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Virostko J, Kuketz G, Higgins E, Wu C, Sorace AG, DiCarlo JC, Avery S, Patt D, Goodgame B, Yankeelov TE. The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy. Eur J Radiol 2021; 136:109534. [PMID: 33454460 PMCID: PMC7897312 DOI: 10.1016/j.ejrad.2021.109534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 12/11/2020] [Accepted: 01/05/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE This study assesses the rate of enhancement of breast fibroglandular tissue after administration of a magnetic resonance imaging (MRI) gadolinium-based contrast agent and determines its relationship with response to neoadjuvant therapy (NAT) in women with breast cancer. METHOD Women with locally advanced breast cancer (N = 19) were imaged four times over the course of NAT. Dynamic contrast-enhanced (DCE) MRI was acquired after administration of a gadolinium-based contrast agent with a temporal resolution of 7.27 s. The tumor, fibroglandular tissue, and adipose tissue were semi-automatically segmented using a manually drawn region of interest encompassing the tumor followed by fuzzy c-means clustering. The rate and relative intensity of signal enhancement were calculated for each voxel within the tumor and fibroglandular tissue. RESULTS The rate of fibroglandular tissue enhancement after contrast agent injection declined by an average of 29 % over the course of NAT. This decline was present in 16 of the 19 patients in the study. The rate of enhancement is significantly higher in women who achieve pathological complete response (pCR) after both 1 cycle (68 % higher, p < 0.05) and after 3-5 cycles of NAT (58 % higher; p < 0.05). The relative intensity of fibroglandular enhancement correlates with the rate of enhancement (R2 = 0.64, p < 0.001) and is higher in women who achieve pCR after both 1 cycle and after 3-5 cycles of NAT (p < 0.05, both timepoints). CONCLUSION The rate of fibroglandular tissue enhancement declines over the course of therapy, provides novel information not reflected by tumoral measures, and may predict pathological response early in the course of therapy, with smaller declines in enhancement in women who achieve favorable response.
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Affiliation(s)
- John Virostko
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, TX, USA; Livestrong Cancer Institutes, University of Texas at Austin, Austin, TX, USA; Department of Oncology, University of Texas at Austin, Austin, TX, USA.
| | - Garrett Kuketz
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Erin Higgins
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Chengyue Wu
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Anna G Sorace
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, USA; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Julie C DiCarlo
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX, USA
| | - Sarah Avery
- Austin Radiological Association, Austin, TX, USA
| | | | - Boone Goodgame
- Seton Hospital, Austin, TX, USA; Department of Internal Medicine, University of Texas at Austin, Austin, TX, USA
| | - Thomas E Yankeelov
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, TX, USA; Livestrong Cancer Institutes, University of Texas at Austin, Austin, TX, USA; Department of Oncology, University of Texas at Austin, Austin, TX, USA; Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA; Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX, USA; Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA
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Are contralateral parenchymal enhancement on dynamic contrast-enhanced MRI and genomic ER-pathway activity in ER-positive/HER2-negative breast cancer related? Eur J Radiol 2019; 121:108705. [PMID: 31655316 DOI: 10.1016/j.ejrad.2019.108705] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 10/07/2019] [Accepted: 10/11/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE To retrospectively explore the relation between parenchymal enhancement of the healthy contralateral breast on dynamic contrast-enhanced magnetic resonance imaging (MRI) and genomic tests for estrogen receptor (ER)-pathway activity in patients with ER-positive/HER2-negative cancer. METHODS A subset of 227 consecutively included patients with unilateral invasive ER-positive/HER2-negative breast cancer underwent dynamic contrast-enhanced MRI prior to breast-conserving therapy between 2000 and 2008. Perfusion of the parenchyma in the healthy breast was assessed using a previously reported measure of contralateral parenchymal enhancement (CPE), consisting of the mean of the top-10% late enhancement. ER-pathway activity was assessed from the surgical resection specimen by the previously reported sensitivity to endocrine therapy (SET)-index and ER-factor. The SET-index is a genetic test to estimate survival benefit from endocrine therapy, consisting of genes related to the ESR1 gene. The ER-factor examines other factors as well including protein expression. The relation between CPE and ER-pathway activity was modeled using linear regression. RESULTS Patients had a median age of 59 years. CPE was not significantly associated with the SET-index (R-squared = 0.005) nor the ER-factor (R-squared = 0.0002). The only variable significantly different between low and high CPE was age at diagnosis (P < 0.001). CONCLUSIONS Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI was not associated with tumor-derived estrogen receptor pathway activity.
