Longitudinal, intermodality registration of quantitative breast PET and MRI data acquired before and during neoadjuvant chemotherapy: Preliminary results. Issue 5 (18th April 2014)

• Record Type: Journal Article
• Authors: Atuegwu, Nkiruka C.; Li, Xia; Arlinghaus, Lori R.; Abramson, Richard G.; Williams, Jason M.; Chakravarthy, A. Bapsi; Abramson, Vandana G.; Yankeelov, Thomas E.
• Is Part Of: Medical physics. Volume 41:Issue 5(2014)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2014-04-18
• Subjects: Positron emission tomography (PET) -- Clinical applications -- Cancer -- Registration; biomedical MRI -- cancer -- data acquisition -- image registration -- medical image processing -- positron emission tomography -- radiation therapy -- tumours; registration -- DCE‐MRI -- FDG‐PET -- breast cancer -- prone PET -- PET/MRI -- longitudinal registration -- treatment response; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Radiation therapy -- Biological material, e.g. blood, urine; Haemocytometers -- Data acquisition and logging -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Scintigraphy -- Measuring half‐life of a radioactive substance; Cancer -- Medical imaging -- Positron emission tomography -- Computed tomography -- Magnetic resonance imaging -- Medical magnetic resonance imaging -- Image registration -- Data analysis -- Medical image spatial resolution -- Data sets; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4870966
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : The authors propose a method whereby serially acquired DCE‐MRI, DW‐MRI, and FDG‐PET breast data sets can be spatially and temporally coregistered to enable the comparison of changes in parameter maps at the voxel level. Methods: : First, the authors aligned the PET and MR images at each time point rigidly and nonrigidly. To register the MR images longitudinally, the authors extended a nonrigid registration algorithm by including a tumor volume‐preserving constraint in the cost function. After the PET images were aligned to the MR images at each time point, the authors then used the transformation obtained from the longitudinal registration of the MRI volumes to register the PET images longitudinally. The authors tested this approach on ten breast cancer patients by calculating a modified Dice similarity of tumor size between the PET and MR images as well as the bending energy and changes in the tumor volume after the application of the registration algorithm. Results: : The median of the modified Dice in the registered PET and DCE‐MRI data was 0.92. For the longitudinal registration, the median tumor volume change was −0.03% for the constrained algorithm, compared to −32.16% for the unconstrained registration algorithms ( p = 8 × 10 −6 ). The medians of the bending energy were 0.0092 and 0.0001 for the unconstrained and constrained algorithms, respectively ( p = 2.84 × 10 −7 ). Conclusions: : The results indicate that the proposed method can accurately spatially align DCE‐MRI, DW‐MRI, and FDG‐PET breast images acquired at different time points during therapy while preventing the tumor from being substantially distorted or compressed.