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Chen K, Yu C, Pan J, Xu Y, Luo Y, Yang T, Yang X, Xie L, Zhang J, Zhuo R. Prediction of the Nottingham prognostic index and molecular subtypes of breast cancer through multimodal magnetic resonance imaging. Magn Reson Imaging 2024; 108:168-175. [PMID: 38408689 DOI: 10.1016/j.mri.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 02/19/2024] [Accepted: 02/21/2024] [Indexed: 02/28/2024]
Abstract
PURPOSE To explore the ability of intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and background parenchyma enhancement (BPE) to predict the Nottingham prognostic index (NPI) and molecular subtypes of breast cancer (BC). MATERIALS AND METHODS In this study, 93 patients with BC were included, and they all underwent DKI, IVIM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examinations. The corresponding mean kurtosis value (MK), pure diffusion (MD), perfusion fraction (f), pseudo diffusion coefficient (D*), true diffusion coefficient (D), and BPE were measured. We used logistic regression analysis to investigate the relevance between the NPI, molecular subtypes and variables. The diagnostic efficacy was analyzed using receiver operating characteristic curves (ROC). RESULTS The MD and D values of the high-level NPI group were significantly lower than those of the low-level NPI group (p < 0.01), and the f value of the high-level NPI group was obviously higher than that of low-level NPI group (p < 0.001). The area under curve (AUC) of the combined model (f + D) was 0.824. Comparing with non-Luminal subtypes, the Luminal subtypes showed obviously lower MK, f and D*, and the AUC of the combined model (MK + f + D*) was 0.785. In comparison to other subtypes, the MK and D* values of triple-negative subtype were higher than other subtypes, and the combined model (MK + D*) represented an AUC of 0.865. CONCLUSION The quantitative parameters of DKI and IVIM have vital value in predicting the NPI and molecular subtypes of BC, while BPE could not provide additional information. Besides, these combined models can obviously improve the prediction performance.
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Affiliation(s)
- Kewei Chen
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China; Department of Radiology, Women and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China
| | - Chengxin Yu
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China.
| | - Junlong Pan
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Yaqia Xu
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Yuqing Luo
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Ting Yang
- Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China
| | - Xiaoling Yang
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Lisi Xie
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Jing Zhang
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Renfeng Zhuo
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
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Wang H, van der Velden BHM, Verburg E, Bakker MF, Pijnappel RM, Veldhuis WB, van Gils CH, Gilhuijs KGA. Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts. Radiology 2023; 308:e222841. [PMID: 37552061 DOI: 10.1148/radiol.222841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. MRI was performed in eight hospitals between December 2011 and January 2016. After segmentation of fibroglandular tissue, quantitative features (including volumetric density, volumetric morphology, and enhancement characteristics) of the parenchyma were extracted from baseline MRI scans. Principal component analysis was used to identify parenchymal measures with the greatest variance. Multivariable Cox proportional hazards regression was applied to assess the association between breast cancer occurrence and quantitative parenchymal features, followed by stratification of significant features into tertiles. Results A total of 4553 women (mean age, 55.7 years ± 6 [SD]) with extremely dense breasts were included; of these women, 122 (3%) were diagnosed with breast cancer. Five principal components representing 96% of the variance were identified, and the component explaining the greatest independent variance (42%) consisted of MRI features relating to volume of enhancing parenchyma. Multivariable analysis showed that volume of enhancing parenchyma was associated with breast cancer occurrence (hazard ratio [HR], 1.09; 95% CI: 1.01, 1.18; P = .02). Additionally, women in the high tertile of volume of enhancing parenchyma showed a breast cancer occurrence twice that of women in the low tertile (HR, 2.09; 95% CI: 1.25, 3.61; P = .005). Conclusion In women with extremely dense breasts, a high volume of enhancing parenchyma on baseline DCE MRI scans was associated with increased occurrence of breast cancer as compared with a low volume of enhancing parenchyma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grimm in this issue.
