914 results on '"Lehman, Constance D"'
Search Results
2. Feasibility of risk assessment for breast cancer molecular subtypes
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McCarthy, Anne Marie, Ehsan, Sarah, Hughes, Kevin S., Lehman, Constance D., Conant, Emily F., Kontos, Despina, Armstrong, Katrina, and Chen, Jinbo
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- 2024
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3. A prospective study of HER3 expression pre and post neoadjuvant therapy of different breast cancer subtypes: implications for HER3 imaging therapy guidance
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Sinevici, Nicoleta, Edmonds, Christine E., Dontchos, Brian N., Wang, Gary, Lehman, Constance D., Isakoff, Steven, and Mahmood, Umar
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- 2024
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4. Missed Screening Mammography Appointments: Patient Sociodemographic Characteristics and Mammography Completion After 1 Year
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Wang, Gary X., Mercaldo, Sarah F., Cahill, Jennifer E., Flanagan, Jane M., Lehman, Constance D., and Park, Elyse R.
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- 2024
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5. Incidence, Timing, and Long-Term Outcomes of COVID-19 Vaccine-Related Lymphadenopathy on Screening Mammography
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Lamb, Leslie R., Mercaldo, Sarah F., Carney, Andrew, Leyva, Alexander, D’Alessandro, Helen Anne, and Lehman, Constance D.
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- 2024
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6. Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.
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Onishi, Natsuko, Li, Wen, Newitt, David C, Harnish, Roy J, Strand, Fredrik, Nguyen, Alex Anh-Tu, Arasu, Vignesh Amal, Gibbs, Jessica, Jones, Ella F, Wilmes, Lisa J, Kornak, John, Joe, Bonnie N, Price, Elissa R, Ojeda-Fournier, Haydee, Eghtedari, Mohammad, Zamora, Kathryn W, Woodard, Stefanie, Umphrey, Heidi R, Nelson, Michael T, Church, An L, Bolan, Patrick J, Kuritza, Theresa, Ward, Kathleen, Morley, Kevin, Wolverton, Dulcy, Fountain, Kelly, Lopez Paniagua, Dan, Hardesty, Lara, Brandt, Kathleen R, McDonald, Elizabeth S, Rosen, Mark, Kontos, Despina, Abe, Hiroyuki, Sheth, Deepa, Crane, Erin, Dillis, Charlotte, Sheth, Pulin, Hovanessian-Larsen, Linda, Bang, Dae Hee, Porter, Bruce, Oh, Karen Y, Jafarian, Neda, Tudorica, Luminita A, Niell, Bethany, Drukteinis, Jennifer, Newell, Mary S, Giurescu, Marina E, Berman, Elise, Lehman, Constance D, Partridge, Savannah C, Fitzpatrick, Kimberly A, Borders, Marisa H, Yang, Wei Tse, Dogan, Basak, Goudreau, Sally Hayward, Chenevert, Thomas, Yau, Christina, DeMichele, Angela, Berry, Donald A, Esserman, Laura J, and Hylton, Nola M
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Breast ,Humans ,Breast Neoplasms ,Contrast Media ,Magnetic Resonance Imaging ,Image Enhancement ,Treatment Outcome ,Chemotherapy ,Adjuvant ,Neoadjuvant Therapy ,Retrospective Studies ,Cohort Studies ,Adult ,Aged ,Middle Aged ,Female ,Young Adult ,Cancer ,Breast Cancer ,Biomedical Imaging ,Aging ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging - Abstract
Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.
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- 2021
7. U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation
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Wang, Shuhang, Hu, Szu-Yeu, Cheah, Eugene, Wang, Xiaohong, Wang, Jingchao, Chen, Lei, Baikpour, Masoud, Ozturk, Arinc, Li, Qian, Chou, Shinn-Huey, Lehman, Constance D., Kumar, Viksit, and Samir, Anthony
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
This paper proposes a novel U-Net variant using stacked dilated convolutions for medical image segmentation (SDU-Net). SDU-Net adopts the architecture of vanilla U-Net with modifications in the encoder and decoder operations (an operation indicates all the processing for feature maps of the same resolution). Unlike vanilla U-Net which incorporates two standard convolutions in each encoder/decoder operation, SDU-Net uses one standard convolution followed by multiple dilated convolutions and concatenates all dilated convolution outputs as input to the next operation. Experiments showed that SDU-Net outperformed vanilla U-Net, attention U-Net (AttU-Net), and recurrent residual U-Net (R2U-Net) in all four tested segmentation tasks while using parameters around 40% of vanilla U-Net's, 17% of AttU-Net's, and 15% of R2U-Net's., Comment: 8 pages MICCAI
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- 2020
8. Breast cancer polygenic risk scores are associated with short-term risk of poor prognosis breast cancer
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McCarthy, Anne Marie, Manning, Alisa K., Hsu, Sarah, Welch, Michaela, Moy, Beverly, Lehman, Constance D., and Armstrong, Katrina
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- 2022
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9. Expert identification of visual primitives used by CNNs during mammogram classification
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Wu, Jimmy, Peck, Diondra, Hsieh, Scott, Dialani, Vandana, Lehman, Constance D., Zhou, Bolei, Syrgkanis, Vasilis, Mackey, Lester, and Patterson, Genevieve
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Computer Science - Computer Vision and Pattern Recognition - Abstract
This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop interpretation method to label the behavior of internal units in convolutional neural networks (CNNs). Expert radiologists identify that the visual patterns detected by the units are correlated with meaningful medical phenomena such as mass tissue and calcificated vessels. We demonstrate that several trained CNN models are able to produce explanatory descriptions to support the final classification decisions. We view this as an important first step toward interpreting the internal representations of medical classification CNNs and explaining their predictions.
