Magnetic resonance imaging as a non-invasive breast cancer tool - the relevance of breast edema score: A retrospective study.

BackgroundSince many newly diagnosed breast cancer patients have breast MRI, the value of preoperative breast magnetic resonance imaging would improve if molecular subtypes could be consistently identified, and prognostic information provided in addition to diagnostic imaging. Breast edema may improve the ability to predict molecular subtypes and clinical and pathological outcomes in invasive breast cancer patients. The prognosis for breast cancer prognosis based on the findings of breast edema by magnetic resonance imaging will be useful in both pretreatment planning and prognosis. Breast edema on T2-weighted images and STIR was scored on a scale of 1 to 4, as follows: (a) breast edema score (BES) 1, no edema; (b) BES 2, peritumoral edema; (c) BES 3, pre pectoral edema; and (d) BES 4, subcutaneous edema (suspicious for occult inflammatory breast cancer “IBC”). Axillary lymph node status and number were also evaluated in T2 and STIR and after contrast administration. The aim of this work was to assess the role of tumour-related breast edema MRI features in distinguishing molecular subtypes of breast cancer and its effect on pathological axillary lymph nodes in patients with breast cancer.ResultsThere was a highly significant difference between BES with respect to the molecular subtypes of breast cancer, size of the mass, Ki-67 expression, LN status, and LN number (p < 0.0001, 0.045, < 0.0001, < 0.0001, and < 0.0001 respectively). However, there was no significant difference between BES and histopathological grade in studied masses, such as p-value = 0.49.ConclusionsTumour-related breast edema MRI characteristics may be useful in distinguishing molecular subtypes of breast cancer and could be used as a promising feature to improve the predictive performance of pathological axillary lymph nodes in patients with breast cancer, contributing to preoperative treatment planning and prognostic outcome.

BackgroundDetermining an appropriate surgical strategy for breast cancer patients with residual suspicious calcifications following neoadjuvant chemotherapy (NAC) remains challenging. Suspicious calcifications often persist on post-treatment mammography, irrespective of tumor viability. This study aimed to identify key predictors of pathologic complete response (pCR) and evaluate the optimal surgical approach for this specific patient cohort.MethodsA retrospective analysis was conducted on breast cancer patients who presented with residual suspicious calcifications on mammography after NAC but demonstrated a radiologic response on magnetic resonance imaging (MRI), classified as complete (CR) or partial (PR) response. Two radiologists, blinded to pathology results, assessed mammography and MRI findings. Molecular subtypes were classified based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status as HR+/HER2−, HR+/HER2+, HR−/HER2+, and triple-negative breast cancer (TNBC). Multivariable regression analysis with an Elastic Net penalty was performed to identify independent predictors of pCR. Diagnostic performance metrics, including sensitivity, specificity, and accuracy, were analyzed by molecular subtypes.ResultsA total of 243 patients, with a mean age of 50.7 years, were included. The overall pCR rate was 33.7%, with HR−/HER2+ demonstrating the highest pCR rate (59.1%) and HR+/HER2− the lowest (3.8%). Multivariable regression analysis identified CR on MRI (compared to PR; odds ratio [OR], 3.13; P = 0.015) and HR−/HER2+ subtype (compared to HR+/HER2−; OR, 29.7; P = 0.005) as significant predictors of pCR. Diagnostic performance metrics of MRI varied by molecular subtype: sensitivity was highest in TNBC (87%) and lowest in HR−/HER2+ (70.4%), while specificity was highest in HR+/HER2− (100%) and lowest in HR−/HER2+ (48.7%). Accuracy was highest in HR+/HER2− (80.8%) and TNBC (78.9%), with lower accuracy in HR+/HER2+ (72.4%) and HR−/HER2+ (57.6%).ConclusionPost-treatment MRI response and molecular subtypes are significant predictors of pCR in breast cancer patients with suspicious calcifications after NAC. Nevertheless, complete surgical excision of the calcifications remains advised, particularly for the HR+/HER2− due to the lowest pCR rate and for the HR−/HER2+ due to suboptimal MRI accuracy, despite its highest pCR rate.

