| First Author | Schmitz J | Year | 2016 |
| Journal | Cancer Res | Volume | 76 |
| Issue | 18 | Pages | 5512-22 |
| PubMed ID | 27466286 | Mgi Jnum | J:235133 |
| Mgi Id | MGI:5792974 | Doi | 10.1158/0008-5472.CAN-15-0642 |
| Citation | Schmitz J, et al. (2016) Decoding Intratumoral Heterogeneity of Breast Cancer by Multiparametric In Vivo Imaging: A Translational Study. Cancer Res 76(18):5512-22 |
| abstractText | Differential diagnosis and therapy of heterogeneous breast tumors poses a major clinical challenge. To address the need for a comprehensive, noninvasive strategy to define the molecular and functional profiles of tumors in vivo, we investigated a novel combination of metabolic PET and diffusion-weighted (DW)-MRI in the polyoma virus middle T antigen transgenic mouse model of breast cancer. The implementation of a voxelwise analysis for the clustering of intra- and intertumoral heterogeneity in this model resulted in a multiparametric profile based on [(18)F]Fluorodeoxyglucose ([(18)F]FDG)-PET and DW-MRI, which identified three distinct tumor phenotypes in vivo, including solid acinar, and solid nodular malignancies as well as cystic hyperplasia. To evaluate the feasibility of this approach for clinical use, we examined estrogen receptor-positive and progesterone receptor-positive breast tumors from five patient cases using DW-MRI and [(18)F]FDG-PET in a simultaneous PET/MRI system. The postsurgical in vivo PET/MRI data were correlated to whole-slide histology using the latter traditional diagnostic standard to define phenotype. By this approach, we showed how molecular, structural (microscopic, anatomic), and functional information could be simultaneously obtained noninvasively to identify precancerous and malignant subtypes within heterogeneous tumors. Combined with an automatized analysis, our results suggest that multiparametric molecular and functional imaging may be capable of providing comprehensive tumor profiling for noninvasive cancer diagnostics. Cancer Res; 76(18); 5512-22. (c)2016 AACR. |
