Magnetic Resonance Imaging for Therapy Selection in Breast Cancer

  • AMT Schmitz

Research output: ThesisDoctoral thesis 1 (Research UU / Graduation UU)

Abstract

More accurate characterization of breast cancer is desirable prior to therapy. MR imaging may ultimately help to resolve the discordant preoperative information from conventional diagnostic workup of breast cancer. Breast MRI has shown potential to provide information on tumor biology, which is related to patient prognosis. The presence of rim enhancement on DCE-MRI has shown strong association with inferior long-term outcome in patients with triple-negative breast cancer, and may serve as a predictive biomarker for more individualized therapy. For imaging of tumor response to NAC, combining DCE-MRI with PET/CT may result in optimal response monitoring of ER-positive tumors. However, for HER2-positive and triple-negative tumors, DCE-MRI was found optimal. In a multiparametric imaging setting, combining DCE-MRI with DWI and 31P-MRS at 7T was shown clinically feasible to visualize tumor biomarkers. Also, associations were found between ADC and tumor grade, and between 31P-MRS and mitotic count of invasive breast cancers. Concerning therapy selection in early-breast cancer, in the preoperative setting, a positive indication for systemic therapy is in high concordance with a positive postoperative indication. Hence, based on conventional diagnostic workup consisting of conventional imaging, tumor biopsy, and assessment of lymph nodes with ultrasound and fine needle aspiration of suspected nodes, an indication for NAC could be extended to patients with early breast cancers showing a positive preoperative indication for systemic therapy. For a negative preoperative indication, MRI may play a role, as DCE-MRI and 31P-MRS were seen to raise confidence towards a negative postoperative indication. Potentially, in future perspective, after validation of our results, these patients may be selected for a less invasive treatment.
Original languageEnglish
Awarding Institution
  • University Medical Center (UMC) Utrecht
Supervisors/Advisors
  • Viergever, Max, Primary supervisor
  • Mali, WPTM, Supervisor
  • Gilhuijs, Kenneth, Co-supervisor
  • Veldhuis, Wouter, Co-supervisor
Award date12 Jan 2016
Publisher
Print ISBNs978-90-8219-6818
Publication statusPublished - 12 Jan 2016

Keywords

  • Breast Cancer
  • Therapy Selection
  • Magnetic Resonance Imaging
  • MRI
  • 7 Tesla

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