To assess whether breast cancer molecular subtype classified by surrogate markers can be used to predict the extent of clinically relevant disease with preoperative breast magnetic resonance (MR) imaging. In this HIPAA-compliant, institutional review board-approved study, informed consent was waived. Preoperative breast MR imaging reports from 441 patients were reviewed for multicentric and/or multifocal disease, lymph node involvement, skin and/or nipple invasion, chest wall and/or pectoralis muscle invasion, or contralateral disease. Pathologic reports were reviewed to confirm the MR imaging findings and for hormone receptors (estrogen and progesterone subtypes), human epidermal growth factor receptor type 2 (HER2 subtype), tumor size, and tumor grade. Surrogates were used to categorize tumors by molecular subtype: hormone receptor positive and HER2 negative (luminal A subtype); hormone receptor positive and HER2 positive (luminal B subtype); hormone receptor negative and HER2 positive (HER2 subtype); hormone receptor negative and HER2 negative (basal subtype). All patients included in the study had a histologic correlation with MR imaging findings or they were excluded. χ(2) analysis was used to compare differences between subtypes, with multivariate logistic regression analysis used to assess for variable independence. Identified were 289 (65.5%) luminal A, 45 (10.2%) luminal B, 26 (5.9%) HER2, and 81 (18.4%) basal subtypes. Among subtypes, significant differences were found in the frequency of multicentric and/or multifocal disease (luminal A, 27.3% [79 of 289]; luminal B, 53.3% [24 of 45]; HER2, 65.4% [17 of 26]; basal, 27.2% [22 of 81]; P < .001) and lymph node involvement (luminal A, 17.3% [50 of 289]; luminal B, 35.6% [26 of 45]; HER2, 34.6% [nine of 26]; basal 24.7% [20 of 81]; P = .014). Multivariate analysis showed that molecular subtype was independently predictive of multifocal and/or multicentric disease. Preoperative breast MR imaging is significantly more likely to help detect multifocal and/or multicentric disease and lymph node involvement in luminal B and HER2 molecular subtype breast cancers. Molecular subtype may help to select patients for preoperative breast MR imaging.

In the present study, clinical tumor response following neoadjuvant chemotherapy (NAC) was diagnosed by magnetic resonance imaging (MRI) and clinicopathological factors, including molecular subtypes at baseline, were analyzed for correlations with pathological tumor responses. In addition, clinicopathological factors were analyzed for a correlation with the MRI capacity to predict pathological complete response (pCR). Clinical tumor response evaluated by MRI following NAC was determined as a clinical CR (cCR) or a residual tumor. cCR was confirmed if no gadolinium enhancement or an enhancement equal to or less than that of glandular tissue was observed in any phase of the MRI. Pathological tumor responses following NAC were classified into grades 0 (no change) to 3 (no residual invasive cancer) according to criteria of the Japanese Breast Cancer Society. pCR was defined as grade 3 in the present study. Of 264 cases of invasive breast cancer in 260 patients (4 synchronous bilateral breast cancer cases), 59 (22%) were diagnosed by MRI following NAC as cCR and 98 (37%) were pathologically diagnosed as pCR. In terms of predicting pCR by MRI, the sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) were 44, 90, 73, 73 and 73%, respectively. Tumor size, hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, molecular subtype and histological type were significantly correlated with pathological tumor responses. pCR rates increased in the following order: luminal/HER2-negative (14%), luminal/HER2-positive (32%), triple-negative (46%) and non-luminal/HER2-positive (73%) tumors. Sensitivity and specificity were the highest (60 and 100%, respectively) in triple-negative tumors. PPV decreased in the following order: triple-negative (100%), non-luminal/HER2-positive (92%), luminal/HER2-positive (46%) and luminal/HER2-negative (33%) tumors. In conclusion, MRI evaluation is useful for predicting pCR following NAC, particularly for triple-negative tumors.

