1
|
Mann RM, Longo V. Contrast-enhanced Mammography versus MR Imaging of the Breast. Radiol Clin North Am 2024; 62:643-659. [PMID: 38777540 DOI: 10.1016/j.rcl.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
Breast MR imaging and contrast-enhanced mammography (CEM) are both techniques that employ intravenously injected contrast agent to assess breast lesions. This approach is associated with a very high sensitivity for malignant lesions that typically exhibit rapid enhancement due to the leakiness of neovasculature. CEM may be readily available at the breast imaging department and can be performed on the spot. Breast MR imaging provides stronger enhancement than the x-ray-based techniques and offers higher sensitivity. From a patient perspective, both modalities have their benefits and downsides; thus, patient preference could also play a role in the selection of the imaging technique.
Collapse
Affiliation(s)
- Ritse M Mann
- Department of Imaging, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Valentina Longo
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiodiagnostica Presidio Columbus, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, Rome 00168, Italy
| |
Collapse
|
2
|
Chikarmane SA, Smith S. Background Parenchymal Enhancement: A Comprehensive Update. Radiol Clin North Am 2024; 62:607-617. [PMID: 38777537 DOI: 10.1016/j.rcl.2023.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
Breast MR imaging is a complementary screening tool for patients at high risk for breast cancer and has been used in the diagnostic setting. Normal enhancement of breast tissue on MR imaging is called breast parenchymal enhancement (BPE), which occurs after administration of an intravenous contrast agent. BPE varies widely due to menopausal status, use of exogenous hormones, and breast cancer treatment. Degree of BPE has also been shown to influence breast cancer risk and may predict treatment outcomes. The authors provide a comprehensive update on BPE with review of the recent literature.
Collapse
Affiliation(s)
- Sona A Chikarmane
- Breast Imaging Division, Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA.
| | - Sharon Smith
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA
| |
Collapse
|
3
|
Shamir SB, Sasson AL, Margolies LR, Mendelson DS. New Frontiers in Breast Cancer Imaging: The Rise of AI. Bioengineering (Basel) 2024; 11:451. [PMID: 38790318 PMCID: PMC11117903 DOI: 10.3390/bioengineering11050451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/18/2024] [Accepted: 04/26/2024] [Indexed: 05/26/2024] Open
Abstract
Artificial intelligence (AI) has been implemented in multiple fields of medicine to assist in the diagnosis and treatment of patients. AI implementation in radiology, more specifically for breast imaging, has advanced considerably. Breast cancer is one of the most important causes of cancer mortality among women, and there has been increased attention towards creating more efficacious methods for breast cancer detection utilizing AI to improve radiologist accuracy and efficiency to meet the increasing demand of our patients. AI can be applied to imaging studies to improve image quality, increase interpretation accuracy, and improve time efficiency and cost efficiency. AI applied to mammography, ultrasound, and MRI allows for improved cancer detection and diagnosis while decreasing intra- and interobserver variability. The synergistic effect between a radiologist and AI has the potential to improve patient care in underserved populations with the intention of providing quality and equitable care for all. Additionally, AI has allowed for improved risk stratification. Further, AI application can have treatment implications as well by identifying upstage risk of ductal carcinoma in situ (DCIS) to invasive carcinoma and by better predicting individualized patient response to neoadjuvant chemotherapy. AI has potential for advancement in pre-operative 3-dimensional models of the breast as well as improved viability of reconstructive grafts.
Collapse
Affiliation(s)
- Stephanie B. Shamir
- Department of Diagnostic, Molecular and Interventional Radiology, The Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029, USA
| | | | | | | |
Collapse
|
4
|
Murakami W, Mortazavi S, Yu T, Kathuria-Prakash N, Yan R, Fischer C, McCann KE, Lee-Felker S, Sung K. Clinical Significance of Background Parenchymal Enhancement in Breast Cancer Risk Stratification. J Magn Reson Imaging 2024; 59:1742-1757. [PMID: 37724902 DOI: 10.1002/jmri.29015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Background parenchymal enhancement (BPE) is an established breast cancer risk factor. However, the relationship between BPE levels and breast cancer risk stratification remains unclear. PURPOSE To evaluate the clinical relationship between BPE levels and breast cancer risk with covariate adjustments for age, ethnicity, and hormonal status. STUDY TYPE Retrospective. POPULATION 954 screening breast MRI datasets representing 721 women divided into four cohorts: women with pathogenic germline breast cancer (BRCA) mutations (Group 1, N = 211), women with non-BRCA germline mutations (Group 2, N = 60), women without high-risk germline mutations but with a lifetime breast cancer risk of ≥20% using the Tyrer-Cuzick model (Group 3, N = 362), and women with <20% lifetime risk (Group 4, N = 88). FIELD STRENGTH/SEQUENCE 3 T/axial non-fat-saturated T1, short tau inversion recovery, fat-saturated pre-contrast, and post-contrast T1-weighted images. ASSESSMENT Data on age, body mass index, ethnicity, menopausal status, genetic predisposition, and hormonal therapy use were collected. BPE levels were evaluated by two breast fellowship-trained radiologists independently in accordance with BI-RADS, with a third breast fellowship-trained radiologist resolving any discordance. STATISTICAL TESTS Propensity score matching (PSM) was utilized to adjust covariates, including age, ethnicity, menopausal status, hormonal treatments, and prior bilateral oophorectomy. The Mann-Whitney U test, chi-squared test, and univariate and multiple logistic regression analysis were performed, with an odds ratio (OR) and corresponding 95% confidence interval. Weighted Kappa statistic was used to assess inter-reader variation. A P value <0.05 indicated a significant result. RESULTS In the assessment of BPE, there was substantial agreement between the two interpreting radiologists (κ = 0.74). Patient demographics were not significantly different between patient groups after PSM. The BPE of Group 1 was significantly lower than that of Group 4 and Group 3 among premenopausal women. In estimating the BPE level, the OR of gene mutations was 0.35. DATA CONCLUSION Adjusting for potential confounders, the BPE level of premenopausal women with BRCA mutations was significantly lower than that of non-high-risk women. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 3.
Collapse
Affiliation(s)
- Wakana Murakami
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
- Department of Radiology, Showa University, School of Medicine, Tokyo, Japan
| | - Shabnam Mortazavi
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Tiffany Yu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Nikhita Kathuria-Prakash
- Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Ran Yan
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, University of California at Los Angeles, Los Angeles, California, USA
| | - Cheryce Fischer
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Kelly E McCann
- Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Stephanie Lee-Felker
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Kyunghyun Sung
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, University of California at Los Angeles, Los Angeles, California, USA
| |
Collapse
|
5
|
Douglas L, Fuhrman J, Hu Q, Edwards A, Sheth D, Abe H, Giger M. Computerized assessment of background parenchymal enhancement on breast dynamic contrast-enhanced-MRI including electronic lesion removal. J Med Imaging (Bellingham) 2024; 11:034501. [PMID: 38737493 PMCID: PMC11086664 DOI: 10.1117/1.jmi.11.3.034501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 03/29/2024] [Accepted: 04/09/2024] [Indexed: 05/14/2024] Open
Abstract
Purpose Current clinical assessment qualitatively describes background parenchymal enhancement (BPE) as minimal, mild, moderate, or marked based on the visually perceived volume and intensity of enhancement in normal fibroglandular breast tissue in dynamic contrast-enhanced (DCE)-MRI. Tumor enhancement may be included within the visual assessment of BPE, thus inflating BPE estimation due to angiogenesis within the tumor. Using a dataset of 426 MRIs, we developed an automated method to segment breasts, electronically remove lesions, and calculate scores to estimate BPE levels. Approach A U-Net was trained for breast segmentation from DCE-MRI maximum intensity projection (MIP) images. Fuzzy c -means clustering was used to segment lesions; the lesion volume was removed prior to creating projections. U-Net outputs were applied to create projection images of both, affected, and unaffected breasts before and after lesion removal. BPE scores were calculated from various projection images, including MIPs or average intensity projections of first- or second postcontrast subtraction MRIs, to evaluate the effect of varying image parameters on automatic BPE assessment. Receiver operating characteristic analysis was performed to determine the predictive value of computed scores in BPE level classification tasks relative to radiologist ratings. Results Statistically significant trends were found between radiologist BPE ratings and calculated BPE scores for all breast regions (Kendall correlation, p < 0.001 ). Scores from all breast regions performed significantly better than guessing (p < 0.025 from the z -test). Results failed to show a statistically significant difference in performance with and without lesion removal. BPE scores of the affected breast in the second postcontrast subtraction MIP after lesion removal performed statistically greater than random guessing across various viewing projections and DCE time points. Conclusions Results demonstrate the potential for automatic BPE scoring to serve as a quantitative value for objective BPE level classification from breast DCE-MR without the influence of lesion enhancement.
Collapse
Affiliation(s)
- Lindsay Douglas
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| | - Jordan Fuhrman
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| | - Qiyuan Hu
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| | - Alexandra Edwards
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| | - Deepa Sheth
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| | - Hiroyuki Abe
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| | - Maryellen Giger
- University of Chicago, Department of Radiology Committee on Medical Physics, Chicago, Illinois, United States
| |
Collapse
|
6
|
Yan R, Murakami W, Mortazavi S, Yu T, Chu FI, Lee-Felker S, Sung K. Quantitative assessment of background parenchymal enhancement is associated with lifetime breast cancer risk in screening MRI. Eur Radiol 2024:10.1007/s00330-024-10758-9. [PMID: 38683385 DOI: 10.1007/s00330-024-10758-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 03/07/2024] [Accepted: 03/16/2024] [Indexed: 05/01/2024]
Abstract
OBJECTIVES To compare the quantitative background parenchymal enhancement (BPE) in women with different lifetime risks and BRCA mutation status of breast cancer using screening MRI. MATERIALS AND METHODS This study included screening MRI of 535 women divided into three groups based on lifetime risk: nonhigh-risk women, high-risk women without BRCA mutation, and BRCA1/2 mutation carriers. Six quantitative BPE measurements, including percent enhancement (PE) and signal enhancement ratio (SER), were calculated on DCE-MRI after segmentation of the whole breast and fibroglandular tissue (FGT). The associations between lifetime risk factors and BPE were analyzed via linear regression analysis. We adjusted for risk factors influencing BPE using propensity score matching (PSM) and compared the BPE between different groups. A two-sided Mann-Whitney U-test was used to compare the BPE with a threshold of 0.1 for multiple testing issue-adjusted p values. RESULTS Age, BMI, menopausal status, and FGT level were significantly correlated with quantitative BPE based on the univariate and multivariable linear regression analyses. After adjusting for age, BMI, menopausal status, hormonal treatment history, and FGT level using PSM, significant differences were observed between high-risk non-BRCA and BRCA groups in PEFGT (11.5 vs. 8.0%, adjusted p = 0.018) and SERFGT (7.2 vs. 9.3%, adjusted p = 0.066). CONCLUSION Quantitative BPE varies in women with different lifetime breast cancer risks and BRCA mutation status. These differences may be due to the influence of multiple lifetime risk factors. Quantitative BPE differences remained between groups with and without BRCA mutations after adjusting for known risk factors associated with BPE. CLINICAL RELEVANCE STATEMENT BRCA germline mutations may be associated with quantitative background parenchymal enhancement, excluding the effects of known confounding factors. This finding can provide potential insights into the cancer pathophysiological mechanisms behind lifetime risk models. KEY POINTS Expanding understanding of breast cancer pathophysiology allows for improved risk stratification and optimized screening protocols. Quantitative BPE is significantly associated with lifetime risk factors and differs between BRCA mutation carriers and noncarriers. This research offers a possible understanding of the physiological mechanisms underlying quantitative BPE and BRCA germline mutations.
Collapse
Affiliation(s)
- Ran Yan
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Department of Bioengineering, Henry Samueli School of Engineering, University of California, Los Angeles, CA, USA.
| | - Wakana Murakami
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Radiology, Showa University Graduate School of Medicine, Tokyo, Japan
| | - Shabnam Mortazavi
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Tiffany Yu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Fang-I Chu
- Department of Radiation Oncology, University of California, Los Angeles, CA, USA
| | - Stephanie Lee-Felker
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Kyunghyun Sung
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Bioengineering, Henry Samueli School of Engineering, University of California, Los Angeles, CA, USA
| |
Collapse
|
7
|
Wang H, H M van der Velden B, Verburg E, Bakker MF, Pijnappel RM, Veldhuis WB, van Gils CH, Gilhuijs KGA. Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial. Eur J Radiol 2024; 175:111442. [PMID: 38583349 DOI: 10.1016/j.ejrad.2024.111442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 02/06/2024] [Accepted: 03/21/2024] [Indexed: 04/09/2024]
Abstract
OBJECTIVES Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI (DCE-MRI) as rated by radiologists is subject to inter- and intrareader variability. We aim to automate BPE category from DCE-MRI. METHODS This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. 4553 women with extremely dense breasts who received supplemental breast MRI screening in eight hospitals were included. Minimal, mild, moderate and marked BPE rated by radiologists were used as reference. Fifteen quantitative MRI features of the fibroglandular tissue were extracted to predict BPE using Random Forest, Naïve Bayes, and KNN classifiers. Majority voting was used to combine the predictions. Internal-external validation was used for training and validation. The inverse-variance weighted mean accuracy was used to express mean performance across the eight hospitals. Cox regression was used to verify non inferiority of the association between automated rating and breast cancer occurrence compared to the association for manual rating. RESULTS The accuracy of majority voting ranged between 0.56 and 0.84 across the eight hospitals. The weighted mean prediction accuracy for the four BPE categories was 0.76. The hazard ratio (HR) of BPE for breast cancer occurrence was comparable between automated rating and manual rating (HR = 2.12 versus HR = 1.97, P = 0.65 for mild/moderate/marked BPE relative to minimal BPE). CONCLUSION It is feasible to rate BPE automatically in DCE-MRI of women with extremely dense breasts without compromising the underlying association between BPE and breast cancer occurrence. The accuracy for minimal BPE is superior to that for other BPE categories.