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Lee JW, Kim SY, Lee HJ, Han SW, Lee JE, Lee SM. Prognostic Significance of CT-Attenuation of Tumor-Adjacent Breast Adipose Tissue in Breast Cancer Patients with Surgical Resection. Cancers (Basel) 2019; 11:E1135. [PMID: 31398863 PMCID: PMC6721593 DOI: 10.3390/cancers11081135] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 08/03/2019] [Accepted: 08/06/2019] [Indexed: 02/06/2023] Open
Abstract
The purpose of this study was to evaluate the prognostic significance of computed tomography (CT)-attenuation of tumor-adjacent breast adipose tissue for predicting recurrence-free survival (RFS) in patients with breast cancer. We retrospectively enrolled 287 breast cancer patients who underwent pretreatment 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT. From non-contrast-enhanced CT images of PET/CT, CT-attenuation values of tumor-adjacent breast adipose tissue (TAT HU) and contralateral breast adipose tissue (CAT HU) were measured. Difference (HU difference) and percent difference (HU difference %) in CT-attenuation values between TAT HU and CAT HU were calculated. The relationships of these breast adipose tissue parameters with tumor factors and RFS were assessed. TAT HU was significantly higher than CAT HU (p < 0.001). TAT HU, HU difference, and HU difference % showed significant correlations with T stage and estrogen receptor and progesterone receptor status (p < 0.05), whereas CAT HU had no significant relationships with tumor factors (p > 0.05). Patients with high TAT HU, HU difference, and HU difference % had significantly worse RFS than those with low values (p < 0.001). In multivariate analysis, TAT HU and HU difference % were significantly associated with RFS after adjusting for clinico-pathologic factors (p < 0.05). CT-attenuation of tumor-adjacent breast adipose tissue was significantly associated with RFS in patients with breast cancer. The findings seem to support the close contact between breast cancer cells and tumor-adjacent adipocytes observed with imaging studies.
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Affiliation(s)
- Jeong Won Lee
- Department of Nuclear Medicine, International St. Mary's Hospital, Catholic Kwandong University College of Medicine, 25 Simgok-ro 100 beon-gil, Seo-gu, Incheon 22711, Korea
| | - Sung Yong Kim
- Department of Surgery, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Korea
| | - Hyun Ju Lee
- Department of Pathology, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Korea
| | - Sun Wook Han
- Department of Surgery, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Korea
| | - Jong Eun Lee
- Department of Surgery, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Korea
| | - Sang Mi Lee
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 31 Suncheonhyang 6-gil, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Korea.
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Braman N, Prasanna P, Whitney J, Singh S, Beig N, Etesami M, Bates DDB, Gallagher K, Bloch BN, Vulchi M, Turk P, Bera K, Abraham J, Sikov WM, Somlo G, Harris LN, Gilmore H, Plecha D, Varadan V, Madabhushi A. Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for HER2 (ERBB2)-Positive Breast Cancer. JAMA Netw Open 2019; 2:e192561. [PMID: 31002322 PMCID: PMC6481453 DOI: 10.1001/jamanetworkopen.2019.2561] [Citation(s) in RCA: 193] [Impact Index Per Article: 38.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
IMPORTANCE There has been significant recent interest in understanding the utility of quantitative imaging to delineate breast cancer intrinsic biological factors and therapeutic response. No clinically accepted biomarkers are as yet available for estimation of response to human epidermal growth factor receptor 2 (currently known as ERBB2, but referred to as HER2 in this study)-targeted therapy in breast cancer. OBJECTIVE To determine whether imaging signatures on clinical breast magnetic resonance imaging (MRI) could noninvasively characterize HER2-positive tumor biological factors and estimate response to HER2-targeted neoadjuvant therapy. DESIGN, SETTING, AND PARTICIPANTS In a retrospective diagnostic study encompassing 209 patients with breast cancer, textural imaging features extracted within the tumor and annular peritumoral tissue regions on MRI were examined as a means to identify increasingly granular breast cancer subgroups relevant to therapeutic approach and response. First, among a cohort of 117 patients who received an MRI prior to neoadjuvant chemotherapy (NAC) at a single institution from April 27, 2012, through September 4, 2015, imaging features that distinguished HER2+ tumors from other receptor subtypes were identified. Next, among a cohort of 42 patients with HER2+ breast cancers with available MRI and RNaseq data accumulated from a multicenter, preoperative clinical trial (BrUOG 211B), a signature of the response-associated HER2-enriched (HER2-E) molecular subtype within HER2+ tumors (n = 42) was identified. The association of this signature with pathologic complete response was explored in 2 patient cohorts from different institutions, where all patients received HER2-targeted NAC (n = 28, n = 50). Finally, the association between significant peritumoral features and lymphocyte distribution was explored in patients within the BrUOG 211B trial who had