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- 2018
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10. Surveillance Breast MRI and Mammography: Comparison in Women with a Personal History of Breast Cancer
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Wernli, Karen J, Ichikawa, Laura, Kerlikowske, Karla, Buist, Diana SM, Brandzel, Susan D, Bush, Mary, Johnson, Dianne, Henderson, Louise M, Nekhlyudov, Larissa, Onega, Tracy, Sprague, Brian L, Lee, Janie M, Lehman, Constance D, and Miglioretti, Diana L
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Prevention ,Women's Health ,Clinical Research ,Biomedical Imaging ,Cancer ,Breast Cancer ,Breast ,Breast Neoplasms ,Cohort Studies ,Female ,Humans ,Magnetic Resonance Imaging ,Mammography ,Middle Aged ,Neoplasms ,Second Primary ,Reproducibility of Results ,Sensitivity and Specificity ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
Background There is lack of consensus regarding the use of breast MRI for routine surveillance for second breast cancer events in women with a personal history of breast cancer. Purpose To compare performance of surveillance mammography with breast MRI. Materials and Methods This observational cohort study used prospectively collected data and included 13 266 women age 18 years and older (mean age, 60 years ± 13) with stage 0-III breast cancer who underwent 33 938 mammographic examinations and 2506 breast MRI examinations from 2005 to 2012 in the Breast Cancer Surveillance Consortium. Women were categorized into two groups: mammography alone (n = 11 745) or breast MRI (n = 1521). Performance measures were calculated by using end-of-day assessment and occurrence of second breast cancer events within 1 year of imaging. Logistic regression was used to compare performance for breast MRI versus mammography alone, adjusting for women, examination, and primary breast cancer characteristics. Analysis was conducted on a per-examination basis. Results Breast MRI was associated with younger age at diagnosis, chemotherapy, and higher education and income. Raw performance measures for breast MRI versus mammography were as follows, respectively: cancer detection rates, 10.8 (95% confidence interval [CI]: 6.7, 14.8) versus 8.2 (95% CI: 7.3, 9.2) per 1000 examinations; sensitivity, 61.4% (27 of 44; 95% CI: 46.5%, 76.2%) versus 70.3% (279 of 397; 95% CI: 65.8%, 74.8%); and biopsy rate, 10.1% (253 of 2506; 95% CI: 8.9%, 11.3%) versus 4.0% (1343 of 33 938; 95% CI: 3.7%, 4.2%). In multivariable models, breast MRI was associated with higher biopsy rate (odds ratio [OR], 2.2; 95% CI: 1.9, 2.7; P < .001) and cancer detection rate (OR, 1.7; 95% CI: 1.1, 2.7; P = .03) than mammography alone. However, there were no differences in sensitivity (OR, 1.1; 95% CI: 0.4, 2.9; P = .84) or interval cancer rate (OR, 1.1; 95% CI: 0.6, 2.2; P = .70). Conclusion Comparison of the performance of surveillance breast MRI with mammography must account for patient characteristics. Whereas breast MRI leads to higher biopsy and cancer detection rates, there were no significant differences in sensitivity or interval cancers compared with mammography. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Newell in this issue.
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- 2019
11. Population-Based Assessment of the Association Between Magnetic Resonance Imaging Background Parenchymal Enhancement and Future Primary Breast Cancer Risk
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Arasu, Vignesh A, Miglioretti, Diana L, Sprague, Brian L, Alsheik, Nila H, Buist, Diana SM, Henderson, Louise M, Herschorn, Sally D, Lee, Janie M, Onega, Tracy, Rauscher, Garth H, Wernli, Karen J, Lehman, Constance D, and Kerlikowske, Karla
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Prevention ,Breast Cancer ,Women's Health ,Clinical Research ,Biomedical Imaging ,Cancer ,4.1 Discovery and preclinical testing of markers and technologies ,Breast ,Breast Density ,Breast Neoplasms ,Carcinoma ,Ductal ,Breast ,Female ,Humans ,Image Enhancement ,Magnetic Resonance Imaging ,Mammography ,Neoplasm Invasiveness ,Parenchymal Tissue ,Registries ,Risk Factors ,SEER Program ,United States ,Clinical Sciences ,Oncology & Carcinogenesis ,Oncology and carcinogenesis - Abstract
PurposeTo evaluate comparative associations of breast magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and mammographic breast density with subsequent breast cancer risk.Patients and methodsWe examined women undergoing breast MRI in the Breast Cancer Surveillance Consortium from 2005 to 2015 (with one exam in 2000) using qualitative BPE assessments of minimal, mild, moderate, or marked. Breast density was assessed on mammography performed within 5 years of MRI. Among women diagnosed with breast cancer, the first BPE assessment was included if it was more than 3 months before their first diagnosis. Breast cancer risk associated with BPE was estimated using Cox proportional hazards regression.ResultsAmong 4,247 women, 176 developed breast cancer (invasive, n = 129; ductal carcinoma in situ,n = 47) over a median follow-up time of 2.8 years. More women with cancer had mild, moderate, or marked BPE than women without cancer (80% v 66%, respectively). Compared with minimal BPE, increasing BPE levels were associated with significantly increased cancer risk (mild: hazard ratio [HR], 1.80; 95% CI, 1.12 to 2.87; moderate: HR, 2.42; 95% CI, 1.51 to 3.86; and marked: HR, 3.41; 95% CI, 2.05 to 5.66). Compared with women with minimal BPE and almost entirely fatty or scattered fibroglandular breast density, women with mild, moderate, or marked BPE demonstrated elevated cancer risk if they had almost entirely fatty or scattered fibroglandular breast density (HR, 2.30; 95% CI, 1.19 to 4.46) or heterogeneous or extremely dense breasts (HR, 2.61; 95% CI, 1.44 to 4.72), with no significant interaction (P = .82). Combined mild, moderate, and marked BPE demonstrated significantly increased risk of invasive cancer (HR, 2.73; 95% CI, 1.66 to 4.49) but not ductal carcinoma in situ (HR, 1.48; 95% CI, 0.72 to 3.05).ConclusionBPE is associated with future invasive breast cancer risk independent of breast density. BPE should be considered for risk prediction models for women undergoing breast MRI.
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- 2019
12. Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice
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Dontchos, Brian N., Cavallo-Hom, Katherine, Lamb, Leslie R., Mercaldo, Sarah F., Eklund, Martin, Dang, Pragya, and Lehman, Constance D.
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- 2022
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13. Stacked dilated convolutions and asymmetric architecture for U-Net-based medical image segmentation
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Wang, Shuhang, Singh, Vivek Kumar, Cheah, Eugene, Wang, Xiaohong, Li, Qian, Chou, Shinn-Huey, Lehman, Constance D., Kumar, Viksit, and Samir, Anthony E.
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- 2022
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14. Power Spectrum Analysis of Breast Parenchyma with Digital Breast Tomosynthesis Images in a Longitudinal Screening Cohort from Two Vendors
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Yang, Kai, Abbey, Craig K, Chou, Shinn-Huey Shirley, Dontchos, Brian N, Li, Xinhua, Lehman, Constance D, and Liu, Bob
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- 2022
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15. Are English-language online patient education materials related to breast cancer risk assessment understandable, readable, and actionable?
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Lamb, Leslie R., Baird, Grayson L., Roy, Ishita T., Choi, Paul H.S., Lehman, Constance D., and Miles, Randy C.
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- 2022
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16. Impact of a Same-Day Breast Biopsy Program on Disparities in Time to Biopsy for Patients With Serious Mental Illness
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Wang, Gary X., Hwong, Alison R., Mercaldo, Sarah F., Lehman, Constance D., and Dontchos, Brian N.
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- 2022
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17. AUR-RRA Review: Logistics of Academic-Industry Partnerships in Artificial Intelligence
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Spilseth, Benjamin, McKnight, Colin D., Li, Matthew D., Park, Christian J., Fried, Jessica G., Yi, Paul H., Brian, James M., Lehman, Constance D., Wang, Xiaoqin Jennifer, Phalke, Vaishali, Pakkal, Mini, Baruah, Dhiraj, Khine, Pwint Phyu, and Fajardo, Laurie L.
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- 2022
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18. The Effect of Digital Breast Tomosynthesis Adoption on Facility-Level Breast Cancer Screening Volume.
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Lee, Christoph I, Zhu, Weiwei, Onega, Tracy L, Germino, Jessica, O'Meara, Ellen S, Lehman, Constance D, Henderson, Louise M, Haas, Jennifer S, Kerlikowske, Karla, Sprague, Brian L, Rauscher, Garth H, Tosteson, Anna NA, Alford-Teaster, Jennifer, Wernli, Karen J, and Miglioretti, Diana L
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Biomedical Imaging ,Women's Health ,Prevention ,Cancer ,Breast Cancer ,Adult ,Aged ,Breast Neoplasms ,Early Detection of Cancer ,Female ,Humans ,Mammography ,Mass Screening ,Middle Aged ,Prospective Studies ,Registries ,breast cancer screening ,capacity ,digital breast tomosynthesis ,technology adoption ,Clinical Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
ObjectiveThe purpose of this study was to determine whether digital breast tomosynthesis (DBT) adoption was associated with a decrease in screening mammography capacity across Breast Cancer Screening Consortium facilities, given concerns about increasing imaging and interpretation times associated with DBT.Subjects and methodsFacility characteristics and examination volume data were collected prospectively from Breast Cancer Screening Consortium facilities that adopted DBT between 2011 and 2014. Interrupted time series analyses using Poisson regression models in which facility was considered a random effect were used to evaluate differences between monthly screening volumes during the 12-month preadoption period and the 12-month postadoption period (with the two periods separated by a 3-month lag) and to test for changes in month-to-month facility-level screening volume during the preadoption and postadoption periods.ResultsAcross five regional breast imaging registries, 15 of 83 facilities (18.1%) adopted DBT for screening between 2011 and 2014. Most had no academic affiliation (73.3% [11/15]), were nonprofit (80.0% [12/15]), and were general radiology practices (66.7% [10/15]). Facility-level monthly screening volumes were slightly higher during the postadoption versus preadoption periods (relative risk [RR], 1.09; 95% CI, 1.06-1.11). Monthly screening volumes remained relatively stable within the preadoption period (RR, 1.00 per month; 95% CI 1.00-1.01 per month) and the postadoption period (RR, 1.00; 95% CI, 1.00-1.01 per month).ConclusionIn a cohort of facilities with varied characteristics, monthly screening examination volumes did not decrease after DBT adoption.
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- 2018
19. Cumulative Risk Distribution for Interval Invasive Second Breast Cancers After Negative Surveillance Mammography.
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Lee, Janie M, Abraham, Linn, Lam, Diana L, Buist, Diana SM, Kerlikowske, Karla, Miglioretti, Diana L, Houssami, Nehmat, Lehman, Constance D, Henderson, Louise M, and Hubbard, Rebecca A
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Breast Cancer ,Women's Health ,Cancer ,Biomedical Imaging ,Prevention ,4.2 Evaluation of markers and technologies ,Adult ,Aged ,Aged ,80 and over ,Breast Neoplasms ,Carcinoma in Situ ,Carcinoma ,Ductal ,Breast ,Female ,Humans ,Mammography ,Middle Aged ,Multivariate Analysis ,Neoplasms ,Second Primary ,Risk ,SEER Program ,United States ,Clinical Sciences ,Oncology & Carcinogenesis ,Oncology and carcinogenesis - Abstract
Purpose The aim of the current study was to characterize the risk of interval invasive second breast cancers within 5 years of primary breast cancer treatment. Methods We examined 65,084 surveillance mammograms from 18,366 women with a primary breast cancer diagnosis of unilateral ductal carcinoma in situ or stage I to III invasive breast carcinoma performed from 1996 to 2012 in the Breast Cancer Surveillance Consortium. Interval invasive breast cancer was defined as ipsilateral or contralateral cancer diagnosed within 1 year after a negative surveillance mammogram. Discrete-time survival models-adjusted for all covariates-were used to estimate the probability of interval invasive cancer, given the risk factors for each surveillance round, and aggregated across rounds to estimate the 5-year cumulative probability of interval invasive cancer. Results We observed 474 surveillance-detected cancers-334 invasive and 140 ductal carcinoma in situ-and 186 interval invasive cancers which yielded a cancer detection rate of 7.3 per 1,000 examinations (95% CI, 6.6 to 8.0) and an interval invasive cancer rate of 2.9 per 1,000 examinations (95% CI, 2.5 to 3.3). Median cumulative 5-year interval cancer risk was 1.4% (interquartile range, 0.8% to 2.3%; 10th to 90th percentile range, 0.5% to 3.7%), and 15% of women had ≥ 3% 5-year interval invasive cancer risk. Cumulative 5-year interval cancer risk was highest for women with estrogen receptor- and progesterone receptor-negative primary breast cancer (2.6%; 95% CI, 1.7% to 3.5%), interval cancer presentation at primary diagnosis (2.2%; 95% CI, 1.5% to 2.9%), and breast conservation without radiation (1.8%; 95% CI, 1.1% to 2.4%). Conclusion Risk of interval invasive second breast cancer varies across women and is influenced by characteristics that can be measured at initial diagnosis, treatment, and imaging. Risk prediction models that evaluate the risk of cancers not detected by surveillance mammography should be developed to inform discussions of tailored surveillance.
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- 2018
20. MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial.
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Scheel, John R, Kim, Eunhee, Partridge, Savannah C, Lehman, Constance D, Rosen, Mark A, Bernreuter, Wanda K, Pisano, Etta D, Marques, Helga S, Morris, Elizabeth A, Weatherall, Paul T, Polin, Sandra M, Newstead, Gillian M, Esserman, Laura J, Schnall, Mitchell D, and Hylton, Nola M
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Biomedical Imaging ,Cancer ,Clinical Research ,Clinical Trials and Supportive Activities ,Breast Cancer ,Adult ,Breast Neoplasms ,Female ,Humans ,Magnetic Resonance Imaging ,Mammography ,Middle Aged ,Neoadjuvant Therapy ,Neoplasm Invasiveness ,Neoplasm ,Residual ,Physical Examination ,Preoperative Care ,Prospective Studies ,Treatment Outcome ,Tumor Burden ,clinical examination ,locally advanced breast cancer ,mammography ,MRI ,neoadjuvant chemotherapy ,pathologic complete response ,ACRIN 6657 Trial Team and I-SPY Investigators Network ,Clinical Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
ObjectiveThe objective of our study was to determine the accuracy of preoperative measurements for detecting pathologic complete response (CR) and assessing residual disease after neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer.Subjects and methodsThe American College of Radiology Imaging Network 6657 Trial prospectively enrolled women with ≥ 3 cm invasive breast cancer receiving NACT. Preoperative measurements of residual disease included longest diameter by mammography, MRI, and clinical examination and functional volume on MRI. The accuracy of preoperative measurements for detecting pathologic CR and the association with final pathology size were assessed for all lesions, separately for single masses and nonmass enhancements (NMEs), multiple masses, and lesions without ductal carcinoma in situ (DCIS).ResultsIn the 138 women with all four preoperative measures, longest diameter by MRI showed the highest accuracy for detecting pathologic CR for all lesions and NME (AUC = 0.76 and 0.84, respectively). There was little difference across preoperative measurements in the accuracy of detecting pathologic CR for single masses (AUC = 0.69-0.72). Longest diameter by MRI and longest diameter by clinical examination showed moderate ability for detecting pathologic CR for multiple masses (AUC = 0.78 and 0.74), and longest diameter by MRI and longest diameter by mammography showed moderate ability for detecting pathologic CR for tumors without DCIS (AUC = 0.74 and 0.71). In subjects with residual disease, longest diameter by MRI exhibited the strongest association with pathology size for all lesions and single masses (r = 0.33 and 0.47). Associations between preoperative measures and pathology results were not significantly influenced by tumor subtype or mammographic density.ConclusionOur results indicate that measurement of longest diameter by MRI is more accurate than by mammography and clinical examination for preoperative assessment of tumor residua after NACT and may improve surgical planning.
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- 2018
21. Deep learning vs traditional breast cancer risk assessment models: Are we offering supplemental services to those who benefit the most?
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Lamb, Leslie R., primary, Albasha, Heba, additional, Mercaldo, Sarah, additional, Carney, Andrew, additional, and Lehman, Constance D, additional
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- 2024
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22. MRI for Screening Women with a Personal History of Breast Cancer
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Bahl, Manisha, Di Leo, Giovanni, Lehman, Constance D., Sardanelli, Francesco, editor, and Podo, Franca, editor
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- 2020
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23. Multilevel Follow-up of Cancer Screening (mFOCUS): Protocol for a multilevel intervention to improve the follow-up of abnormal cancer screening test results
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Haas, Jennifer S., Atlas, Steven J., Wright, Adam, Orav, E. John, Aman, David G., Breslau, Erica S., Burdick, Timothy E., Carpenter, Emily, Chang, Frank, Dang, Tin, Diamond, Courtney J., Feldman, Sarah, Harris, Kimberly A., Hort, Shoshana J., Housman, Molly L., Mecker, Amrita, Lehman, Constance D., Percac-Lima, Sanja, Smith, Rebecca, Wint, Amy J., Yang, Jie, Zhou, Li, and Tosteson, Anna N.A.
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- 2021
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24. Leveraging Emergency Department Encounters to Improve Cancer Screening Adherence
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Miles, Randy C., Flores, Efren J., Lopez, Diego B., Sohn, Young-Jin, Gillis, Eleanor A., Lehman, Constance D., and Narayan, Anand K.
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- 2021
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25. Unilateral Lymphadenopathy After COVID-19 Vaccination: A Practical Management Plan for Radiologists Across Specialties
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Lehman, Constance D., D’Alessandro, Helen Anne, Mendoza, Dexter P., Succi, Marc D., Kambadakone, Avinash, and Lamb, Leslie R.
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- 2021
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26. External Validation of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice
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Dontchos, Brian N., Yala, Adam, Barzilay, Regina, Xiang, Justin, and Lehman, Constance D.
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- 2021
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27. Performance Benchmarks for Screening Breast MR Imaging in Community Practice
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Lee, Janie M, Ichikawa, Laura, Valencia, Elizabeth, Miglioretti, Diana L, Wernli, Karen, Buist, Diana SM, Kerlikowske, Karla, Henderson, Louise M, Sprague, Brian L, Onega, Tracy, Rauscher, Garth H, and Lehman, Constance D
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Breast Cancer ,Biomedical Imaging ,Health Services ,Prevention ,Cancer ,Clinical Research ,Women's Health ,4.2 Evaluation of markers and technologies ,Benchmarking ,Breast ,Breast Neoplasms ,Cohort Studies ,Early Detection of Cancer ,Female ,Humans ,Magnetic Resonance Imaging ,Middle Aged ,Predictive Value of Tests ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
Purpose To compare screening magnetic resonance (MR) imaging performance in the Breast Cancer Surveillance Consortium (BCSC) with Breast Imaging Reporting and Data System (BI-RADS) benchmarks. Materials and Methods This study was approved by the institutional review board and compliant with HIPAA and included BCSC screening MR examinations collected between 2005 and 2013 from 5343 women (8387 MR examinations) linked to regional Surveillance, Epidemiology, and End Results program registries, state tumor registries, and pathologic information databases that identified breast cancer cases and tumor characteristics. Clinical, demographic, and imaging characteristics were assessed. Performance measures were calculated according to BI-RADS fifth edition and included cancer detection rate (CDR), positive predictive value of biopsy recommendation (PPV2), sensitivity, and specificity. Results The median patient age was 52 years; 52% of MR examinations were performed in women with a first-degree family history of breast cancer, 46% in women with a personal history of breast cancer, and 15% in women with both risk factors. Screening MR imaging depicted 146 cancers, and 35 interval cancers were identified (181 total-54 in situ, 125 invasive, and two status unknown). The CDR was 17 per 1000 screening examinations (95% confidence interval [CI]: 15, 20 per 1000 screening examinations; BI-RADS benchmark, 20-30 per 1000 screening examinations). PPV2 was 19% (95% CI: 16%, 22%; benchmark, 15%). Sensitivity was 81% (95% CI: 75%, 86%; benchmark, >80%), and specificity was 83% (95% CI: 82%, 84%; benchmark, 85%-90%). The median tumor size of invasive cancers was 10 mm; 88% were node negative. Conclusion The interpretative performance of screening MR imaging in the BCSC meets most BI-RADS benchmarks and approaches benchmark levels for remaining measures. Clinical practice performance data can inform ongoing benchmark development and help identify areas for quality improvement. © RSNA, 2017.
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- 2017
28. Mammography Performance Benchmarks in an Era of Value-based Care.
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Lee, Janie M, Miglioretti, Diana L, Burnside, Elizabeth S, Morris, Elizabeth A, Smith, Robert A, and Lehman, Constance D
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Biomedical and Clinical Sciences ,Clinical Sciences ,Benchmarking ,Breast Neoplasms ,Humans ,Mammography ,Mass Screening ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Published
- 2017
29. MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial
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Bolan, Patrick J, Kim, Eunhee, Herman, Benjamin A, Newstead, Gillian M, Rosen, Mark A, Schnall, Mitchell D, Pisano, Etta D, Weatherall, Paul T, Morris, Elizabeth A, Lehman, Constance D, Garwood, Michael, Nelson, Michael T, Yee, Douglas, Polin, Sandra M, Esserman, Laura J, Gatsonis, Constantine A, Metzger, Gregory J, Newitt, David C, Partridge, Savannah C, Hylton, Nola M, and Investigators, for the ACRIN Trial team ISPY‐1
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Clinical Research ,Cancer ,Biomedical Imaging ,Breast Cancer ,Adult ,Aged ,Algorithms ,Biomarkers ,Tumor ,Breast Neoplasms ,Choline ,Early Detection of Cancer ,Female ,Humans ,Magnetic Resonance Spectroscopy ,Male ,Middle Aged ,Molecular Imaging ,Reproducibility of Results ,Secondary Prevention ,Sensitivity and Specificity ,magnetic resonance spectroscopy ,breast cancer ,choline ,treatment response ,ACRIN Trial team ISPY-1 Investigators ,Physical Sciences ,Engineering ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
PurposeTo estimate the accuracy of predicting response to neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer using MR spectroscopy (MRS) measurements made very early in treatment.Materials and methodsThis prospective Health Insurance Portability and Accountability Act (HIPAA)-compliant protocol was approved by the American College of Radiology and local-site institutional review boards. One hundred nineteen women with invasive breast cancer of ≥3 cm undergoing NACT were enrolled between September 2007 and April 2010. MRS measurements of the concentration of choline-containing compounds ([tCho]) were performed before the first chemotherapy regimen (time point 1, TP1) and 20-96 h after the first cycle of treatment (TP2). The change in [tCho] was assessed for its ability to predict pathologic complete response (pCR) and radiologic response using the area under the receiver operating characteristic curve (AUC) and logistic regression models.ResultsOf the 119 subjects enrolled, only 29 cases (24%) with eight pCRs provided usable data for the primary analysis. Technical challenges in acquiring quantitative MRS data in a multi-site trial setting limited the capture of usable data. In this limited data set, the decrease in tCho from TP1 to TP2 had poor ability to predict either pCR (AUC = 0.53, 95% confidence interval [CI]: 0.27-0.79) or radiologic response (AUC = 0.51, 95% CI: 0.27-0.75).ConclusionThe technical difficulty of acquiring quantitative MRS data in a multi-site clinical trial setting led to a low yield of analyzable data, which was insufficient to accurately measure the ability of early MRS measurements to predict response to NACT.Level of evidence1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:290-302.