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Affiliation(s)
- Hui Wang
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Bas H M van der Velden
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Erik Verburg
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Marije F Bakker
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Ruud M Pijnappel
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Wouter B Veldhuis
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Carla H van Gils
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Kenneth G A Gilhuijs
- From the Image Sciences Institute (H.W., B.H.M.v.d.V., E.V., K.G.A.G.), Julius Center for Health Sciences and Primary Care (M.F.B., C.H.v.G.), and Department of Radiology (R.M.P., W.B.V.), University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
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Wang W, Lv S, Xun J, Wang L, Zhao F, Wang J, Zhou Z, Chen Y, Sun Z, Zhu L. Comparison of diffusion kurtosis imaging and dynamic contrast enhanced MRI in prediction of prognostic factors and molecular subtypes in patients with breast cancer. Eur J Radiol 2022; 154:110392. [DOI: 10.1016/j.ejrad.2022.110392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 05/18/2022] [Accepted: 05/31/2022] [Indexed: 11/16/2022]
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Wang W, Zhang X, Zhu L, Chen Y, Dou W, Zhao F, Zhou Z, Sun Z. Prediction of Prognostic Factors and Genotypes in Patients With Breast Cancer Using Multiple Mathematical Models of MR Diffusion Imaging. Front Oncol 2022; 12:825264. [PMID: 35174093 PMCID: PMC8841854 DOI: 10.3389/fonc.2022.825264] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/07/2022] [Indexed: 01/31/2023] Open
Abstract
Purpose To explore the clinical value of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) based on diffusion-weighted MRI (DW-MRI) for predicting genotypes and prognostic factors of breast cancer. Materials and Methods A total of 227 patients with breast cancer confirmed by pathology were reviewed retrospectively. Diffusion-weighted imaging (DWI), IVIM, and DKI were performed in all patients. The corresponding ADC, true diffusion coefficient (D), perfusion-related diffusion coefficient (D*), perfusion fraction (f), mean diffusion rate (MD), and mean kurtosis value (MK) were measured. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curve were used to analyze the diagnostic efficacy in predicting the Nottingham prognostic index (NPI), the expression of antigen Ki-67, and the molecular subtypes of breast cancer. The nomogram of the combined genotype-prediction model was established based on the multivariate logistic regression model results. Results D* and MK values were significantly higher in the high-grade Nottingham group (NPI ≥ 3.4) than the low-grade Nottingham group (NPI < 3.4) (p < 0.01). When D* ≥ 30.95 × 10−3 mm2/s and MK ≥ 0.69, the NPI tended to be high grade (with areas under the curve (AUCs) of 0.712 and 0.647, respectively). The combination of D* and MK demonstrated the highest AUC of 0.734 in grading NPI with sensitivity and accuracy of 71.7% and 77.1%, respectively. Additionally, higher D*, f, and MK and lower ADC and D values were observed in the high Ki-67 than low Ki-67 expression groups (p < 0.05). The AUC of the combined model (D + D* + f + MK) was 0.755, being significantly higher than that of single parameters (Z = 2.770~3.244, p = 0.001~0.006) in distinguishing high from low Ki-67 expression. D* and f values in the Luminal A subtype were significantly lower than in other subtypes (p < 0.05). Luminal B showed decreased D value compared with other subtypes (p < 0.05). The HER-2-positive subtype demonstrated increased ADC values compared with the Luminal B subtype (p < 0.05). Luminal A/B showed significantly lower D, D*, MD, and MK than the non-Luminal subtypes (p < 0.05). The combined model (D + D* + MD + MK) showed an AUC of 0.830 in diagnosing the Luminal and non-Luminal subtypes, which is significantly higher than that of a single parameter (Z = 3.273~4.440, p < 0.01). f ≥ 54.30% [odds ratio (OR) = 1.038, p < 0.001] and MK ≥ 0.68 (OR = 24.745, p = 0.012) were found to be significant predictors of triple-negative subtypes. The combination of f and MK values demonstrated superior diagnostic performance with AUC, sensitivity, specificity, and accuracy of 0.756, 67.5%, 77.5%, and 82.4%, respectively. Moreover, as shown in the calibration curve, strong agreements were observed between nomogram prediction probability and actual findings in the prediction of genotypes (p = 0.22, 0.74). Conclusion DWI, IVIM, and DKI, as MR diffusion imaging techniques with different mathematical models showed potential to identify the prognosis and genotype of breast cancer. In addition, the combination of these three models can improve the diagnostic efficiency and thus may contribute to opting for an appropriate therapeutic approach in clinic treatment.
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Affiliation(s)
- Weiwei Wang
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | - Xindong Zhang
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | - Laimin Zhu
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | - Yueqin Chen
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | | | - Fan Zhao
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | - Zhe Zhou
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
| | - Zhanguo Sun
- Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining, China
- *Correspondence: Zhanguo Sun,
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Bauer E, Levy MS, Domachevsky L, Anaby D, Nissan N. Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review. Clin Imaging 2021; 83:41-50. [PMID: 34953310 DOI: 10.1016/j.clinimag.2021.11.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/29/2021] [Accepted: 11/15/2021] [Indexed: 12/20/2022]
Abstract
Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.
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Affiliation(s)
- Ethan Bauer
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Miri Sklair Levy
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Liran Domachevsky
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Noam Nissan
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel.