corresponding biopsy hematoxylin-eosin-stained slide images. Data analysis was conducted from January 15, 2017, to February 14, 2019. MAIN OUTCOMES AND MEASURES Evaluation of imaging signatures by the area under the receiver operating characteristic curve (AUC) in identifying HER2+ molecular subtypes and distinguishing pathologic complete response (ypT0/is) to NAC with HER2-targeting. RESULTS In the 209 patients included (mean [SD] age, 51.1 [11.7] years), features from the peritumoral regions better discriminated HER2-E tumors (maximum AUC, 0.85; 95% CI, 0.79-0.90; 9-12 mm from the tumor) compared with intratumoral features (AUC, 0.76; 95% CI, 0.69-0.84). A classifier combining peritumoral and intratumoral features identified the HER2-E subtype (AUC, 0.89; 95% CI, 0.84-0.93) and was significantly associated with response to HER2-targeted therapy in both validation cohorts (AUC, 0.80; 95% CI, 0.61-0.98 and AUC, 0.69; 95% CI, 0.53-0.84). Features from the 0- to 3-mm peritumoral region were significantly associated with the density of tumor-infiltrating lymphocytes (R2 = 0.57; 95% CI, 0.39-0.75; P = .002). CONCLUSIONS AND RELEVANCE A combination of peritumoral and intratumoral characteristics appears to identify intrinsic molecular subtypes of HER2+ breast cancers from imaging, offering insights into immune response within the peritumoral environment and suggesting potential benefit for treatment guidance.
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Affiliation(s)
- Nathaniel Braman
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Prateek Prasanna
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Jon Whitney
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Salendra Singh
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio
| | - Niha Beig
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Maryam Etesami
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - David D. B. Bates
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Katherine Gallagher
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - B. Nicolas Bloch
- Department of Radiology, Boston Medical Center, Boston, Massachusetts
- Department of Radiology, Boston University School of Medicine, Boston, Massachusetts
| | - Manasa Vulchi
- Department of Hematology and Medical Oncology, The Cleveland Clinic, Cleveland, Ohio
| | - Paulette Turk
- Department of Diagnostic Radiology, The Cleveland Clinic, Cleveland, Ohio
| | - Kaustav Bera
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Jame Abraham
- Department of Hematology and Medical Oncology, The Cleveland Clinic, Cleveland, Ohio
| | - William M. Sikov
- Program in Women’s Oncology, Women and Infants Hospital, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - George Somlo
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California
- Department of Hematology and Hematopoietic Cell Transplantation, City of Hope National Medical Center, Duarte, California
| | - Lyndsay N. Harris
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio
- National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Hannah Gilmore
- Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Donna Plecha
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Vinay Varadan
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio
| | - Anant Madabhushi
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
- Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, Ohio
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Olshen A, Wolf D, Jones EF, Newitt D, van ‘t Veer LJ, Yau C, Esserman L, Wulfkuhle JD, Gallagher RI, Singer L, Petricoin EF, Hylton N, Park CC. Features of MRI stromal enhancement with neoadjuvant chemotherapy: a subgroup analysis of the ACRIN 6657/I-SPY TRIAL. J Med Imaging (Bellingham) 2017; 5:011014. [PMID: 29296631 PMCID: PMC5741993 DOI: 10.1117/1.jmi.5.1.011014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 11/06/2017] [Indexed: 12/29/2022] Open
Abstract
Although the role of cancer-activated stroma in malignant progression has been well investigated, the influence of an activated stroma in therapy response is not well understood. Using retrospective pilot cohorts, we previously observed that MRI detected stromal contrast enhancement was associated with proximity to the tumor and was predictive for relapse-free survival in patients with breast cancer receiving neoadjuvant chemotherapy. Here, to evaluate the association of stromal contrast enhancement to therapy, we applied an advanced tissue mapping technique to evaluate stromal enhancement patterns within 71 patients enrolled in the I-SPY 1 neoadjuvant breast cancer trial. We correlated MR stromal measurements with stromal protein levels involved in tumor progression processes. We found that stromal percent enhancement values decrease with distance from the tumor edge with the estimated mean change ranging [Formula: see text] to [Formula: see text] ([Formula: see text]) for time points T2 through T4. While not statistically significant, we found a decreasing trend in global stromal signal enhancement ratio values with the use of chemotherapy. There were no statistically significant differences between MR enhancement measurements and stromal protein levels. Findings from this study indicate that stromal features characterized by MRI are impacted by chemotherapy and may have predictive value in a larger study.