To investigate machine learning approaches for radiomics-based prediction of prognostic biomarkers and molecular subtypes of breast cancer using quantification of tumor heterogeneity and angiogenesis properties on magnetic resonance imaging (MRI). This prospective study examined 291 invasive cancers in 288 patients who underwent breast MRI at 3 T before treatment between May 2017 and July 2019. Texture and perfusion analyses were performed and a total of 160 parameters for each cancer were extracted. Relationships between MRI parameters and prognostic biomarkers were analyzed using five machine learning algorithms. Each model was built using only texture features, only perfusion features, or both. Model performance was compared using the area under the receiver-operating characteristic curve (AUC) and the DeLong method, and the importance of MRI parameters in prediction was derived. Texture parameters were associated with the status of hormone receptors, human epidermal growth factor receptor 2, and Ki67, tumor size, grade, and molecular subtypes (p < 0.002). Perfusion parameters were associated with the status of hormone receptors and Ki67, grade, and molecular subtypes (p < 0.003). The random forest model integrating texture and perfusion parameters showed the highest performance (AUC = 0.75). The performance of the random forest model was the best with a special scale filter of 0 (AUC = 0.80). The important parameters for prediction were texture irregularity (entropy) and relative extracellular extravascular space (Ve). Radiomic machine learning that integrates tumor heterogeneity and angiogenesis properties on MRI has the potential to noninvasively predict prognostic factors of breast cancer. • Machine learning, integrating tumor heterogeneity and angiogenesis properties on MRI, can be applied to predict prognostic biomarkers and molecular subtypes in breast cancer. • The random forest model showed the best predictive performance among the five machine learning models (logistic regression, decision tree, naïve Bayes, random forest, and artificial neural network). • The most important MRI parameters for predicting prognostic factors in breast cancer were texture irregularity (entropy) among texture parameters and relative extracellular extravascular space (Ve) among perfusion parameters.

To retrospectively evaluate the magnetic resonance (MR) imaging findings of "triple-negative" breast cancer (ie, cancer that is estrogen receptor [ER] negative, progesterone receptor [PR] negative, and human epidermal growth factor receptor 2 [HER2] negative) and to compare them with those of breast cancers that are ER positive, PR positive, and HER2 negative. Institutional review board approval and informed consent were obtained. The MR imaging findings in 176 randomly assigned women (mean age, 56 years; range, 29-87 years) with surgically confirmed triple-negative breast cancers (n = 59) or ER-positive/PR-positive/HER2-negative breast cancers (n = 117) were reviewed. MR imaging findings included tumor shape, margin, internal enhancement, and size, as well as intratumoral signal intensity that was stronger than or almost the same as that of water or vessels on T2-weighted MR images. The MR imaging findings were compared with the pathologic findings. High histologic grade (P < .001), unifocal lesion (P = .012), mass lesion type (P < .001), smooth mass margin (P = .001), rim enhancement (P < .001), persistent enhancement pattern (P = .005), and very high intratumoral signal intensity on T2-weighted MR images (P = .002) were significantly associated with triple-negative breast cancer. Very high intratumoral signal intensity on T2-weighted MR images was significantly associated with intratumoral necrosis (P < .001). Several MR imaging features might be used for detecting triple-negative breast cancer.

Improved discrimination of molecular subtypes in invasive breast cancer: Comparison of multiple quantitative parameters from breast MRI