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Ragusi MAA, Bismeijer T, van der Velden BHM, Loo CE, Canisius S, Wesseling J, Wessels LFA, Elias SG, Gilhuijs KGA. Contralateral parenchymal enhancement on MRI is associated with tumor proteasome pathway gene expression and overall survival of early ER+/HER2-breast cancer patients. Breast 2021; 60:230-237. [PMID: 34763270 PMCID: PMC8591464 DOI: 10.1016/j.breast.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/26/2021] [Accepted: 11/02/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose To assess whether contralateral parenchymal enhancement (CPE) on MRI is associated with gene expression pathways in ER+/HER2-breast cancer, and if so, whether such pathways are related to survival. Methods Preoperative breast MRIs were analyzed of early ER+/HER2-breast cancer patients eligible for breast-conserving surgery included in a prospective observational cohort study (MARGINS). The contralateral parenchyma was segmented and CPE was calculated as the average of the top-10% delayed enhancement. Total tumor RNA sequencing was performed and gene set enrichment analysis was used to reveal gene expression pathways associated with CPE (N = 226) and related to overall survival (OS) and invasive disease-free survival (IDFS) in multivariable survival analysis. The latter was also done for the METABRIC cohort (N = 1355). Results CPE was most strongly correlated with proteasome pathways (normalized enrichment statistic = 2.04, false discovery rate = .11). Patients with high CPE showed lower tumor proteasome gene expression. Proteasome gene expression had a hazard ratio (HR) of 1.40 (95% CI = 0.89, 2.16; P = .143) for OS in the MARGINS cohort and 1.53 (95% CI = 1.08, 2.14; P = .017) for IDFS, in METABRIC proteasome gene expression had an HR of 1.09 (95% CI = 1.01, 1.18; P = .020) for OS and 1.10 (95% CI = 1.02, 1.18; P = .012) for IDFS. Conclusion CPE was negatively correlated with tumor proteasome gene expression in early ER+/HER2-breast cancer patients. Low tumor proteasome gene expression was associated with improved survival in the METABRIC data. Contralateral parenchymal enhancement on MRI was associated with tumor proteasome gene expression in ER+/HER2-breast cancer. A high contralateral parenchymal enhancement was associated with a low proteasome gene expression in the breast cancer. Low proteasome tumor gene expression was associated with improved survival in an independent patient cohort.
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Affiliation(s)
- Max A A Ragusi
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands; Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands.
| | - Tycho Bismeijer
- Division of Molecular Carcinogenesis - Oncode Institute, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Bas H M van der Velden
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Claudette E Loo
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Sander Canisius
- Division of Molecular Carcinogenesis - Oncode Institute, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Jelle Wesseling
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Lodewyk F A Wessels
- Division of Molecular Carcinogenesis - Oncode Institute, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Mekelweg 5, 2628 CD Delft, the Netherlands
| | - Sjoerd G Elias
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands
| | - Kenneth G A Gilhuijs
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
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Tagde P, Tagde S, Bhattacharya T, Tagde P, Chopra H, Akter R, Kaushik D, Rahman MH. Blockchain and artificial intelligence technology in e-Health. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:52810-52831. [PMID: 34476701 PMCID: PMC8412875 DOI: 10.1007/s11356-021-16223-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 08/24/2021] [Indexed: 05/21/2023]
Abstract
Blockchain and artificial intelligence technologies are novel innovations in healthcare sector. Data on healthcare indices are collected from data published on Web of Sciences and other Google survey from various governing bodies. In this review, we focused on various aspects of blockchain and artificial intelligence and also discussed about integrating both technologies for making a significant difference in healthcare by promoting the implementation of a generalizable analytical technology that can be integrated into a more comprehensive risk management approach. This article has shown the various possibilities of creating reliable artificial intelligence models in e-Health using blockchain, which is an open network for the sharing and authorization of information. Healthcare professionals will have access to the blockchain to display the medical records of the patient, and AI uses a variety of proposed algorithms and decision-making capability, as well as large quantities of data. Thus, by integrating the latest advances of these technologies, the medical system will have improved service efficiency, reduced costs, and democratized healthcare. Blockchain enables the storage of cryptographic records, which AI needs.
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Affiliation(s)
- Priti Tagde
- Bhabha Pharmacy Research Institute, Bhabha University Bhopal, Bhopal M.P, India.
- PRISAL Foundation (Pharmaceutical Royal International Society), New delhi, India.
| | - Sandeep Tagde
- PRISAL Foundation (Pharmaceutical Royal International Society), New delhi, India
| | - Tanima Bhattacharya
- School of Chemistry & Chemical Engineering, Hubei University, Wuhan, China
- Department of Science & Engineering, Novel Global Community Education Foundation, Hebersham, Australia
| | - Pooja Tagde
- Practice of Medicine Department, Govt. Homeopathy College, Bhopal, M.P, India
| | - Hitesh Chopra
- Chitkara College of Pharmacy, Rajpura, Punjab, 140401, India
| | - Rokeya Akter
- Department of Pharmacy, Jagannath University, Sadarghat, Dhaka, 1100, Bangladesh
| | - Deepak Kaushik
- Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
| | - Md Habibur Rahman
- Department of Pharmacy, Southeast University, Banani, Dhaka, 1213, Bangladesh.