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- 2017
30. National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium.
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Lehman, Constance D, Arao, Robert F, Sprague, Brian L, Lee, Janie M, Buist, Diana SM, Kerlikowske, Karla, Henderson, Louise M, Onega, Tracy, Tosteson, Anna NA, Rauscher, Garth H, and Miglioretti, Diana L
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Cancer ,Women's Health ,Breast Cancer ,Prevention ,Biomedical Imaging ,4.2 Evaluation of markers and technologies ,Good Health and Well Being ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Benchmarking ,Breast Neoplasms ,Early Detection of Cancer ,Female ,Humans ,Mammography ,Mass Screening ,Middle Aged ,Registries ,Sensitivity and Specificity ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
Purpose To establish performance benchmarks for modern screening digital mammography and assess performance trends over time in U.S. community practice. Materials and Methods This HIPAA-compliant, institutional review board-approved study measured the performance of digital screening mammography interpreted by 359 radiologists across 95 facilities in six Breast Cancer Surveillance Consortium (BCSC) registries. The study included 1 682 504 digital screening mammograms performed between 2007 and 2013 in 792 808 women. Performance measures were calculated according to the American College of Radiology Breast Imaging Reporting and Data System, 5th edition, and were compared with published benchmarks by the BCSC, the National Mammography Database, and performance recommendations by expert opinion. Benchmarks were derived from the distribution of performance metrics across radiologists and were presented as 50th (median), 10th, 25th, 75th, and 90th percentiles, with graphic presentations using smoothed curves. Results Mean screening performance measures were as follows: abnormal interpretation rate (AIR), 11.6 (95% confidence interval [CI]: 11.5, 11.6); cancers detected per 1000 screens, or cancer detection rate (CDR), 5.1 (95% CI: 5.0, 5.2); sensitivity, 86.9% (95% CI: 86.3%, 87.6%); specificity, 88.9% (95% CI: 88.8%, 88.9%); false-negative rate per 1000 screens, 0.8 (95% CI: 0.7, 0.8); positive predictive value (PPV) 1, 4.4% (95% CI: 4.3%, 4.5%); PPV2, 25.6% (95% CI: 25.1%, 26.1%); PPV3, 28.6% (95% CI: 28.0%, 29.3%); cancers stage 0 or 1, 76.9%; minimal cancers, 57.7%; and node-negative invasive cancers, 79.4%. Recommended CDRs were achieved by 92.1% of radiologists in community practice, and 97.1% achieved recommended ranges for sensitivity. Only 59.0% of radiologists achieved recommended AIRs, and only 63.0% achieved recommended levels of specificity. Conclusion The majority of radiologists in the BCSC surpass cancer detection recommendations for screening mammography; however, AIRs continue to be higher than the recommended rate for almost half of radiologists interpreting screening mammograms. © RSNA, 2016 Online supplemental material is available for this article.
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- 2017
31. National Performance Benchmarks for Modern Diagnostic Digital Mammography: Update from the Breast Cancer Surveillance Consortium
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Sprague, Brian L, Arao, Robert F, Miglioretti, Diana L, Henderson, Louise M, Buist, Diana SM, Onega, Tracy, Rauscher, Garth H, Lee, Janie M, Tosteson, Anna NA, Kerlikowske, Karla, Lehman, Constance D, and Consortium, For the Breast Cancer Surveillance
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Breast Cancer ,Prevention ,Biomedical Imaging ,Women's Health ,Cancer ,4.2 Evaluation of markers and technologies ,Good Health and Well Being ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Benchmarking ,Breast Neoplasms ,Early Detection of Cancer ,Female ,Humans ,Mammography ,Mass Screening ,Middle Aged ,Registries ,Sensitivity and Specificity ,Breast Cancer Surveillance Consortium ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
Purpose To establish contemporary performance benchmarks for diagnostic digital mammography with use of recent data from the Breast Cancer Surveillance Consortium (BCSC). Materials and Methods Institutional review board approval was obtained for active or passive consenting processes or to obtain a waiver of consent to enroll participants, link data, and perform analyses. Data were obtained from six BCSC registries (418 radiologists, 92 radiology facilities). Mammogram indication and assessments were prospectively collected for women undergoing diagnostic digital mammography and linked with cancer diagnoses from state cancer registries. The study included 401 548 examinations conducted from 2007 to 2013 in 265 360 women. Results Overall diagnostic performance measures were as follows: cancer detection rate, 34.7 per 1000 (95% confidence interval [CI]: 34.1, 35.2); abnormal interpretation rate, 12.6% (95% CI: 12.5%, 12.7%); positive predictive value (PPV) of a biopsy recommendation (PPV2), 27.5% (95% CI: 27.1%, 27.9%); PPV of biopsies performed (PPV3), 30.4% (95% CI: 29.9%, 30.9%); false-negative rate, 4.8 per 1000 (95% CI: 4.6, 5.0); sensitivity, 87.8% (95% CI: 87.3%, 88.4%); and specificity, 90.5% (95% CI: 90.4%, 90.6%). Among cancers detected, 63.4% were stage 0 or 1 cancers, 45.6% were minimal cancers, the mean size of invasive cancers was 21.2 mm, and 69.6% of invasive cancers were node negative. Performance metrics varied widely across diagnostic indications, with cancer detection rate (64.5 per 1000) and abnormal interpretation rate (18.7%) highest for diagnostic mammograms obtained to evaluate a breast problem with a lump. Compared with performance during the screen-film mammography era, diagnostic digital performance showed increased abnormal interpretation and cancer detection rates and decreasing PPVs, with less than 70% of radiologists within acceptable ranges for PPV2 and PPV3. Conclusion These performance measures can serve as national benchmarks that may help transform the marked variation in radiologists' diagnostic performance into targeted quality improvement efforts. © RSNA, 2017 Online supplemental material is available for this article.
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- 2017
32. Opportunities for Radiology Trainee Education Amid the COVID-19 Pandemic: Lessons From an Academic Breast Imaging Program
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Wang, Gary X., Chou, Shinn-Huey S., Lamb, Leslie R., Narayan, Anand K., Dontchos, Brian N., Lehman, Constance D., and Miles, Randy C.
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- 2021
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33. Stargazing through the lens of AI in clinical oncology
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Lehman, Constance D. and Wu, Shandong
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- 2021
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34. The Adoption and Impact on Performance of an Automated Outcomes Feedback Application for Tomosynthesis Screening Mammography
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Sippo, Dorothy A., Sullivan, Amy M., Cohen, Amy, Mercaldo, Sarah F., Bahl, Manisha, and Lehman, Constance D.
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- 2020
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35. Implementation and Utilization of a “Pink Card” Walk-In Screening Mammography Program Integrated With Physician Visits
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Wang, Gary X., Pizzi, Beverly T., Miles, Randy C., Dontchos, Brian N., LaPointe, Annette P., Lehman, Constance D., and Narayan, Anand K.
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- 2020
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36. Screening for Breast Cancer
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Narayan, Anand K., Lee, Christoph I., and Lehman, Constance D.
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- 2020
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37. Ductal Carcinoma In Situ (DCIS) at Breast MRI: Predictors of Upgrade to Invasive Carcinoma
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Lamb, Leslie R., Lehman, Constance D., Oseni, Tawakalitu O., and Bahl, Manisha
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- 2020
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38. Screening Mammography Visits as Opportunities to Engage Smokers With Tobacco Cessation Services and Lung Cancer Screening
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Wang, Gary X., Narayan, Anand K., Park, Elyse R., Lehman, Constance D., Gorenstein, Jonina T., and Flores, Efren J.
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- 2020
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39. Kinetic Analysis of Lesions Identified on a Rapid Abridged Multiphase (RAMP) Breast MRI Protocol
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Choudhery, Sadia, Chou, Shinn-Huey S., Chang, Ken, Kalpathy-Cramer, Jayashree, and Lehman, Constance D.
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- 2020
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40. Impact of Background Parenchymal Enhancement on Diagnostic Performance in Screening Breast MRI
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Sippo, Dorothy A., Rutledge, Geoffrey M., Mercaldo, Sarah F., Burk, Kristine S., Edmonds, Christine E., Dang, Pragya A., and Lehman, Constance D.
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- 2020
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41. The Impact of Preoperative Breast MRI on Surgical Management of Women with Newly Diagnosed Ductal Carcinoma In Situ
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Lam, Diana L., Smith, Jacob, Partridge, Savannah C., Kim, Adrienne, Javid, Sara H., Hippe, Daniel S., Lehman, Constance D., Lee, Janie M., and Rahbar, Habib
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- 2020
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42. Potential of using mammography screening appointments to identify high-risk women: cross sectional survey results from the national health interview survey
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Narayan, Anand K., Mercaldo, Sarah F., Gupta, Yasha P., Warner, Erica T., Lehman, Constance D., and Miles, Randy C.
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- 2021
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43. Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival-Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL.
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Hylton, Nola M, Gatsonis, Constantine A, Rosen, Mark A, Lehman, Constance D, Newitt, David C, Partridge, Savannah C, Bernreuter, Wanda K, Pisano, Etta D, Morris, Elizabeth A, Weatherall, Paul T, Polin, Sandra M, Newstead, Gillian M, Marques, Helga S, Esserman, Laura J, Schnall, Mitchell D, and ACRIN 6657 Trial Team and I-SPY 1 TRIAL Investigators
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ACRIN 6657 Trial Team and I-SPY 1 TRIAL Investigators ,Humans ,Breast Neoplasms ,Antineoplastic Combined Chemotherapy Protocols ,Magnetic Resonance Imaging ,Disease-Free Survival ,Treatment Outcome ,Neoadjuvant Therapy ,Tumor Burden ,Follow-Up Studies ,Predictive Value of Tests ,Adult ,Aged ,Middle Aged ,United States ,Female ,Clinical Trials as Topic ,Biopsy ,Large-Core Needle ,Cancer ,Biomedical Imaging ,Breast Cancer ,Clinical Research ,Clinical Trials and Supportive Activities ,4.2 Evaluation of markers and technologies ,Detection ,screening and diagnosis ,Medical and Health Sciences ,Nuclear Medicine & Medical Imaging - Abstract
PurposeTo evaluate volumetric magnetic resonance (MR) imaging for predicting recurrence-free survival (RFS) after neoadjuvant chemotherapy (NACT) of breast cancer and to consider its predictive performance relative to pathologic complete response (PCR).Materials and methodsThis HIPAA-compliant prospective multicenter study was approved by institutional review boards with written informed consent. Women with breast tumors 3 cm or larger scheduled for NACT underwent dynamic contrast-enhanced MR imaging before treatment (examination 1), after one cycle (examination 2), midtherapy (examination 3), and before surgery (examination 4). Functional tumor volume (FTV), computed from MR images by using enhancement thresholds, and change from baseline (ΔFTV) were measured after one cycle and before surgery. Association of RFS with FTV was assessed by Cox regression and compared with association of RFS with PCR and residual cancer burden (RCB), while controlling for age, race, and hormone receptor (HR)/ human epidermal growth factor receptor type 2 (HER2) status. Predictive performance of models was evaluated by C statistics.ResultsFemale patients (n = 162) with FTV and RFS were included. At univariate analysis, FTV2, FTV4, and ΔFTV4 had significant association with RFS, as did HR/HER2 status and RCB class. PCR approached significance at univariate analysis and was not significant at multivariate analysis. At univariate analysis, FTV2 and RCB class had the strongest predictive performance (C statistic = 0.67; 95% confidence interval [CI]: 0.58, 0.76), greater than for FTV4 (0.64; 95% CI: 0.53, 0.74) and PCR (0.57; 95% CI: 0.39, 0.74). At multivariate analysis, a model with FTV2, ΔFTV2, RCB class, HR/HER2 status, age, and race had the highest C statistic (0.72; 95% CI: 0.60, 0.84).ConclusionBreast tumor FTV measured by MR imaging is a strong predictor of RFS, even in the presence of PCR and RCB class. Models combining MR imaging, histopathology, and breast cancer subtype demonstrated the strongest predictive performance in this study.
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- 2016
44. Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations
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Lee, Christoph I, Bogart, Andy, Germino, Jessica C, Goldman, L Elizabeth, Hubbard, Rebecca A, Haas, Jennifer S, Hill, Deirdre A, Tosteson, Anna NA, Alford-Teaster, Jennifer A, DeMartini, Wendy B, Lehman, Constance D, and Onega, Tracy L
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Health Services and Systems ,Health Sciences ,Cancer ,Health Services ,Prevention ,Women's Health ,Clinical Research ,Health Disparities ,Biomedical Imaging ,Breast Cancer ,4.4 Population screening ,Breast Neoplasms ,Early Detection of Cancer ,Educational Status ,Ethnicity ,Female ,Health Expenditures ,Health Facilities ,Health Services Accessibility ,Humans ,Image-Guided Biopsy ,Logistic Models ,Magnetic Resonance Imaging ,Mammography ,Minority Groups ,Multivariate Analysis ,Registries ,Rural Population ,Socioeconomic Factors ,Ultrasonography ,Mammary ,United States ,Vulnerable Populations ,breast cancer ,screening mammography ,disparities ,access ,advanced breast imaging ,Public Health and Health Services ,Public Health ,Public health - Abstract
ObjectiveAmong vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavourable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound, magnetic resonance imaging [MRI], and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations.Setting73 imaging facilities across five Breast Cancer Surveillance Consortium regional registries in the United States during 2011 and 2012.MethodsWe examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence.We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women.ResultsFacilities serving vulnerable populations were as likely (Relative risk [RR] for MRI = 0.71, 95% Confidence Interval [CI] 0.42, 1.19; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for ultrasound = 1.38 [95% CI 1.09, 1.74]; RR for ultrasound-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations.ConclusionsAdvanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use.
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- 2016
45. Concordance of BI-RADS Assessments and Management Recommendations for Breast MRI in Community Practice.
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Lee, Amie Y, Ichikawa, Laura, Lee, Janie M, Lee, Christoph I, DeMartini, Wendy B, Joe, Bonnie N, Wernli, Karen J, Sprague, Brian L, Herschorn, Sally D, and Lehman, Constance D
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Cancer ,Clinical Research ,Biomedical Imaging ,Prevention ,Women's Health ,Breast Cancer ,Adolescent ,Adult ,Aged ,Breast Neoplasms ,Female ,Humans ,Magnetic Resonance Imaging ,Mammography ,Middle Aged ,Population Surveillance ,Registries ,United States ,BI-RADS ,breast cancer ,Breast Cancer Surveillance Consortium ,breast MRI ,concordance ,Clinical Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
ObjectiveThe purpose of this study was to evaluate concordance between BI-RADS assessments and management recommendations for breast MRI in community practice.Materials and methodsBreast MRI data were collected from four regional Breast Cancer Surveillance Consortium registries from 2005 to 2011 for women who were 18-79 years old. Assessments and recommendations were compared to determine concordance according to BI-RADS guidelines. Concordance was compared by assessment category as well as by year of examination and clinical indication.ResultsIn all, 8283 MRI examinations were included in the analysis. Concordance was highest (93% [2475/2657]) in examinations with a BI-RADS category 2 (benign) assessment. Concordance was also high in examinations with category 1 (negative) (87% [1669/1909]), category 0 (incomplete) (83% [348/417]), category 5 (highly suggestive of malignancy) (83% [208/252]), and category 4 (suspicious) (74% [734/993]) assessments. Examinations with categories 3 (probably benign) and 6 (known biopsy-proven malignancy) assessments had the lowest concordance rates (36% [302/837] and 56% [676/1218], respectively). The most frequent discordant recommendation for a category 3 assessment was routine follow-up. The most frequent discordant recommendation for a category 6 assessment was biopsy. Concordance of assessments and management recommendations differed across clinical indications (p < 0.0001), with the lowest concordance in examinations to assess disease extent.ConclusionBreast MRI BI-RADS management recommendations were most concordant for assessments of negative, incomplete, suspicious, and highly suggestive of malignancy. Lower concordance for assessments of probably benign and known biopsy-proven malignancy and for examinations performed to assess disease extent highlight areas for interventions to improve breast MRI reporting.
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- 2016
46. Do Eligibility Criteria for Ductal Carcinoma In Situ (DCIS) Active Surveillance Trials Identify Patients at Low Risk for Upgrade to Invasive Carcinoma?
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Oseni, Tawakalitu O., Smith, Barbara L., Lehman, Constance D., Vijapura, Charmi A., Pinnamaneni, Niveditha, and Bahl, Manisha
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- 2020
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47. Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection
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Lehman, Constance D, Wellman, Robert D, Buist, Diana SM, Kerlikowske, Karla, Tosteson, Anna NA, and Miglioretti, Diana L
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Health Services and Systems ,Biomedical and Clinical Sciences ,Health Sciences ,Cancer ,Breast Cancer ,Biomedical Imaging ,Women's Health ,Prevention ,Clinical Research ,4.2 Evaluation of markers and technologies ,Adult ,Aged ,Aged ,80 and over ,Breast Neoplasms ,Early Detection of Cancer ,Female ,Humans ,Logistic Models ,Mammography ,Mass Screening ,Middle Aged ,Radiographic Image Interpretation ,Computer-Assisted ,Registries ,Reproducibility of Results ,Sensitivity and Specificity ,United States ,Breast Cancer Surveillance Consortium ,Clinical Sciences ,Opthalmology and Optometry ,Public Health and Health Services ,Clinical sciences ,Health services and systems - Abstract
ImportanceAfter the US Food and Drug Administration (FDA) approved computer-aided detection (CAD) for mammography in 1998, and the Centers for Medicare and Medicaid Services (CMS) provided increased payment in 2002, CAD technology disseminated rapidly. Despite sparse evidence that CAD improves accuracy of mammographic interpretations and costs over $400 million a year, CAD is currently used for most screening mammograms in the United States.ObjectiveTo measure performance of digital screening mammography with and without CAD in US community practice.Design, setting, and participantsWe compared the accuracy of digital screening mammography interpreted with (n = 495 818) vs without (n = 129 807) CAD from 2003 through 2009 in 323 973 women. Mammograms were interpreted by 271 radiologists from 66 facilities in the Breast Cancer Surveillance Consortium. Linkage with tumor registries identified 3159 breast cancers in 323 973 women within 1 year of the screening.Main outcomes and measuresMammography performance (sensitivity, specificity, and screen-detected and interval cancers per 1000 women) was modeled using logistic regression with radiologist-specific random effects to account for correlation among examinations interpreted by the same radiologist, adjusting for patient age, race/ethnicity, time since prior mammogram, examination year, and registry. Conditional logistic regression was used to compare performance among 107 radiologists who interpreted mammograms both with and without CAD.ResultsScreening performance was not improved with CAD on any metric assessed. Mammography sensitivity was 85.3% (95% CI, 83.6%-86.9%) with and 87.3% (95% CI, 84.5%-89.7%) without CAD. Specificity was 91.6% (95% CI, 91.0%-92.2%) with and 91.4% (95% CI, 90.6%-92.0%) without CAD. There was no difference in cancer detection rate (4.1 in 1000 women screened with and without CAD). Computer-aided detection did not improve intraradiologist performance. Sensitivity was significantly decreased for mammograms interpreted with vs without CAD in the subset of radiologists who interpreted both with and without CAD (odds ratio, 0.53; 95% CI, 0.29-0.97).Conclusions and relevanceComputer-aided detection does not improve diagnostic accuracy of mammography. These results suggest that insurers pay more for CAD with no established benefit to women.
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- 2015
48. Breast Cancer Characteristics Associated With Digital Versus Film-Screen Mammography for Screen-Detected and Interval Cancers.
