publication . Article . Other literature type . 2019

Radiomic signatures with contrast-enhanced magnetic resonance imaging for the assessment of breast cancer receptor status and molecular subtypes: initial results.

Blanca Bernard-Davila; Maxine S. Jochelson; Danny F. Martinez; Joao V. Horvat; Katja Pinker; Elizabeth A. Morris; Sunitha B. Thakur; Maria Adele Marino; Maria Adele Marino; Doris Leithner; ...
Open Access English
  • Published: 01 Sep 2019 Journal: Breast Cancer Research : BCR, volume 21 (issn: 1465-5411, eissn: 1465-542X, Copyright policy)
  • Publisher: BioMed Central
Abstract
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>To evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular subtypes.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>One hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, <jats:italic>n</jats:italic> = 49; luminal B, <jats:italic>n</jats:italic> =...
Subjects
free text keywords: Research Article, Radiomics, Contrast-enhanced, Magnetic resonance imaging, Breast cancer, Molecular subtype, Cancer Research, Oncology, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282, medicine.diagnostic_test, medicine, Probability of error, Nuclear medicine, business.industry, business, medicine.disease, Linear discriminant analysis, Correlation, Receptor Status, Contrast-enhanced Magnetic Resonance Imaging, Diagnostic accuracy
Funded by
NIH| MOUSE GENETICS
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2P30CA008748-43
  • Funding stream: NATIONAL CANCER INSTITUTE
,
EC| HYPMED
Project
HYPMED
Digital Hybrid Breast PET/MRI for Enhanced Diagnosis of Breast Cancer
  • Funder: European Commission (EC)
  • Project Code: 667211
  • Funding stream: H2020 | RIA
36 references, page 1 of 3

Carey, LA, Perou, CM, Livasy, CA, Dressler, LG, Cowan, D, Conway, K. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA.. 2006; 295: 2492-2502 [OpenAIRE] [PubMed] [DOI]

Huber, KE, Carey, LA, Wazer, DE. Breast cancer molecular subtypes in patients with locally advanced disease: impact on prognosis, patterns of recurrence, and response to therapy. Semin Radiat Oncol. 2009; 19: 204-210 [OpenAIRE] [PubMed] [DOI]

Lam, SW, Jimenez, CR, Boven, E. Breast cancer classification by proteomic technologies: current state of knowledge. Cancer Treat Rev. 2014; 40: 129-138 [OpenAIRE] [PubMed] [DOI]

Wirapati, P, Sotiriou, C, Kunkel, S, Farmer, P, Pradervand, S, Haibe-Kains, B. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008; 10: R65 [OpenAIRE] [PubMed] [DOI]

Haynes, B, Sarma, A, Nangia-Makker, P, Shekhar, MP. Breast cancer complexity: implications of intratumoral heterogeneity in clinical management. Cancer Metastasis Rev. 2017; 36: 547-555 [OpenAIRE] [PubMed] [DOI]

Zardavas, D, Irrthum, A, Swanton, C, Piccart, M. Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol. 2015; 12: 381-394 [OpenAIRE] [PubMed] [DOI]

Martelotto, LG, Ng, CK, Piscuoglio, S, Weigelt, B, Reis-Filho, JS. Breast cancer intra-tumor heterogeneity. Breast Cancer Res. 2014; 16: 210 [OpenAIRE] [PubMed] [DOI]

Cancer Genome Atlas, N. Comprehensive molecular portraits of human breast tumours. Nature.. 2012; 490: 61-70 [OpenAIRE] [PubMed] [DOI]

Prat, A, Perou, CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol. 2011; 5: 5-23 [OpenAIRE] [PubMed] [DOI]

Prat, A, Pineda, E, Adamo, B, Galvan, P, Fernandez, A, Gaba, L. Clinical implications of the intrinsic molecular subtypes of breast cancer. Breast.. 2015; 24 (Suppl 2): S26-S35 [OpenAIRE] [PubMed] [DOI]

Mazurowski, MA, Zhang, J, Grimm, LJ, Yoon, SC, Silber, JI. Radiogenomic analysis of breast cancer: luminal B molecular subtype is associated with enhancement dynamics at MR imaging. Radiology.. 2014; 273: 365-372 [OpenAIRE] [PubMed] [DOI]

Tsoutsou, PG, Vozenin, MC, Durham, AD, Bourhis, J. How could breast cancer molecular features contribute to locoregional treatment decision making?. Crit Rev Oncol Hematol. 2017; 110: 43-48 [OpenAIRE] [PubMed] [DOI]

Ahn, HJ, Jung, SJ, Kim, TH, Oh, MK, Yoon, HK. Differences in clinical outcomes between luminal A and B type breast cancers according to the St. Gallen Consensus 2013. J Breast Cancer. 2015; 18: 149-159 [OpenAIRE] [PubMed] [DOI]

Senn, HJ. St. Gallen consensus 2013: optimizing and personalizing primary curative therapy of breast cancer worldwide. Breast Care (Basel). 2013; 8: 101 [OpenAIRE] [PubMed] [DOI]