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Rella R, Contegiacomo A, Bufi E, Mercogliano S, Belli P, Manfredi R. Background parenchymal enhancement and breast cancer: a review of the emerging evidences about its potential use as imaging biomarker. Br J Radiol 2021; 94:20200630. [PMID: 33035073 DOI: 10.1259/bjr.20200630] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVES To conduct a systematic review of evidences about the relationship between background parenchymal enhancement (BPE) of the contralateral healthy breast and breast cancer: its association with clinicopathological breast cancer characteristics, its potential as predictive and prognostic biomarker and the biological linkage between BPE and breast cancer. METHODS A computerized literature search using PubMed and Google Scholar was performed up to June 2020. Two authors independently conducted search, screening, quality assessment, and extraction of data from the eligible studies. Studies were assessed for quality and risk of bias using the revised Quality Assessment of Diagnostic Accuracy Studies tool. RESULTS Of the 476 articles identified, 22 articles met the inclusion criteria. No significant association was found between BPE and invasiveness, histological cancer type, T- and N-stage, multifocality, lymphatic and vascular invasion and histological tumour grade while the association between BPE and molecular subtypes is still unclear. As predictive biomarker, a greater decrease in BPE during and after neoadjuvant chemotherapy was associated with pathological complete response. Results about the role of BPE as prognostic factor were inconsistent. An association between high BPE and microvessel density, CD34 and VEGF (histological markers of vascularization and angiogenesis) was found. CONCLUSIONS BPE of the contralateral breast is associated with breast cancer in several aspects, therefore it has been proposed as a tool to refine breast cancer decision-making process. ADVANCES IN KNOWLEDGE Additional researches with standardized BPE assessment are needed to translate this emerging biomarker into clinical practice in the era of personalized medicine.
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Affiliation(s)
- Rossella Rella
- UOC di Diagnostica per immagini ed Interventistica Generale, Dipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli 8, 00168 Roma, Italia
| | - Andrea Contegiacomo
- UOC di Diagnostica per immagini ed Interventistica Generale, Dipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli 8, 00168 Roma, Italia
| | - Enida Bufi
- UOC di Diagnostica per immagini ed Interventistica Generale, Dipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli 8, 00168 Roma, Italia
| | - Sara Mercogliano
- Università Cattolica Sacro Cuore, Largo F. Vito 1, 00168 Roma, Italia
| | - Paolo Belli
- UOC di Diagnostica per immagini ed Interventistica Generale, Dipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli 8, 00168 Roma, Italia.,Università Cattolica Sacro Cuore, Largo F. Vito 1, 00168 Roma, Italia
| | - Riccardo Manfredi
- UOC di Diagnostica per immagini ed Interventistica Generale, Dipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli 8, 00168 Roma, Italia.,Università Cattolica Sacro Cuore, Largo F. Vito 1, 00168 Roma, Italia
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Zhang M, Sadinski M, Haddad D, Bae MS, Martinez D, Morris EA, Gibbs P, Sutton EJ. Background Parenchymal Enhancement on Breast MRI as a Prognostic Surrogate: Correlation With Breast Cancer Oncotype Dx Score. Front Oncol 2021; 10:595820. [PMID: 33614481 PMCID: PMC7890019 DOI: 10.3389/fonc.2020.595820] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 12/11/2020] [Indexed: 12/11/2022] Open
Abstract
Purpose Breast MRI background parenchymal enhancement (BPE) can potentially serve as a prognostic marker, by possible correlation with molecular subtype. Oncotype Dx, a gene assay, is a prognostic and predictive surrogate for tumor aggressiveness and treatment response. The purpose of this study was to investigate the association between contralateral non-tumor breast magnetic resonance imaging (MRI) background parenchymal enhancement and tumor oncotype score. Methods In this retrospective study, patients with ER+ and HER2− early stage invasive ductal carcinoma who underwent preoperative breast MRI, oncotype risk scoring, and breast conservation surgery from 2008–2010 were identified. After registration, BPE from the pre and three post-contrast phases was automatically extracted using a k-means clustering algorithm. Four metrics were calculated: initial enhancement (IE) relative to the pre-contrast signal, late enhancement, overall enhancement (OE), and area under the enhancement curve (AUC). Histogram analysis was performed to determine first order metrics which were compared to oncotype risk score groups using Mann–Whitney tests and Spearman rank correlation analysis. Results This study included 80 women (mean age = 51.1 ± 10.3 years); 46 women were categorized as low risk (≤17) and 34 women were categorized as intermediate/high risk (≥18) according to Oncotype Dx. For the mean of the top 10% pixels, significant differences were noted for IE (p = 0.032), OE (p = 0.049), and AUC (p = 0.044). Using the risk score as a continuous variable, correlation analysis revealed a weak but significant correlation with the mean of the top 10% pixels for IE (r = 0.26, p = 0.02), OE (r = 0.25, p = 0.02), and AUC (r = 0.27, p = 0.02). Conclusion BPE metrics of enhancement in the non-tumor breast are associated with tumor Oncotype Dx recurrence score, suggesting that the breast microenvironment may relate to likelihood of recurrence and magnitude of chemotherapy benefit.
