Triple-negative breast cancer: Pretreatment magnetic resonance imaging features and clinicopathological factors associated with recurrence

A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives

Breast cancer is one of the most common and deadly cancers worldwide. Approximately, 20% of all breast cancers are characterized as triple negative (TNBC). TNBC typically is associated with a poorer prognosis relative to other breast cancer subtypes. Due to its aggressiveness and lack of response to hormonal therapy, conventional cytotoxic chemotherapy is the usual treatment; however, this treatment is not always effective, and an important percentage of patients develop recurrence. More recently, immunotherapy has started to be used on some populations with TNBC showing promising results. Unfortunately, immunotherapy is only applicable to a minority of patients and responses in metastatic TNBC have overall been modest in comparison to other cancer types. This situation evidences the need for developing effective biomarkers that help to stratify and personalize patient management. Thanks to recent advances in artificial intelligence (AI), there has been an increasing interest in its use for medical applications aiming at supporting clinical decision making. Several works have used AI in combination with diagnostic medical imaging, more specifically radiology and digitized histopathological tissue samples, aiming to extract disease-specific information that is difficult to quantify by the human eye. These works have demonstrated that analysis of such images in the context of TNBC has great potential for (1) risk-stratifying patients to identify those patients who are more likely to experience disease recurrence or die from the disease and (2) predicting pathologic complete response. In this manuscript, we present an overview on AI and its integration with radiology and histopathological images for developing prognostic and predictive approaches for TNBC. We present state of the art approaches in the literature and discuss the opportunities and challenges with developing AI algorithms regarding further development and clinical deployment, including identifying those patients who may benefit from certain treatments (e.g., adjuvant chemotherapy) from those who may not and thereby should be directed toward other therapies, discovering potential differences between populations, and identifying disease subtypes.

Triple-negative breast cancer: predictive model of early recurrence based on MRI features

AIM

To develop an integrated model based on preoperative magnetic resonance imaging (MRI) features for predicting early recurrence in patients with triple-negative breast cancer (TNBC).

MATERIALS AND METHODS

Women with TNBC who underwent breast MRI and surgery between 2009 and 2019 were evaluated retrospectively. Two breast radiologists reviewed MRI images independently based on the Breast Imaging Reporting and Data System Lexicon (BI-RADS), and classified the breast oedema scores on T2-weighted imaging (WI) as no oedema, peritumoural oedema, prepectoral oedema, or subcutaneous oedema. The relationship between disease-free survival (DFS) and MRI features was analysed by Cox regression, and a nomogram model was generated based on the results.

RESULTS

150 patients with TNBC were included and divided into a training cohort (n=78) and validation cohort (n=72). MRI features including subcutaneous oedema and rim enhancement showed a tendency to worsen DFS in univariate analysis. Multivariate analysis showed that subcutaneous oedema (p=0.049, HR [95% confidence interval {CI} = 8.24 [1.01-67.52]) and rim enhancement (p=0.016, HR [95% CI] = 4.38 [1.32-14.54]) were independent predictors for DFS. In the nomogram, the areas under the curves (AUCs) of the training cohort was 0.808, and that of the validation cohort was 0.875.

CONCLUSION

The presence of subcutaneous oedema or rim enhancement on preoperative breast MRI was shown to be a good predictor of poor survival outcomes in patients with TNBC.

Triple-Negative Breast Cancer: Histopathologic Features, Genomics, and Treatment

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive group of tumors that are defined by the absence of estrogen and progesterone receptors and lack of ERBB2 (formerly HER2 or HER2/neu) overexpression. TNBC accounts for 8%-13% of breast cancers. In addition, it accounts for a higher proportion of breast cancers in younger women compared with those in older women, and it disproportionately affects non-Hispanic Black women. TNBC has high metastatic potential, and the risk of recurrence is highest during the 5 years after it is diagnosed. TNBC exhibits benign morphologic imaging features more frequently than do other breast cancer subtypes. Mammography can be suboptimal for early detection of TNBC owing to factors that include the fast growth of this cancer, increased mammographic density in young women, and lack of the typical features of malignancy at imaging. US is superior to mammography for TNBC detection, but benign-appearing features can lead to misdiagnosis. Breast MRI is the most sensitive modality for TNBC detection. Most cases of TNBC are treated with neoadjuvant chemotherapy, followed by surgery and radiation. MRI is the modality of choice for evaluating the response to neoadjuvant chemotherapy. Survival rates for individuals with TNBC are lower than those for persons with hormone receptor-positive and human epidermal growth factor receptor 2-positive cancers. The 5-year survival rates for patients with localized, regional, and distant disease at diagnosis are 91.3%, 65.8%, and 12.0%, respectively. The early success of immunotherapy has raised hope regarding the development of personalized strategies to treat TNBC. Imaging and tumor biomarkers are likely to play a crucial role in the prediction of TNBC treatment response and TNBC patient survival in the future. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

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

Background

Breast cancer (BC) includes different pathological and molecular subtypes. This study aimed to investigate whether multiparametric magnetic resonance imaging (mpMRI) could reliably predict the molecular status of BC, comparing mpMRI features with pathological and immunohistochemical results.