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Affiliation(s)
- Adam Olshen
- University of California San Francisco, Department of Biostatistics and Epidemiology, San Francisco, California, United States.,University of California San Francisco, UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, California, United States
| | - Denise Wolf
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States
| | - Ella F Jones
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States
| | - David Newitt
- University of California San Francisco, Department of Surgery, San Francisco, California, United States
| | - Laura J van ‘t Veer
- University of California San Francisco, Department of Laboratory Medicine, San Francisco, California, United States
| | - Christina Yau
- University of California San Francisco, Department of Surgery, San Francisco, California, United States
| | - Laura Esserman
- University of California San Francisco, Department of Surgery, San Francisco, California, United States
| | - Julia D Wulfkuhle
- George Mason University, Center for Applied Proteomics and Molecular Medicine, Manassas, Virginia, United States
| | - Rosa I Gallagher
- George Mason University, Center for Applied Proteomics and Molecular Medicine, Manassas, Virginia, United States
| | - Lisa Singer
- University of California San Francisco, Department of Radiation Oncology, San Francisco, California, United States
| | - Emanuel F Petricoin
- George Mason University, Center for Applied Proteomics and Molecular Medicine, Manassas, Virginia, United States
| | - Nola Hylton
- University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States
| | - Catherine C Park
- University of California San Francisco, UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, California, United States.,University of California San Francisco, Department of Radiation Oncology, San Francisco, California, United States
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Wu J, Li B, Sun X, Cao G, Rubin DL, Napel S, Ikeda DM, Kurian AW, Li R. Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer. Radiology 2017; 285:401-413. [PMID: 28708462 DOI: 10.1148/radiol.2017162823] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Purpose To identify the molecular basis of quantitative imaging characteristics of tumor-adjacent parenchyma at dynamic contrast material-enhanced magnetic resonance (MR) imaging and to evaluate their prognostic value in breast cancer. Materials and Methods In this institutional review board-approved, HIPAA-compliant study, 10 quantitative imaging features depicting tumor-adjacent parenchymal enhancement patterns were extracted and screened for prognostic features in a discovery cohort of 60 patients. By using data from The Cancer Genome Atlas (TCGA), a radiogenomic map for the tumor-adjacent parenchymal tissue was created and molecular pathways associated with prognostic parenchymal imaging features were identified. Furthermore, a multigene signature of the parenchymal imaging feature was built in a training cohort (n = 126), and its prognostic relevance was evaluated in two independent cohorts (n = 879 and 159). Results One image feature measuring heterogeneity (ie, information measure of correlation) was significantly associated with prognosis (false-discovery rate < 0.1), and at a cutoff of 0.57 stratified patients into two groups with different recurrence-free survival rates (log-rank P = .024). The tumor necrosis factor signaling pathway was identified as the top enriched pathway (hypergeometric P < .0001) among genes associated with the image feature. A 73-gene signature based on the tumor profiles in TCGA achieved good association with the tumor-adjacent parenchymal image feature (R2 = 0.873), which stratified patients into groups regarding recurrence-free survival (log-rank P = .029) and overall survival (log-rank P = .042) in an independent TCGA cohort. The prognostic value was confirmed in another independent cohort (Gene Expression Omnibus GSE 1456), with log-rank P = .00058 for recurrence-free survival and log-rank P = .0026 for overall survival. Conclusion Heterogeneous enhancement patterns of tumor-adjacent parenchyma at MR imaging are associated with the tumor necrosis signaling pathway and poor survival in breast cancer. © RSNA, 2017 Online supplemental material is available for this article.