Pisco, AO, Huang, S. Non-genetic cancer cell plasticity and therapy-induced stemness in tumour relapse: ‘What does not kill me strengthens me’. Br J Cancer. 2015; 112: 1725-1732 [OpenAIRE] [PubMed] [DOI]

36 references, page 1 of 3
Abstract
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>To evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular subtypes.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>One hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, <jats:italic>n</jats:italic> = 49; luminal B, <jats:italic>n</jats:italic> =...
Subjects
free text keywords: Research Article, Radiomics, Contrast-enhanced, Magnetic resonance imaging, Breast cancer, Molecular subtype, Cancer Research, Oncology, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282, medicine.diagnostic_test, medicine, Probability of error, Nuclear medicine, business.industry, business, medicine.disease, Linear discriminant analysis, Correlation, Receptor Status, Contrast-enhanced Magnetic Resonance Imaging, Diagnostic accuracy
Funded by
NIH| MOUSE GENETICS
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2P30CA008748-43
  • Funding stream: NATIONAL CANCER INSTITUTE
,
EC| HYPMED
Project
HYPMED
Digital Hybrid Breast PET/MRI for Enhanced Diagnosis of Breast Cancer
  • Funder: European Commission (EC)
  • Project Code: 667211
  • Funding stream: H2020 | RIA
36 references, page 1 of 3

Carey, LA, Perou, CM, Livasy, CA, Dressler, LG, Cowan, D, Conway, K. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA.. 2006; 295: 2492-2502 [OpenAIRE] [PubMed] [DOI]

Huber, KE, Carey, LA, Wazer, DE. Breast cancer molecular subtypes in patients with locally advanced disease: impact on prognosis, patterns of recurrence, and response to therapy. Semin Radiat Oncol. 2009; 19: 204-210 [OpenAIRE] [PubMed] [DOI]

Lam, SW, Jimenez, CR, Boven, E. Breast cancer classification by proteomic technologies: current state of knowledge. Cancer Treat Rev. 2014; 40: 129-138 [OpenAIRE] [PubMed] [DOI]

Wirapati, P, Sotiriou, C, Kunkel, S, Farmer, P, Pradervand, S, Haibe-Kains, B. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008; 10: R65 [OpenAIRE] [PubMed] [DOI]

Haynes, B, Sarma, A, Nangia-Makker, P, Shekhar, MP. Breast cancer complexity: implications of intratumoral heterogeneity in clinical management. Cancer Metastasis Rev. 2017; 36: 547-555 [OpenAIRE] [PubMed] [DOI]

Zardavas, D, Irrthum, A, Swanton, C, Piccart, M. Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol. 2015; 12: 381-394 [OpenAIRE] [PubMed] [DOI]

Martelotto, LG, Ng, CK, Piscuoglio, S, Weigelt, B, Reis-Filho, JS. Breast cancer intra-tumor heterogeneity. Breast Cancer Res. 2014; 16: 210 [OpenAIRE] [PubMed] [DOI]

Cancer Genome Atlas, N. Comprehensive molecular portraits of human breast tumours. Nature.. 2012; 490: 61-70 [OpenAIRE] [PubMed] [DOI]

Prat, A, Perou, CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol. 2011; 5: 5-23 [OpenAIRE] [PubMed] [DOI]

Prat, A, Pineda, E, Adamo, B, Galvan, P, Fernandez, A, Gaba, L. Clinical implications of the intrinsic molecular subtypes of breast cancer. Breast.. 2015; 24 (Suppl 2): S26-S35 [OpenAIRE] [PubMed] [DOI]

Mazurowski, MA, Zhang, J, Grimm, LJ, Yoon, SC, Silber, JI. Radiogenomic analysis of breast cancer: luminal B molecular subtype is associated with enhancement dynamics at MR imaging. Radiology.. 2014; 273: 365-372 [OpenAIRE] [PubMed] [DOI]

Tsoutsou, PG, Vozenin, MC, Durham, AD, Bourhis, J. How could breast cancer molecular features contribute to locoregional treatment decision making?. Crit Rev Oncol Hematol. 2017; 110: 43-48 [OpenAIRE] [PubMed] [DOI]

Ahn, HJ, Jung, SJ, Kim, TH, Oh, MK, Yoon, HK. Differences in clinical outcomes between luminal A and B type breast cancers according to the St. Gallen Consensus 2013. J Breast Cancer. 2015; 18: 149-159 [OpenAIRE] [PubMed] [DOI]

Senn, HJ. St. Gallen consensus 2013: optimizing and personalizing primary curative therapy of breast cancer worldwide. Breast Care (Basel). 2013; 8: 101 [OpenAIRE] [PubMed] [DOI]

Pisco, AO, Huang, S. Non-genetic cancer cell plasticity and therapy-induced stemness in tumour relapse: ‘What does not kill me strengthens me’. Br J Cancer. 2015; 112: 1725-1732 [OpenAIRE] [PubMed] [DOI]

36 references, page 1 of 3
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