Literature DB >> 28708462

Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer.

Jia Wu1, Bailiang Li1, Xiaoli Sun1, Guohong Cao1, Daniel L Rubin1, Sandy Napel1, Debra M Ikeda1, Allison W Kurian1, Ruijiang Li1.   

Abstract

Purpose To identify the molecular basis of quantitative imaging characteristics of tumor-adjacent parenchyma at dynamic contrast material-enhanced magnetic resonance (MR) imaging and to evaluate their prognostic value in breast cancer. Materials and Methods In this institutional review board-approved, HIPAA-compliant study, 10 quantitative imaging features depicting tumor-adjacent parenchymal enhancement patterns were extracted and screened for prognostic features in a discovery cohort of 60 patients. By using data from The Cancer Genome Atlas (TCGA), a radiogenomic map for the tumor-adjacent parenchymal tissue was created and molecular pathways associated with prognostic parenchymal imaging features were identified. Furthermore, a multigene signature of the parenchymal imaging feature was built in a training cohort (n = 126), and its prognostic relevance was evaluated in two independent cohorts (n = 879 and 159). Results One image feature measuring heterogeneity (ie, information measure of correlation) was significantly associated with prognosis (false-discovery rate < 0.1), and at a cutoff of 0.57 stratified patients into two groups with different recurrence-free survival rates (log-rank P = .024). The tumor necrosis factor signaling pathway was identified as the top enriched pathway (hypergeometric P < .0001) among genes associated with the image feature. A 73-gene signature based on the tumor profiles in TCGA achieved good association with the tumor-adjacent parenchymal image feature (R2 = 0.873), which stratified patients into groups regarding recurrence-free survival (log-rank P = .029) and overall survival (log-rank P = .042) in an independent TCGA cohort. The prognostic value was confirmed in another independent cohort (Gene Expression Omnibus GSE 1456), with log-rank P = .00058 for recurrence-free survival and log-rank P = .0026 for overall survival. Conclusion Heterogeneous enhancement patterns of tumor-adjacent parenchyma at MR imaging are associated with the tumor necrosis signaling pathway and poor survival in breast cancer. © RSNA, 2017 Online supplemental material is available for this article.

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Year:  2017        PMID: 28708462      PMCID: PMC5673053          DOI: 10.1148/radiol.2017162823

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  69 in total

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4.  Macrophage-induced angiogenesis is mediated by tumour necrosis factor-alpha.

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5.  Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay.

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9.  Enhancing area surrounding breast carcinoma on MR mammography: comparison with pathological examination.

Authors:  M Van Goethem; K Schelfout; E Kersschot; C Colpaert; I Verslegers; I Biltjes; W A Tjalma; J Weyler; A De Schepper
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  38 in total

Review 1.  Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images.

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Journal:  Med Biol Eng Comput       Date:  2018-01-02       Impact factor: 2.602

Review 2.  Clinical role of breast MRI now and going forward.

Authors:  D Leithner; G J Wengert; T H Helbich; S Thakur; R E Ochoa-Albiztegui; E A Morris; K Pinker
Journal:  Clin Radiol       Date:  2017-12-09       Impact factor: 2.350

3.  Radiomic analysis of imaging heterogeneity in tumours and the surrounding parenchyma based on unsupervised decomposition of DCE-MRI for predicting molecular subtypes of breast cancer.

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Review 4.  Machine learning in breast MRI.

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Authors:  Geraldine J Liao; Leah C Henze Bancroft; Roberta M Strigel; Rhea D Chitalia; Despina Kontos; Linda Moy; Savannah C Partridge; Habib Rahbar
Journal:  J Magn Reson Imaging       Date:  2019-04-19       Impact factor: 4.813

6.  Tumor stiffness measured by shear-wave elastography: association with disease-free survival in women with early-stage breast cancer.

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7.  High-background parenchymal enhancement in the contralateral breast is an imaging biomarker for favorable prognosis in patients with triple-negative breast cancer treated with chemotherapy.

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8.  Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy.

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Journal:  Radiology       Date:  2018-05-01       Impact factor: 11.105

Review 9.  The Biological Meaning of Radiomic Features.

Authors:  Michal R Tomaszewski; Robert J Gillies
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10.  Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment.

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Journal:  Sci Rep       Date:  2021-07-21       Impact factor: 4.379

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