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Affiliation(s)
- Michelle Zhang
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.,Department of Radiology, McGill University, Montreal, QC, Canada
| | - Meredith Sadinski
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Dana Haddad
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.,Department of Radiology, Montefiore, New York, NY, United States.,Department of Radiology, Mediclinic Middle East, Dubai, United Arab Emirates.,College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Min Sun Bae
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.,Department of Radiology, Seoul National University Hospital, Seoul, South Korea
| | - Danny Martinez
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Elizabeth A Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Peter Gibbs
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Elizabeth J Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
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10
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Contralateral parenchymal enhancement on breast MRI before and during neoadjuvant endocrine therapy in relation to the preoperative endocrine prognostic index. Eur Radiol 2020; 30:6740-6748. [PMID: 32691100 PMCID: PMC7599193 DOI: 10.1007/s00330-020-07058-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 04/30/2020] [Accepted: 07/01/2020] [Indexed: 02/07/2023]
Abstract
Objectives To investigate whether contralateral parenchymal enhancement (CPE) on MRI during neoadjuvant endocrine therapy (NET) is associated with the preoperative endocrine prognostic index (PEPI) of ER+/HER2− breast cancer. Methods This retrospective observational cohort study included 40 unilateral ER+/HER2− breast cancer patients treated with NET. Patients received NET for 6 to 9 months with MRI response monitoring after 3 and/or 6 months. PEPI was used as endpoint. PEPI is based on surgery-derived pathology (pT- and pN-stage, Ki67, and ER-status) and stratifies patients in three groups with distinct prognoses. Mixed effects and ROC analysis were performed to investigate whether CPE was associated with PEPI and to assess discriminatory ability. Results The median patient age was 61 (interquartile interval: 52, 69). Twelve patients had PEPI-1 (good prognosis), 15 PEPI-2 (intermediate), and 13 PEPI-3 (poor). High pretreatment CPE was associated with PEPI-3: pretreatment CPE was 39.4% higher on average (95% CI = 1.3, 91.9%; p = .047) compared with PEPI-1. CPE decreased after 3 months in PEPI-2 and PEPI-3. The average reduction was 24.4% (95% CI = 2.6, 41.3%; p = .032) in PEPI-2 and 29.2% (95% CI = 7.8, 45.6%; p = .011) in PEPI-3 compared with baseline. Change in CPE was predictive of PEPI-1 vs PEPI-2+3 (AUC = 0.77; 95% CI = 0.57, 0.96). Conclusions CPE during NET is associated with PEPI-group in ER+/HER2− breast cancer: a high pretreatment CPE and a decrease in CPE during NET were associated with a poor prognosis after NET on the basis of PEPI. Key Points • Change in contralateral breast parenchymal enhancement on MRI during neoadjuvant endocrine therapy distinguished between patients with a good and intermediate/poor prognosis at final pathology. • Patients with a poor prognosis at final pathology showed higher baseline parenchymal enhancement on average compared to patients with a good prognosis. • Patients with an intermediate/poor prognosis at final pathology showed a higher average reduction in parenchymal enhancement after 3 months of neoadjuvant endocrine therapy. Electronic supplementary material The online version of this article (10.1007/s00330-020-07058-3) contains supplementary material, which is available to authorized users.