Methods

This retrospective study included 156 patients with an ultrasound-guided biopsy-proven BC, who underwent breast mpMRI (including diffusion-weighted imaging) on a 3-T scanner from 2017 to 2020. Histopathological analyses were performed on the surgical specimens. Kolmogorov–Smirnov Z, χ², and univariate and multivariate logistic regression analyses were performed.

Results

Fifteen patients were affected with ductal carcinoma in situ, 122 by invasive carcinoma of no special type, and 19 with invasive lobular carcinoma. Out of a total of 141 invasive cancers, 45 were luminal A-like, 54 luminal B-like, 5 human epidermal growth factor receptor 2 (HER2) positive, and 37 triple negative. The regression analyses showed that size < 2 cm predicted luminal A-like status (p = 0.025), while rim enhancement (p < 0.001), intralesional necrosis (p = 0.001), peritumoural oedema (p < 0.001), and axillary adenopathies (p = 0.012) were negative predictors. Oppositely, round shape (p = 0.001), rim enhancement (p < 0.001), intralesional necrosis (p < 0.001), and peritumoural oedema (p < 0.001) predicted triple-negative status.

Conclusions

mpMRI has been confirmed to be a valid noninvasive predictor of BC subtypes, especially luminal A and triple negative. Considering the central role of pathology in BC diagnosis and immunohistochemical profiling in the current precision medicine era, a detailed radiologic-pathologic correlation seems vital to properly evaluate BC.

Immunohistochemical signaling pathways of triple negative and triple positive breast cancers: What is new?

BACKGROUND

Breast cancer (BC) is a heterogeneous disease with different clinically heterogeneous phenotypes. Triple negative BC (TNBC) (ER-/PR-/HER2-) and triple positive BC (TPBC) (ER+/PR+/HER2+) are characterized by unique clinical behavior and therapeutic challenges. However, their exact molecular pathogenesis is not well studied. This study aims to evaluate the immunohistochemical expression of androgen receptor (AR) and c-Myc in TPBCs and TNBCs, correlate their expression with the clinicopathologic features, and assess the correlation between AR and c-Myc expression in TPBCs and TNBCs.

MATERIAL AND METHODS

AR and c-Myc were immunohistochemically assessed in 45 TNBC and 15 TPBC specimens.

RESULTS

AR expression was detected in 17.7% of TNBC and in all TPBC specimens. c-Myc was expressed in 46.7% of TNBC and in all TPBC specimens. AR and c-Myc expression in TNBC was not associated with any of the clinicopathological features. In TPBC, AR expression was higher in older age, larger size, higher stage, and lymph node metastasis while c-Myc expression was higher in tumors with perineural invasion. This is the first study that reported a significant positive correlation between AR and c-Myc expression in TNBC and TPBC.

CONCLUSION

The current results suggested that AR and c-Myc proteins may contribute to the pathogenesis of TNBC and TPBC. The positive correlation between the two proteins in these subtypes sheds new light on a distinct pathway by which BC cells can modulate their proliferation. Targeting both molecules may provide new therapeutic approaches to improve therapeutic sensitivity and patients' outcomes of these subtypes.

Background Parenchymal Enhancement on Breast MRI: Assessment and Clinical Implications

Purpose of Review

To present recent literature regarding the assessment and clinical implications of background parenchymal enhancement on breast MRI.

Recent Findings

The qualitative assessment of BPE remains variable within the literature, as well as in clinical practice. Several different quantitative approaches have been investigated in recent years, most commonly region of interest-based and segmentation-based assessments. However, quantitative assessment has not become standard in clinical practice to date. Numerous studies have demonstrated a clear association between higher BPE and future breast cancer risk. While higher BPE does not appear to significantly impact cancer detection, it may result in a higher abnormal interpretation rate. BPE is also likely a marker of pathologic complete response after neoadjuvant chemotherapy, with decreases in BPE during and after neoadjuvant chemotherapy correlated with pCR. In contrast, pre-treatment BPE does not appear to be predictive of pCR. The association between BPE and prognosis is less clear, with heterogeneous results in the literature.

Summary

Assessment of BPE continues to evolve, with heterogeneity in approaches to both qualitative and quantitative assessment. The level of BPE has important clinical implications, with associations with future breast cancer risk and treatment response. BPE may also be an imaging marker of prognosis, but future research is needed on this topic.