Aim: Preoperative breast magnetic resonance imaging (MRI) findings can provide rich information about the prognosis of the disease. Morphologic and dynamic features are especially used for it. We aimed to compare peritumoral, prepectoral, and diffuse edema identified in MRI with histopathologic findings, and to show how prognostic information can be gathered from the identification of edema.Methods: We conducted a retrospective cohort study with forty-six women who underwent breast DCE-MRI as part of the pre-surgical evaluation between January and August 2018 were included in the study. Signal enhancements similar to water that were localized to the prepectoral or peritumoral areas or diffuse enhancements on T2A-weighted sequences were considered as edema. The presence of edema was compared with clinicopathologic parameters such as cancer type, tumor size, histologic grade, ER-PR receptor positivity, Her2 positivity, Ki-67 labelling index and lymphovascular invasion.Results: The mean age of the participants was 53.15±11.75 (range, 27-80) years. Eleven patients had diffuse edema, 27 patients had peritumoral edema, and 5 patients had prepectoral edema. Nineteen luminal A cancers, 17 luminal B, 9 triple-negative, and 1 Her2 cancer were seen. Peritumoral edema was associated with lymphovascular invasion positivity (p=0.002). Tumor size and the level of Ki-67 was associated with peritumoral edema (p=0.001, p=0.009). The odds of observing prepectoral edema showed no statistically significant difference in the presence of lymphovascular invasion positivity and other parameters. The presence of diffuse edema showed significant differences depending on tumor size measurements (p=0.026).Conclusion: Edema in breast MRI can provide information about histopathologic findings, particularly about lymphovascular invasion. The authors suggest that different edema types could be mentioned in radiology reports as a matter of routine given that such findings can provide information about the prognosis.

Preoperative Breast MRI: Barking up the Wrong Endpoints

Background Human epidermal growth factor receptor 2-positive (HER2+) breast cancer has two distinct subtypes according to hormone receptor (HR) status. Survival, pattern of recurrence, and treatment response differ between HR-/HER2+ and HR+/HER2+ cancers. Purpose To investigate imaging and clinicopathologic features of HER2+ cancers and their correlation with HR expression. Material and Methods Between 2011 and 2013, 252 consecutive patients with 252 surgically confirmed HER2+ cancers (125 HR- and 127 HR+) were included. Two experienced breast radiologists blinded to the clinicopathologic findings reviewed the mammograms and magnetic resonance (MR) images using the BI-RADS lexicon. Tumor kinetic features were acquired by computer-aided detection (CAD). The imaging and clinicopathologic features of 125 HR-/HER2+ cancers were compared with those of 127 HR+/HER2+ cancers. Association between the HR status and each feature was assessed. Results Multiple logistic regression analysis showed that circumscribed mass margin (odds ratio [OR], 4.73; P < 0.001), associated non-mass enhancement (NME) on MR images (OR, 3.29; P = 0.001), high histologic grade (OR, 3.89; P = 0.002), high Ki-67 index (OR, 3.06; P = 0.003), and older age (OR, 2.43; P = 0.006) remained independent indicators associated with HR-/HER2+ cancers. Between the two HER2+ subtypes, there were no differences in mammographic imaging presentations and calcification features and MR kinetic features by a CAD. Conclusion HER2+ breast cancers have different MR imaging (MRI) phenotypes and clinicopathologic feature according to HR status. MRI features related to HR and HER2 status have the potential to be used for the diagnosis and treatment decisions in HER2+ breast cancer patients.