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Affiliation(s)
- Jia Wu
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Bailiang Li
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Xiaoli Sun
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Guohong Cao
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Daniel L Rubin
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Sandy Napel
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Debra M Ikeda
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Allison W Kurian
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
| | - Ruijiang Li
- From the Department of Radiation Oncology (J.W., B.L., R.L.), Department of Radiology (D.L.R., S.N., D.M.I.), Department of Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Department of Medicine (A.W.K.), Department of Health Research and Policy (A.W.K.), and Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Stanford, CA 94305; Department of Radiotherapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.); and Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.)
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Park VY, Kim EK, Kim MJ, Yoon JH, Moon HJ. Breast parenchymal signal enhancement ratio at preoperative magnetic resonance imaging: association with early recurrence in triple-negative breast cancer patients. Acta Radiol 2016; 57:802-8. [PMID: 26516288 DOI: 10.1177/0284185115609803] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2015] [Accepted: 09/02/2015] [Indexed: 12/31/2022]
Abstract
BACKGROUND The signal enhancement ratio (SER) of surrounding non-tumor parenchyma at breast magnetic resonance imaging (MRI) can be helpful in breast cancer patients, but has not been investigated in patients with triple negative breast cancer (TNBC). PURPOSE To investigate the association between background parenchymal SER around the tumor on preoperative dynamic contrast-enhanced MRI with recurrence-free survival in patients with TNBC. MATERIAL AND METHODS Between April 2012 and May 2013, 71 TNBC patients who underwent preoperative MRI were included. SER values were calculated from regions of interest placed in the breast parenchyma around the tumor. Cox proportional hazards models were used to determine associations between MRI variables, clinical-pathologic variables, and recurrence-free survival. RESULTS Recurrence occurred in 8.5% (6/71) of patients. At univariate analysis, a higher SER around the tumor, larger tumor size, lymphovascular invasion, lymph node metastasis, receipt of neoadjuvant chemotherapy, receipt of total mastectomy, and not receiving adjuvant chemotherapy were associated with worse recurrence-free survival. At multivariate analysis of preoperative variables, a higher SER around the tumor was independently associated with worse recurrence-free survival (hazard ratio [HR] = 7.072, P = 0.003 for SER1; HR = 6.268, P = 0.006 for SER2; HR = 3.004, P = 0.039 for SER3). CONCLUSION Higher SER around the tumor at preoperative dynamic contrast-enhanced MRI is an independent predictor for recurrence in TNBC patients.
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Affiliation(s)
- Vivian Youngjean Park
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eun-Kyung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Min Jung Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jung Hyun Yoon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hee Jung Moon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
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van der Velden BHM, Dmitriev I, Loo CE, Pijnappel RM, Gilhuijs KGA. Association between Parenchymal Enhancement of the Contralateral Breast in Dynamic Contrast-enhanced MR Imaging and Outcome of Patients with Unilateral Invasive Breast Cancer. Radiology 2015; 276:675-85. [DOI: 10.1148/radiol.15142192] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Guenther S, Muirhead LJ, Speller AVM, Golf O, Strittmatter N, Ramakrishnan R, Goldin RD, Jones E, Veselkov K, Nicholson J, Darzi A, Takats Z. Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry. Cancer Res 2015; 75:1828-37. [PMID: 25691458 DOI: 10.1158/0008-5472.can-14-2258] [Citation(s) in RCA: 122] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2014] [Accepted: 01/20/2015] [Indexed: 11/16/2022]
Abstract
Breast cancer is a heterogeneous disease characterized by varying responses to therapeutic agents and significant differences in long-term survival. Thus, there remains an unmet need for early diagnostic and prognostic tools and improved histologic characterization for more accurate disease stratification and personalized therapeutic intervention. This study evaluated a comprehensive metabolic phenotyping method in breast cancer tissue that uses desorption electrospray ionization mass spectrometry imaging (DESI MSI), both as a novel diagnostic tool and as a method to further characterize metabolic changes in breast cancer tissue and the tumor microenvironment. In this prospective single-center study, 126 intraoperative tissue biopsies from tumor and tumor bed from 50 patients undergoing surgical resections were subject to DESI MSI. Global DESI MSI models were able to distinguish adipose, stromal, and glandular tissue based on their metabolomic fingerprint. Tumor tissue and tumor-associated stroma showed evident changes in their fatty acid and phospholipid composition compared with normal glandular and stromal tissue. Diagnosis of breast cancer was achieved with an accuracy of 98.2% based on DESI MSI data (PPV 0.96, NVP 1, specificity 0.96, sensitivity 1). In the tumor group, correlation between metabolomic profile and tumor grade/hormone receptor status was found. Overall classification accuracy was 87.7% (PPV 0.92, NPV 0.9, specificity 0.9, sensitivity 0.92). These results demonstrate that DESI MSI may be a valuable tool in the improved diagnosis of breast cancer in the future. The identified tumor-associated metabolic changes support theories of de novo lipogenesis in tumor tissue and the role of stroma tissue in tumor growth and development and overall disease prognosis.