Collapse
Affiliation(s)
- Hui Wang
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Erik Verburg
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marije F Bakker
- Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands
| | - Ruud M Pijnappel
- Department of Radiology, University Medical Center Utrecht, The Netherlands
| | - Wouter B Veldhuis
- Department of Radiology, University Medical Center Utrecht, The Netherlands
| | - Carla H van Gils
- Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands
| | - Kenneth G A Gilhuijs
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
| |
Collapse
|
8
|
Musall BC, Rauch DE, Mohamed RMM, Panthi B, Boge M, Candelaria RP, Chen H, Guirguis MS, Hunt KK, Huo L, Hwang KP, Korkut A, Litton JK, Moseley TW, Pashapoor S, Patel MM, Reed BJ, Scoggins ME, Son JB, Tripathy D, Valero V, Wei P, White JB, Whitman GJ, Xu Z, Yang WT, Yam C, Adrada BE, Ma J. Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy. J Magn Reson Imaging 2024. [PMID: 38294179 DOI: 10.1002/jmri.29267] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/18/2024] [Accepted: 01/18/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST). PURPOSE To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST. STUDY TYPE Prospective. POPULATION Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR). FIELD STRENGTH/SEQUENCE 3.0 T/reduced field of view single-shot echo-planar DTI sequence. ASSESSMENT Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery. STATISTICAL TESTS Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant. RESULTS 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s). DATA CONCLUSION Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 4.
Collapse
Affiliation(s)
- Benjamin C Musall
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David E Rauch
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rania M M Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Bikash Panthi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Medine Boge
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rosalind P Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Huiqin Chen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Mary S Guirguis
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kelly K Hunt
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Anil Korkut
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Tanya W Moseley
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sanaz Pashapoor
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Miral M Patel
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Brandy J Reed
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Marion E Scoggins
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gary J Whitman
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Zhan Xu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Wei T Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Beatriz E Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| |
Collapse
|
9
|
Zheng G, Hou J, Shu Z, Peng J, Han L, Yuan Z, He X, Gong X. Prediction of neoadjuvant chemotherapy pathological complete response for breast cancer based on radiomics nomogram of intratumoral and derived tissue. BMC Med Imaging 2024; 24:22. [PMID: 38245712 PMCID: PMC10800060 DOI: 10.1186/s12880-024-01198-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 01/10/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Non-invasive identification of breast cancer (BCa) patients with pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) is critical to determine appropriate surgical strategies and guide the resection range of tumor. This study aimed to examine the effectiveness of a nomogram created by combining radiomics signatures from both intratumoral and derived tissues with clinical characteristics for predicting pCR after NACT. METHODS The clinical data of 133 BCa patients were analyzed retrospectively and divided into training and validation sets. The radiomics features for Intratumoral, peritumoral, and background parenchymal enhancement (BPE) in the training set were dimensionalized. Logistic regression analysis was used to select the optimal feature set, and a radiomics signature was constructed using a decision tree. The signature was combined with clinical features to build joint models and generate nomograms. The area under curve (AUC) value of receiver operating characteristic (ROC) curve was then used to assess the performance of the nomogram and independent predictors. RESULTS Among single region, intratumoral had the best predictive value. The diagnostic performance of the intratumoral improved after adding the BPE features. The AUC values of the radiomics signature were 0.822 and 0.82 in the training and validation sets. Multivariate logistic regression analysis revealed that age, ER, PR, Ki-67, and radiomics signature were independent predictors of pCR in constructing a nomogram. The AUC of the nomogram in the training and validation sets were 0.947 and 0.933. The DeLong test showed that the nomogram had statistically significant differences compared to other independent predictors in both the training and validation sets (P < 0.05). CONCLUSION BPE has value in predicting the efficacy of neoadjuvant chemotherapy, thereby revealing the potential impact of tumor growth environment on the efficacy of neoadjuvant chemotherapy.
Collapse
Affiliation(s)
- Guangying Zheng
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Jie Hou
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Zhenyu Shu
- Cancer Center, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, No. 158 Shangtang Road, Hangzhou City, Zhejiang Province, China
| | - Jiaxuan Peng
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Lu Han
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Zhongyu Yuan
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Xiaodong He
- Cancer Center, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, No. 158 Shangtang Road, Hangzhou City, Zhejiang Province, China
| | - Xiangyang Gong
- Cancer Center, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, No. 158 Shangtang Road, Hangzhou City, Zhejiang Province, China.
| |
Collapse
|
10
|
Hirsch L, Huang Y, Makse HA, Martinez DF, Hughes M, Eskreis-Winkler S, Pinker K, Morris E, Parra LC, Sutton EJ. [WITHDRAWN] Predicting breast cancer with AI for individual risk-adjusted MRI screening and early detection. ARXIV 2024:arXiv:2312.00067v2. [PMID: 38076513 PMCID: PMC10705586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
This paper has been withdrawn by Lukas Hirsch. Major revisions and rewriting in progress.
Collapse
|
11
|
Arefan D, Zuley ML, Berg WA, Yang L, Sumkin JH, Wu S. Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk. Radiology 2024; 310:e230269. [PMID: 38259203 PMCID: PMC10831474 DOI: 10.1148/radiol.230269] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 11/17/2023] [Accepted: 12/07/2023] [Indexed: 01/24/2024]
Abstract
Background Background parenchymal enhancement (BPE) at dynamic contrast-enhanced (DCE) MRI of cancer-free breasts increases the risk of developing breast cancer; implications of quantitative BPE in ipsilateral breasts with breast cancer are largely unexplored. Purpose To determine whether quantitative BPE measurements in one or both breasts could be used to predict recurrence risk in women with breast cancer, using the Oncotype DX recurrence score as the reference standard. Materials and Methods This HIPAA-compliant retrospective single-institution study included women diagnosed with breast cancer between January 2007 and January 2012 (development set) and between January 2012 and January 2017 (internal test set). Quantitative BPE was automatically computed using an in-house-developed computer algorithm in both breasts. Univariable logistic regression was used to examine the association of BPE with Oncotype DX recurrence score binarized into high-risk (recurrence score >25) and low- or intermediate-risk (recurrence score ≤25) categories. Models including BPE measures were assessed for their ability to distinguish patients with high risk versus those with low or intermediate risk and the actual recurrence outcome. Results The development set included 127 women (mean age, 58 years ± 10.2 [SD]; 33 with high risk and 94 with low or intermediate risk) with an actual local or distant recurrence rate of 15.7% (20 of 127) at a minimum 10 years of follow-up. The test set included 60 women (mean age, 57.8 years ± 11.6; 16 with high risk and 44 with low or intermediate risk). BPE measurements quantified in both breasts were associated with increased odds of a high-risk Oncotype DX recurrence score (odds ratio range, 1.27-1.66 [95% CI: 1.02, 2.56]; P < .001 to P = .04). Measures of BPE combined with tumor radiomics helped distinguish patients with a high-risk Oncotype DX recurrence score from those with a low- or intermediate-risk score, with an area under the receiver operating characteristic curve of 0.94 in the development set and 0.79 in the test set. For the combined models, the negative predictive values were 0.97 and 0.93 in predicting actual distant recurrence and local recurrence, respectively. Conclusion Ipsilateral and contralateral DCE MRI measures of BPE quantified in patients with breast cancer can help distinguish patients with high recurrence risk from those with low or intermediate recurrence risk, similar to Oncotype DX recurrence score. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zhou and Rahbar in this issue.
Collapse
Affiliation(s)
- Dooman Arefan
- From the Department of Radiology, University of Pittsburgh School of
Medicine, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213 (D.A., M.L.Z., W.A.B.,
L.Y., J.H.S., S.W.); Department of Radiology, Magee-Womens Hospital, University
of Pittsburgh Medical Center, Pittsburgh, PA, 15213 (M.L.Z., W.A.B., J.H.S.);
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and
Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China
(L.Y.); and Department of Biomedical Informatics (S.W.), Department of
Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of
Pittsburgh, Pittsburgh, Pa
| | - Margarita L. Zuley
- From the Department of Radiology, University of Pittsburgh School of
Medicine, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213 (D.A., M.L.Z., W.A.B.,
L.Y., J.H.S., S.W.); Department of Radiology, Magee-Womens Hospital, University
of Pittsburgh Medical Center, Pittsburgh, PA, 15213 (M.L.Z., W.A.B., J.H.S.);
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and
Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China
(L.Y.); and Department of Biomedical Informatics (S.W.), Department of
Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of
Pittsburgh, Pittsburgh, Pa
| | - Wendie A. Berg
- From the Department of Radiology, University of Pittsburgh School of
Medicine, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213 (D.A., M.L.Z., W.A.B.,
L.Y., J.H.S., S.W.); Department of Radiology, Magee-Womens Hospital, University
of Pittsburgh Medical Center, Pittsburgh, PA, 15213 (M.L.Z., W.A.B., J.H.S.);
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and
Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China
(L.Y.); and Department of Biomedical Informatics (S.W.), Department of
Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of
Pittsburgh, Pittsburgh, Pa
| | - Lu Yang
- From the Department of Radiology, University of Pittsburgh School of
Medicine, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213 (D.A., M.L.Z., W.A.B.,
L.Y., J.H.S., S.W.); Department of Radiology, Magee-Womens Hospital, University
of Pittsburgh Medical Center, Pittsburgh, PA, 15213 (M.L.Z., W.A.B., J.H.S.);
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and
Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China
(L.Y.); and Department of Biomedical Informatics (S.W.), Department of
Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of
Pittsburgh, Pittsburgh, Pa
| | - Jules H. Sumkin
- From the Department of Radiology, University of Pittsburgh School of
Medicine, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213 (D.A., M.L.Z., W.A.B.,
L.Y., J.H.S., S.W.); Department of Radiology, Magee-Womens Hospital, University
of Pittsburgh Medical Center, Pittsburgh, PA, 15213 (M.L.Z., W.A.B., J.H.S.);
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and
Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China
(L.Y.); and Department of Biomedical Informatics (S.W.), Department of
Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of
Pittsburgh, Pittsburgh, Pa
| | - Shandong Wu
- From the Department of Radiology, University of Pittsburgh School of
Medicine, 3240 Craft Pl, Room 322, Pittsburgh, PA 15213 (D.A., M.L.Z., W.A.B.,
L.Y., J.H.S., S.W.); Department of Radiology, Magee-Womens Hospital, University
of Pittsburgh Medical Center, Pittsburgh, PA, 15213 (M.L.Z., W.A.B., J.H.S.);
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and
Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, China
(L.Y.); and Department of Biomedical Informatics (S.W.), Department of
Bioengineering (S.W.), and Intelligent Systems Program (S.W.), University of
Pittsburgh, Pittsburgh, Pa
| |
Collapse
|
12
|
Zhang J, Cui Z, Zhou L, Sun Y, Li Z, Liu Z, Shen D. Breast Fibroglandular Tissue Segmentation for Automated BPE Quantification With Iterative Cycle-Consistent Semi-Supervised Learning. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:3944-3955. [PMID: 37756174 DOI: 10.1109/tmi.2023.3319646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Background Parenchymal Enhancement (BPE) quantification in Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) plays a pivotal role in clinical breast cancer diagnosis and prognosis. However, the emerging deep learning-based breast fibroglandular tissue segmentation, a crucial step in automated BPE quantification, often suffers from limited training samples with accurate annotations. To address this challenge, we propose a novel iterative cycle-consistent semi-supervised framework to leverage segmentation performance by using a large amount of paired pre-/post-contrast images without annotations. Specifically, we design the reconstruction network, cascaded with the segmentation network, to learn a mapping from the pre-contrast images and segmentation predictions to the post-contrast images. Thus, we can implicitly use the reconstruction task to explore the inter-relationship between these two-phase images, which in return guides the segmentation task. Moreover, the reconstructed post-contrast images across multiple auto-context modeling-based iterations can be viewed as new augmentations, facilitating cycle-consistent constraints across each segmentation output. Extensive experiments on two datasets with various data distributions show great segmentation and BPE quantification accuracy compared with other state-of-the-art semi-supervised methods. Importantly, our method achieves 11.80 times of quantification accuracy improvement along with 10 times faster, compared with clinical physicians, demonstrating its potential for automated BPE quantification. The code is available at https://github.com/ZhangJD-ong/Iterative-Cycle-consistent-Semi-supervised-Learning-for-fibroglandular-tissue-segmentation.
Collapse
|
13
|
Sassi A, Salminen A, Jukkola A, Tervo M, Mäenpää N, Turtiainen S, Tiainen L, Liimatainen T, Tolonen T, Huhtala H, Rinta-Kiikka I, Arponen O. Breast density and the likelihood of malignant MRI-detected lesions in women diagnosed with breast cancer. Eur Radiol 2023; 33:8080-8088. [PMID: 37646814 PMCID: PMC10598189 DOI: 10.1007/s00330-023-10072-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 05/04/2023] [Accepted: 06/30/2023] [Indexed: 09/01/2023]
Abstract
OBJECTIVES To assess whether mammographic breast density in women diagnosed with breast cancer correlates with the total number of incidental magnetic resonance imaging (MRI)-detected lesions and the likelihood of the lesions being malignant. METHODS Patients diagnosed with breast cancer meeting the EUSOBI and EUSOMA criteria for preoperative breast MRI routinely undergo mammography and ultrasound before MRI at our institution. Incidental suspicious breast lesions detected in MRI are biopsied. We included patients diagnosed with invasive breast cancers between 2014 and 2019 who underwent preoperative breast MRI. One reader retrospectively determined breast density categories according to the 5th edition of the BI-RADS lexicon. RESULTS Of 946 patients with 973 malignant primary breast tumors, 166 (17.5%) had a total of 175 (18.0%) incidental MRI-detected lesions (82 (46.9%) malignant and 93 (53.1%) benign). High breast density according to BI-RADS was associated with higher incidence of all incidental enhancing lesions in preoperative breast MRIs: 2.66 (95% confidence interval: 1.03-6.86) higher for BI-RADS density category B, 2.68 (1.04-6.92) for category C, and 3.67 (1.36-9.93) for category D compared to category A (p < 0.05). However, high breast density did not predict higher incidence of malignant incidental lesions (p = 0.741). Incidental MRI-detected lesions in the contralateral breast were more likely benign (p < 0.001): 18 (27.3%)/48 (72.7%) vs. 64 (58.7%)/45 (41.3%) malignant/benign incidental lesions in contralateral vs. ipsilateral breasts. CONCLUSION Women diagnosed with breast cancer who have dense breasts have more incidental MRI-detected lesions, but higher breast density does not translate to increased likelihood of malignant incidental lesions. CLINICAL RELEVANCE STATEMENT Dense breasts should not be considered as an indication for preoperative breast MRI in women diagnosed with breast cancer. KEY POINTS • The role of preoperative MRI of patients with dense breasts diagnosed with breast cancer is under debate. • Women with denser breasts have a higher incidence of all MRI-detected incidental breast lesions, but the incidence of malignant MRI-detected incidental lesions is not higher than in women with fatty breasts. • High breast density alone should not indicate preoperative breast MRI.
