scholarly journals Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhiqi Yang ◽  
Xiaofeng Chen ◽  
Tianhui Zhang ◽  
Fengyan Cheng ◽  
Yuting Liao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Progesterone Receptor ◽  
Molecular Subtypes ◽  
Proliferation Index ◽  
Imaging Biomarkers ◽  
Luminal A ◽  
Receptor Status ◽  
Estrogen Receptor Positivity ◽  
Adc Values

ObjectivesTo assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques.MethodsA total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor, progesterone receptor, human epidermal growth factorreceptor-2 (HER-2) status, and the Ki-67 proliferation index were collected for analysis. Quantitative parameters (Ktrans, Ve, Kep), semiquantitative parameters (W-in, W-out, TTP), and apparent diffusion coefficient (ADC) values were compared in relation to breast cancer receptor status and molecular subtypes. Statistical analysis were performed to compare the parameters in the receptor status and molecular subtype groups.Multivariate analysis was performed to explore confounder-adjusted associations, and receiver operating characteristic curve analysis was used to assess the classification performance and calculate thresholds.ResultsYounger age (<49.5 years, odds ratio (OR) =0.95, P=0.004), lower Kep (<0.704,OR=0.14, P=0.044),and higher TTP (>0.629 min, OR=24.65, P=0.011) were independently associated with progesterone receptor positivity. A higher TTP (>0.585 min, OR=28.19, P=0.01) was independently associated with estrogen receptor positivity. Higher Kep (>0.892, OR=11.6, P=0.047), lower TTP (<0.582 min, OR<0.001, P=0.004), and lower ADC (<0.719 ×10-3 mm2/s, OR<0.001, P=0.048) had stronger independent associations with triple-negative breast cancer (TNBC) compared to luminal A, and those parameters could differentiate TNBC from luminal A with the highest AUC of 0.811.ConclusionsKep and TTP were independently associated with hormone receptor status. In addition, the Kep, TTP, and ADC values had stronger independent associations with TNBC than with luminal A and could be used as imaging biomarkers for differentiate TNBC from Luminal A.

scholarly journals Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis

Breast Care ◽  
2021 ◽  
pp. 1-8
Author(s):  
Hans-Jonas Meyer ◽  
Andreas Wienke ◽  
Alexey Surov
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Diffusion Weighted Imaging ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Luminal A ◽  
Diagnose Breast Cancer ◽  
Luminal B ◽  
Diffusion Weighted ◽  
Adc Values

Background: Magnetic resonance imaging can be used to diagnose breast cancer (BC).Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Objectives: This analysis aimed to compare ADC values between molecular subtypes of BC based on a large sample of patients. Method: The MEDLINE library and Scopus database were screened for the associations between ADC and molecular subtypes of BC up to April 2020. The primary end point of the systematic review was the ADC value in different BC subtypes. Overall, 28 studies were included. Results: The included studies comprised a total of 2,990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), luminal B in 899 (30.1%), human epidermal growth factor receptor (Her2)-enriched in 597 (20.0%), and triple-negative in 629 (21.0%). The mean ADC values of the subtypes were as follows: luminal A: 0.99 × 10–3 mm2/s (95% CI 0.94–1.04), luminal B: 0.97 × 10–3 mm2/s (95% CI 0.89–1.05), Her2-enriched: 1.02 × 10–3 mm2/s (95% CI 0.95–1.08), and triple-negative: 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.

Male Versus Female Breast Cancers

2003 ◽  
Vol 127 (1) ◽  
pp. 36-41 ◽  
Author(s):  
D. Muir ◽  
R. Kanthan ◽  
S. C. Kanthan
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Progesterone Receptor ◽  
Male Breast Cancer ◽  
Male Breast ◽  
High Grade ◽  
Breast Cancers ◽  
Receptor Status ◽  
Female Breast ◽  
Grade 3

