Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles.
about
Association between Ultrasound Features and the 21-Gene Recurrence Score Assays in Patients with Oestrogen Receptor-Positive, HER2-Negative, Invasive Breast Cancer.Integration and comparison of different genomic data for outcome prediction in cancer.Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data setAssociations between gene expression profiles of invasive breast cancer and Breast Imaging Reporting and Data System MRI lexicon.A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores.Breast DCE-MRI Kinetic Heterogeneity Tumor Markers: Preliminary Associations With Neoadjuvant Chemotherapy Response.Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage.Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma.Relating Doses of Contrast Agent Administered to TIC and Semi-Quantitative Parameters on DCE-MRI: Based on a Murine Breast Tumor ModelBreast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay.How Can Advanced Imaging Be Used to Mitigate Potential Breast Cancer Overdiagnosis?Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer.Imaging genomics in cancer research: limitations and promisesMR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays.DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic.Predictive radiogenomics modeling of EGFR mutation status in lung cancerIntravoxel incoherent motion diffusion-weighted MRI during chemoradiation therapy to characterize and monitor treatment response in human papillomavirus head and neck squamous cell carcinoma.MR and mammographic imaging features of HER2-positive breast cancers according to hormone receptor status: a retrospective comparative study.Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma.Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer.Breast cancer molecular subtype classifier that incorporates MRI featuresRadiogenomics of lower-grade glioma: algorithmically-assessed tumor shape is associated with tumor genomic subtypes and patient outcomes in a multi-institutional study with The Cancer Genome Atlas data.Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapyIdentifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation.Diffusion-weighted MRI characteristics associated with prognostic pathological factors and recurrence risk in invasive ER+/HER2- breast cancers.Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.Background, current role, and potential applications of radiogenomics.Radiomics and radiogenomics for precision radiotherapy.Apparent diffusion coefficient in estrogen receptor-positive and lymph node-negative invasive breast cancers at 3.0T DW-MRI: A potential predictor for an oncotype Dx test recurrence score.MRI features predictive of negative surgical margins in patients with HER2 overexpressing breast cancer undergoing breast conservation.A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.Interobserver variability in identification of breast tumors in MRI and its implications for prognostic biomarkers and radiogenomics.Breast MRI radiogenomics: Current status and research implications.Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study.Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis.Effects of MRI scanner parameters on breast cancer radiomicsMagnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer
P2860
Q30378787-683E3E7A-0FEF-42AF-AC41-017B6FA66C0BQ31013326-8517F89E-4DA5-4220-BAF6-78F637590845Q31142731-1C2F92F8-F9A4-4A0D-99A5-593B25F08E0BQ33899089-C12C2DA1-181B-4BC3-A072-B43DA83A3CBCQ34514621-55BC5B22-EF7B-449F-B04F-BAB77AE5BCC8Q35804283-9900BFF7-0F5B-4A3D-9ED1-1BB2CB5C5251Q35855936-9FFE7ED1-0B04-40C0-945C-96F3B3F7C998Q35861706-CA5C77CB-7BA9-4121-A6C9-96A56C4E3F65Q35931492-AD6045CE-550A-4F9A-A8EE-C424E8B3C5A6Q36668293-F535E755-E358-4198-9C84-6684DDF46B9AQ36902060-C9CC9619-0245-4FAE-8ECF-175BC26E94CCQ37119479-2148C70B-96E8-4536-8BD1-1E16FE360557Q37176568-80A139F0-36CD-46A7-AA70-57E1F9B1BB16Q37348196-46558C0D-468F-46B2-A5FF-79958A6804F1Q37368258-DC1AFA86-F985-4BC3-A568-7C636F9271D5Q37615306-0DA81087-9E9F-4775-A4A2-3EA0FD4EE808Q37717953-A86B8B12-6535-42A8-A005-864F29B95C63Q38409734-596CEF9F-3DAC-4E9A-A26B-D5FCE41FD2E0Q38637824-A7595F14-D83B-425E-9F83-98A8F6049828Q38679084-09D7848C-7CBC-4231-8282-CCA38C409861Q38693206-FFE1A153-35B5-49BB-BD69-753DB4873068Q38805727-80B3B984-A96D-4785-B40B-A686EDE7F591Q38808843-C28C3B89-8041-4110-8D20-5D809C96E2F3Q42505424-EE688F99-A392-4A26-A8C7-F049C392CC52Q47409196-81EAC954-8D0F-4879-836E-1A60A589AFB7Q47562329-1E7DF600-074D-4A36-9925-EBD1940E7C1AQ47669653-F07D39ED-667F-4988-A34D-44A20285624EQ47701839-F767CC6D-E607-44AE-8EB4-CAA350FAC7CDQ48236804-86A26DC8-88A0-4232-8B72-60F2948A4DC7Q48266960-C50B762E-AA7D-4E64-9F79-07847E4B071DQ50089374-98CC3590-244B-4647-BEAA-4CA208C32093Q50599911-52301A63-1EFD-4373-AFE9-E7A5DA33F01CQ50756326-8212818E-AF16-4E7C-AA98-8889CC0587A9Q52622002-8425CC54-1C6E-4B07-85E5-CB2A9FFA724EQ52647855-E2138378-CF5D-4860-8C60-16015CFA5603Q54948216-978ECEC1-ED98-4BA5-81A5-0987DDB92BE8Q57498713-C5644EBD-7F1B-416E-9607-6A10AB387808Q58768185-18140AB0-61BF-44AF-A0FC-3A56DABB926B
P2860
Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
2014年论文
@zh
2014年论文
@zh-cn
name
Identification of intrinsic im ...... with gene expression profiles.
@ast
Identification of intrinsic im ...... with gene expression profiles.
@en
type
label
Identification of intrinsic im ...... with gene expression profiles.
@ast
Identification of intrinsic im ...... with gene expression profiles.
@en
prefLabel
Identification of intrinsic im ...... with gene expression profiles.
@ast
Identification of intrinsic im ...... with gene expression profiles.
@en
P2093
P2860
P356
P1433
P1476
Identification of intrinsic im ...... with gene expression profiles.
@en
P2093
Ahmed Bilal Ashraf
Carolyn Mies
Dania Daye
Despina Kontos
Mark Rosen
Michael Feldman
Sara Gavenonis
P2860
P304
P356
10.1148/RADIOL.14131375
P407
P577
2014-04-04T00:00:00Z