Collapse
Affiliation(s)
- Antti Sassi
- Department of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland.
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
| | - Annukka Salminen
- Department of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Arja Jukkola
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Oncology, Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | - Maija Tervo
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Niina Mäenpää
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Oncology, Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | - Saara Turtiainen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Surgery, Tampere University Hospital, Tampere, Finland
| | - Leena Tiainen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Oncology, Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | - Timo Liimatainen
- Research Unit of Medical Imaging Physics and Technology, University of Oulu, Oulu, Finland
- Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Teemu Tolonen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Pathology, Fimlab Laboratories, Tampere University Hospital, Tampere, Finland
| | - Heini Huhtala
- Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Irina Rinta-Kiikka
- Department of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Otso Arponen
- Department of Radiology, Tampere University Hospital, Elämänaukio 1, 33520, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| |
Collapse
|
14
|
Eskreis-Winkler S, Sung JS, Dixon L, Monga N, Jindal R, Simmons A, Thakur S, Sevilimedu V, Sutton E, Comstock C, Feigin K, Pinker K. High-Temporal/High-Spatial Resolution Breast Magnetic Resonance Imaging Improves Diagnostic Accuracy Compared With Standard Breast Magnetic Resonance Imaging in Patients With High Background Parenchymal Enhancement. J Clin Oncol 2023; 41:4747-4755. [PMID: 37561962 PMCID: PMC10602549 DOI: 10.1200/jco.22.00635] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 01/05/2023] [Accepted: 06/16/2023] [Indexed: 08/12/2023] Open
Abstract
PURPOSE To compare breast magnetic resonance imaging (MRI) diagnostic performance using a standard high-spatial resolution protocol versus a simultaneous high-temporal/high-spatial resolution (HTHS) protocol in women with high levels of background parenchymal enhancement (BPE). MATERIALS AND METHODS We conducted a retrospective study of contrast-enhanced breast MRIs performed at our institution before and after the introduction of the HTHS protocol. We compared diagnostic performance of the HTHS and standard protocol by comparing cancer detection rate (CDR) and positive predictive value of biopsy (PPV3) among women with high BPE (ie, marked or moderate). RESULTS Among women with high BPE, the HTHS protocol demonstrated increased CDR (23.6 per 1,000 patients v 7.9 per 1,000 patients; P = 0. 013) and increased PPV3 (16.0% v 6.3%; P = .021) compared with the standard protocol. This corresponded to a 9.8% (95% CI, 1.29 to 18.3) decrease in the proportion of unnecessary biopsies among high-BPE patients and an additional cancer yield of 15.7 per 1,000 patients (95% CI, 1.3 to 18.3). CONCLUSION Among women with high BPE, HTHS MRI improved diagnostic performance, leading to an additional cancer yield of 15.7 cancers per 1,000 women and concomitantly decreasing unnecessary biopsies by 9.8%. A multisite prospective trial is warranted to confirm these findings and to pave the way for more widespread clinical implementation.
Collapse
Affiliation(s)
| | - Janice S. Sung
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Linden Dixon
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Natasha Monga
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ragni Jindal
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Sunitha Thakur
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Varadan Sevilimedu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Elizabeth Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Kimberly Feigin
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Katja Pinker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| |
Collapse
|
15
|
Wang H, Gao L, Chen X, Wang SJ. Quantitative evaluation of Kaiser score in diagnosing breast dynamic contrast-enhanced magnetic resonance imaging for patients with high-grade background parenchymal enhancement. Quant Imaging Med Surg 2023; 13:6384-6394. [PMID: 37869283 PMCID: PMC10585520 DOI: 10.21037/qims-23-113] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 07/28/2023] [Indexed: 10/24/2023]
Abstract
Background High-grade background parenchymal enhancement (BPE), including moderate and marked, poses a considerable challenge for the diagnosis of breast disease due to its tendency to increase the rate of false positives and false negatives. The purpose of our study was to explore whether the Kaiser score can be used for more accurate assessment of benign and malignant lesions in high-grade BPE compared with the Breast Imaging Reporting and Data System (BI-RADS). Methods A retrospective review was conducted on consecutive breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) scans from 2 medical centers. Included were patients who underwent DCE-MRI demonstrating high-grade BPE and who had a pathology-confirmed diagnosis. Excluded were patients who had received neoadjuvant chemotherapy or who had undergone biopsy prior to MRI examination. Two physicians with more than 7 years of experience specializing in breast imaging diagnosis jointly reviewed breast magnetic resonance (MR) images. The Kaiser score was used to determine the sensitivity, specificity, and positive predictive value (PPV), and negative predictive value (NPV) of the BI-RADS from different BPE groups and different enhancement types. The performance of the Kaiser score and BI-RADS were compared according to diagnostic accuracy. Results A total of 126 cases of high-grade BPE from 2 medical centers were included in this study. The Kaiser score had a higher specificity and PPV than did the BI-RADS (87.5% vs. 46.3%) as well as a higher PPV (94.3% vs. 79.8%). The value of diagnostic accuracy and 95% confidence interval (CI) for the Kaiser score (accuracy 0.928; 95% CI: 0.883-0.973) was larger than that for BI-RADS (accuracy 0.810; 95% CI: 0.741-0.879). Moreover, the Kaiser score had a significantly higher value of diagnostic accuracy for both mass and non-mass enhancement, especially mass lesions (Kaiser score: accuracy 0.947, 95% CI: 0.902-0.992; BI-RADS: accuracy 0.821, 95% CI: 0.782-0.860), with a P value of 0.006. Conclusions The Kaiser score is a useful diagnostic tool for the evaluation of high-grade BPE lesions, with a higher specificity, PPV, and diagnostic accuracy as compared to the BI-RADS.
Collapse
Affiliation(s)
- Hui Wang
- Department of Radiology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, China
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ling Gao
- Department of Radiology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, China
| | - Xu Chen
- Department of Thyroid and Breast Surgery, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, China
| | - Shou-Ju Wang
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| |
Collapse
|
16
|
Watt GP, Thakran S, Sung JS, Jochelson MS, Lobbes MBI, Weinstein SP, Bradbury AR, Buys SS, Morris EA, Apte A, Patel P, Woods M, Liang X, Pike MC, Kontos D, Bernstein JL. Association of Breast Cancer Odds with Background Parenchymal Enhancement Quantified Using a Fully Automated Method at MRI: The IMAGINE Study. Radiology 2023; 308:e230367. [PMID: 37750771 PMCID: PMC10546291 DOI: 10.1148/radiol.230367] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 06/13/2023] [Accepted: 06/16/2023] [Indexed: 09/27/2023]
Abstract
Background Background parenchymal enhancement (BPE) at breast MRI has been associated with increased breast cancer risk in several independent studies. However, variability of subjective BPE assessments have precluded its use in clinical practice. Purpose To examine the association between fully objective measures of BPE at MRI and odds of breast cancer. Materials and Methods This prospective case-control study included patients who underwent a bilateral breast MRI examination and were receiving care at one of three centers in the United States from November 2010 to July 2017. Breast volume, fibroglandular tissue (FGT) volume, and BPE were quantified using fully automated software. Fat volume was defined as breast volume minus FGT volume. BPE extent was defined as the proportion of FGT voxels with enhancement of 20% or more. Spearman rank correlation between quantitative BPE extent and Breast Imaging Reporting and Data System (BI-RADS) BPE categories assigned by an experienced board-certified breast radiologist was estimated. With use of multivariable logistic regression, breast cancer case-control status was regressed on tertiles (low, moderate, and high) of BPE, FGT volume, and fat volume, with adjustment for covariates. Results In total, 536 case participants with breast cancer (median age, 48 years [IQR, 43-55 years]) and 940 cancer-free controls (median age, 46 years [IQR, 38-55 years]) were included. BPE extent was positively associated with BI-RADS BPE (rs = 0.54; P < .001). Compared with low BPE extent (range, 2.9%-34.2%), high BPE extent (range, 50.7%-97.3%) was associated with increased odds of breast cancer (odds ratio [OR], 1.74 [95% CI: 1.23, 2.46]; P for trend = .002) in a multivariable model also including FGT volume (OR, 1.39 [95% CI: 0.97, 1.98]) and fat volume (OR, 1.46 [95% CI: 1.04, 2.06]). The association of high BPE extent with increased odds of breast cancer was similar for premenopausal and postmenopausal women (ORs, 1.75 and 1.83, respectively; interaction P = .73). Conclusion Objectively measured BPE at breast MRI is associated with increased breast cancer odds for both premenopausal and postmenopausal women. Clinical trial registration no. NCT02301767 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bokacheva in this issue.
Collapse
Affiliation(s)
- Gordon P. Watt
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Snekha Thakran
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Janice S. Sung
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Maxine S. Jochelson
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Marc B. I. Lobbes
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Susan P. Weinstein
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Angela R. Bradbury
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Saundra S. Buys
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Elizabeth A. Morris
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Aditya Apte
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Prusha Patel
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Meghan Woods
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Xiaolin Liang
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Malcolm C. Pike
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Despina Kontos
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| | - Jonine L. Bernstein
- From the Department of Epidemiology and Biostatistics (G.P.W., P.P., M.W., X.L., M.C.P., J.L.B.), Department of Radiology (J.S.S., M.S.J.), and Department of Medical Physics (A.A.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Perelman Center for Advanced Medicine at the University of Pennsylvania, Philadelphia, Pa (S.T., S.P.W., A.R.B., D.K.); Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, the Netherlands (M.B.I.L.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (M.B.I.L.); GROW School for Oncology and Reproduction, Maastricht University, Maastricht, the Netherlands (M.B.I.L.); Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (S.S.B.); and Department of Radiology, University of California Davis Medical Center, Davis, Calif (E.A.M.)
| |
Collapse
|
17
|
Sallam H, Lenga L, Solbach C, Becker S, Vogl TJ. Correlation of background parenchymal enhancement on breast MRI with breast cancer. Clin Radiol 2023:S0009-9260(23)00218-0. [PMID: 37330320 DOI: 10.1016/j.crad.2023.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 03/05/2023] [Accepted: 05/11/2023] [Indexed: 06/19/2023]
Abstract
AIM To evaluate the prognostic value of background parenchymal enhancement (BPE) in breast magnetic resonance imaging (MRI) in women referred to radiological department as a high risk for breast cancer. MATERIALS AND METHODS A retrospective, cross-sectional study included 327 consecutive patients (mean age: 60 years, age range: 30-90 years) who underwent breast MRI and tissue biopsy between 2007 and 2016. All MRI images (T1, T2, and subtraction images) were evaluated visually. The relationship of BPE with patient age, fibroglandular tissue (FGT), Breast Imaging Reporting and Data System (BIRADS) categories, presence of breast cancer, and expression of human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR), oestrogen receptor (ER), and Ki67 were analysed. Furthermore, all variables were correlated with pre- and postmenopausal status. RESULTS BPE of bilateral breast showed a weak correlation with FGT (right BPE: r=-0.14, p=0.004; left BPE: r=0.16, p=0.003), a weak negative correlation with patient age (right BPE: r=-0.14, p=0.007; left BPE: r=-0.15, p=0.006), and significant correlation with HER2 (right BPE, p=0.02), left BPE with HER2 was not significant. Among the correlations between BPE and BIRADS, only between right BPE and right BIRADS was significant (p=0.031). No clear evidence of an association between breast MRI BPE and breast cancer in premenopausal and postmenopausal status was observed, and no difference was found between the right and left breasts. CONCLUSIONS The results of the present study showed no significant correlations between BPE and breast cancer. In addition, there was no significant difference between the right and left breast. Hence, BPE of MRI may not be a reliable biomarker of breast cancer development.
Collapse
Affiliation(s)
- H Sallam
- Department of Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
| | - L Lenga
- Department of Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - C Solbach
- Department Gynaecology and Obstetrics, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - S Becker
- Department Gynaecology and Obstetrics, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - T J Vogl
- Department of Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| |
Collapse
|
18
|
Xu C, Jiang M, Lin F, Zhang K, Xie H, Lv W, Ji H, Mao N. Qualitative assessments of density and background parenchymal enhancement on contrast-enhanced spectral mammography associated with breast cancer risk in high-risk women. Br J Radiol 2023:20220051. [PMID: 37227804 PMCID: PMC10392639 DOI: 10.1259/bjr.20220051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023] Open
Abstract
OBJECTIVE To investigate the correlation between the risk of breast cancer for high-risk females and the density and background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM). METHODS Females at high-risk, without breast cancer history and received CESM from July 2016 to December 2017 were retrospectively enrolled. The longest follow-up time was 4.5 years, and patients who developed breast cancer with maximized follow-up time were classified as cancer cohort, while females who did not develop breast cancer were categorized as control cohort. These two cohorts were one-to-one matched in age, family and/or genetic history of breast cancer, menopausal status and BRCA status. The density and BPE at CESM imaging were assessed. Conditional logistic regression was applied to evaluate the relationship between imaging features and breast cancer risk. RESULTS During the follow-up interval, 90 women at high-risk without history of breast cancer were newly diagnosed. Compared with minimal BPE, increasing BPE levels were associated with the risk of breast cancer among high-risk females in a time interval of 4.5 years (mild: odds ratio [OR]=3.2, p = 0.001; moderate: OR = 4.0, p = 0.002; marked: OR = 11.2, p < 0.001). In addition, females with mild, moderate or marked BPE were four times more likely to be diagnosed with breast cancer than females with minimal BPE in a time interval of 4.5 years (OR = 4.0, p < 0.001). CONCLUSION Qualitative CESM BPE assessment may be useful in the prediction of breast cancer risk among high-risk females. ADVANCES IN KNOWLEDGE • Qualitative CESM BPE assessment may be useful in the prediction of breast cancer risk among high-risk women during the follow-up period of 4.5 years.• The significance of breast density as an independent risk factor is not fully established for high-risk women during the follow-up period of 4.5 years.