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11
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van der Velden BHM, van Rijssel MJ, Lena B, Philippens MEP, Loo CE, Ragusi MAA, Elias SG, Sutton EJ, Morris EA, Bartels LW, Gilhuijs KGA. Harmonization of Quantitative Parenchymal Enhancement in T 1 -Weighted Breast MRI. J Magn Reson Imaging 2020; 52:1374-1382. [PMID: 32491246 PMCID: PMC7687185 DOI: 10.1002/jmri.27244] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 05/19/2020] [Accepted: 05/20/2020] [Indexed: 12/11/2022] Open
Abstract
Background Differences in imaging parameters influence computer‐extracted parenchymal enhancement measures from breast MRI. Purpose To investigate the effect of differences in dynamic contrast‐enhanced MRI acquisition parameter settings on quantitative parenchymal enhancement of the breast, and to evaluate harmonization of contrast‐enhancement values with respect to flip angle and repetition time. Study Type Retrospective. Phantom/Populations We modeled parenchymal enhancement using simulations, a phantom, and two cohorts (N = 398 and N = 302) from independent cancer centers. Sequence Field/Strength 1.5T dynamic contrast‐enhanced T1‐weighted spoiled gradient echo MRI. Vendors: Philips, Siemens, General Electric Medical Systems. Assessment We assessed harmonization of parenchymal enhancement in simulations and phantom by varying the MR parameters that influence the amount of T1‐weighting: flip angle (8°–25°) and repetition time (4–12 msec). We calculated the median and interquartile range (IQR) of the enhancement values before and after harmonization. In vivo, we assessed overlap of quantitative parenchymal enhancement in the cohorts before and after harmonization using kernel density estimations. Cohort 1 was scanned with flip angle 20° and repetition time 8 msec; cohort 2 with flip angle 10° and repetition time 6 msec. Statistical Tests Paired Wilcoxon signed‐rank‐test of bootstrapped kernel density estimations. Results Before harmonization, simulated enhancement values had a median (IQR) of 0.46 (0.34–0.49). After harmonization, the IQR was reduced: median (IQR): 0.44 (0.44–0.45). In the phantom, the IQR also decreased, median (IQR): 0.96 (0.59–1.22) before harmonization, 0.96 (0.91–1.02) after harmonization. Harmonization yielded significantly (P < 0.001) better overlap in parenchymal enhancement between the cohorts: median (IQR) was 0.46 (0.37–0.58) for cohort 1 vs. 0.37 (0.30–0.44) for cohort 2 before harmonization (57% overlap); and 0.35 (0.28–0.43) vs. .0.37 (0.30–0.44) after harmonization (85% overlap). Data Conclusion The proposed practical harmonization method enables an accurate comparison between patients scanned with differences in imaging parameters. Level of Evidence 3 Technical Efficacy Stage 4
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Affiliation(s)
- Bas H M van der Velden
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Michael J van Rijssel
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Beatrice Lena
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marielle E P Philippens
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Claudette E Loo
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Max A A Ragusi
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Sjoerd G Elias
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Elizabeth J Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Elizabeth A Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Lambertus W Bartels
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kenneth G A Gilhuijs
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Bismeijer T, van der Velden BHM, Canisius S, Lips EH, Loo CE, Viergever MA, Wesseling J, Gilhuijs KGA, Wessels LFA. Radiogenomic Analysis of Breast Cancer by Linking MRI Phenotypes with Tumor Gene Expression. Radiology 2020; 296:277-287. [PMID: 32452738 DOI: 10.1148/radiol.2020191453] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background Better understanding of the molecular biology associated with MRI phenotypes may aid in the diagnosis and treatment of breast cancer. Purpose To discover the associations between MRI phenotypes of breast cancer and their underlying molecular biology derived from gene expression data. Materials and Methods This is a secondary analysis of the Multimodality Analysis and Radiologic Guidance in Breast-Conserving Therapy, or MARGINS, study. MARGINS included patients eligible for breast-conserving therapy between November 2000 and December 2008 for preoperative breast MRI. Tumor RNA was collected for sequencing from surgical specimen. Twenty-one computer-generated MRI features of tumors were condensed into seven MRI factors related to tumor size, shape, initial enhancement, late enhancement, smoothness of enhancement, sharpness, and sharpness variation. These factors were associated with gene expression levels from RNA sequencing by using gene set enrichment analysis. Statistical significance of these associations was evaluated by using a sample permutation test and the false discovery rate. Results Gene expression and MRI data were obtained for 295 patients (mean age, 56 years ± 10.3 [standard deviation]). Larger and more irregular tumors showed increased expression of cell cycle and DNA damage checkpoint genes (false discovery rate <0.25; normalized enrichment statistic [NES], 2.15). Enhancement and sharpness of the tumor margin were associated with expression of ribosomal proteins (false discovery rate <0.25; NES, 1.95). Smoothness of enhancement, tumor size, and tumor shape were associated with expression of genes involved in the extracellular matrix (false discovery rate <0.25; NES, 2.25). Conclusion Breast cancer MRI phenotypes were related to their underlying molecular biology revealed by using RNA sequencing. The association between enhancements and sharpness of the tumor margin with the ribosome suggests that these MRI features may be imaging biomarkers for drugs targeting the ribosome. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Cho in this issue.
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Affiliation(s)
- Tycho Bismeijer
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Bas H M van der Velden
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Sander Canisius
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Esther H Lips
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Claudette E Loo
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Max A Viergever
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Jelle Wesseling
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Kenneth G A Gilhuijs
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
| | - Lodewyk F A Wessels
- From the Division of Molecular Carcinogenesis, Oncode Institute (T.B., S.C., L.F.A.W.), Division of Molecular Pathology (S.C., E.H.L., J.W.), Department of Radiology (C.E.L.), and Department of Pathology (J.W.), the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (B.H.M.v.d.V., M.A.V., K.G.A.G.); and Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, the Netherlands (L.F.A.W.)