Abstract Context.—The rate of male breast cancer is a small fraction of that observed in females, thus severely limiting our understanding of the pathogenesis of this condition. It remains unclear whether the biological behavior and tumor progression associated with male breast cancer parallel that of the female form. Objectives.—To evaluate the immunohistochemical profile of male breast carcinomas and to compare this profile with that of stage-matched female breast cancers. Design.—Seventy-five cases of primary male breast cancer were identified using the records of the Saskatchewan Cancer Foundation over a period of 26 years (1970–1996). Fifty-nine of these cases had formalin-fixed, paraffin-embedded tissue blocks available for the purposes of this study. All cases were reviewed and a standardized modified Bloom-Richardson grading criterion was applied. Estrogen receptor status, progesterone receptor status, c-Erb-B2 expression, p53 expression, and Bcl-2 expression were evaluated by immunohistochemistry. Results from 240 consecutive cases of stage-matched female breast cancers analyzed in the same laboratory were used as a standard set for comparison. Results.—Male breast cancers tended to be high grade (85% grade 3) in comparison with the female breast cancers (50% grade 3). In descriptive analysis across all stages of disease, male carcinomas were more frequently estrogen receptor positive (81% vs 69%) than their female counterparts. Despite their high grade, they were less likely to overexpress p53 (9% vs 28%) and Erb-B2 (5% vs 17%) than the female counterparts. There was no significant difference in either progesterone receptor (63% vs 56%) or Bcl-2 (79% vs 76%) overexpression. Stratified analysis by stage-matched controls showed no statistically significant differences among the men and women with stage I disease. However, in stage II–matched samples, statistically significant differences were observed between the 2 groups. The male cancers were more likely to overexpress estrogen receptor (81.6% vs 64.4%, P = .04), progesterone receptor (71.1% vs 47.5%, P = .01), and Bcl-2 (78.9% vs 69.4%, P = .20). They also showed statistically significant lower expression of p53 (7.9% vs 36.3%, P = .001) and Erb-B2 (5.3% vs 23.8% P = .01). Conclusion.—Male breast cancers display distinct immunophenotypic differences from those occurring in women, implying a different pathogenesis in the evolution and progression of this disease. Such differences may play key roles in therapeutic management, warranting different treatment strategies in comparison to female breast cancers.

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

2020 ◽  
Author(s):  
Hans-Jonas Meyer ◽  
Andreas Wienke ◽  
Alexey Surov
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Diffusion Weighted Imaging ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Luminal A ◽  
Adc Value ◽  
Luminal B ◽  
Adc Values ◽  
Her 2

Abstract 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.

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

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Doris Leithner ◽  
Joao V. Horvat ◽  
Maria Adele Marino ◽  
Blanca Bernard-Davila ◽  
Maxine S. Jochelson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative ◽  
Molecular Subtypes ◽  
Training Dataset ◽  
Validation Dataset ◽  
Resonance Imaging ◽  
Luminal A ◽  
Receptor Status ◽  
Luminal B ◽  
Contrast Enhanced

Abstract Background 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. Methods 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, n = 49; luminal B, n = 8; HER2-enriched, n = 11; triple negative, n = 23), while the validation dataset comprised 52 patients from a second institution (luminal A, n = 17; luminal B, n = 17; triple negative, n = 18). Radiomic analysis of manually segmented tumors included calculation of features derived from the first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient (GRA), autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry (GEO). Fisher, probability of error and average correlation (POE + ACC), and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise radiomic-based separation of receptor status and molecular subtypes. Histopathology served as the standard of reference. Results In the training dataset, radiomic signatures yielded the following accuracies > 80%: luminal B vs. luminal A, 84.2% (mainly based on COM features); luminal B vs. triple negative, 83.9% (mainly based on GEO features); luminal B vs. all others, 89% (mainly based on COM features); and HER2-enriched vs. all others, 81.3% (mainly based on COM features). Radiomic signatures were successfully validated in the separate validation dataset for luminal A vs. luminal B (79.4%) and luminal B vs. triple negative (77.1%). Conclusions In this preliminary study, radiomic signatures with CE-MRI enable the assessment of breast cancer receptor status and molecular subtypes with high diagnostic accuracy. These results need to be confirmed in future larger studies.

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