Collapse
Affiliation(s)
- Cong Xu
- Physical Examination Center, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Meiping Jiang
- Department of Ultrasound, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Fan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Kun Zhang
- Department of Breast Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Wei Lv
- Physical Examination Center, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Haixia Ji
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
- Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China
| |
Collapse
|
19
|
Zhao X, Bai JW, Guo Q, Ren K, Zhang GJ. Clinical applications of deep learning in breast MRI. Biochim Biophys Acta Rev Cancer 2023; 1878:188864. [PMID: 36822377 DOI: 10.1016/j.bbcan.2023.188864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/05/2023] [Accepted: 01/17/2023] [Indexed: 02/25/2023]
Abstract
Deep learning (DL) is one of the most powerful data-driven machine-learning techniques in artificial intelligence (AI). It can automatically learn from raw data without manual feature selection. DL models have led to remarkable advances in data extraction and analysis for medical imaging. Magnetic resonance imaging (MRI) has proven useful in delineating the characteristics and extent of breast lesions and tumors. This review summarizes the current state-of-the-art applications of DL models in breast MRI. Many recent DL models were examined in this field, along with several advanced learning approaches and methods for data normalization and breast and lesion segmentation. For clinical applications, DL-based breast MRI models were proven useful in five aspects: diagnosis of breast cancer, classification of molecular types, classification of histopathological types, prediction of neoadjuvant chemotherapy response, and prediction of lymph node metastasis. For subsequent studies, further improvement in data acquisition and preprocessing is necessary, additional DL techniques in breast MRI should be investigated, and wider clinical applications need to be explored.
Collapse
Affiliation(s)
- Xue Zhao
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China; Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Jing-Wen Bai
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Department of Oncology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Cancer Research Center, School of Medicine, Xiamen University, Xiamen, China
| | - Qiu Guo
- Department of Radiology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Ke Ren
- Department of Radiology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
| | - Guo-Jun Zhang
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Xiamen Research Center of Clinical Medicine in Breast & Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Cancer Research Center, School of Medicine, Xiamen University, Xiamen, China.
| |
Collapse
|
20
|
Acciavatti RJ, Lee SH, Reig B, Moy L, Conant EF, Kontos D, Moon WK. Beyond Breast Density: Risk Measures for Breast Cancer in Multiple Imaging Modalities. Radiology 2023; 306:e222575. [PMID: 36749212 PMCID: PMC9968778 DOI: 10.1148/radiol.222575] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/23/2022] [Accepted: 12/05/2022] [Indexed: 02/08/2023]
Abstract
Breast density is an independent risk factor for breast cancer. In digital mammography and digital breast tomosynthesis, breast density is assessed visually using the four-category scale developed by the American College of Radiology Breast Imaging Reporting and Data System (5th edition as of November 2022). Epidemiologically based risk models, such as the Tyrer-Cuzick model (version 8), demonstrate superior modeling performance when mammographic density is incorporated. Beyond just density, a separate mammographic measure of breast cancer risk is parenchymal textural complexity. With advancements in radiomics and deep learning, mammographic textural patterns can be assessed quantitatively and incorporated into risk models. Other supplemental screening modalities, such as breast US and MRI, offer independent risk measures complementary to those derived from mammography. Breast US allows the two components of fibroglandular tissue (stromal and glandular) to be visualized separately in a manner that is not possible with mammography. A higher glandular component at screening breast US is associated with higher risk. With MRI, a higher background parenchymal enhancement of the fibroglandular tissue has also emerged as an imaging marker for risk assessment. Imaging markers observed at mammography, US, and MRI are powerful tools in refining breast cancer risk prediction, beyond mammographic density alone.
Collapse
Affiliation(s)
| | | | - Beatriu Reig
- From the Department of Radiology, University of Pennsylvania, 3400
Spruce St, Philadelphia, PA 19104 (R.J.A., E.F.C., D.K.); Department of
Radiology, Seoul National University Hospital, Seoul, South Korea (S.H.L.,
W.K.M.); and Department of Radiology, NYU Langone Health, New York, NY (B.R.,
L.M.)
| | - Linda Moy
- From the Department of Radiology, University of Pennsylvania, 3400
Spruce St, Philadelphia, PA 19104 (R.J.A., E.F.C., D.K.); Department of
Radiology, Seoul National University Hospital, Seoul, South Korea (S.H.L.,
W.K.M.); and Department of Radiology, NYU Langone Health, New York, NY (B.R.,
L.M.)
| | - Emily F. Conant
- From the Department of Radiology, University of Pennsylvania, 3400
Spruce St, Philadelphia, PA 19104 (R.J.A., E.F.C., D.K.); Department of
Radiology, Seoul National University Hospital, Seoul, South Korea (S.H.L.,
W.K.M.); and Department of Radiology, NYU Langone Health, New York, NY (B.R.,
L.M.)
| | | | | |
Collapse
|
21
|
Brown JC, Ligibel JA, Crane TE, Kontos D, Yang S, Conant EF, Mack JA, Ahima RS, Schmitz KH. Obesity and metabolic dysfunction correlate with background parenchymal enhancement in premenopausal women. Obesity (Silver Spring) 2023; 31:479-486. [PMID: 36628617 PMCID: PMC10141499 DOI: 10.1002/oby.23649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 10/14/2022] [Accepted: 10/17/2022] [Indexed: 01/12/2023]
Abstract
OBJECTIVE This study tested the hypothesis that obesity and metabolic abnormalities correlate with background parenchymal enhancement (BPE), the volume and intensity of enhancing fibroglandular breast tissue on dynamic contrast-enhanced magnetic resonance imaging. METHODS Participants included 59 premenopausal women at high risk of breast cancer. Obesity was defined as BMI ≥ 30 kg/m2 . Metabolic parameters included dual-energy x-ray absorptiometry-quantified body composition, plasma biomarkers of insulin resistance, adipokines, inflammation, lipids, and urinary sex hormones. BPE was assessed using computerized algorithms on dynamic contrast-enhanced magnetic resonance imaging. RESULTS BMI was positively correlated with BPE (r = 0.69; p < 0.001); participants with obesity had higher BPE than those without obesity (404.9 ± 189.6 vs. 261.8 ± 143.8 cm2 ; Δ: 143.1 cm2 [95% CI: 49.5-236.7]; p = 0.003). Total body fat mass (r = 0.68; p < 0.001), body fat percentage (r = 0.64; p < 0.001), visceral adipose tissue area (r = 0.65; p < 0.001), subcutaneous adipose tissue area (r = 0.60; p < 0.001), insulin (r = 0.59; p < 0.001), glucose (r = 0.35; p = 0.011), homeostatic model of insulin resistance (r = 0.62; p < 0.001), and leptin (r = 0.60; p < 0.001) were positively correlated with BPE. Adiponectin (r = -0.44; p < 0.001) was negatively correlated with BPE. Plasma biomarkers of inflammation and lipids and urinary sex hormones were not correlated with BPE. CONCLUSIONS In premenopausal women at high risk of breast cancer, increased BPE is associated with obesity, insulin resistance, leptin, and adiponectin.
Collapse
Affiliation(s)
- Justin C. Brown
- Pennington Biomedical Research Center, 6400 Perkins Rd, Baton Rouge, LA 70808, USA
- LSU Health Sciences Center New Orleans School of Medicine, 1901 Perdido St, New Orleans, LA 70112, USA
- Stanley S. Scott Cancer Center, Louisiana State University Health Sciences Center, 533 Bolivar St, New Orleans, LA, 70112, USA
| | | | - Tracy E. Crane
- University of Miami, Miller School of Medicine, 1600 NW 10 Ave, Miami, FL 33136
| | - Despina Kontos
- University of Pennsylvania, Perelman School of Medicine, 3400 Civic Center, Boulevard, Philadelphia, PA, 10104
| | - Shengping Yang
- Pennington Biomedical Research Center, 6400 Perkins Rd, Baton Rouge, LA 70808, USA
| | - Emily F. Conant
- University of Pennsylvania, Perelman School of Medicine, 3400 Civic Center, Boulevard, Philadelphia, PA, 10104
| | - Julie A. Mack
- Penn State College of Medicine, 500 University Drive, Hershey, PA 17033
| | - Rexford S. Ahima
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, 1830 E. Monument St., Baltimore, MD 21287
| | | |
Collapse
|
22
|
Lee SH, Jang MJ, Yoen H, Lee Y, Kim YS, Park AR, Ha SM, Kim SY, Chang JM, Cho N, Moon WK. Background Parenchymal Enhancement at Postoperative Surveillance Breast MRI: Association with Future Second Breast Cancer Risk. Radiology 2023; 306:90-99. [PMID: 36040335 DOI: 10.1148/radiol.220440] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Background Background parenchymal enhancement (BPE) is a known risk factor for breast cancer. However, studies on the association between BPE and second breast cancer risk are still lacking. Purpose To investigate whether BPE at surveillance breast MRI is associated with subsequent second breast cancer risk in women with a personal history of breast cancer. Materials and Methods A retrospective search of the imaging database of an academic medical center identified consecutive surveillance breast MRI examinations performed between January 2008 and December 2017 in women who underwent surgery for primary breast cancer and had no prior diagnosis of second breast cancer. BPE at surveillance breast MRI was qualitatively assessed using a four-category classification of minimal, mild, moderate, or marked. Future second breast cancer was defined as ipsilateral breast tumor recurrence or contralateral breast cancer diagnosed at least 1 year after each surveillance breast MRI examination. Factors associated with future second breast cancer risk were evaluated using the multivariable Fine-Gray subdistribution hazard model. Results Among the 2668 women (mean age at baseline surveillance breast MRI, 49 years ± 8 [SD]), 109 developed a second breast cancer (49 ipsilateral, 58 contralateral, and two ipsilateral and contralateral) at a median follow-up of 5.8 years. Mild, moderate, or marked BPE at surveillance breast MRI (hazard ratio [HR], 2.1 [95% CI: 1.4, 3.1]; P < .001), young age (<45 years) at initial breast cancer diagnosis (HR, 3.4 [95% CI: 1.7, 6.4]; P < .001), positive results from a BRCA1/2 genetic test (HR, 6.5 [95% CI: 3.5, 12.0]; P < .001), and negative hormone receptor expression in the initial breast cancer (HR, 1.6 [95% CI: 1.1, 2.6]; P = .02) were independently associated with an increased risk of future second breast cancer. Conclusion Background parenchymal enhancement at surveillance breast MRI was associated with future second breast cancer risk in women with a personal history of breast cancer. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Niell in this issue.
Collapse
Affiliation(s)
- Su Hyun Lee
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Myoung-Jin Jang
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Heera Yoen
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Youkyoung Lee
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yeon Soo Kim
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ah Reum Park
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Su Min Ha
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soo-Yeon Kim
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jung Min Chang
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Nariya Cho
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Woo Kyung Moon
- From the Department of Radiology (S.H.L., H.Y., Y.L., Y.S.K., A.R.P., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.) and Medical Research Collaborating Center (M.J.J.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea; and the Department of Radiology (S.H.L., S.M.H., S.Y.K., J.M.C., N.C., W.K.M.), Seoul National University College of Medicine, Seoul, Republic of Korea
| |
Collapse
|
23
|
Eskreis-Winkler S, Sutton EJ, D’Alessio D, Gallagher K, Saphier N, Stember J, Martinez DF, Morris EA, Pinker K. Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist. J Magn Reson Imaging 2022; 56:1068-1076. [PMID: 35167152 PMCID: PMC9376189 DOI: 10.1002/jmri.28111] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/01/2022] [Accepted: 02/02/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Background parenchymal enhancement (BPE) is assessed on breast MRI reports as mandated by the Breast Imaging Reporting and Data System (BI-RADS) but is prone to inter and intrareader variation. Semiautomated and fully automated BPE assessment tools have been developed but none has surpassed radiologist BPE designations. PURPOSE To develop a deep learning model for automated BPE classification and to compare its performance with current standard-of-care radiology report BPE designations. STUDY TYPE Retrospective. POPULATION Consecutive high-risk patients (i.e. >20% lifetime risk of breast cancer) who underwent contrast-enhanced screening breast MRI from October 2013 to January 2019. The study included 5224 breast MRIs, divided into 3998 training, 444 validation, and 782 testing exams. On radiology reports, 1286 exams were categorized as high BPE (i.e., marked or moderate) and 3938 as low BPE (i.e., mild or minimal). FIELD STRENGTH/SEQUENCE A 1.5 T or 3 T system; one precontrast and three postcontrast phases of fat-saturated T1-weighted dynamic contrast-enhanced imaging. ASSESSMENT Breast MRIs were used to develop two deep learning models (Slab artificial intelligence (AI); maximum intensity projection [MIP] AI) for BPE categorization using radiology report BPE labels. Models were tested on a heldout test sets using radiology report BPE and three-reader averaged consensus as the reference standards. STATISTICAL TESTS Model performance was assessed using receiver operating characteristic curve analysis. Associations between high BPE and BI-RADS assessments were evaluated using McNemar's chi-square test (α* = 0.025). RESULTS The Slab AI model significantly outperformed the MIP AI model across the full test set (area under the curve of 0.84 vs. 0.79) using the radiology report reference standard. Using three-reader consensus BPE labels reference standard, our AI model significantly outperformed radiology report BPE labels. Finally, the AI model was significantly more likely than the radiologist to assign "high BPE" to suspicious breast MRIs and significantly less likely than the radiologist to assign "high BPE" to negative breast MRIs. DATA CONCLUSION Fully automated BPE assessments for breast MRIs could be more accurate than BPE assessments from radiology reports. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY STAGE: 3.