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Are contralateral parenchymal enhancement on dynamic contrast-enhanced MRI and genomic ER-pathway activity in ER-positive/HER2-negative breast cancer related? Eur J Radiol 2019; 121:108705. [PMID: 31655316 DOI: 10.1016/j.ejrad.2019.108705] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 10/07/2019] [Accepted: 10/11/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE To retrospectively explore the relation between parenchymal enhancement of the healthy contralateral breast on dynamic contrast-enhanced magnetic resonance imaging (MRI) and genomic tests for estrogen receptor (ER)-pathway activity in patients with ER-positive/HER2-negative cancer. METHODS A subset of 227 consecutively included patients with unilateral invasive ER-positive/HER2-negative breast cancer underwent dynamic contrast-enhanced MRI prior to breast-conserving therapy between 2000 and 2008. Perfusion of the parenchyma in the healthy breast was assessed using a previously reported measure of contralateral parenchymal enhancement (CPE), consisting of the mean of the top-10% late enhancement. ER-pathway activity was assessed from the surgical resection specimen by the previously reported sensitivity to endocrine therapy (SET)-index and ER-factor. The SET-index is a genetic test to estimate survival benefit from endocrine therapy, consisting of genes related to the ESR1 gene. The ER-factor examines other factors as well including protein expression. The relation between CPE and ER-pathway activity was modeled using linear regression. RESULTS Patients had a median age of 59 years. CPE was not significantly associated with the SET-index (R-squared = 0.005) nor the ER-factor (R-squared = 0.0002). The only variable significantly different between low and high CPE was age at diagnosis (P < 0.001). CONCLUSIONS Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI was not associated with tumor-derived estrogen receptor pathway activity.
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Vreemann S, Dalmis MU, Bult P, Karssemeijer N, Broeders MJM, Gubern-Mérida A, Mann RM. Amount of fibroglandular tissue FGT and background parenchymal enhancement BPE in relation to breast cancer risk and false positives in a breast MRI screening program : A retrospective cohort study. Eur Radiol 2019; 29:4678-4690. [PMID: 30796568 PMCID: PMC6682856 DOI: 10.1007/s00330-019-06020-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 12/18/2018] [Accepted: 01/18/2019] [Indexed: 12/17/2022]
Abstract
Objectives The purpose of this study is to evaluate the predictive value of the amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE), measured at baseline on breast MRI, for breast cancer development and risk of false-positive findings in women at increased risk for breast cancer. Methods Negative baseline MRI scans of 1533 women participating in a screening program for women at increased risk for breast cancer between January 1, 2003, and January 1, 2014, were selected. Automated tools based on deep learning were used to obtain quantitative measures of FGT and BPE. Logistic regression using forward selection was used to assess relationships between FGT, BPE, cancer detection, false-positive recall, and false-positive biopsy. Results Sixty cancers were detected in follow-up. FGT was only associated to short-term cancer risk; BPE was not associated with cancer risk. High FGT and BPE did lead to more false-positive recalls at baseline (OR 1.259, p = 0.050, and OR 1.475, p = 0.003) and to more frequent false-positive biopsies at baseline (OR 1.315, p = 0.049, and OR 1.807, p = 0.002), but were not predictive for false-positive findings in subsequent screening rounds. Conclusions FGT and BPE, measured on baseline MRI, are not predictive for overall breast cancer development in women at increased risk. High FGT and BPE lead to more false-positive findings at baseline. Key Points • Amount of fibroglandular tissue is only predictive for short-term breast cancer risk in women at increased risk. • Background parenchymal enhancement measured on baseline MRI is not predictive for breast cancer development in women at increased risk. • High amount of fibroglandular tissue and background parenchymal enhancement lead to more false-positive findings at baseline MRI. Electronic supplementary material The online version of this article (10.1007/s00330-019-06020-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Suzan Vreemann
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, route 766, 6525 GA, Nijmegen, the Netherlands
| | - Mehmet U Dalmis
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, route 766, 6525 GA, Nijmegen, the Netherlands
| | - Peter Bult
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Nico Karssemeijer
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, route 766, 6525 GA, Nijmegen, the Netherlands
| | - Mireille J M Broeders
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Albert Gubern-Mérida
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, route 766, 6525 GA, Nijmegen, the Netherlands
| | - Ritse M Mann
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, route 766, 6525 GA, Nijmegen, the Netherlands.
