metastases from primary breast cancer. A semi-automated segmentation approach was used to identify liver metastases. Linear regression analysis was used to assess the relationship between baseline values of the apparent diffusion coefficient (ADC) and change in tumor size by day 39. Results: A semi-automated segmentation scheme was critical for obtaining the most reliable ADC measurements. A statistically significant relationship between baseline ADC values and change in tumor size at day 39 was observed for minimally treated patients with metastatic liver lesions measuring 2-5cm in size (p=0.002), but not for heavily treated patients with the same tumor size range (p=0.29), or for tumors of smaller or larger sizes. ROC analysis identified a baseline threshold ADC value of 1.33μm2/ms as 75% sensitive and 83% specific for identifying non-responding metastases in minimally treated patients with 2-5cm liver lesions. Conclusion: Quantitative imaging can substantially benefit from a semi-automated segmentation scheme. Quantitative diffusion MRI results can be predictive of therapeutic outcome in selected patients with liver metastases, but not for all liver metastases, and therefore should be considered to be a restricted biomarker.

Original languageEnglish (US)
Pages (from-to)1267-1273
Number of pages7
JournalMagnetic Resonance Imaging
Volume33
Issue number10
DOIs
Publication statusPublished - Dec 1 2015

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Keywords

  • Breast cancer
  • Diffusion MRI
  • Liver imaging
  • Restricted biomarker

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering

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