Is there a correlation between 3T multiparametric MRI and molecular subtypes of breast cancer?

Montemezzi, Stefania; Camera, Lucia; Giri, Maria Grazia; A, Pozzetto; Caliò, Anna; Meliadò, Gabriele; Caumo, Francesca; Cavedon, Carlo

doi:10.1016/j.ejrad.2018.09.024

Cited by 36 publications

(33 citation statements)

References 28 publications

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“…could not identify an in uence of the Her 2 status on the ADC values [53]. In another study by Montemezzi et al, Luminal A type showed the highest ADC values compared to all other subtypes (0.924 × 10−3± 0.033 mm2/s) [34]. According to other authors, triple negative type showed the highest ADC values [25,38].…”

Section: Discussionmentioning

confidence: 86%

Diffusion Weighted Imaging of Different Breast Cancer Molecular Subtypes. A Systematic Review and Meta Analysis.

Meyer

Wienke

Surov

2020

Preprint

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Background: Magnetic resonance imaging can be used to diagnose breast cancer (BC)s. Diffusion weighted imaging and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. The present analysis sought to compare ADC values between molecular subtypes of BC based upon a large patient sample.Methods: MEDLINE library and SCOPUS databases were screened for the associations between ADC and molecular suptype of BC to April 2020. Primary endpoint of the systematic review was the ADC value in different BC. Overall, 28 studies were suitable for the analysis and included into the present study.Results: The included studies comprised a total of 2990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), Luminal B in 899 cases (30.1%), Her-2 enriched in 597 cases (20.0%) and triple negative in 629 cases (21.0%). The mean ADC value of the Luminal A type was 0.99 × 10− 3 mm2/s [95% CI 0.94-1.04], of the Luminal B type was 0.99 × 10− 3 mm2/s [95% CI 0.89-1.05], of Her 2-enriched type was 1.02 × 10− 3 mm2/s [95% CI 0.95-1.08] and of the triple negative type was 0.99 × 10− 3 mm2/s [95% CI 0.91-1.07].Conclusions: ADC values cannot be used to discriminate between molecular subtypes of BC.

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Section: Discussionmentioning

confidence: 86%

Diffusion Weighted Imaging of Different Breast Cancer Molecular Subtypes. A Systematic Review and Meta Analysis.

Meyer

Wienke

Surov

2020

Preprint

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“…Contrast enhancement metrics have proven to be the most commonly identified imaging feature associated with radiogenomics outcomes (4)(5)(6)(7)(8)(9)(10). MRI also allows for the assessment of additional tumoral features via diffusion weighted imaging (DWI), which have been a promising area of investigation (11)(12)(13)(14)(15)(16). Since DWI measures the in vivo motion of water molecules, which reflects tissue cellularity, differences in tumoral genetics may be expressed in DWI metrics.…”

Section: Mrimentioning

confidence: 99%

Breast Cancer Radiogenomics: Current Status and Future Directions

Grimm

Mazurowski

2020

Academic Radiology

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“…Montemezzi et al showed significant correlations between the Luminal‐A, Luminal‐B, HER2‐enriched, and triple‐negative molecular subtypes of breast cancer and mpMRI features through multivariate analysis. This study investigated the correlations between the four molecular subtypes and mpMRI parameters, such as lesion volume, margins or distribution, enhancement pattern, ADC, type of kinetic curve, and total choline [tCho] signal‐to‐noise ratio [SNR] …”

Section: Diagnostic Applications Of Biomarkersmentioning

confidence: 99%

“…This study investigated the correlations between the four molecular subtypes and mpMRI parameters, such as lesion volume, margins or distribution, enhancement pattern, ADC, type of kinetic curve, and total choline [tCho] signal-to-noise ratio [SNR]. 43 Markers of Pancreatic Cancer IHC is being increasingly used to understand pancreatic tumor biology by studying the fate of molecular markers during the initiation, progression, and metastasis of pancreatic neoplasms. 44 Pancreatic ductal adenocarcinoma (PDAC) and its variants, such as colloid carcinoma and medullary carcinoma, account for~85% of pancreatic neoplasms.…”

Section: Biomarkers Of Breast Tumorsmentioning

confidence: 99%

Overview of established and emerging immunohistochemical biomarkers and their role in correlative studies in MRI

Alvi

Gupta

Borok

et al. 2019

Magnetic Resonance Imaging

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Clinical practice in radiology and pathology requires professional expertise and many years of training to visually evaluate and interpret abnormal phenotypic features in medical images and tissue sections to generate diagnoses that guide patient management and treatment. Recent advances in digital image analysis methods and machine learning have led to significant interest in extracting additional information from medical and digital whole‐slide images in radiology and pathology, respectively. This has led to significant interest and research in radiomics and pathomics to correlate phenotypic features of disease with image analytics in order to identify image‐based biomarkers. The expanding role of big data in radiology and pathology parallels the development and role of immunohistochemistry (IHC) in the daily practice of pathology. IHC methods were initially developed to provide additional information to help classify tumors and then transformed into an indispensable tool to guide treatment in many types of cancer. IHC markers are used in daily practice to identify specific types of cells and highlight their distributions in tissues in order to distinguish benign from neoplastic cells, determine tumor origin, subclassify neoplasms, and support and confirm diagnoses. In this regard, radiomics, pathomics, and IHC methods are very similar since they enable the extraction of image‐based features to characterize various properties of diseases. Due to the dramatic advancements in recent radiomics research, we provide a brief overview of the role of established and emerging IHC biomarkers in various tumor types that have been correlated with radiologic biomarkers to improve diagnostic accuracy, predict prognosis, guide patient management, and select treatment strategies. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:341–354.

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Is there a correlation between 3T multiparametric MRI and molecular subtypes of breast cancer?

Cited by 36 publications

References 28 publications

Diffusion Weighted Imaging of Different Breast Cancer Molecular Subtypes. A Systematic Review and Meta Analysis.

Diffusion Weighted Imaging of Different Breast Cancer Molecular Subtypes. A Systematic Review and Meta Analysis.

Breast Cancer Radiogenomics: Current Status and Future Directions

Overview of established and emerging immunohistochemical biomarkers and their role in correlative studies in MRI

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