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Henderson, Louise M, Miglioretti, Diana L, Kerlikowske, Karla, Wernli, Karen J, Sprague, Brian L, and Lehman, Constance D
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Clinical Research ,Breast Cancer ,Cancer ,Prevention ,Women's Health ,Biomedical Imaging ,Adult ,Aged ,Aged ,80 and over ,Biopsy ,Breast Neoplasms ,Female ,Humans ,Incidence ,Lymphatic Metastasis ,Mammography ,Middle Aged ,Population Surveillance ,Registries ,United States ,digital mammography ,film mammography ,interval cancer ,screen-detected cancer ,Clinical Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
ObjectiveThe purpose of this study was to determine whether pathologic findings of screen-detected and interval cancers differ for digital versus film mammography.Materials and methodsBreast Cancer Surveillance Consortium data from 2003-2011 on 3,021,515 screening mammograms (40.3% digital, 59.7% film) of women 40-89 years old were reviewed. Cancers were considered screen detected if diagnosed within 12 months of an examination with positive findings and interval if diagnosed within 12 months of an examination with negative findings. Tumor characteristics for screen-detected and interval cancers were compared for digital versus film mammography by use of logistic regression models to estimate the odds ratio and 95% CI with adjustment for age, race and ethnicity, hormone therapy use, screening interval, examination year, and registry. Generalized estimating equations were used to account for correlation within facilities.ResultsAmong 15,729 breast cancers, 85.3% were screen detected and 14.7% were interval. Digital and film mammography had similar rates of screen-detected (4.47 vs 4.42 per 1000 examinations) and interval (0.73 vs 0.79 per 1000 examinations) cancers for digital versus film. In adjusted analyses, interval cancers diagnosed after digital examinations with negative findings were less likely to be American Joint Committee on Cancer stage IIB or higher (odds ratio, 0.69; 95% CI, 0.52-0.93), have positive nodal status (odds ratio, 0.78; 95% CI, 0.64-0.95), or be estrogen receptor negative (odds ratio, 0.71; 95% CI, 0.56-0.91) than were interval cancers diagnosed after a film examination with negative findings.ConclusionScreen-detected cancers diagnosed after digital and film mammography had similar rates of unfavorable tumor characteristics. Interval-detected cancers diagnosed after a digital examination were less likely to have unfavorable tumor features than those diagnosed after film mammography, but the absolute differences were small.
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- 2015
49. Identifying women with dense breasts at high risk for interval cancer: a cohort study.
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Kerlikowske, Karla, Zhu, Weiwei, Tosteson, Anna NA, Sprague, Brian L, Tice, Jeffrey A, Lehman, Constance D, and Miglioretti, Diana L
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Clinical Research ,Women's Health ,Biomedical Imaging ,Health Services ,Breast Cancer ,Prevention ,Cancer ,Good Health and Well Being ,Adult ,Aged ,Breast ,Breast Neoplasms ,Early Detection of Cancer ,False Positive Reactions ,Female ,Humans ,Mammography ,Mass Screening ,Middle Aged ,Prospective Studies ,Risk Assessment ,Sensitivity and Specificity ,Breast Cancer Surveillance Consortium ,Clinical Sciences ,Public Health and Health Services - Abstract
BackgroundTwenty-one states have laws requiring that women be notified if they have dense breasts and that they be advised to discuss supplemental imaging with their provider.ObjectiveTo better direct discussions of supplemental imaging by determining which combinations of breast cancer risk and Breast Imaging Reporting and Data System (BI-RADS) breast density categories are associated with high interval cancer rates.DesignProspective cohort.SettingBreast Cancer Surveillance Consortium (BCSC) breast imaging facilities.Patients365,426 women aged 40 to 74 years who had 831,455 digital screening mammography examinations.MeasurementsBI-RADS breast density, BCSC 5-year breast cancer risk, and interval cancer rate (invasive cancer ≤12 months after a normal mammography result) per 1000 mammography examinations. High interval cancer rate was defined as more than 1 case per 1000 examinations.ResultsHigh interval cancer rates were observed for women with 5-year risk of 1.67% or greater and extremely dense breasts or 5-year risk of 2.50% or greater and heterogeneously dense breasts (24% of all women with dense breasts). The interval rate of advanced-stage disease was highest (>0.4 case per 1000 examinations) among women with 5-year risk of 2.50% or greater and heterogeneously or extremely dense breasts (21% of all women with dense breasts). Five-year risk was low to average (0% to 1.66%) for 51.0% of women with heterogeneously dense breasts and 52.5% with extremely dense breasts, with interval cancer rates of 0.58 to 0.63 and 0.72 to 0.89 case per 1000 examinations, respectively.LimitationThe benefit of supplemental imaging was not assessed.ConclusionBreast density should not be the sole criterion for deciding whether supplemental imaging is justified because not all women with dense breasts have high interval cancer rates. BCSC 5-year risk combined with BI-RADS breast density can identify women at high risk for interval cancer to inform patient-provider discussions about alternative screening strategies.Primary funding sourceNational Cancer Institute.
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- 2015
50. Accuracy of 3T versus 1.5T breast MRI for pre-operative assessment of extent of disease in newly diagnosed DCIS
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Rahbar, Habib, DeMartini, Wendy B, Lee, Amie Y, Partridge, Savannah C, Peacock, Sue, and Lehman, Constance D
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Patient Safety ,Breast Cancer ,Cancer ,Clinical Research ,Biomedical Imaging ,Detection ,screening and diagnosis ,4.2 Evaluation of markers and technologies ,Adult ,Aged ,Breast Neoplasms ,Carcinoma ,Intraductal ,Noninfiltrating ,Diagnosis ,Differential ,Female ,Humans ,Image Enhancement ,Magnetic Resonance Imaging ,Middle Aged ,Neoplasm Invasiveness ,Preoperative Care ,Prospective Studies ,Reproducibility of Results ,3T ,Breast MRI ,Ductal carcinoma in situ ,Pre-operative ,Clinical Sciences ,Nuclear Medicine & Medical Imaging - Abstract
ObjectivesWhile 3T breast magnetic resonance imaging has increased in use over the past decade, there is little data comparing its use for assessing ductal carcinoma in situ (DCIS) versus 1.5 T. We sought to compare the accuracies of DCIS extent of disease measures on pre-operative 3T versus 1.5 T MRI.MethodsThis institutional review board-approved prospective study included 20 patients with ductal carcinoma in situ diagnosed by core needle biopsy (CNB) who underwent pre-operative breast MRI at both 3T (resolution=0.5 mm×0.5 mm×1.3 mm) and 1.5 T (0.85 mm×0.85 mm×1.6 mm). All patients provided informed consent, and the study was HIPPA compliant. Lesion sizes and imaging characteristics (morphologic and kinetic enhancement) were recorded for the 3 T and 1.5 T examinations. Lesion size measures at both field strengths were correlated to final pathology, and imaging characteristics also were compared.ResultsOf the initial cohort of 20 patients with CNB-diagnosed DCIS, 19 underwent definitive surgery. Median DCIS sizes of these 19 patients were 6mm (range: 0-67 mm) on 3T, 13 mm (0-60 mm) on 1.5 T, and 6mm (0-55 mm) on surgical pathology. Size correlation between MRI and pathology was higher for 3T (Spearman's ρ=0.66, p=0.002) than 1.5 T (ρ=0.36, p=0.13). In 10 women in which a residual area of suspicious enhancement was identified on both field strengths, there was agreement of morphologic description (NME vs. mass) in nine, and no significant difference in dynamic contrast enhanced kinetics at 3T compared to 1.5 T.ConclusionsPre-operative breast MRI at 3T provided higher correlation with final pathology size of DCIS lesions compared to 1.5 T, and may be more accurate for assessment of disease extent prior to definitive surgery.
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- 2015
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