Collapse
Affiliation(s)
- Sarah Eskreis-Winkler
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| | - Elizabeth J. Sutton
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| | - Donna D’Alessio
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| | - Katherine Gallagher
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| | - Nicole Saphier
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| | - Joseph Stember
- Department of Radiology, Neuroradiology Service, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Danny F Martinez
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| | | | - Katja Pinker
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY 10065, USA
| |
Collapse
|
24
|
Brooks JD, Christensen RAG, Sung JS, Pike MC, Orlow I, Bernstein JL, Morris EA. MRI background parenchymal enhancement, breast density and breast cancer risk factors: A cross-sectional study in pre- and post-menopausal women. NPJ Breast Cancer 2022; 8:97. [PMID: 36008488 PMCID: PMC9411561 DOI: 10.1038/s41523-022-00458-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 07/13/2022] [Indexed: 11/11/2022] Open
Abstract
Breast tissue enhances on contrast MRI and is called background parenchymal enhancement (BPE). Having high BPE has been associated with an increased risk of breast cancer. We examined the relationship between BPE and the amount of fibroglandular tissue on MRI (MRI-FGT) and breast cancer risk factors. This was a cross-sectional study of 415 women without breast cancer undergoing contrast-enhanced breast MRI at Memorial Sloan Kettering Cancer Center. All women completed a questionnaire assessing exposures at the time of MRI. Prevalence ratios (PR) and 95% confidence intervals (CI) describing the relationship between breast cancer risk factors and BPE and MRI-FGT were generated using modified Poisson regression. In multivariable-adjusted models a positive association between body mass index (BMI) and BPE was observed, with a 5-unit increase in BMI associated with a 14% and 44% increase in prevalence of high BPE in pre- and post-menopausal women, respectively. Conversely, a strong inverse relationship between BMI and MRI-FGT was observed in both pre- (PR = 0.66, 95% CI 0.57, 0.76) and post-menopausal (PR = 0.66, 95% CI 0.56, 0.78) women. Use of preventive medication (e.g., tamoxifen) was associated with having low BPE, while no association was observed for MRI-FGT. BPE is an imaging marker available from standard contrast-enhanced MRI, that is influenced by endogenous and exogenous hormonal exposures in both pre- and post-menopausal women.
Collapse
Affiliation(s)
- Jennifer D Brooks
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
| | | | - Janice S Sung
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Malcolm C Pike
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Irene Orlow
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jonine L Bernstein
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elizabeth A Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Radiology, University of California Davis, Sacramento, CA, USA
| |
Collapse
|
25
|
Dołęga-Kozierowski B, Lis M, Marszalska-Jacak H, Koziej M, Celer M, Bandyk M, Kasprzak P, Szynglarewicz B, Matkowski R. Multimodality imaging in lobular breast cancer: Differences in mammography, ultrasound, and MRI in the assessment of local tumor extent and correlation with molecular characteristics. Front Oncol 2022; 12:855519. [PMID: 36072800 PMCID: PMC9441946 DOI: 10.3389/fonc.2022.855519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 07/11/2022] [Indexed: 11/28/2022] Open
Abstract
Introduction Invasive lobular breast cancer (ILC) is a diagnostic challenge due to the diversity of morphological features. The objective of the study was to investigate the presentation and local extent of ILC using various imaging techniques and to assess the correlation between imaging and molecular profile. Materials and methods We reviewed 162 consecutive patients with ILC found on vacuum-assisted biopsy, who underwent evaluation of the lesion morphology and extent using ultrasound (US), mammography (MMG), and magnetic resonance imaging (MRI). Radiographic features were compared with ILC intrinsic subtype based on the expression of Ki-67 and estrogen, progesterone, and HER2 receptors. Results A total of 113 mass lesions and 49 non-mass enhancements (NMEs) were found in MRI. Masses were typically irregular and spiculated, showing heterogeneous contrast enhancement, diffusion restriction, and type III enhancement curve. NMEs presented mainly as the area of focal or multiregional distribution with heterogeneous or clumped contrast enhancement, diffusion restriction, and type III enhancement curve. Lesion extent significantly varied between MRI and MMG/ultrasonography (USG) (P < 0.001) but did not differ between MGF and ultrasonography (USG). The larger the ILC, the higher the disproportion when lesion extent in MRI was compared with MMG (P < 0.001) and ultrasonography (USG) (P < 0.001). In the study group, there were 97 cases of luminal A subtype (59.9%), 54 cases of luminal B HER2− (33.3%), nine cases of luminal B HER2+ (5.5%), and two cases of triple negative (1.2%). The HER2 type was not found in the study group. We did not observe any significant correlation between molecular profile and imaging. Conclusion MRI is the most effective technique for the assessment of ILC local extent, which is important for optimal treatment planning. Further studies are needed to investigate if the intrinsic subtype of ILC can be predicted by imaging features on MRI.
Collapse
Affiliation(s)
- Bartosz Dołęga-Kozierowski
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Michał Lis
- Burn and Plastic Surgery Department, Ludwik Rydygier Memorial Specialized Hospital in Krakow, Krakow, Poland
- *Correspondence: Michał Lis,
| | - Hanna Marszalska-Jacak
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Mateusz Koziej
- Department of Anatomy, Jagiellonian University Medical College, Krakow, Poland
| | - Marcin Celer
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Małgorzata Bandyk
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Piotr Kasprzak
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Bartłomiej Szynglarewicz
- Breast Unit, Department of Breast Surgery, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
- Department of Oncology, Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Rafał Matkowski
- Breast Unit, Department of Breast Surgery, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
- Department of Oncology, Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| |
Collapse
|
26
|
BI-RADS BERT and Using Section Segmentation to Understand Radiology Reports. J Imaging 2022; 8:jimaging8050131. [PMID: 35621895 PMCID: PMC9148091 DOI: 10.3390/jimaging8050131] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 04/29/2022] [Accepted: 05/06/2022] [Indexed: 02/01/2023] Open
Abstract
Radiology reports are one of the main forms of communication between radiologists and other clinicians, and contain important information for patient care. In order to use this information for research and automated patient care programs, it is necessary to convert the raw text into structured data suitable for analysis. State-of-the-art natural language processing (NLP) domain-specific contextual word embeddings have been shown to achieve impressive accuracy for these tasks in medicine, but have yet to be utilized for section structure segmentation. In this work, we pre-trained a contextual embedding BERT model using breast radiology reports and developed a classifier that incorporated the embedding with auxiliary global textual features in order to perform section segmentation. This model achieved 98% accuracy in segregating free-text reports, sentence by sentence, into sections of information outlined in the Breast Imaging Reporting and Data System (BI-RADS) lexicon, which is a significant improvement over the classic BERT model without auxiliary information. We then evaluated whether using section segmentation improved the downstream extraction of clinically relevant information such as modality/procedure, previous cancer, menopausal status, purpose of exam, breast density, and breast MRI background parenchymal enhancement. Using the BERT model pre-trained on breast radiology reports, combined with section segmentation, resulted in an overall accuracy of 95.9% in the field extraction tasks. This is a 17% improvement, compared to an overall accuracy of 78.9% for field extraction with models using classic BERT embeddings and not using section segmentation. Our work shows the strength of using BERT in the analysis of radiology reports and the advantages of section segmentation by identifying the key features of patient factors recorded in breast radiology reports.
Collapse
|
27
|
Henze Bancroft L, Holmes J, Bosca-Harasim R, Johnson J, Wang P, Korosec F, Block W, Strigel R. An Anthropomorphic Digital Reference Object (DRO) for Simulation and Analysis of Breast DCE MRI Techniques. Tomography 2022; 8:1005-1023. [PMID: 35448715 PMCID: PMC9031444 DOI: 10.3390/tomography8020081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/11/2022] [Accepted: 03/14/2022] [Indexed: 11/29/2022] Open
Abstract
Advances in accelerated magnetic resonance imaging (MRI) continue to push the bounds on achievable spatial and temporal resolution while maintaining a clinically acceptable image quality. Validation tools, including numerical simulations, are needed to characterize the repeatability and reproducibility of such methods for use in quantitative imaging applications. We describe the development of a simulation framework for analyzing and optimizing accelerated MRI acquisition and reconstruction techniques used in dynamic contrast enhanced (DCE) breast imaging. The simulation framework, in the form of a digital reference object (DRO), consists of four modules that control different aspects of the simulation, including the appearance and physiological behavior of the breast tissue as well as the MRI acquisition settings, to produce simulated k-space data for a DCE breast exam. The DRO design and functionality are described along with simulation examples provided to show potential applications of the DRO. The included simulation results demonstrate the ability of the DRO to simulate a variety of effects including the creation of simulated lesions, tissue enhancement modeled by the generalized kinetic model, T1-relaxation, fat signal precession and saturation, acquisition SNR, and changes in temporal resolution.
Collapse
Affiliation(s)
- Leah Henze Bancroft
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA; (J.H.); (J.J.); (F.K.); (W.B.); (R.S.)
- Correspondence:
| | - James Holmes
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA; (J.H.); (J.J.); (F.K.); (W.B.); (R.S.)
- Department of Radiology, University of Iowa, 169 Newton Road, Iowa City, IA 52333, USA
- Holden Comprehensive Cancer Center, University of Iowa, 169 Newton Road, Iowa City, IA 52333, USA
| | - Ryan Bosca-Harasim
- Department of Imaging Physics, Sanford Health, 801 Broadway North, Fargo, ND 58102, USA;
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA;
| | - Jacob Johnson
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA; (J.H.); (J.J.); (F.K.); (W.B.); (R.S.)
| | - Pingni Wang
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA;
| | - Frank Korosec
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA; (J.H.); (J.J.); (F.K.); (W.B.); (R.S.)
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA;
| | - Walter Block
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA; (J.H.); (J.J.); (F.K.); (W.B.); (R.S.)
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA;
- Department of Biomedical Engineering, University of Wisconsin, 1415 Engineering Drive, Madison, WI 53706, USA
| | - Roberta Strigel
- Department of Radiology, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA; (J.H.); (J.J.); (F.K.); (W.B.); (R.S.)
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, USA;
- Carbone Cancer Center, University of Wisconsin, 600 Highland Avenue, Madison, WI 53792, USA
| |
Collapse
|
28
|
Mathelin C, Barranger E, Boisserie-Lacroix M, Boutet G, Brousse S, Chabbert-Buffet N, Coutant C, Daraï E, Delpech Y, Duraes M, Espié M, Fornecker L, Golfier F, Grosclaude P, Hamy AS, Kermarrec E, Lavoué V, Lodi M, Luporsi É, Maugard CM, Molière S, Seror JY, Taris N, Uzan C, Vaysse C, Fritel X. [Non-genetic indications for risk reducing mastectomies: Guidelines of the National College of French Gynecologists and Obstetricians (CNGOF)]. GYNECOLOGIE, OBSTETRIQUE, FERTILITE & SENOLOGIE 2022; 50:107-120. [PMID: 34920167 DOI: 10.1016/j.gofs.2021.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE To determine the value of performing a risk-reducting mastectomy (RRM) in the absence of a deleterious variant of a breast cancer susceptibility gene, in 4 clinical situations at risk of breast cancer. DESIGN The CNGOF Commission of Senology, composed of 26 experts, developed these recommendations. A policy of declaration and monitoring of links of interest was applied throughout the process of making the recommendations. Similarly, the development of these recommendations did not benefit from any funding from a company marketing a health product. The Commission of Senology adhered to the AGREE II (Advancing guideline development, reporting and evaluation in healthcare) criteria and followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method to assess the quality of the evidence on which the recommendations were based. The potential drawbacks of making recommendations in the presence of poor quality or insufficient evidence were highlighted. METHODS The Commission of Senology considered 8 questions on 4 topics, focusing on histological, familial (no identified genetic abnormality), radiological (of unrecognized cancer), and radiation (history of Hodgkin's disease) risk. For each situation, it was determined whether performing RRM compared with surveillance would decrease the risk of developing breast cancer and/or increase survival. RESULTS The Commission of Senology synthesis and application of the GRADE method resulted in 11 recommendations, 6 with a high level of evidence (GRADE 1±) and 5 with a low level of evidence (GRADE 2±). CONCLUSION There was significant agreement among the Commission of Senology members on recommendations to improve practice for performing or not performing RRM in the clinical setting.