Background: Understanding prognosis in de novo metastatic breast cancer (dnMBC) requires accounting for both where the disease first spreads and the tumour’s molecular subtype, yet recent population level studies that analyse these two determinants together are uncommon. Objectives: To determine, in a recent nationwide cohort, how the first metastatic organ and the tumour molecular subtype jointly influence breast cancer specific survival (BCSS) among women diagnosed with dnMBC between 2010 and 2022. Methods: Using the US SEER-17 Research database (diagnoses 2010-2022), we identified women presenting with dnMBC (N = 38,078). Molecular subtype was derived from estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2) status and classified as hormone receptor positive/HER2-negative (HR+/HER2-), HR+/HER2+, HR-/HER2+, or triple negative breast cancer (TNBC). The first metastatic organ was coded from SEER Combined Mets at Diagnosis (bone, brain, liver, lung, multiple, other/unspecified). BCSS was estimated with Kaplan Meier curves, and multivariable Cox models adjusted for age, race/ethnicity and grade generated adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs). Reference categories were bone only (site) and HR-/HER2+ (subtype). Sensitivity analysis excluded unknown organ codes. Results: Spread pattern: Bone only metastasis predominated (59% overall; 73% in HR+/HER2-). Liver only, lung only and brain only spread accounted for 20%, 14% and 7%, respectively; 28% presented with ≥ 2 metastatic organs. TNBC showed the highest lung or multi-site involvement (≥ 35%). Survival: Five year BCSS differed markedly by site (log-rank p &amp;lt; 0.001): bone 31%, liver 12%, lung 14%, brain 5%, multiple 8%. Adjusted prognosis: Brain only metastasis carried the poorest outlook versus bone only (aHR 1.78, 95% CI 1.60-1.98), closely followed by multi organ dissemination (1.81, 1.76-1.87). Liver only disease conferred intermediate risk (1.33, 1.26-1.41), whereas lung only spread did not differ significantly from bone (1.03, 0.98-1.07; p = 0.30). Relative to HR-/HER2+ tumours, HR+/HER2+ showed the most favourable prognosis (0.75, 0.71-0.79); HR+/HER2- provided a modest benefit (0.88, 0.83-0.92); and TNBC more than doubled the risk of breast-cancer death (2.27, 2.14-2.40). All aHRs shifted by &amp;lt; 5% after excluding unknown sites. Conclusions: The first metastatic organ and tumour molecular subtype independently determine prognosis in dnMBC. Brain involvement and multi organ dissemination portend the worst survival, whereas lung only disease is comparable to bone only after adjustment. HR+/HER2+ tumours confer the most favourable subtype profile, while TNBC remains high risk. These findings support subtype guided imaging and site specific eligibility stratification in metastatic clinical trials. Citation Format: P. Jain, R. Patel, N. Ganatra, M. Patel, A. Jamal, S. Patel, S. Modi, T. Naqvi. Organ specific metastasis and survival across molecular subtypes in de novo stage IV breast cancer: A population based retrospective cohort study, 2010-2022 [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-09-28.

Purpose To investigate the performance of tumor subtype and various magnetic resonance (MR) imaging parameters in the assessment of tumor response to neoadjuvant systemic therapy (NST) in patients with breast cancer and to outline a model of pathologic response, considering pathologic complete response (pCR) as the complete absence of any residual invasive cancer or ductal carcinoma in situ (DCIS). Materials and Methods This was an institutional review board-approved retrospective study, with waiver of the need to obtain informed consent. From November 2009 to December 2014, 111 patients with histopathologically confirmed invasive breast cancer who were undergoing NST were included (mean age, 54 years; range, 27-84 years). Breast MR imaging was performed before and after treatment. Presence of late enhancement was assessed. Apparent diffusion coefficients (ADCs) were obtained by using two different methods. ADC ratio (mean posttreatment ADC/mean pretreatment ADC) was calculated. pCR was defined as absence of any residual invasive cancer or DCIS. Multivariate regression analysis and receiver operating characteristic analysis were performed. Results According to their immunohistochemical (IHC) profile, tumors were classified as human epidermal growth factor receptor 2 (HER2) positive (n = 51), estrogen receptor (ER) positive/HER2 negative (n = 40), and triple negative (n = 20). pCR was achieved in 19% (21 of 111) of cases; 86% of them were triple-negative or HER2-positive subtypes. Absence of late enhancement at posttreatment MR imaging was significantly associated with pCR (area under the curve [AUC], 0.85). Mean ADC ratio significantly increased when pCR was achieved (P < .001). A κ value of 0.479 was found for late enhancement (P < .001), and the intraclass correlation coefficient for ADCs was 0.788 (P < .001). Good correlation of ADCs obtained with the single-value method and those obtained with the mean-value methods was observed. The model combining the IHC subtype, ADC ratio, and late enhancement had the highest association with pathologic response, achieving an AUC of 0.92 (95% confidence interval: 0.86, 0.97). Conclusion Triple-negative or HER2-positive tumors showing absence of late enhancement and high ADC ratio after NST are associated with pCR. © RSNA, 2016 Online supplemental material is available for this article.