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Affiliation(s)
- Sabine Guenther
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Laura J Muirhead
- Section of Biosurgery and Surgical Technology, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Abigail V M Speller
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Ottmar Golf
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Nicole Strittmatter
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Rathi Ramakrishnan
- Centre for Pathology, Department of Medicine, Imperial College London, London, United Kingdom
| | - Robert D Goldin
- Centre for Pathology, Department of Medicine, Imperial College London, London, United Kingdom
| | - Emrys Jones
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Kirill Veselkov
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jeremy Nicholson
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Ara Darzi
- Section of Biosurgery and Surgical Technology, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Zoltan Takats
- Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
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Kim SA, Cho N, Ryu EB, Seo M, Bae MS, Chang JM, Moon WK. Background Parenchymal Signal Enhancement Ratio at Preoperative MR Imaging: Association with Subsequent Local Recurrence in Patients with Ductal Carcinoma in Situ after Breast Conservation Surgery. Radiology 2014; 270:699-707. [DOI: 10.1148/radiol.13130459] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Jones EF, Sinha SP, Newitt DC, Klifa C, Kornak J, Park CC, Hylton NM. MRI enhancement in stromal tissue surrounding breast tumors: association with recurrence free survival following neoadjuvant chemotherapy. PLoS One 2013; 8:e61969. [PMID: 23667451 PMCID: PMC3646993 DOI: 10.1371/journal.pone.0061969] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2013] [Accepted: 03/15/2013] [Indexed: 11/24/2022] Open
Abstract
RATIONALE AND OBJECTIVES Normal-appearing stromal tissues surrounding breast tumors can harbor abnormalities that lead to increased risk of local recurrence. The objective of this study was to develop a new imaging methodology to characterize the signal patterns of stromal tissue and to investigate their association with recurrence-free survival following neoadjuvant chemotherapy. MATERIALS AND METHODS Fifty patients with locally-advanced breast cancer were imaged with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) before (V1) and after one cycle (V2) of adriamycin-cytoxan therapy. Contrast enhancement in normal-appearing stroma around the tumor was characterized by the mean percent enhancement (PE) and mean signal enhancement ratio (SER) in distance bands of 5 mm from the tumor edge. Global PE and SER were calculated by averaging all stromal bands 5 to 40 mm from tumor. Proximity-dependent PE and SER were analyzed using a linear mixed effects model and Cox proportional hazards model for recurrence-free survival. RESULTS The mixed effects model displayed a decreasing radial trend in PE at both V1 and V2. An increasing trend was less pronounced in SER. Survival analysis showed that the hazard ratio estimates for each unit decrease in global SER was statistically significant at V1 [estimated hazard ratio = 0.058, 95% Wald CI (0.003, 1.01), likelihood ratio p = 0.03]; but was not so for V2. CONCLUSIONS These findings show that stromal tissue outside the tumor can be quantitatively characterized by DCE-MRI, and suggest that stromal enhancement measurements may be further developed for use as a potential predictor of recurrence/disease-free survival following therapy.
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Affiliation(s)
- Ella F Jones
- Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America.
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