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Shin GW, Zhang Y, Kim MJ, Su MY, Kim EK, Moon HJ, Yoon JH, Park VY. Role of dynamic contrast-enhanced MRI in evaluating the association between contralateral parenchymal enhancement and survival outcome in ER-positive, HER2-negative, node-negative invasive breast cancer. J Magn Reson Imaging 2018; 48:1678-1689. [PMID: 29734483 DOI: 10.1002/jmri.26176] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 04/12/2018] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Background parenchymal enhancement (BPE) on dynamic contrast-enhanced (DCE)-MRI has been associated with breast cancer risk, both based on qualitative and quantitative assessments. PURPOSE To investigate whether BPE of the contralateral breast on preoperative DCE-MRI is associated with therapy outcome in ER-positive, HER2-negative, node-negative invasive breast cancer. STUDY TYPE Retrospective. POPULATION In all, 289 patients with unilateral ER-positive, HER2-negative, node-negative breast cancer larger than 5 mm. FIELD STRENGTH/SEQUENCE 3T, T1 -weighted DCE sequence. ASSESSMENT BPE of the contralateral breast was assessed qualitatively by two dedicated radiologists and quantitatively (using region-of-interest and automatic breast segmentation). STATISTICAL TESTS Cox regression analysis was used to determine associations with recurrence-free survival (RFS) and distant metastasis-free survival (DFS). Interobserver variability for parenchymal enhancement was assessed using kappa statistics and intraclass correlation coefficient (ICC). RESULTS The median follow-up time was 75.8 months. Multivariate analysis showed receipt of total mastectomy (hazard ratio [HR]: 5.497) and high Ki-67 expression level (HR: 5.956) were independent factors associated with worse RFS (P < 0.05). Only a high Ki-67 expression level was associated with worse DFS (HR: 3.571, P = 0.045). BPE assessments were not associated with outcome (RFS [qualitative BPE: P = 0.75, 0.92 for readers 1 and 2; quantitative BPE: P = 0.38-0.99], DFS, [qualitative BPE: P = 0.41, 0.16 for readers 1 and 2; quantitative BPE: P = 0.68-0.99]). For interobserver variability, there was good agreement between qualitative (κ = 0.700) and good to perfect agreement for most quantitative parameters of BPE. DATA CONCLUSION Contralateral BPE showed no association with survival outcome in patients with ER-positive, HER2-negative, node-negative invasive breast cancer. A high Ki-67 expression level was associated with both worse recurrence-free and distant metastasis-free survival. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;48:1678-1689.
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Affiliation(s)
- Gi Won Shin
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Yang Zhang
- Department of Radiological Sciences, Tu & Yuen Center for Functional Onco-Imaging. University of California, Irvine, California, USA
| | - Min Jung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Min-Ying Su
- Department of Radiological Sciences, Tu & Yuen Center for Functional Onco-Imaging. University of California, Irvine, California, USA
| | - Eun-Kyung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Hee Jung Moon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Jung Hyun Yoon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Vivian Youngjean Park
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
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Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI reproduces as a biomarker of survival in ER-positive/HER2-negative breast cancer patients. Eur Radiol 2018; 28:4705-4716. [PMID: 29736850 PMCID: PMC6182741 DOI: 10.1007/s00330-018-5470-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 03/19/2018] [Accepted: 04/10/2018] [Indexed: 10/24/2022]
Abstract
OBJECTIVES To assess whether contralateral parenchymal enhancement reproduces as an independent biomarker for patient survival in an independent patient cohort from a different cancer institution. METHODS This is a HIPAA-compliant IRB approved retrospective study. Patients with ER-positive/HER2-negative operable invasive ductal carcinoma and preoperative dynamic contrast-enhanced MRI were consecutively included between 2005 and 2009. The parenchyma of the breast contralateral to known cancer was segmented automatically on MRI and contralateral parenchymal enhancement (CPE) was calculated. CPE was split into tertiles and tested for association with invasive disease-free survival (IDFS) and overall survival (OS). Propensity score analysis with inverse probability weighting (IPW) was used to adjust CPE for patient and tumour characteristics as well as systemic therapy. RESULTS Three hundred and two patients were included. The median age at diagnosis was 48 years (interquartile range, 42-57). Median follow-up was 88 months (interquartile range, 76-102); 15/302 (5%) patients died and 37/302 (13%) had a recurrence or died. In context of multivariable analysis, IPW-adjusted CPE was associated with IDFS [hazard ratio (HR) = 0.27, 95% confidence interval (CI) = 0.05-0.68, p = 0.004] and OS (HR = 0.22, 95% CI = 0.00-0.83, p = 0.032). CONCLUSIONS Contralateral parenchymal enhancement on pre-treatment dynamic contrast-enhanced MRI as an independent biomarker of survival in patients with ER-positive/HER2-negative breast cancer has been upheld in this study. These findings are a promising next step towards a practical and inexpensive test for risk stratification of ER-positive/HER2-negative breast cancer. KEY POINTS • High parenchymal-enhancement in the disease-free contralateral breast reproduces as biomarker for survival. • This is in patients with ER-positive/HER2-negative breast cancer from an independent cancer centre. • This is independent of patient and pathology parameters and systemic therapy.
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