Literature DB >> 29178616

Diffusion-weighted MRI characteristics associated with prognostic pathological factors and recurrence risk in invasive ER+/HER2- breast cancers.

Nita Amornsiripanitch1, Vicky T Nguyen1, Habib Rahbar1, Daniel S Hippe1, Vijayakrishna K Gadi2, Mara H Rendi3, Savannah C Partridge1.   

Abstract

BACKGROUND: Hormone receptor-positive breast cancer is the most common subtype; better tools to identify which patients in this group would derive clear benefit from chemotherapy are needed.
PURPOSE: To evaluate the prognostic potential of diffusion-weighted MRI (DWI) by investigating associations with pathologic biomarkers and a genomic assay for 10-year recurrence risk. STUDY TYPE: Retrospective.
SUBJECTS: In all, 107 consecutive patients (from 2/2010 to 1/2013) with estrogen receptor (ER)-positive/HER2neu-negative invasive breast cancer who had the 21-gene recurrence score (RS) test (Oncotype DX, Genomic Health). FIELD STRENGTH/SEQUENCE: Each subject underwent presurgical 3T breast MRI, which included DWI (b = 0, 800 s/mm2 ). ASSESSMENT: Apparent diffusion coefficient (ADC) and contrast-to-noise ratio (CNR) were measured for each lesion by a fifth year radiology resident. Pathological markers (Nottingham histologic grade, Ki-67, RS) were determined from pathology reports. Medical records were reviewed to assess recurrence-free survival. STATISTICAL TESTS: RS was stratified into low (<18), moderate (18-30), and high (>30)-risk groups. Associations of DWI characteristics with pathologic biomarkers were evaluated by binary or ordinal logistic regression, as appropriate, with adjustment for multiple comparisons. Post-hoc comparisons between specific groups were also performed.
RESULTS: ADCmean (odds ratio [OR] = 0.61 per 1 standard deviation [SD] increase, adj. P = 0.044) and CNR (OR = 1.76 per 1-SD increase, adj. P = 0.026) were significantly associated with increasing tumor grade. DWI CNR was also significantly associated with a high (Ki-67 ≥14%) proliferation rate (OR = 2.55 per 1-SD increase, adj. P = 0.026). While there were no statistically significant linear associations in ADC (adj. P = 0.80-0.85) and CNR (adj. P = 0.56) across all three RS groups by ordinal logistic regression, post-hoc analyses suggested that high RS lesions exhibited lower ADCmean (P = 0.037) and ADCmax (P = 0.004) values and higher CNR (P = 0.008) compared to lesions with a low or moderate RS. DATA
CONCLUSION: DWI characteristics correlated with tumor grade, proliferation index, and RS, and may potentially help to identify those with highest recurrence risk and most potential benefit from chemotherapy. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage 3 J. Magn. Reson. Imaging 2017.
© 2017 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  Oncotype DX 21-gene recurrence score; adjuvant chemotherapy; breast cancer; diffusion-weighted imaging (DWI); prognostic biomarker

Mesh:

Substances:

Year:  2017        PMID: 29178616      PMCID: PMC5971126          DOI: 10.1002/jmri.25909

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  35 in total

1.  Diffusion-weighted imaging in breast cancer: relationship between apparent diffusion coefficient and tumour aggressiveness.

Authors:  M Costantini; P Belli; P Rinaldi; E Bufi; G Giardina; G Franceschini; G Petrone; L Bonomo
Journal:  Clin Radiol       Date:  2010-09-24       Impact factor: 2.350

2.  Diffusion-weighted MRI: association between patient characteristics and apparent diffusion coefficients of normal breast fibroglandular tissue at 3 T.

Authors:  Elizabeth S McDonald; Jennifer G Schopp; Sue Peacock; Wendy B DeMartini; Wendy D DeMartini; Habib Rahbar; Constance D Lehman; Savannah C Partridge
Journal:  AJR Am J Roentgenol       Date:  2014-05       Impact factor: 3.959

3.  Histogram analysis of apparent diffusion coefficient at 3.0t: Correlation with prognostic factors and subtypes of invasive ductal carcinoma.

Authors:  Eun Jeong Kim; Sung Hun Kim; Ga Eun Park; Bong Joo Kang; Byung Joo Song; Yun Ju Kim; Dongeon Lee; Hyunsoo Ahn; Inah Kim; Yo Han Son; Robert Grimm
Journal:  J Magn Reson Imaging       Date:  2015-04-27       Impact factor: 4.813

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

Authors:  Elizabeth J Sutton; Jung Hun Oh; Brittany Z Dashevsky; Harini Veeraraghavan; Aditya P Apte; Sunitha B Thakur; Joseph O Deasy; Elizabeth A Morris
Journal:  J Magn Reson Imaging       Date:  2015-04-07       Impact factor: 4.813

5.  Correlation of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer.

Authors:  S Y Choi; Y-W Chang; H J Park; H J Kim; S S Hong; D Y Seo
Journal:  Br J Radiol       Date:  2011-11-29       Impact factor: 3.039

6.  Diffusion-Weighted Breast Magnetic Resonance Imaging: A Semiautomated Voxel Selection Technique Improves Interreader Reproducibility of Apparent Diffusion Coefficient Measurements.