Collapse
Affiliation(s)
- Carole Mathelin
- CHRU, avenue Molière, 67200 Strasbourg, France; ICANS, 17, rue Albert-Calmette, 67033 Strasbourg cedex, France.
| | | | | | - Gérard Boutet
- AGREGA, service de chirurgie gynécologique et médecine de la reproduction, centre Aliénor d'Aquitaine, centre hospitalier universitaire de Bordeaux, groupe hospitalier Pellegrin, place Amélie-Raba-Léon, 33000 Bordeaux, France.
| | - Susie Brousse
- CHU de Rennes, 2, rue Henri-le-Guilloux, 35033 Rennes cedex 9, France.
| | | | - Charles Coutant
- Département d'oncologie chirurgicale, centre Georges-François-Leclerc, 1, rue du Pr-Marion, 21079 Dijon cedex, France.
| | - Emile Daraï
- Hôpital Tenon, service de gynécologie-obstétrique, 4, rue de la Chine, 75020 Paris, France.
| | - Yann Delpech
- Centre Antoine-Lacassagne, 33, avenue de Valombrose, 06189 Nice, France.
| | - Martha Duraes
- CHU de Montpellier, 191, avenue du Doyen-Giraud, 34295 Montpellier cedex, France.
| | - Marc Espié
- Hôpital Saint-Louis, 1, avenue Claude-Vellefaux, 75010 Paris, France.
| | - Luc Fornecker
- Département d'onco-hématologie, ICANS, 17, rue Albert-Calmette, 67033 Strasbourg cedex, France.
| | - François Golfier
- Centre hospitalier Lyon Sud, bâtiment 3B, 165, chemin du Grand-Revoyet, 69495 Pierre-Bénite, France.
| | | | | | - Edith Kermarrec
- Hôpital Tenon, service de radiologie, 4, rue de la Chine, 75020 Paris, France.
| | - Vincent Lavoué
- CHU, service de gynécologie, 16, boulevard de Bulgarie, 35200 Rennes, France.
| | | | - Élisabeth Luporsi
- Oncologie médicale et oncogénétique, CHR Metz-Thionville, hôpital de Mercy, 1, allée du Château, 57085 Metz, France.
| | - Christine M Maugard
- Service de génétique oncologique clinique, unité de génétique oncologique moléculaire, hôpitaux universitaires de Strasbourg, 1, avenue Molière, 67200 Strasbourg, France.
| | | | | | - Nicolas Taris
- Oncogénétique, ICANS, 17, rue Albert-Calmette, 67033 Strasbourg, France.
| | - Catherine Uzan
- Hôpital Pitié-Salpetrière, 47, boulevard de l'Hôpital, 75013 Paris, France.
| | - Charlotte Vaysse
- Service de chirurgie oncologique, CHU Toulouse, institut universitaire du cancer de Toulouse-Oncopole, 1, avenue Irène-Joliot-Curie, 31059 Toulouse, France.
| | - Xavier Fritel
- Centre hospitalo-universitaire de Poitiers, 2, rue de la Milétrie, 86021 Poitiers, France.
| |
Collapse
|
29
|
Background parenchymal enhancement in contrast-enhanced MR imaging suggests systemic effects of intrauterine contraceptive devices. Eur Radiol 2022; 32:7430-7438. [PMID: 35524784 PMCID: PMC9668774 DOI: 10.1007/s00330-022-08809-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 04/03/2022] [Accepted: 04/13/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVES Levonorgestrel-releasing intrauterine contraceptive devices (LNG-IUDs) are designed to exhibit only local hormonal effects. There is an ongoing debate on whether LNG-IUDs can have side effects similar to systemic hormonal medication. Benign background parenchymal enhancement (BPE) in dynamic contrast-enhanced (DCE) MRI has been established as a sensitive marker of hormonal stimulation of the breast. We investigated the association between LNG-IUD use and BPE in breast MRI to further explore possible systemic effects of LNG-IUDs. METHODS Our hospital database was searched to identify premenopausal women without personal history of breast cancer, oophorectomy, and hormone replacement or antihormone therapy, who had undergone standardized DCE breast MRI at least twice, once with and without an LNG-IUD in place. To avoid confounding aging-related effects on BPE, half of included women had their first MRI without, the other half with, LNG-IUD in place. Degree of BPE was analyzed according to the ACR categories. Wilcoxon-matched-pairs signed-rank test was used to compare the distribution of ACR categories with vs. without LNG-IUD. RESULTS Forty-eight women (mean age, 46 years) were included. In 24/48 women (50% [95% CI: 35.9-64.1%]), ACR categories did not change with vs. without LNG-IUDs. In 23/48 women (48% [33.9-62.1%]), the ACR category was higher with vs. without LNG-IUDs; in 1/48 (2% [0-6%]), the ACR category was lower with vs. without LNG-IUDs. The change of ACR category depending on the presence or absence of an LNG-IUD proved highly significant (p < 0.001). CONCLUSION The use of an LNG-IUD can be associated with increased BPE in breast MRI, providing further evidence that LNG-IUDs do have systemic effects. KEY POINTS • The use of levonorgestrel-releasing intrauterine contraceptive devices is associated with increased background parenchymal enhancement in breast MRI. • This suggests that hormonal effects of these devices are not only confined to the uterine cavity, but may be systemic. • Potential systemic effects of levonorgestrel-releasing intrauterine contraceptive devices should therefore be considered.
Collapse
|
30
|
Bauer E, Levy MS, Domachevsky L, Anaby D, Nissan N. Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review. Clin Imaging 2021; 83:41-50. [PMID: 34953310 DOI: 10.1016/j.clinimag.2021.11.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/29/2021] [Accepted: 11/15/2021] [Indexed: 12/20/2022]
Abstract
Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.
Collapse
Affiliation(s)
- Ethan Bauer
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Miri Sklair Levy
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Liran Domachevsky
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel
| | - Noam Nissan
- Department of Radiology, Sheba Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel.
| |
Collapse
|
31
|
Ragusi MAA, Bismeijer T, van der Velden BHM, Loo CE, Canisius S, Wesseling J, Wessels LFA, Elias SG, Gilhuijs KGA. Contralateral parenchymal enhancement on MRI is associated with tumor proteasome pathway gene expression and overall survival of early ER+/HER2-breast cancer patients. Breast 2021; 60:230-237. [PMID: 34763270 PMCID: PMC8591464 DOI: 10.1016/j.breast.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/26/2021] [Accepted: 11/02/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose To assess whether contralateral parenchymal enhancement (CPE) on MRI is associated with gene expression pathways in ER+/HER2-breast cancer, and if so, whether such pathways are related to survival. Methods Preoperative breast MRIs were analyzed of early ER+/HER2-breast cancer patients eligible for breast-conserving surgery included in a prospective observational cohort study (MARGINS). The contralateral parenchyma was segmented and CPE was calculated as the average of the top-10% delayed enhancement. Total tumor RNA sequencing was performed and gene set enrichment analysis was used to reveal gene expression pathways associated with CPE (N = 226) and related to overall survival (OS) and invasive disease-free survival (IDFS) in multivariable survival analysis. The latter was also done for the METABRIC cohort (N = 1355). Results CPE was most strongly correlated with proteasome pathways (normalized enrichment statistic = 2.04, false discovery rate = .11). Patients with high CPE showed lower tumor proteasome gene expression. Proteasome gene expression had a hazard ratio (HR) of 1.40 (95% CI = 0.89, 2.16; P = .143) for OS in the MARGINS cohort and 1.53 (95% CI = 1.08, 2.14; P = .017) for IDFS, in METABRIC proteasome gene expression had an HR of 1.09 (95% CI = 1.01, 1.18; P = .020) for OS and 1.10 (95% CI = 1.02, 1.18; P = .012) for IDFS. Conclusion CPE was negatively correlated with tumor proteasome gene expression in early ER+/HER2-breast cancer patients. Low tumor proteasome gene expression was associated with improved survival in the METABRIC data. Contralateral parenchymal enhancement on MRI was associated with tumor proteasome gene expression in ER+/HER2-breast cancer. A high contralateral parenchymal enhancement was associated with a low proteasome gene expression in the breast cancer. Low proteasome tumor gene expression was associated with improved survival in an independent patient cohort.
Collapse
Affiliation(s)
- Max A A Ragusi
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands; Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands.
| | - Tycho Bismeijer
- Division of Molecular Carcinogenesis - Oncode Institute, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Bas H M van der Velden
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Claudette E Loo
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Sander Canisius
- Division of Molecular Carcinogenesis - Oncode Institute, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Jelle Wesseling
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Lodewyk F A Wessels
- Division of Molecular Carcinogenesis - Oncode Institute, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Mekelweg 5, 2628 CD Delft, the Netherlands
| | - Sjoerd G Elias
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands
| | - Kenneth G A Gilhuijs
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| |
Collapse
|
32
|
Hu X, Jiang L, You C, Gu Y. Fibroglandular Tissue and Background Parenchymal Enhancement on Breast MR Imaging Correlates With Breast Cancer. Front Oncol 2021; 11:616716. [PMID: 34660251 PMCID: PMC8515131 DOI: 10.3389/fonc.2021.616716] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 09/16/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives To evaluate the association of breast cancer with both the background parenchymal enhancement intensity and volume (BPEI and BPEV, respectively) and the amount of fibroglandular tissue (FGT) using an automatic quantitative assessment method in breast magnetic resonance imaging (MRI). Materials and Methods Among 17,274 women who underwent breast MRI, 132 normal women (control group), 132 women with benign breast lesions (benign group), and 132 women with breast cancer (cancer group) were randomly selected and matched by age and menopausal status. The area under the receiver operating characteristic curve (AUC) was compared in Cancer vs Control and Cancer vs Benign groups to assess the discriminative ability of BPEI, BPEV and FGT. Results Compared with the control groups, the cancer group showed a significant difference in BPEV with a maximum AUC of 0.715 and 0.684 for patients in premenopausal and postmenopausal subgroup, respectively. And the cancer group showed a significant difference in BPEV with a maximum AUC of 0.622 and 0.633 for patients in premenopausal and postmenopausal subgroup, respectively, when compared with the benign group. FGT showed no significant difference when breast cancer group was compared with normal control and benign lesion group, respectively. Compared with the control groups, BPEI showed a slight difference in the cancer group. Compared with the benign group, no significant difference was seen in cancer group. Conclusion Increased BPEV is correlated with a high risk of breast cancer While FGT is not.
Collapse
Affiliation(s)
- Xiaoxin Hu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China
| | - Luan Jiang
- Center for Advanced Medical Imaging Technology, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
| | - Chao You
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China
| |
Collapse
|
33
|
You C, Zhang Y, Chen Y, Hu X, Hu D, Wu J, Gu Y, Peng W. Evaluation of Background Parenchymal Enhancement and Histogram-Based Diffusion-Weighted Image in Determining the Molecular Subtype of Breast Cancer. J Comput Assist Tomogr 2021; 45:711-716. [PMID: 34546678 DOI: 10.1097/rct.0000000000001239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
RATIONALE AND OBJECTIVES This study aimed to evaluate the value of background parenchymal enhancement (BPE) and diffusion-weighted image (DWI) histogram features in differentiating among different molecular subtypes of breast cancers and investigate the relationship between BPE and DWI features. MATERIALS AND METHODS We prospectively enrolled 142 patients with breast cancer between January and November 2018. All patients underwent breast magnetic resonance imaging before core needle biopsy. The quantitative BPE from dynamic enhanced images and the first-order histogram features extracted from DWI were analyzed. Univariate analysis of variance was used to compare differences in DWI histogram features and BPE characteristics among different molecular subtypes. Spearman test was used to compare the correlation between these imaging indexes. RESULTS A total of 142 patients had 142 lesions, including 17 cases of triple-negative breast cancer, 12 cases of luminal A type breast cancer, 39 cases of luminal B type breast cancer, and 74 cases of human epidermal growth factor receptor 2-positive breast cancer. The apparent diffusion coefficient (ADC) 95th percentile, ADC kurtosis, and BPE were significantly different among 4 subtype groups (P < 0.05), especially between the triple-negative subtype and any other subtype (P < 0.05 in pairwise comparisons). There was a weak but significant correlation between BPE and kurtosis of ADC (r = -0.176, P = 0.036). CONCLUSIONS Diffusion-weighted image histogram features (95th percentile ADC value and kurtosis value of ADC) and BPE features were different in the 4 molecular subtypes of breast cancer, especially in the triple-negative breast cancer subtype. Background parenchymal enhancement was negatively correlated with the kurtosis value of ADC.
Collapse
Affiliation(s)
- Chao You
- From the Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
| | - Yunyan Zhang
- Department of Radiology, Shanghai Proton and Heavy Ion Center
| | - Yanqiong Chen
- From the Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
| | - Xiaoxin Hu
- From the Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
| | - Danting Hu
- From the Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
| | - Jiong Wu
- Department of Breast Surgery, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China
| | - Yajia Gu
- From the Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
| | - Weijun Peng
- From the Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
| |
Collapse
|
34
|
Hunt KN. Molecular Breast Imaging: A Scientific Review. JOURNAL OF BREAST IMAGING 2021; 3:416-426. [PMID: 38424795 DOI: 10.1093/jbi/wbab039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Indexed: 03/02/2024]
Abstract
Molecular breast imaging (MBI) is a nuclear medicine technique that has evolved considerably over the past two decades. Technical advances have allowed reductions in administered doses to the point that they are now acceptable for screening. The most common radiotracer used in MBI, 99mTc-sestamibi, has a long history of safe use. Biopsy capability has become available in recent years, with early clinical experience demonstrating technically successful biopsies of MBI-detected lesions. MBI has been shown to be an effective supplemental screening tool in women with dense breasts and is also utilized for breast cancer staging, assessment of response to neoadjuvant chemotherapy, problem solving, and as an alternative to breast MRI in women who have a contraindication to MRI. The degree of background parenchymal uptake on MBI shows promise as a tool for breast cancer risk stratification. Radiologist interpretation is guided by a validated MBI lexicon that mirrors the BI-RADS lexicon. With short interpretation times, a fast learning curve for radiologists, and a substantially lower cost than breast MRI, MBI provides many benefits in the practices in which it is utilized. This review will discuss the current state of MBI technology, clinical applications of MBI, MBI interpretation, radiation dose associated with MBI, and the future of MBI.
Collapse
Affiliation(s)
- Katie N Hunt
- Mayo Clinic, Department of Radiology, Rochester, MN, USA
| |
Collapse
|
35
|
Vong S, Ronco AJ, Najafpour E, Aminololama-Shakeri S. Screening Breast MRI and the Science of Premenopausal Background Parenchymal Enhancement. JOURNAL OF BREAST IMAGING 2021; 3:407-415. [PMID: 38424792 DOI: 10.1093/jbi/wbab045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Indexed: 03/02/2024]
Abstract
The significance of background parenchymal enhancement (BPE) on screening and diagnostic breast MRI continues to be elucidated. Background parenchymal enhancement was initially deemed probably benign and followed or thought of as an artifact degrading the accuracy of breast cancer detection on breast MRI examinations. Subsequent research has focused on understanding the role of BPE regarding screening breast MRI. Today, there is growing evidence that a myriad of factors affect BPE, which in turn may influence patient outcomes. Additionally, BPE could represent an important risk factor for the future development of breast cancer. This article aims to describe the most up-to-date research on BPE as it relates to screening breast MRI in premenopausal women.
