3 research outputs found
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Evaluation of Breast Imaging Biomarkers for Breast Cancer Future Risk and Treatment Response
Imaging biomarkers are representations of an in vivo biological state and phenotype. The incorporation of breast density in breast cancer risk models, as well as state-mandated reporting of mammographic breast density to women, underscores the central role of imaging biomarkers in risk assessment. In this dissertation, I evaluate breast imaging biomarkers from breast MRI and mammography in their role of future risk prediction and treatment response. The chapters, ordered chronologically, show the evolution of my research interests from quantitative imaging science within a well-controlled experimental trial (Chapter 1), to a population-based evaluation of qualitative clinically derived imaging assessments in an observational cohort (Chapter 2), to finally combining quantitative imaging science for comparative evaluations through a population-based pragmatic assessment in a large managed health system (Chapter 3).Chapters 1 and 2 focus on background parenchymal enhancement (BPE), which describes the natural phenomenon observed on breast MRI in which normal breast tissue demonstrates signal enhancement related to uptake of intravenous contrast. Biologically, BPE is believed to represent tissue “activated” by endogenous hormones (primarily estrogen) and is dynamic in appearance over time and distribution within a woman’s breast tissue. Chapter 1 focuses on manually defined quantitative imaging biomarkers in the experimental I-SPY 2 trial, an on-going multicenter prospective randomized clinical trial framework used to monitor treatment response and assess novel investigational neoadjuvant chemotherapy (NAC) agents for breast cancer. Women with advanced HER2- breast cancer have limited treatment options. Breast MRI functional tumor volume (FTV) is used to predict pathologic complete response (pCR) to improve treatment efficacy. In addition to FTV, background parenchymal enhancement (BPE) may predict response and was explored for HER2- patients in the ISPY-2 TRIAL. We found that among women with HER2- cancer, BPE alone demonstrated association with pCR in women with HR+HER2- breast cancer, with similar diagnostic performance to FTV. BPE predictors remained significant in multivariate FTV models, but without added discrimination for pCR prediction. This may be due to small sample size limiting ability to create subtype specific multivariate models.Chapter 2 extends BPE evaluation through comparative associations of qualitative BPE and mammographic breast density for future risk in a population-based assessment using the Breast Cancer Surveillance Consortium (BCSC), involving 46 radiology facilities that participate in one of six regional BCSC registries. Higher levels of BPE were found to be associated with future invasive breast cancer risk independent of breast density. The combination of both high BPE and high breast density was associated with higher risk than either factor alone. BPE also demonstrates subtype specific associations with less aggressive disease, although the association with aggressive disease was noted at moderate and marked levels.Finally, Chapter 3 examines whether using computer vision artificial intelligence (AI)–based computer vision algorithms, most of which are trained to extract features from mammograms to detect visible breast cancer, can also predict future risk using a population-based case cohort from the Kaiser Permanente Northern California managed health system. We found that all AI mammography algorithms evaluated had clinically and statistically significantly higher discrimination than the BCSC clinical risk model for interval cancer and 5-year future cancer risk, indicating their usefulness. The combination of BCSC and AI further improves risk prediction above AI alone, and decreases the gap in future risk performance between AI algorithms. Training AI algorithms to predict longer-term outcomes may yield further improvements, but the potential impact on clinical decisions requires further study
Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.
Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant -chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with -inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue
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Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.
Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue