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Kim E, Lewin AA. Breast Density: Where Are We Now? Radiol Clin North Am 2024; 62:593-605. [PMID: 38777536 DOI: 10.1016/j.rcl.2023.12.007] [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 density refers to the amount of fibroglandular tissue relative to fat on mammography and is determined either qualitatively through visual assessment or quantitatively. It is a heritable and dynamic trait associated with age, race/ethnicity, body mass index, and hormonal factors. Increased breast density has important clinical implications including the potential to mask malignancy and as an independent risk factor for the development of breast cancer. Breast density has been incorporated into breast cancer risk models. Given the impact of dense breasts on the interpretation of mammography, supplemental screening may be indicated.
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Affiliation(s)
- Eric Kim
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Alana A Lewin
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; New York University Grossman School of Medicine, New York University Langone Health, Laura and Isaac Perlmutter Cancer Center, 160 East 34th Street 3rd Floor, New York, NY 10016, USA.
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2
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Hruska CB, Gray LR, Jenkins SM, Block EA, Hunt KN, Conners AL, Zingula SN, O'Connor MK, Rhodes DJ. A Survey of Patient Experience During Molecular Breast Imaging. J Nucl Med Technol 2024; 52:107-114. [PMID: 38839120 DOI: 10.2967/jnmt.123.266856] [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] [Received: 10/16/2023] [Revised: 11/09/2023] [Indexed: 06/07/2024] Open
Abstract
Molecular breast imaging (MBI) is one of several options available to patients seeking supplemental screening due to mammographically dense breasts. Patient experience during MBI may influence willingness to undergo the test but has yet to be formally assessed. We aimed to assess patient comfort level during MBI, to compare MBI comfort with mammography comfort, to identify factors associated with MBI discomfort, and to evaluate patients' willingness to return for future MBI. Methods: A 10-question survey was sent by e-mail to patients undergoing MBI between August and December 2022 to obtain quantitative assessments and qualitative opinions about MBI. Results: Of 561 invited patients, 209 (37%) completed the survey and provided study consent. Their average age was 60.1 y (range, 40-81 y). Of the 209 responders, 202 (97%) were presenting for screening MBI, 195 (94%) had dense breasts, and 46 (22%) had a personal history of breast cancer. The average rating of MBI comfort was 2.9 (SD, 1.5; median, 3.0) on a 7-point scale (1 indicating extremely comfortable and 7 indicating extremely uncomfortable). The rating distribution was as follows: 140 (67%) comfortable (rating, 1-3); 24 (12%) neither comfortable nor uncomfortable (rating, 4); and 45 (22%) uncomfortable (rating, 5 or 6). No responders gave a 7 rating. The most frequently mentioned sources of discomfort included breast compression (n = 16), back or neck discomfort (n = 14), and maintaining position during the examination (n = 14). MBI comfort was associated with responder age (74% ≥55 y old were comfortable, versus 53% <55 y old [P = 0.003]) and history of MBI (71% with prior MBI were comfortable, versus 61% having a first MBI [P = 0.006]). Of 208 responders with a prior mammogram, 148 (71%) said MBI is more comfortable than mammography (a significant majority [P < 0.001]). Of 202 responders to the question of whether they were willing to return for a future MBI, 196 (97%) were willing. A notable factor in positive patient experience was interaction with the MBI nuclear medicine technologist. Conclusion: Most responders thought MBI to be a comfortable examination and more comfortable than mammography. Patient experience during MBI may be improved by ensuring back support and soliciting patient feedback at the time of positioning and throughout the examination. Methods under study to reduce imaging time may be most important for improving patient experience.
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Affiliation(s)
| | - Lacey R Gray
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Sarah M Jenkins
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Emily A Block
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Katie N Hunt
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | - Deborah J Rhodes
- Department of Internal Medicine, Yale New Haven Hospital, New Haven, Connecticut; and
- Department of Medicine, Mayo Clinic, Rochester, Minnesota
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Yamashita MW, Larsen LH, Perez J, Edwards AV, Papaioannou J, Jiang Y. Comparison of Mammography and Mammography with Supplemental Whole-Breast US Tomography for Cancer Detection in Patients with Dense Breasts. Radiology 2024; 311:e231680. [PMID: 38888480 DOI: 10.1148/radiol.231680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
BACKGROUND Women with dense breasts benefit from supplemental cancer screening with US, but US has low specificity. PURPOSE To evaluate the performance of breast US tomography (UST) combined with full-field digital mammography (FFDM) compared with FFDM alone for breast cancer screening in women with dense breasts. MATERIALS AND METHODS This retrospective multireader multicase study included women with dense breasts who underwent FFDM and UST at 10 centers between August 2017 and October 2019 as part of a prospective case collection registry. All patients in the registry with cancer were included; patients with benign biopsy or negative follow-up imaging findings were randomly selected for inclusion. Thirty-two Mammography Quality Standards Act-qualified radiologists independently evaluated FFDM followed immediately by FFDM plus UST for suspicious findings and assigned a Breast Imaging Reporting and Data System (BI-RADS) category. The superiority of FFDM plus UST versus FFDM alone for cancer detection (assessed with area under the receiver operating characteristic curve [AUC]), BI-RADS 4 sensitivity, and BI-RADS 3 sensitivity and specificity were evaluated using the two-sided significance level of α = .05. Noninferiority of BI-RADS 4 specificity was evaluated at the one-sided significance level of α = .025 with a -10% margin. RESULTS Among 140 women (mean age, 56 years ±10 [SD]; 36 with cancer, 104 without), FFDM plus UST achieved superior performance compared with FFDM alone (AUC, 0.60 [95% CI: 0.51, 0.69] vs 0.54 [95% CI: 0.45, 0.64]; P = .03). For FFDM plus UST versus FFDM alone, BI-RADS 4 mean sensitivity was superior (37% [428 of 1152] vs 30% [343 of 1152]; P = .03) and BI-RADS 4 mean specificity was noninferior (82% [2741 of 3328] vs 88% [2916 of 3328]; P = .004). For FFDM plus UST versus FFDM, no difference in BI-RADS 3 mean sensitivity was observed (40% [461 of 1152] vs 33% [385 of 1152]; P = .08), but BI-RADS 3 mean specificity was superior (75% [2491 of 3328] vs 69% [2299 of 3328]; P = .04). CONCLUSION In women with dense breasts, FFDM plus UST improved cancer detection by radiologists versus FFDM alone. Clinical trial registration nos. NCT03257839 and NCT04260620 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Mann in this issue.
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Affiliation(s)
- Mary W Yamashita
- From the Department of Radiology, University of Southern California, Keck School of Medicine, Keck Hospital, 1500 San Pablo St, 2nd Floor, Suite 2250, Los Angeles, CA 90033 (M.W.Y., L.H.L.); Department of Biostatistics, Avania U.S., Marlborough, Mass (J. Perez); and Department of Radiology, The University of Chicago, Chicago, Ill (A.V.E., J. Papaioannou, Y.J.)
| | - Linda H Larsen
- From the Department of Radiology, University of Southern California, Keck School of Medicine, Keck Hospital, 1500 San Pablo St, 2nd Floor, Suite 2250, Los Angeles, CA 90033 (M.W.Y., L.H.L.); Department of Biostatistics, Avania U.S., Marlborough, Mass (J. Perez); and Department of Radiology, The University of Chicago, Chicago, Ill (A.V.E., J. Papaioannou, Y.J.)
| | - Jeremiah Perez
- From the Department of Radiology, University of Southern California, Keck School of Medicine, Keck Hospital, 1500 San Pablo St, 2nd Floor, Suite 2250, Los Angeles, CA 90033 (M.W.Y., L.H.L.); Department of Biostatistics, Avania U.S., Marlborough, Mass (J. Perez); and Department of Radiology, The University of Chicago, Chicago, Ill (A.V.E., J. Papaioannou, Y.J.)
| | - Alexandra V Edwards
- From the Department of Radiology, University of Southern California, Keck School of Medicine, Keck Hospital, 1500 San Pablo St, 2nd Floor, Suite 2250, Los Angeles, CA 90033 (M.W.Y., L.H.L.); Department of Biostatistics, Avania U.S., Marlborough, Mass (J. Perez); and Department of Radiology, The University of Chicago, Chicago, Ill (A.V.E., J. Papaioannou, Y.J.)
| | - John Papaioannou
- From the Department of Radiology, University of Southern California, Keck School of Medicine, Keck Hospital, 1500 San Pablo St, 2nd Floor, Suite 2250, Los Angeles, CA 90033 (M.W.Y., L.H.L.); Department of Biostatistics, Avania U.S., Marlborough, Mass (J. Perez); and Department of Radiology, The University of Chicago, Chicago, Ill (A.V.E., J. Papaioannou, Y.J.)
| | - Yulei Jiang
- From the Department of Radiology, University of Southern California, Keck School of Medicine, Keck Hospital, 1500 San Pablo St, 2nd Floor, Suite 2250, Los Angeles, CA 90033 (M.W.Y., L.H.L.); Department of Biostatistics, Avania U.S., Marlborough, Mass (J. Perez); and Department of Radiology, The University of Chicago, Chicago, Ill (A.V.E., J. Papaioannou, Y.J.)
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Grubstein A, Friehmann T, Dahan M, Abitbol C, Gadiel I, Schejtman DM, Shochat T, Atar E, Tamir S. Digital Breast Tomosynthesis for Upgraded BIRADS Scoring towards the True Pathology of Lesions Detected by Contrast-Enhanced Mammography. Tomography 2024; 10:806-815. [PMID: 38787021 PMCID: PMC11125662 DOI: 10.3390/tomography10050061] [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] [Received: 04/23/2024] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 05/25/2024] Open
Abstract
OBJECTIVE To determine the added value of digital breast tomosynthesis (DBT) in the assessment of lesions detected by contrast-enhanced mammography (CEM). MATERIAL AND METHODS A retrospective study was conducted in a tertiary university medical center. All CEM studies including DBT performed between January 2016 and December 2020 were included. Lesions were categorized and scored by four dedicated breast radiologists according to the recent CEM and DBT supplements to the Breast Imaging Reporting and Data System (BIRADS) lexicon. Changes in the BIRADS score of CEM-detected lesions with the addition of DBT were evaluated according to the pathology results and 1-year follow-up imaging study. RESULTS BIRADS scores of CEM-detected lesions were upgraded toward the lesion's pathology with the addition of DBT (p > 0.0001), overall and for each reader. The difference in BIRADS scores before and after the addition of DBT was more significant for readers who were less experienced. The reason for changes in the BIRADS score was better lesion margin visibility. The main BIRADS descriptors applied in the malignant lesions were spiculations, calcifications, architectural distortion, and sharp or obscured margins. CONCLUSIONS The addition of DBT to CEM provides valuable information on the enhancing lesion, leading to a more accurate BIRADS score.
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Affiliation(s)
- Ahuva Grubstein
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Tal Friehmann
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Marva Dahan
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Chen Abitbol
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Ithai Gadiel
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Dario M. Schejtman
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Tzippy Shochat
- Biostatistics, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel;
| | - Eli Atar
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
| | - Shlomit Tamir
- Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel; (T.F.); (M.D.); (C.A.); (I.G.); (D.M.S.); (E.A.); (S.T.)
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5
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Conley CC, Cheraghi N, Anderson A, Rodriguez JD, Ginocchi A, Song JH, Crane E, Mishori R, O'Neill SC. Patterns and Predictors of Referral for Screening Breast MRI: A Mixed-Methods Study. J Womens Health (Larchmt) 2024; 33:639-649. [PMID: 38484303 DOI: 10.1089/jwh.2023.0557] [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] [Indexed: 05/29/2024] Open
Abstract
Introduction: Women with ≥20% lifetime breast cancer risk can receive supplemental breast cancer screening with MRI. We examined factors associated with recommendation for screening breast MRI among primary care providers (PCPs), gynecologists (GYNs), and radiologists. Methods: We conducted a sequential mixed-methods study. Quantitative: Participants (N = 72) reported recommendations for mammogram and breast MRI via clinical vignettes describing hypothetical patients with moderate, high, and very high breast cancer risk. Logistic regressions assessed the relationships of clinician-level factors (gender, specialty, years practicing) and practice-level factors (practice type, imaging facilities available) with screening recommendations. Qualitative: We interviewed a subset of survey participants (n = 17, 17/72 = 24%) regarding their decision-making about breast cancer screening recommendations. Interviews were audio-recorded, transcribed, and analyzed with directed content analysis. Results: Compared with PCPs, GYNs and radiologists were significantly more likely to recommend breast MRI for high-risk (ORs = 4.09 and 4.09, respectively) and very-high-risk patients (ORs = 8.56 and 18.33, respectively). Qualitative analysis identified two key phases along the clinical pathway for high-risk women. Phase 1 was "identifying high-risk women," which included three subthemes (systems for risk assessment, barriers to risk assessment, scope of practice issues). Phase 2 was "referral for screening," which included three subthemes (conflicting guidelines, scope of practice issues, legal implications). Frequency of themes differed between specialties, potentially explaining findings from the quantitative phase. Conclusions: There are significant differences between specialties in supplemental breast cancer screening recommendations. Multilevel interventions are needed to support identification and management of women with high breast cancer risk, particularly for PCPs.
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Affiliation(s)
- Claire C Conley
- Department of, Oncology, Georgetown University, Washington, District of Columbia, USA
| | - Nora Cheraghi
- Department of, Oncology, Georgetown University, Washington, District of Columbia, USA
| | - Alaina Anderson
- Department of, Oncology, Georgetown University, Washington, District of Columbia, USA
| | - Jennifer D Rodriguez
- Department of, Oncology, Georgetown University, Washington, District of Columbia, USA
| | - Annalisa Ginocchi
- Department of, Oncology, Georgetown University, Washington, District of Columbia, USA
| | - Judy H Song
- Radiology, Georgetown University, Washington, District of Columbia, USA
| | - Erin Crane
- Radiology, Georgetown University, Washington, District of Columbia, USA
| | - Ranit Mishori
- Family Medicine, Georgetown University, Washington, District of Columbia, USA
| | - Suzanne C O'Neill
- Department of, Oncology, Georgetown University, Washington, District of Columbia, USA
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6
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Upadhyay N, Wolska J. Imaging the dense breast. J Surg Oncol 2024. [PMID: 38685673 DOI: 10.1002/jso.27661] [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: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 05/02/2024]
Abstract
The sensitivity of mammography reduces as breast density increases, which impacts breast screening and locoregional staging in breast cancer. Supplementary imaging with other modalities can offer improved cancer detection, but this often comes at the cost of more false positives. Magnetic resonance imaging and contrast-enhanced mammography, which assess tumour enhancement following contrast administration, are more sensitive than digital breast tomosynthesis and ultrasound, which predominantly rely on the assessment of tumour morphology.
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Affiliation(s)
- Neil Upadhyay
- Faculty of Medicine, Imperial College London, London, UK
- Imaging Department, Imperial College Healthcare NHS Trust, London, UK
| | - Joanna Wolska
- Imaging Department, Imperial College Healthcare NHS Trust, London, UK
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7
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Littrup PJ, Mehrmohammadi M, Duric N. Breast Tomographic Ultrasound: The Spectrum from Current Dense Breast Cancer Screenings to Future Theranostic Treatments. Tomography 2024; 10:554-573. [PMID: 38668401 PMCID: PMC11053617 DOI: 10.3390/tomography10040044] [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] [Received: 02/24/2024] [Revised: 04/03/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
This review provides unique insights to the scientific scope and clinical visions of the inventors and pioneers of the SoftVue breast tomographic ultrasound (BTUS). Their >20-year collaboration produced extensive basic research and technology developments, culminating in SoftVue, which recently received the Food and Drug Administration's approval as an adjunct to breast cancer screening in women with dense breasts. SoftVue's multi-center trial confirmed the diagnostic goals of the tissue characterization and localization of quantitative acoustic tissue differences in 2D and 3D coronal image sequences. SoftVue mass characterizations are also reviewed within the standard cancer risk categories of the Breast Imaging Reporting and Data System. As a quantitative diagnostic modality, SoftVue can also function as a cost-effective platform for artificial intelligence-assisted breast cancer identification. Finally, SoftVue's quantitative acoustic maps facilitate noninvasive temperature monitoring and a unique form of time-reversed, focused US in a single theranostic device that actually focuses acoustic energy better within the highly scattering breast tissues, allowing for localized hyperthermia, drug delivery, and/or ablation. Women also prefer the comfort of SoftVue over mammograms and will continue to seek out less-invasive breast care, from diagnosis to treatment.
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Affiliation(s)
- Peter J. Littrup
- Department of Imaging Sciences, University of Rochester, Rochester, NY 14642, USA; (M.M.); (N.D.)
- Delphinus Medical Technologies, Inc., Novi, MI 48374, USA
| | - Mohammad Mehrmohammadi
- Department of Imaging Sciences, University of Rochester, Rochester, NY 14642, USA; (M.M.); (N.D.)
| | - Nebojsa Duric
- Department of Imaging Sciences, University of Rochester, Rochester, NY 14642, USA; (M.M.); (N.D.)
- Delphinus Medical Technologies, Inc., Novi, MI 48374, USA
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8
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Freitas V, Li X, Scaranelo A, Au F, Kulkarni S, Ghai S, Taeb S, Bubon O, Baldassi B, Komarov B, Parker S, Macsemchuk CA, Waterston M, Olsen KO, Reznik A. Breast Cancer Detection Using a Low-Dose Positron Emission Digital Mammography System. Radiol Imaging Cancer 2024; 6:e230020. [PMID: 38334470 PMCID: PMC10988332 DOI: 10.1148/rycan.230020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 02/10/2024]
Abstract
Purpose To investigate the feasibility of low-dose positron emission mammography (PEM) concurrently to MRI to identify breast cancer and determine its local extent. Materials and Methods In this research ethics board-approved prospective study, participants newly diagnosed with breast cancer with concurrent breast MRI acquisitions were assigned independently of breast density, tumor size, and histopathologic cancer subtype to undergo low-dose PEM with up to 185 MBq of fluorine 18-labeled fluorodeoxyglucose (18F-FDG). Two breast radiologists, unaware of the cancer location, reviewed PEM images taken 1 and 4 hours following 18F-FDG injection. Findings were correlated with histopathologic results. Detection accuracy and participant details were examined using logistic regression and summary statistics, and a comparative analysis assessed the efficacy of PEM and MRI additional lesions detection (ClinicalTrials.gov: NCT03520218). Results Twenty-five female participants (median age, 52 years; range, 32-85 years) comprised the cohort. Twenty-four of 25 (96%) cancers (19 invasive cancers and five in situ diseases) were identified with PEM from 100 sets of bilateral images, showcasing comparable performance even after 3 hours of radiotracer uptake. The median invasive cancer size was 31 mm (range, 10-120). Three additional in situ grade 2 lesions were missed at PEM. While not significant, PEM detected fewer false-positive additional lesions compared with MRI (one of six [16%] vs eight of 13 [62%]; P = .14). Conclusion This study suggests the feasibility of a low-dose PEM system in helping to detect invasive breast cancer. Though large-scale clinical trials are essential to confirm these preliminary results, this study underscores the potential of this low-dose PEM system as a promising imaging tool in breast cancer diagnosis. ClinicalTrials.gov registration no. NCT03520218 Keywords: Positron Emission Digital Mammography, Invasive Breast Cancer, Oncology, MRI Supplemental material is available for this article. © RSNA, 2024 See also commentary by Barreto and Rapelyea in this issue.
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Affiliation(s)
- Vivianne Freitas
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Xuan Li
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Anabel Scaranelo
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Frederick Au
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Supriya Kulkarni
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Sandeep Ghai
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Samira Taeb
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Oleksandr Bubon
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Brandon Baldassi
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Borys Komarov
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Shayna Parker
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Craig A. Macsemchuk
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Michael Waterston
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Kenneth O. Olsen
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
| | - Alla Reznik
- From the Temerty Faculty of Medicine, Joint Department of Medical
Imaging, University Health Network, Sinai Health System, Women's College
Hospital, University of Toronto, 610 University Ave, Toronto, ON, Canada M5G 2M9
(V.F., A.S., F.A., S.K., S.G.); Department of Biostatistics, Princess Margaret
Cancer Centre, University Health Network, Toronto, Canada (X.L.); Thunder Bay
Regional Health Research Institute, Thunder Bay, Canada (S.T., O.B., A.R.);
Lakehead University, Thunder Bay, Canada (O.B., B.B., A.R.); Radialis Inc,
Thunder Bay, Canada (O.B., B.B., B.K., S.P., C.A.M., M.W., K.O.O.); Institute of
Biomedical Engineering, University of Toronto, Toronto, Canada (C.A.M.); and
Posluns Centre for Image-Guided Innovation and Therapeutic Intervention, The
Hospital for Sick Children, Toronto, Canada (C.A.M.)
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9
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Kerlikowske K, Zhu W, Su YR, Sprague BL, Stout NK, Onega T, O’Meara ES, Henderson LM, Tosteson ANA, Wernli K, Miglioretti DL. Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density. J Natl Cancer Inst 2024; 116:249-257. [PMID: 37897090 PMCID: PMC10852604 DOI: 10.1093/jnci/djad201] [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: 06/19/2023] [Revised: 09/13/2023] [Accepted: 09/18/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Examining screening outcomes by breast density for breast magnetic resonance imaging (MRI) with or without mammography could inform discussions about supplemental MRI in women with dense breasts. METHODS We evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography pairs propensity score-matched to 65 810 screening mammograms. Rates per 1000 examinations of interval, advanced, and screen-detected early stage invasive cancers and false-positive recall and biopsy recommendation were estimated by breast density (nondense = almost entirely fatty or scattered fibroglandular densities; dense = heterogeneously/extremely dense) adjusting for registry, examination year, age, race and ethnicity, family history of breast cancer, and prior breast biopsy. RESULTS Screen-detected early stage cancer rates were statistically higher for MRI plus mammography vs mammography for nondense (9.3 vs 2.9; difference = 6.4, 95% confidence interval [CI] = 2.5 to 10.3) and dense (7.5 vs 3.5; difference = 4.0, 95% CI = 1.4 to 6.7) breasts and for MRI vs MRI plus mammography for dense breasts (19.2 vs 7.5; difference = 11.7, 95% CI = 4.6 to 18.8). Interval rates were not statistically different for MRI plus mammography vs mammography for nondense (0.8 vs 0.5; difference = 0.4, 95% CI = -0.8 to 1.6) or dense breasts (1.5 vs 1.4; difference = 0.0, 95% CI = -1.2 to 1.3), nor were advanced cancer rates. Interval rates were not statistically different for MRI vs MRI plus mammography for nondense (2.6 vs 0.8; difference = 1.8 (95% CI = -2.0 to 5.5) or dense breasts (0.6 vs 1.5; difference = -0.9, 95% CI = -2.5 to 0.7), nor were advanced cancer rates. False-positive recall and biopsy recommendation rates were statistically higher for MRI groups than mammography alone. CONCLUSION MRI screening with or without mammography increased rates of screen-detected early stage cancer and false-positives for women with dense breasts without a concomitant decrease in advanced or interval cancers.
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Affiliation(s)
- Karla Kerlikowske
- Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
- General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA, USA
| | - Weiwei Zhu
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - Yu-Ru Su
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - Brian L Sprague
- Departments of Surgery and Radiology, University of Vermont, Burlington, VT, USA
| | - Natasha K Stout
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Tracy Onega
- Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, UT, USA
| | - Ellen S O’Meara
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - Louise M Henderson
- Department of Radiology, University of North Carolina, Chapel Hill, NC, USA
| | - Anna N A Tosteson
- The Dartmouth Institute for Health Policy and Clinical Practice and Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Karen Wernli
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - Diana L Miglioretti
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Department of Public Health Sciences, University of California, Davis, CA, USA
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10
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Berg WA, Seitzman RL, Pushkin J. Implementing the National Dense Breast Reporting Standard, Expanding Supplemental Screening Using Current Guidelines, and the Proposed Find It Early Act. JOURNAL OF BREAST IMAGING 2023; 5:712-723. [PMID: 38141231 DOI: 10.1093/jbi/wbad034] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Indexed: 12/25/2023]
Abstract
Thirty-eight states and the District of Columbia (DC) have dense breast notification laws that mandate varying levels of patient notification about breast density after a mammogram, and these cover over 90% of American women. On March 10, 2023, the Food and Drug Administration issued a final rule amending regulations under the Mammography Quality Standards Act for a national dense breast reporting standard for both patient results letters and mammogram reports. Effective September 10, 2024, letters will be required to tell a woman her breasts are "dense" or "not dense," that dense tissue makes it harder to find cancers on a mammogram, and that it increases the risk of developing cancer. Women with dense breasts will also be told that other imaging tests in addition to a mammogram may help find cancers. The specific density category can be added (eg, if mandated by a state "inform" law). Reports to providers must include the Breast Imaging Reporting and Data System density category. Implementing appropriate supplemental screening should be based on patient risk for missed breast cancer on mammography; such assessment should include consideration of breast density and other risk factors. This article discusses strategies for implementation. Currently 21 states and DC have varying insurance laws for supplemental breast imaging; in addition, Oklahoma requires coverage for diagnostic breast imaging. A federal insurance bill, the Find It Early Act, has been introduced that would ensure no-cost screening and diagnostic imaging for women with dense breasts or at increased risk and close loopholes in state laws.