Collapse
Affiliation(s)
- Stephen Vong
- University of California Davis, Department of Radiology, Sacramento, CA, USA
| | - Anthony J Ronco
- University of California Davis, Department of Radiology, Sacramento, CA, USA
| | - Elham Najafpour
- University of California Davis, Department of Radiology, Sacramento, CA, USA
| | | |
Collapse
|
36
|
Marzocca F, Moffa G, Landi VN, Panzironi G, Kirchin MA, Pediconi F, Galati F. Gadoteridol-enhanced MRI of the breast: can contrast agent injection rate impact background parenchymal enhancement? Acta Radiol 2021; 63:1173-1179. [PMID: 34323589 DOI: 10.1177/02841851211034038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Normal background parenchymal enhancement (BPE) is a dynamic parameter affected by multiple factors. PURPOSE To determine whether contrast agent injection rate affects the degree of BPE in women undergoing breast magnetic resonance imaging (MRI). MATERIAL AND METHODS A total of 85 patients included in our prospective study randomly received 0.1 mmol/kg gadoteridol at a rate of 3 mL/s (group A; n = 46) or 2 mL/s (group B; n = 39). Breast MRI was performed at 3T using a standard protocol including postcontrast axial 3D GRE T1-weighted sequences. Two expert breast radiologists, blinded to clinical and radiological information, independently quantified BPE on early postcontrast subtracted images, assigning a score of 1-4. Mean comparison and regression analysis were performed to assess the influence of injection rate on BPE. RESULTS Groups were homogeneous in terms of age and final BI-RADS score. The mean BPE score was significantly lower among patients in group A (mean of two readers: 1.36 vs. 1.90; P < 0.01) with 70%-72% of patients assigned a BPE score of 1, compared with 36%-38% of patients in group B. Lower BPE scores were noted with the higher flow rate in subgroup analyses of both pre- and postmenopausal women, although the effect was more evident in premenopausal women. Regression analysis confirmed that the likelihood of a BPE 1 score was significantly increased with a higher flow rate (P < 0.01). The inter-reader agreement was excellent (0.83). CONCLUSION A higher contrast agent injection flow rate (3 mL/s) during breast MRI significantly reduces the degree of BPE, potentially allowing improved diagnostic accuracy by reducing false-positive and false-negative findings.
Collapse
Affiliation(s)
- Flaminia Marzocca
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Sapienza University of Rome, Rome, Italy
| | - Giuliana Moffa
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Sapienza University of Rome, Rome, Italy
| | | | - Giovanna Panzironi
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Sapienza University of Rome, Rome, Italy
| | | | - Federica Pediconi
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Sapienza University of Rome, Rome, Italy
| | - Francesca Galati
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Sapienza University of Rome, Rome, Italy
| |
Collapse
|
37
|
Quantitative Measures of Background Parenchymal Enhancement Predict Breast Cancer Risk. AJR Am J Roentgenol 2021; 217:64-75. [PMID: 32876474 PMCID: PMC9801515 DOI: 10.2214/ajr.20.23804] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND. Higher categories of background parenchymal enhancement (BPE) increase breast cancer risk. However, current clinical BPE categorization is subjective. OBJECTIVE. Using a semiautomated segmentation algorithm, we calculated quantitative BPE measures and investigated the utility of individual features and feature pairs in significantly predicting subsequent breast cancer risk compared with radiologist-assigned BPE category. METHODS. In this retrospective case-control study, we identified 95 women at high risk of breast cancer but without a personal history of breast cancer who underwent breast MRI. Of these women, 19 subsequently developed breast cancer and were included as cases. Each case was age matched to four control patients (76 control patients total). Sociodemographic characteristics were compared between the cases and matched control patients using the Mann-Whitney U test. From each dynamic contrast-enhanced MRI examination, quantitative fibroglandular tissue and BPE measures were computed by averaging enhancing voxels above enhancement ratio thresholds (0-100%), totaling the enhancing volume above thresholds (BPE volume in cm3), and estimating the percentage of enhancing tissue above thresholds relative to total breast volume (BPE%) on each gadolinium-enhanced phase. For the 91 imaging features generated, we compared predictive performance using conditional logistic regression with 80:20 hold-out cross validation and ROC curve analysis. ROC AUC was the figure of merit. Sensitivity, specificity, PPV, and NPV were also computed. All feature pairs were exhaustively searched to identify those with the highest AUC and Youden index. A DeLong test was used to compare predictive performance (AUCs). RESULTS. Women subsequently diagnosed with breast cancer were more likely to have mild, moderate, or marked BPE (odds ratio, 3.0; 95% CI, 0.9-10.0; p = .07). According to ROC curve analysis, a BPE category threshold greater than minimal resulted in a maximized AUC (0.62) in distinguishing cases from control patients. Compared with BPE category, the first gadolinium-enhanced (phase 1) BPE% at the 30% and 40% enhancement ratio thresholds yielded significantly higher AUC values of 0.85 (p = .0007) and 0.84 (p = .0004), respectively. Feature combinations showed similar AUC values with improved sensitivity. CONCLUSION. Preliminary data indicate that quantitative BPE measures may outperform radiologist-assigned category in breast cancer risk prediction. CLINICAL IMPACT. Future risk prediction models that incorporate quantitative measures warrant additional investigation.
Collapse
|
38
|
Nguyen AAT, Arasu VA, Strand F, Li W, Onishi N, Gibbs J, Jones EF, Joe BN, Esserman LJ, Newitt DC, Hylton NM. Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy. ACTA ACUST UNITED AC 2021; 6:101-110. [PMID: 32548286 PMCID: PMC7289261 DOI: 10.18383/j.tom.2020.00009] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Breast parenchymal enhancement (BPE) has shown association with breast cancer risk and response to neoadjuvant treatment. However, BPE quantification is challenging, and there is no standardized segmentation method for measurement. We investigated the use of a fully automated breast fibroglandular tissue segmentation method to calculate BPE from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for use as a predictor of pathologic complete response (pCR) following neoadjuvant treatment in the I-SPY 2 TRIAL. In this trial, patients had DCE-MRI at baseline (T0), after 3 weeks of treatment (T1), after 12 weeks of treatment and between drug regimens (T2), and after completion of treatment (T3). A retrospective analysis of 2 cohorts was performed: one with 735 patients and another with a final cohort of 340 patients, meeting a high-quality benchmark for segmentation. We evaluated 3 subvolumes of interest segmented from bilateral T1-weighted axial breast DCE-MRI: full stack (all axial slices), half stack (center 50% of slices), and center 5 slices. The differences between methods were assessed, and a univariate logistic regression model was implemented to determine the predictive performance of each segmentation method. The results showed that the half stack method provided the best compromise between sampling error from too little tissue and inclusion of incorrectly segmented tissues from extreme superior and inferior regions. Our results indicate that BPE calculated using the half stack segmentation approach has potential as an early biomarker for response to treatment in the hormone receptor–negative and human epidermal growth factor receptor 2–positive subtype.
Collapse
Affiliation(s)
- Alex Anh-Tu Nguyen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Vignesh A Arasu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA.,Department of Radiology, Kaiser Permanente Medical Center, Vallejo, CA
| | - Fredrik Strand
- Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden; and
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Natsuko Onishi
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Jessica Gibbs
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Ella F Jones
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Bonnie N Joe
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Laura J Esserman
- Department of Surgery, University of California, San Francisco, San Francisco, CA
| | - David C Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA
| |
Collapse
|
39
|
Xu C, Yu J, Wu F, Li X, Hu D, Chen G, Wu G. High-background parenchymal enhancement in the contralateral breast is an imaging biomarker for favorable prognosis in patients with triple-negative breast cancer treated with chemotherapy. Am J Transl Res 2021; 13:4422-4436. [PMID: 34150024 PMCID: PMC8205756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 03/12/2021] [Indexed: 06/12/2023]
Abstract
This study aimed to analyze the association between background parenchymal enhancement (BPE) in the contralateral breast tissue on magnetic resonance imaging (MRI) and clinicopathologic parameters in patients with unilateral breast carcinoma and to investigate its potential prognostic significance. A total of 467 patients who were pathologically confirmed to have unilateral breast cancer and underwent breast MRI were recruited to participate in this cohort study. BPE was assessed in the healthy contralateral breast. Minimal and mild levels were classified as low BPE, whereas moderate and marked levels were classified as high BPE. The effects of BPE on clinicopathologic parameters, overall survival (OS), and invasive disease-free survival (IDFS) were determined. Among the 467 patients, 327 cases were classified into the low-BPE group, whereas 140 cases were classified into the high-BPE group. The high-BPE pattern markedly correlated with age at diagnosis, menopausal status, histologic grading, and estrogen receptor status. BPE pattern did not correlate with OS and IDFS in the entire breast cancer cohort, regardless of whether adjuvant chemotherapy was received. Notably, BPE in the healthy contralateral breast on MRI is markedly related to OS and IDFS in triple-negative breast cancer (TNBC) cases who received chemotherapy. High BPE is related to chemotherapeutic benefits and can be an independent favorable prognostic factor for TNBC patients. Thus, our observations suggest that high BPE pattern can potentially be used as an imaging biomarker for relatively favorable prognosis in TNBC cases receiving chemotherapy. However, the findings need to be verified in a large-scale study.
Collapse
Affiliation(s)
- Chuanhui Xu
- Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan UniversityShanghai, China
| | - Jinhui Yu
- Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan UniversityShanghai, China
| | - Feifei Wu
- Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan UniversityShanghai, China
| | - Xuemei Li
- Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan UniversityShanghai, China
| | - Dongmin Hu
- Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan UniversityShanghai, China
| | - Guiming Chen
- Department of General Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of MedicineShanghai, China
| | - Gang Wu
- Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan UniversityShanghai, China
| |
Collapse
|
40
|
Berg WA, Bandos AI, Zuley ML, Waheed UX. Training Radiologists to Interpret Contrast-enhanced Mammography: Toward a Standardized Lexicon. JOURNAL OF BREAST IMAGING 2021; 3:176-189. [PMID: 38424825 DOI: 10.1093/jbi/wbaa115] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/05/2020] [Indexed: 03/02/2024]
Abstract
OBJECTIVE Using terms adapted from the BI-RADS Mammography and MRI lexicons, we trained radiologists to interpret contrast-enhanced mammography (CEM) and assessed reliability of their description and assessment. METHODS A 60-minute presentation on CEM and terminology was reviewed independently by 21 breast imaging radiologist observers. For 21 CEM exams with 31 marked findings, observers recorded background parenchymal enhancement (BPE) (minimal, mild, moderate, marked), lesion type (oval/round or irregular mass, or non-mass enhancement), intensity of enhancement (none, weak, medium, strong), enhancement quality (none, homogeneous, heterogeneous, rim), and BI-RADS assessment category (2, 3, 4A, 4B, 4C, 5). "Expert" consensus of 3 other radiologists experienced in CEM was developed. Kappa statistic was used to assess agreement between radiologists and expert consensus, and between radiologists themselves, on imaging feature categories and final assessments. Reproducibility of specific feature descriptors was assessed as fraction of consensus-concordant responses. RESULTS Radiologists demonstrated moderate agreement for BPE, (mean kappa, 0.43; range, 0.05-0.69), and lowest reproducibility for "minimal." Agreement was substantial for lesion type (mean kappa, 0.70; range, 0.47-0.93), moderate for intensity of enhancement (mean kappa, 0.57; range, 0.44-0.76), and moderate for enhancement quality (mean kappa, 0.59; range, 0.20-0.78). Agreement on final assessment was fair (mean kappa, 0.26; range, 0.09-0.44), with BI-RADS category 3 the least reproducible. Decision to biopsy (BI-RADS 2-3 vs 4-5) showed moderate agreement with consensus (mean kappa, 0.54; range, -0.06-0.87). CONCLUSION With minimal training, agreement for description of CEM findings by breast imaging radiologists was comparable to other BI-RADS lexicons.
Collapse
Affiliation(s)
- Wendie A Berg
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA
| | - Andriy I Bandos
- University of Pittsburgh Graduate School of Public Health, Department of Biostatistics, Pittsburgh, PA
| | - Margarita L Zuley
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA
| | - Uzma X Waheed
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA
| |
Collapse
|
41
|
Hesse LS, Kuling G, Veta M, Martel AL. Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols. IEEE Trans Biomed Eng 2021; 68:759-770. [DOI: 10.1109/tbme.2020.3016602] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
42
|
Hu N, Zhao J, Li Y, Fu Q, Zhao L, Chen H, Qin W, Yang G. Breast cancer and background parenchymal enhancement at breast magnetic resonance imaging: a meta-analysis. BMC Med Imaging 2021; 21:32. [PMID: 33607959 PMCID: PMC7893738 DOI: 10.1186/s12880-021-00566-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 02/09/2021] [Indexed: 11/10/2022] Open
Abstract
Background The background parenchymal enhancement at breast magnetic resonance imaging use to predict breast cancer attracts many searchers to draw a possible relationship. However, the results of their relationships were conflicting. This meta-analysis was performed to assess breast cancer frequency associations with background parenchymal enhancement. Methods A systematic literature search up to January 2020 was performed to detect studies recording associations between breast cancer frequency and background parenchymal enhancement. We found thirteen studies including 13,788 women at the start with 4046 breast cancer. We calculated the odds ratio (OR) and the 95% confidence intervals (CIs) between breast cancer frequency and background parenchymal enhancement by the dichotomous technique with a random or fixed-effect model. Results Women with minimal or mild background parenchymal enhancement at breast magnetic resonance imaging did not have any risk of breast cancer compared to control women (OR, 1.20; 95% CI 0.54–2.67). However, high background parenchymal enhancement at breast magnetic resonance imaging (OR, 2.66; 95% CI 1.36–5.19) and moderate (OR, 2.51; 95% CI 1.49–4.21) was associated with a significantly higher rate of breast cancer frequency compared to control women. Conclusions Our meta-analysis showed that the women with high and moderate background parenchymal enhancement at breast magnetic resonance imaging have higher risks, up to 2.66 fold, of breast cancer. We suggest that women with high or moderate background parenchymal enhancement at breast magnetic resonance imaging to be scheduled for more frequent follow-up and screening for breast cancer to avoid any complications.