Features from MRI texture analysis associated with survival outcomes in triple-negative breast cancer patients

PURPOSE

The purpose of the study is to evaluate the associations between intratumoral or peritumoral textural features derived from pretreatment magnetic resonance imaging (MRI) and recurrence-free survival (RFS) in triple-negative breast cancer (TNBC) patients.

METHODS

Forty-three patients with TNBC who underwent preoperative MRI between February 2008 and March 2014 were included. We performed two-dimensional texture analysis on the intratumoral or peritumoral region of interest (ROI) on axial of T2-weighted image (T2WI), dynamic contrast-enhanced (DCE)-MRI and DCE-MRI subtraction images. We also analyzed histopathological data. Cox proportional hazards models were used to investigate associations with survival outcomes.

RESULTS

Twelve of the 43 patients (27.9%) had recurrence disease, at a median of 32.5 months follow-up (1.4-61.5 months). In univariate analysis, nine texture features in T2WI and DCE-MRI subtraction images were significantly associated with RFS. In multivariate analysis, intratumoral difference entropy in DCE-MRI subtraction images in the initial phase (hazard ratio 11.71; 95% confidence interval (CI) [1.41, 97.00]; p value 0.023) and, peritumoral difference variance in DCE-MRI subtraction images in the delayed phase (hazard ratio 9.60; 95% CI [1.98, 46.51]; p value 0.005), were both independently associated with RFS. Moreover, multivariate analysis revealed the presence of lymphovascular invasion as independently associated with RFS (hazard ratio 8.13; 95% CI [2.16, 30.30]; p value 0.002).

CONCLUSIONS

At pretreatment MRI, an intratumoral and peritumoral quantitative approach using texture analysis has the potential to serve as a prognostic marker in patients with TNBC.

Preoperative Rim Enhancement on Magnetic Resonance Imaging Indicates Larger Tumor Size and Poor Prognosis in Chinese Basal-Like Breast Cancer Patients

Background: This study was to investigate the prevalence of preoperative rim enhancement, and its association with clinicopathological features, relapse, and survival profiles in Chinese basal-like breast cancer (BC) patients. Materials and Methods: The preoperative breast magnetic resonance imaging images of 145 basal-like BC patients who underwent surgical excision were obtained to determine rim enhancement. Besides, based on disease status and survival status during follow-up, the 1-year relapse rate/mortality, 3-year relapse rate/mortality, 5-year relapse rate/mortality were calculated; disease-free survival (DFS) and overall survival (OS) were determined. Results: There were 51 (35.2%) patients with rim enhancement and 94 (64.8%) patients without rim enhancement. Furthermore, rim enhancement was associated with larger tumor size and advanced T stage, whereas it did not associate with age, pathological differentiation, N stage, or TNM stage. In addition, rim enhancement was associated with higher 1-, 3-, and 5-year relapse rate and shorter DFS; meanwhile, rim enhancement was associated with increased 1-, 3-, and 5-year mortality rate and decreased OS. By multivariate Cox's regression analyses, rim enhancement, pathological differentiation, and N stage independently predicted reduced DFS; T stage independently predicted declined OS. Conclusion: Preoperative rim enhancement on MRI might be a possible noninvasive indicator for guiding personalized treatment strategies and improving prognosis in Chinese basal-like BC patients.

Can MRI Biomarkers Predict Triple-Negative Breast Cancer?

The purpose of this study was to investigate MRI features of triple-negative breast cancer (TNBC) compared with non-TNBC, to predict histopathological results. In the study, 26 patients with TNBC and 24 with non-TNBC who underwent multiparametric MRI of the breast on a 3 T magnet over a 10-months period were retrospectively recruited. MR imaging sets were evaluated by two experienced breast radiologists in consensus and classified according to the 2013 American College of Radiology (ACR) BI-RADS lexicon. The comparison between the two groups was performed using the Chi-square test and followed by logistic regression analyses. We found that 92% of tumors presented as mass enhancements (p = 0.192). 41.7% of TNBC and 86.4% of non-TNBC had irregular shape (p = 0.005); 58.3% of TNBC showed circumscribed margins, compared to 9.1% of non-TNBC masses (p = 0.001); 75% of TNBC and 9.1% of non-TNBC showed rim enhancement (p < 0.001). Intralesional necrosis was significantly associated with TNBC (p = 0.016). Rim enhancement and intralesional necrosis risulted to be positive predictors at univariate analysis (OR = 29.86, and 8.10, respectively) and the multivariate analysis confirmed that rim enhancement is independently associated with TNBC (OR = 33.08). The mean ADC values were significantly higher for TNBC (p = 0.011). In conclusion, TNBC is associated with specific MRI features that can be possible predictors of pathological results, with a consequent prognostic value.