Radiologic-pathologic correlation in breast cancer: do MRI biomarkers correlate with pathologic features and molecular subtypes?

Galati, Francesca; Rizzo, Veronica; Moffa, Giuliana; Caramanico, Claudia; Kripa, Endi; Cerbelli, Bruna; d’Amati, Giulia; Pediconi, Federica

doi:10.1186/s41747-022-00289-7

Cited by 22 publications

(12 citation statements)

References 53 publications

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“…Central necrosis is particularly common in the TN, which could increase its mean T2 values. 37 A particular type of VEGF level was associated with the expression level of Ki-67. 38 This may explain our observation that the IDC type with Ki-67 > 14% showed higher mean T2 values.…”

Section: Discussionmentioning

confidence: 97%

Feasibility of Quantitative MRI Using 3D‐QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast

Amano

Fujita

Takei³

et al. 2023

Magnetic Resonance Imaging

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BackgroundTwo‐dimensional synthetic MRI of the breast has limited spatial coverage. Three‐dimensional (3D) synthetic MRI could provide volumetric quantitative parameters that may reflect the immunohistochemical (IHC) status in invasive ductal carcinoma (IDC) of the breast.PurposeTo evaluate the feasibility of 3D synthetic MRI using an interleaved Look–Locker acquisition sequence with a T2 preparation pulse (QALAS) for discriminating the IHC status, including hormone receptor (HR), human epidermal growth factor receptor 2 (HER 2), and Ki‐67 expression in IDC.Study TypeProspective observational study.PopulationA total of 33 females with IDC of the breast (mean, 52.3 years).Field Strength/SequenceA 3‐T, 3D‐QALAS gradient‐echo and fat‐suppressed T1‐weighted 3D fast spoiled gradient‐echo sequences.AssessmentTwo radiologists semiautomatically delineated 3D regions of interest (ROIs) of the whole tumors on the dynamic MRI that was registered to the synthetic T1‐weighted images acquired from 3D‐QALAS. The mean T1 and T2 were measured for each IDC.Statistical TestsIntraclass correlation coefficient for assessing interobserver agreement. Mann–Whitney U test to determine the relationship between the mean T1 or T2 and the IHC status. Multivariate logistic regression analysis followed by receiver operating characteristics (ROC) analysis for discriminating IHC status. A P value <0.05 was considered statistically significant.ResultsThe interobserver agreement was good to excellent. There was a significant difference in the mean T1 between HR‐positive and HR‐negative lesions, while the mean T2 value differed between HR‐positive and HR‐negative lesions, between the triple‐negative and HR‐positive or HER2‐positive lesions, and between the Ki‐67 level > 14% and ≤ 14%. Multivariate analysis showed that the mean T2 was higher in HR‐negative IDC than in HR‐positive IDC. ROC analysis revealed that the mean T2 was predictive for discriminating HR status, triple‐negative status, and Ki‐67 level.Data Conclusion3D synthetic MRI using QALAS may be useful for discriminating IHC status in IDC of the breast.Evidence Level1.Technical EfficacyStage 2.

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Section: Discussionmentioning

confidence: 97%

Feasibility of Quantitative MRI Using 3D‐QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast

Amano

Fujita

Takei³

et al. 2023

Magnetic Resonance Imaging

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“…However, multiparametric data are now also used to tackle more complex tasks such as predicting subtypes and treatment response after neoadjuvant treatment. We have summarized selected recent research investigating the prediction of subtypes 10,27,29,30,91,[103][104][105][106][107][108][109] (Table 2), response after neoadjuvant treatment [110][111][112] (Table 3), and evaluating TILs or CAF [113][114][115][116] (Table 4) to provide an overview of the trends in parameters and methods used for analysis. The most popular combinations of imaging include DCE, DWI (ADC value), and T2WI.…”

Section: Multiparametric Approaches To Breast Cancer: Recent Advancesmentioning

confidence: 99%

“…105 Mutiparametric approach succeeded in predicting triple negative subtype. 10,29,30,91,105,106 Multiparametric MRI is applied to predict response after neoadjuvant treatment. Multiple parameters are used to achieve best MRI, magnetic resonance imaging; TME, tumor microenvironment; DCE, dynamic contrast-enhanced; UF, ultrafast DCE; ADC, apparent diffusion coefficient; PET, positron emission tomography; AUC, area under the receiver operating characteristic curve; TN, triple negative; HER2, human epidermal growth factor 2; NAC, neoadjuvant chemotherapy; TIL, tumor-infiltrating lymphocyte; FDG, fluorodeoxyglucose; CAF, cancer-associated fibroblast.…”

Section: Multiparametric Approaches To Breast Cancer: Recent Advancesmentioning

confidence: 99%

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Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment

Kataoka,

Iima,

Miyake

et al. 2023

Invest Radiol

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A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.

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“…Biomarkers derived from multiparametric MRI (MP-MRI) examinations, including traditional T2-weighted and contrast-enhanced sequences, diffusion-weighted imaging (DWI) and MR spectroscopy, have shown to be highly correlated with histology, molecular subtypes of BC and other prognostic and predictive factors as response to treatment, risk of recurrence and overall survival [ 5 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence Score® Test?

et al. 2022

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The aim of this study was to combine breast MRI-derived biomarkers with clinical-pathological parameters to identify patients who truly need an Oncotype DX Breast Recurrence Score® (ODXRS) genomic assay, currently used to predict the benefit of adjuvant chemotherapy in ER-positive/HER2-negative early breast cancer, with the ultimate goal of customizing therapeutic decisions while reducing healthcare costs. Patients who underwent a preoperative multiparametric MRI of the breast and ODXRS tumor profiling were retrospectively included in this study. Imaging sets were evaluated independently by two breast radiologists and classified according to the 2013 American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) lexicon. In a second step of the study, a combined oncologic and radiologic assessment based on clinical-pathological and radiological data was performed, in order to identify patients who may need adjuvant chemotherapy. Results were correlated with risk levels expressed by ODXRS, using the decision made on the basis of the ODXRS test as a gold standard. The χ2 test was used to evaluate associations between categorical variables, and significant ones were further investigated using logistic regression analyses. A total of 58 luminal-like, early-stage breast cancers were included. A positive correlation was found between ODXRS and tumor size (p = 0.003), staging (p = 0.001) and grading (p = 0.005), and between BI-RADS categories and ODXRS (p < 0.05 for both readers), the latter being confirmed at multivariate regression analysis. Moreover, BI-RADS categories proved to be positive predictors of the therapeutic decision taken after performing an ODXRS assay. A statistically significant association was also found between the therapeutic decision based on the ODXRS and the results of combined onco-radiologic assessment (p < 0.001). Our study suggests that there is a correlation between BI-RADS categories at MRI and ODXRS and that a combined onco-radiological assessment may predict the decision made on the basis of the results of ODXRS genomic test.

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Radiologic-pathologic correlation in breast cancer: do MRI biomarkers correlate with pathologic features and molecular subtypes?

Cited by 22 publications

References 53 publications

Feasibility of Quantitative MRI Using 3D‐QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast

Feasibility of Quantitative MRI Using 3D‐QALAS for Discriminating Immunohistochemical Status in Invasive Ductal Carcinoma of the Breast

Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment

Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence Score® Test?

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