Authors:  Habib Rahbar; Brenda F Kurland; Matthew L Olson; Averi E Kitsch; John R Scheel; Xiaoyu Chai; Joshua Usoro; Constance D Lehman; Savannah C Partridge
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Review 7.  American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer.

Authors:  Lyndsay Harris; Herbert Fritsche; Robert Mennel; Larry Norton; Peter Ravdin; Sheila Taube; Mark R Somerfield; Daniel F Hayes; Robert C Bast
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8.  Prediction of Low versus High Recurrence Scores in Estrogen Receptor-Positive, Lymph Node-Negative Invasive Breast Cancer on the Basis of Radiologic-Pathologic Features: Comparison with Oncotype DX Test Recurrence Scores.

Authors:  Vandana Dialani; Shantanu Gaur; Tejas S Mehta; Shambhavi Venkataraman; Valerie Fein-Zachary; Jordana Phillips; Alexander Brook; Priscilla J Slanetz
Journal:  Radiology       Date:  2016-03-03       Impact factor: 11.105

9.  Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study.

Authors:  Mitch Dowsett; Jack Cuzick; Christopher Wale; John Forbes; Elizabeth A Mallon; Janine Salter; Emma Quinn; Anita Dunbier; Michael Baum; Aman Buzdar; Anthony Howell; Roberto Bugarini; Frederick L Baehner; Steven Shak
Journal:  J Clin Oncol       Date:  2010-03-08       Impact factor: 44.544

10.  A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores.

Authors:  Tao Wan; B Nicolas Bloch; Donna Plecha; CheryI L Thompson; Hannah Gilmore; Carl Jaffe; Lyndsay Harris; Anant Madabhushi
Journal:  Sci Rep       Date:  2016-02-18       Impact factor: 4.379

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  17 in total

1.  Role of DCE-MR in predicting breast cancer subtypes.

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Journal:  Radiol Med       Date:  2018-06-05       Impact factor: 3.469

2.  Quantitative parameters of MRI and 18F-FDG PET/CT in the prediction of breast cancer prognosis and molecular type: an original study.

Authors:  Pavel Borisovich Gelezhe; Ivan Andreevich Blokhin; Damir Ildarovich Marapov; Sergey Pavlovich Morozov
Journal:  Am J Nucl Med Mol Imaging       Date:  2020-12-15

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.

Authors:  Ming Fan; Peng Zhang; Yue Wang; Weijun Peng; Shiwei Wang; Xin Gao; Maosheng Xu; Lihua Li
Journal:  Eur Radiol       Date:  2019-01-07       Impact factor: 5.315

4.  Diffusion-weighted MRI of estrogen receptor-positive, HER2-negative, node-negative breast cancer: association between intratumoral heterogeneity and recurrence risk.

Authors:  Jin You Kim; Jin Joo Kim; Lee Hwangbo; Ji Won Lee; Nam Kyung Lee; Kyung Jin Nam; Ki Seok Choo; Taewoo Kang; Heeseung Park; Yohan Son; Robert Grimm
Journal:  Eur Radiol       Date:  2019-08-05       Impact factor: 5.315

5.  Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis.

Authors:  Alexey Surov; Paola Clauser; Yun-Woo Chang; Lihua Li; Laura Martincich; Savannah C Partridge; Jin You Kim; Hans Jonas Meyer; Andreas Wienke
Journal:  Breast Cancer Res       Date:  2018-06-19       Impact factor: 6.466

6.  Apparent diffusion coefficient cannot predict molecular subtype and lymph node metastases in invasive breast cancer: a multicenter analysis.

Authors:  Alexey Surov; Yun-Woo Chang; Lihua Li; Laura Martincich; Savannah C Partridge; Jin You Kim; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-11-05       Impact factor: 4.430

7.  Predicting the expression level of Ki-67 in breast cancer using multi-modal ultrasound parameters.

Authors:  Chen Cheng; Hongyan Zhao; Wei Tian; Chunhong Hu; Haitao Zhao
Journal:  BMC Med Imaging       Date:  2021-10-16       Impact factor: 1.930

Review 8.  Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends.

Authors:  Mami Iima
Journal:  Magn Reson Med Sci       Date:  2020-06-15       Impact factor: 2.471

Review 9.  Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis.

Authors:  Ioannis Tsougos; Alexandros Vamvakas; Constantin Kappas; Ioannis Fezoulidis; Katerina Vassiou
Journal:  Comput Math Methods Med       Date:  2018-09-23       Impact factor: 2.238

Review 10.  Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role.

Authors:  Julia Camps-Herrero
Journal:  BJR Open       Date:  2019-03-08
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