PurposeTriple-negative breast cancer (TNBC) has some distinctive features. The aim of the study was to compare clinical and breast magnetic resonance imaging (MRI) findings of TNBC with non-triple-negative breast cancer (nTNBC) in molecular subtypes such as ADC (apparent diffusion coefficient) values, T2-weighted (T2W) image intensity, shape, margin, lymph node involvement, grade, multifocality, multicentricity, bilaterality, and enhancement pattern differences between tumour subtypes.Material and methodsA total of 141 patients who underwent breast biopsy at our institution between January 2010 and June 2018 were included in this study. Patients were divided into molecular subtypes according to hormone receptor status, and Ki-67 index. Tumour grade, enhancement patterns, age, lymph node involvement, ADC values, breast imaging reporting and data system (BI-RADS) category, bilaterality, multifocality, multicentricity, margin, shape, and T2W image intensity were evaluated for these subtypes.ResultsADC values were higher in triple-negative tumours than in luminal A and luminal B tumours (p = 0.010 and p = 0.002, respectively). Circumscribed margin, type 2 enhancement curve, and rim enhancement were significantly higher in triple-negative tumours (p < 0.001). No significant difference was found between the groups in terms of other MRI findings including bilaterality, multifocality, multicentricity, shape, and T2W image intensity (p > 0.05).ConclusionsADC values, circumscribed margin, and rim enhancement can provide important information about the tumour’s biological behaviour and the course of the disease.

Abstract #4012 Recent data suggests that breast MRI is a more sensitive diagnostic test for detecting invasive breast cancer than mammography or breast ultrasound. Breast MRI may be particularly useful in younger premenopausal women with higher density breast tissue for differentiating between dense fibroglandular breast tissue and breast malignancies. The primary objective of this study was to determine the impact of pre-operative breast MRI on surgical decision-making in young women with breast cancer.&amp;#x2028; Methods: A retrospective review of 32 patients with newly diagnosed invasive breast cancer and age ≤ 50 was performed. All patients underwent a physical examination, preoperative mammogram, breast ultrasound, and bilateral breast MRI. Two breast cancer surgeons reviewed the preoperative mammogram report, breast ultrasound report, and physical examination summary for each case and were asked if they would recommend a lumpectomy, quandrantectomy, or mastectomy. A few weeks later, the two surgeons were shown the same information with the breast MRI report and were asked what type of surgery they would now recommend. In each case, MRI was classified by two adjudicators as having affected the surgical outcome in a positive, negative, or neutral fashion. A 'Positive Impact' was defined as the situation where breast MRI detected additional disease that was not found on physical exam, mammogram, or breast ultrasound and led to an appropriate change in surgical management. A 'Negative Impact' was defined as the situation where the breast MRI results led the surgeon to recommend more extensive surgery, with less extensive disease actually found at pathology. 'No Impact' was defined as the situation where MRI findings did not alter surgical recommendations or outcome.&amp;#x2028; Results: The median age was 41.5 years. The pathologic diagnosis was invasive ductal carcinoma in 94% (30/32) and invasive lobular carcinoma in 6% (2/32) of cases. For surgeon A, clinical management was altered in 21/32 (66%) of cases, and for surgeon B, management was altered in 13/32 (41%) of cases. The most common change in surgical decision-making after breast MRI was from breast conserving surgery to a mastectomy. Mastectomy rates were similar between both surgeons after breast MRI. After reviewing the pathology results and comparing them with the breast MRI results, it was determined that breast MRI led to a positive outcome in 13/32 cases (41%). Breast MRI led to no change in surgical management in 15/32 (47%) cases and resulted in a negative change in surgical management in 4/32 (13%) cases. Bilateral breast MRI detected a contralateral breast cancer in 2/32 (6%) patients.&amp;#x2028; Conclusions: Preoperative breast MRI appears to result in a change in surgical management in a significant proportion of younger women. Further research is needed to determine if this change in surgical decision-making will result in improved local control. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4012.

Distribution and prognosis of molecular breast cancer subtypes defined by immunohistochemical biomarkers in a Spanish population-based study