Collapse
Affiliation(s)
- Na Hu
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Jinghao Zhao
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Yong Li
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Quanshui Fu
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Linwei Zhao
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Hong Chen
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Wei Qin
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China.
| | - Guoqing Yang
- Department of Radiology, Suining Central Hospital, Suining, 629000, Sichuan, China.
| |
Collapse
|
43
|
Zhang M, Sadinski M, Haddad D, Bae MS, Martinez D, Morris EA, Gibbs P, Sutton EJ. Background Parenchymal Enhancement on Breast MRI as a Prognostic Surrogate: Correlation With Breast Cancer Oncotype Dx Score. Front Oncol 2021; 10:595820. [PMID: 33614481 PMCID: PMC7890019 DOI: 10.3389/fonc.2020.595820] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 12/11/2020] [Indexed: 12/11/2022] Open
Abstract
Purpose Breast MRI background parenchymal enhancement (BPE) can potentially serve as a prognostic marker, by possible correlation with molecular subtype. Oncotype Dx, a gene assay, is a prognostic and predictive surrogate for tumor aggressiveness and treatment response. The purpose of this study was to investigate the association between contralateral non-tumor breast magnetic resonance imaging (MRI) background parenchymal enhancement and tumor oncotype score. Methods In this retrospective study, patients with ER+ and HER2− early stage invasive ductal carcinoma who underwent preoperative breast MRI, oncotype risk scoring, and breast conservation surgery from 2008–2010 were identified. After registration, BPE from the pre and three post-contrast phases was automatically extracted using a k-means clustering algorithm. Four metrics were calculated: initial enhancement (IE) relative to the pre-contrast signal, late enhancement, overall enhancement (OE), and area under the enhancement curve (AUC). Histogram analysis was performed to determine first order metrics which were compared to oncotype risk score groups using Mann–Whitney tests and Spearman rank correlation analysis. Results This study included 80 women (mean age = 51.1 ± 10.3 years); 46 women were categorized as low risk (≤17) and 34 women were categorized as intermediate/high risk (≥18) according to Oncotype Dx. For the mean of the top 10% pixels, significant differences were noted for IE (p = 0.032), OE (p = 0.049), and AUC (p = 0.044). Using the risk score as a continuous variable, correlation analysis revealed a weak but significant correlation with the mean of the top 10% pixels for IE (r = 0.26, p = 0.02), OE (r = 0.25, p = 0.02), and AUC (r = 0.27, p = 0.02). Conclusion BPE metrics of enhancement in the non-tumor breast are associated with tumor Oncotype Dx recurrence score, suggesting that the breast microenvironment may relate to likelihood of recurrence and magnitude of chemotherapy benefit.
Collapse
Affiliation(s)
- Michelle Zhang
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.,Department of Radiology, McGill University, Montreal, QC, Canada
| | - Meredith Sadinski
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Dana Haddad
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.,Department of Radiology, Montefiore, New York, NY, United States.,Department of Radiology, Mediclinic Middle East, Dubai, United Arab Emirates.,College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Min Sun Bae
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.,Department of Radiology, Seoul National University Hospital, Seoul, South Korea
| | - Danny Martinez
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Elizabeth A Morris
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Peter Gibbs
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Elizabeth J Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| |
Collapse
|
44
|
Elmi A, Conant EF, Kozlov A, Young AJ, Long Q, Doot RK, McDonald ES. Preoperative breast MR imaging in newly diagnosed breast cancer: Comparison of outcomes based on mammographic modality, breast density and breast parenchymal enhancement. Clin Imaging 2021; 70:18-24. [PMID: 33120285 PMCID: PMC10870106 DOI: 10.1016/j.clinimag.2020.10.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/26/2020] [Accepted: 10/07/2020] [Indexed: 01/06/2023]
Abstract
PURPOSE To compare the role of MR for assessment of extent of disease in women newly diagnosed with breast cancer imaged with digital mammography (DM) alone versus digital breast tomosynthesis (DBT). METHODS Retrospective review was conducted of 401 consecutive breast MR exams (10/1/2013-7/31/2015) from women who underwent preoperative MR for newly diagnosed breast cancer by either DM or DBT, leaving 388 exams (201 DM and 187 DBT). MR detection of additional, otherwise occult, disease was stratified by modality, breast density, and background parenchymal enhancement. A true-positive finding was defined as malignancy in the ipsilateral-breast >2 cm away from the index-lesion or in the contralateral breast. RESULTS 50 additional malignancies were detected in 388 exams (12.9%), 37 ipsilateral and 13 contralateral. There was no difference in the MR detection of additional disease in women imaged by either DM versus DBT (p = 0.53). In patients with DM, there was no significant difference in the rate of MR additional cancer detection in dense versus non-dense breasts (p = 0.790). However, in patients with DBT, MR detected significantly more additional sites of malignancy in dense compared to non-dense breasts (p = 0.017). There was no difference in false-positive MR exams (p = 0.470) for DM versus DBT. For both DM and DBT cohorts, higher MR background parenchymal enhancement was associated with higher false-positive (p = 0.040) but no significant difference in true-positive exams. CONCLUSIONS Among patients with DBT imaging at cancer diagnosis, women with dense breasts appear to benefit more from preoperative MR than non-dense women. In women imaged only with DM, MR finds additional malignancy across all breast densities.
Collapse
Affiliation(s)
- Azadeh Elmi
- Breast Imaging Division, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Emily F Conant
- Breast Imaging Division, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
| | - Andrew Kozlov
- Breast Imaging Division, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
| | - Anthony J Young
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
| | - Qi Long
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
| | - Robert K Doot
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
| | - Elizabeth S McDonald
- Breast Imaging Division, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
| |
Collapse
|
45
|
Kim JJ, Kim JY. Fusion of high b-value diffusion-weighted and unenhanced T1-weighted images to diagnose invasive breast cancer: factors associated with false-negative results. Eur Radiol 2021; 31:4860-4871. [PMID: 33443601 DOI: 10.1007/s00330-020-07644-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 11/06/2020] [Accepted: 12/17/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVES We sought factors associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast breast magnetic resonance imaging (MRI) using fused high b-value diffusion-weighted imaging (DWI) and unenhanced T1-weighted images (T1WI). METHODS Between 2018 and 2019, 316 consecutive women (mean age, 54.6 years) with invasive breast cancer who underwent preoperative breast MRI, including fused high b-value DWI and unenhanced T1WI, were retrospectively evaluated. Malignancy confidence ratings of the most suspicious breast lesions evident on fused DWI were derived by two radiologists using a 6-point Likert-type scale. Both clinicopathological and imaging features were analyzed. Multivariate regression analysis was performed to identify factors associated with false-negative DWI results in the diagnosis of invasive breast cancer. RESULTS Of the 316 breast cancers, fused DWI yielded 289 (91.5%) true-positive and 27 (8.5%) false-negative results. Multivariate analysis showed that small tumor size (≤ 1 cm) (odds ratio [OR], 5.95; 95% confidence interval [CI], 2.11, 16.81; p = 0.001), presence of calcifications in the tumor (OR, 3.41; 95% CI, 1.27, 9.15; p = 0.015), and a moderate/marked background diffusion signal (ORs, 4.23 and 19.18; 95% CI, 1.31, 13.67 and 6.51, 56.46; p = 0.016 and p < 0.001, respectively) were significantly associated with false-negative results. In subgroup analysis of 141 screening-detected cancers, a marked background diffusion signal (OR, 7.94; 95% CI, 2.30, 27.35; p = 0.001) remained significantly associated with false-negative results in the multivariate analysis. CONCLUSIONS In addition to histopathological features, a higher background diffusion signal was associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast MRI using fused high b-value DWI and unenhanced T1WI. KEY POINTS • Subcentimeter tumors and presence of calcifications in the tumor are associated with false-negative diffusion-weighted imaging results in the diagnosis of invasive breast cancer. • A higher degree of background diffusion signal may lead to false-negative interpretation of diffusion-weighted imaging in patients with invasive breast cancer.
Collapse
Affiliation(s)
- Jin Joo Kim
- Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea
| | - Jin You Kim
- Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea.
| |
Collapse
|
46
|
|
47
|
You C, Xiao Q, Zhu X, Sun Y, Di G, Liu G, Hou Y, Chen C, Wu J, Shao Z, Gu Y, Hu Z. The clinicopathological and MRI features of patients with BRCA1/2 mutations in familial breast cancer. Gland Surg 2021; 10:262-272. [PMID: 33633982 DOI: 10.21037/gs-20-596] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Background To determine the histopathological and MRI features of BRCA1/2 mutation-associated familial breast cancers compared with those of BRCA1/2 mutation-negative and sporadic breast cancers and to further compare the imaging features of cancers from BRCA1 and BRCA2 mutation carriers according to lesion type on MRI. Methods A retrospective review of medical records was conducted to determine tumour clinicopathologic features and MRI characteristics between June 2011 and July 2017, and 93 lesions with BRCA mutations, 93 lesions without BRCA mutations from familial breast cancers and 93 lesions from sporadic breast cancers were included. Histopathologic data, including immunohistochemistry findings and MRI data according to the BI-RADS lexicon, were reviewed. The association between MRI or histopathologic findings and BRCA mutations was analysed. Results BRCA-positive familial breast cancers had a higher number of IDCs with high nuclear grade and lymph node metastasis (all P<0.05), while the BRCA-negative group had a significantly lower Ki-67 index (P<0.001). BPE on MRI was found to be significantly lower for BRCA mutations of familial breast cancer (P=0.024). BRCA1 carriers tended to exhibit the triple-negative phenotype with a more benign shape and margin (P=0.006 and 0.019), whereas BRCA2 mutations were associated with the luminal phenotype and more malignant features. Conclusions BRCA mutation carriers had a significantly higher number of IDCs with more aggressive cancer, and BRCA-negative cancers had low proliferation levels. Background features on MRI may help to identify BRCA status, while tumour characteristics can differentiate the BRCA1/2 mutation status, consistent with the differences in their clinicopathologic features.
Collapse
Affiliation(s)
- Chao You
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qin Xiao
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xinyi Zhu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yiqun Sun
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Genhong Di
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Guangyu Liu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yifeng Hou
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Canming Chen
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jiong Wu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhimin Shao
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yajia Gu
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhen Hu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| |
Collapse
|
48
|
Spear GG, Mendelson EB. Automated breast ultrasound: Supplemental screening for average-risk women with dense breasts. Clin Imaging 2020; 76:15-25. [PMID: 33548888 DOI: 10.1016/j.clinimag.2020.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 11/24/2020] [Accepted: 12/17/2020] [Indexed: 11/25/2022]
Abstract
OBJECTIVE We review ultrasound (US) options for supplemental breast cancer screening of average risk women with dense breasts. CONCLUSION Performance data of physician-performed handheld US (HHUS), technologist-performed HHUS, and automated breast ultrasound (AUS) indicate that all are appropriate for adjunctive screening. Volumetric 3D acquisitions, reduced operator dependence, protocol standardization, reliable comparison with previous studies, independence of performance and interpretation, and whole breast depiction on coronal view may favor selection of AUS. Important considerations are workflow adjustments for physicians and staff.
Collapse
Affiliation(s)
- Georgia Giakoumis Spear
- NorthShore University HealthSystem, The University of Chicago Pritzker School of Medicine, United States of America.
| | - Ellen B Mendelson
- Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America
| |
Collapse
|
49
|
Yu L, Wang Y, Xing D, Gong P, Chen Q, Lv Y. Background parenchymal enhancement on contrast-enhanced spectral mammography does not represent an influencing factor for breast cancer: A preliminary study. Medicine (Baltimore) 2020; 99:e23857. [PMID: 33350778 PMCID: PMC7769306 DOI: 10.1097/md.0000000000023857] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 11/05/2020] [Indexed: 11/26/2022] Open
Abstract
To compare the relationship between background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM), mammographic breast density (MBD), age, in the group with benign vs malignant breast lesions.Four hundred thirty three non-high-risk patients from January 2018 to May 2019 were retrospectively analyzed. Patients were assigned into 4 groups: premenopausal benign lesions, premenopausal malignant lesions, postmenopausal benign lesions, and postmenopausal malignant lesions. The differences in CESM BPE and MBD between premenopausal benign lesions and premenopausal malignant lesions, between postmenopausal benign lesions and postmenopausal malignant lesions, between premenopausal and postmenopausal benign lesions, and between premenopausal and postmenopausal malignant lesions were evaluated. Pearson Chi-Squared test was used to analyze the differences between the above groups. Spearman rank correlation analysis was used to evaluate the correlations between BPE, MBD, and age. Multiple logistic regression was used to analyze the influencing factors of breast cancer. P < .05 was considered statistically significant.There was no significant difference in CESM BPE or MBD of benign and malignant lesions regardless of premenopausal or postmenopausal status, but there was a significant difference in CESM BPE and MBD of premenopausal and postmenopausal patients regardless of the presence of benign or malignant lesions. The intensity of CESM BPE was positively correlated with MBD, and the intensity of CESM BPE and MBD were negatively correlated with age. Multiple logistic regression analysis showed that age was an influencing factor for breast cancer in both premenopausal and postmenopausal patients.For non-high-risk women, CESM BPE and MBD were not correlated with benign or malignant breast lesions, and age was an influencing factor for breast cancer.
Collapse
Affiliation(s)
| | | | - Dong Xing
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong
| | - Peiyou Gong
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong
| | - Qianqian Chen
- GE Healthcare, Institute of Precision Medicine, Shanghai, PR China
| | - Yongbin Lv
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong
| |
Collapse
|
50
|
Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems. AJR Am J Roentgenol 2020; 216:860-873. [PMID: 33295802 DOI: 10.2214/ajr.20.24894] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BI-RADS is a communication and data tracking system that has evolved since its inception as a brief mammography lexicon and reporting guide into a robust structured reporting platform and comprehensive quality assurance tool for mammography, ultrasound, and MRI. Consistent and appropriate use of the BI-RADS lexicon terminology and assessment categories effectively communicates findings, estimates the risk of malignancy, and provides management recommendations to patients and referring clinicians. The impact of BI-RADS currently extends internationally through six language translations. A condensed version has been proposed to facilitate a phased implementation of BI-RADS in resource-constrained regions. The primary advance of the 5th edition of BI-RADS is harmonization of the lexicon terms across mammography, ultrasound, and MRI. Harmonization has also been achieved across these modalities for the reporting structure, assessment categories, management recommendations, and data tracking system. Areas for improvement relate to certain common findings that lack lexicon descriptors and a need for further clarification of proper use of category 3. BI-RADS is anticipated to continue to evolve for application to a range of emerging breast imaging modalities.
Collapse
|