Voxelwise analysis of simultaneously acquired and spatially correlated 18 F-fluorodeoxyglucose (FDG)-PET and intravoxel incoherent motion metrics in breast cancer.
Publication Type | Academic Article |
Authors | Ostenson J, Pujara A, Mikheev A, Moy L, Kim S, Melsaether A, Jhaveri K, Adams S, Faul D, Glielmi C, Geppert C, Feiweier T, Jackson K, Cho G, Boada F, Sigmund E |
Journal | Magn Reson Med |
Volume | 78 |
Issue | 3 |
Pagination | 1147-1156 |
Date Published | 10/25/2016 |
ISSN | 1522-2594 |
Keywords | Breast, Breast Neoplasms, Diffusion Magnetic Resonance Imaging, Image Interpretation, Computer-Assisted, Positron-Emission Tomography |
Abstract | PURPOSE: Diffusion-weighted imaging (DWI) and 18 F-fluorodeoxyglucose-positron emission tomography (18 F-FDG-PET) independently correlate with malignancy in breast cancer, but the relationship between their structural and metabolic metrics is not completely understood. This study spatially correlates diffusion, perfusion, and glucose avidity in breast cancer with simultaneous PET/MR imaging and compares correlations with clinical prognostics. METHODS: In this Health Insurance Portability and Accountability Act-compliant prospective study, with written informed consent and approval of the institutional review board and using simultaneously acquired FDG-PET and DWI, tissue diffusion (Dt ), and perfusion fraction (fp ) from intravoxel incoherent motion (IVIM) analysis were registered to FDG-PET within 14 locally advanced breast cancers. Lesions were analyzed using 2D histograms and correlation coefficients between Dt , fp , and standardized uptake value (SUV). Correlations were compared with prognostics from biopsy, metastatic burden from whole-body PET, and treatment history. RESULTS: SUV||Dt correlation coefficient significantly distinguished treated (0.11 ± 0.24) from nontreated (-0.33 ± 0.26) patients (P = 0.005). SUV||fp correlations were on average negative for the whole cohort (-0.17 ± 0.13). CONCLUSION: Simultaneously acquired and registered FDG-PET/DWI allowed quantifiable descriptions of breast cancer microenvironments that may provide a framework for monitoring and predicting response to treatment. Magn Reson Med 78:1147-1156, 2017. © 2016 International Society for Magnetic Resonance in Medicine. |
DOI | 10.1002/mrm.26505 |
PubMed ID | 27779790 |
PubMed Central ID | PMC5405014 |