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Affiliation(s)
- Wendie A Berg
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA, USA
| | - Robin L Seitzman
- Seitzman Epidemiology, LLC, San Diego, CA, USA
- DenseBreast-info, Inc, Deer Park, NY, USA
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11
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Brown AL, Vijapura C, Patel M, De La Cruz A, Wahab R. Breast Cancer in Dense Breasts: Detection Challenges and Supplemental Screening Opportunities. Radiographics 2023; 43:e230024. [PMID: 37792590 DOI: 10.1148/rg.230024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Dense breast tissue at mammography is associated with higher breast cancer incidence and mortality rates, which have prompted new considerations for breast cancer screening in women with dense breasts. The authors review the definition and classification of breast density, density assessment methods, breast cancer risk, current legislation, and future efforts and summarize trials and key studies that have affected the existing guidelines for supplemental screening. Cases of breast cancer in dense breasts are presented, highlighting a variety of modalities and specific imaging findings that can aid in cancer detection and staging. Understanding the current state of breast cancer screening in patients with dense breasts and its challenges is important to shape future considerations for care. Shifting the paradigm of breast cancer detection toward early diagnosis for women with dense breasts may be the answer to reducing the number of deaths from this common disease. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Yeh in this issue.
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Affiliation(s)
- Ann L Brown
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Charmi Vijapura
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Mitva Patel
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Alexis De La Cruz
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
| | - Rifat Wahab
- From the Department of Radiology, University of Cincinnati Medical Center, 3188 Bellevue Ave, Cincinnati, OH 45219-0772 (A.L.B., C.V., A.D.L.C., R.W.); and Department of Radiology, Ohio State University Medical Center, Columbus, Ohio (M.P.)
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12
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Berg WA, Bandos AI, Sava MG. Analytic Hierarchy Process Analysis of Patient Preferences for Contrast-Enhanced Mammography Versus MRI as Supplemental Screening Options for Breast Cancer. J Am Coll Radiol 2023; 20:758-768. [PMID: 37394083 DOI: 10.1016/j.jacr.2023.05.014] [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] [Received: 02/22/2023] [Revised: 04/20/2023] [Accepted: 05/03/2023] [Indexed: 07/04/2023]
Abstract
OBJECTIVE To guide implementation of supplemental breast screening by assessing patient preferences for contrast-enhanced mammography (CEM) versus MRI using analytic hierarchy process (AHP) methodology. METHODS In an institutional review board-approved, HIPAA-compliant protocol, from March 23 to June 3, 2022, we contacted 579 women who had both CEM screening and MRI. Women were e-mailed an invitation to complete an online survey developed using an AHP-based model to elicit preferences for CEM or MRI. Methods for categorical data analysis were used to evaluate factors affecting preferences, under the Bonferroni correction for multiplicity. RESULTS Complete responses were received from 222 (38.3%) women; the 189 women with a personal history of breast cancer had a mean age 61.8 years, and the 34 women without a personal history of breast cancer had a mean age of 53.6 years. Of 222 respondents, 157 (70.7%, confidence interval [CI]: 64.7-76.7) were determined to prefer CEM to MRI. Breast positioning was the most important criterion for 74 of 222 (33.3%) respondents, with claustrophobia, intravenous line placement, and overall stress most important for 38, 37, and 39 women (17.1%, 16.7%, and 17.6%), respectively, and noise level, contrast injection, and indifference being emphasized least frequently (by 10 [4.5%], 11 [5.0%], and 13 [5.9%] women, respectively). CEM preference was most prevalent (MRI least prevalent) for respondents emphasizing claustrophobia (37 of 38 [97%], CI: 86.2-99.9); CEM preference was least prevalent (MRI most prevalent) for respondents emphasizing breast positioning (40 of 74 [54%], CI: 42.1-65.7). CONCLUSIONS AHP-based modeling reveals strong patient preferences for CEM over MRI, with claustrophobia favoring preference for CEM and breast positioning relatively favoring preference for MRI. Our results should help guide implementation of screening CEM and MRI.
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Affiliation(s)
- Wendie A Berg
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, Pennsylvania; ACR and the Society of Breast Imaging, Honorary Fellow of the Austrian Roentgen Society, and voluntary Chief Scientific Advisor to DenseBreast-info website.
| | - Andriy I Bandos
- Department of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
| | - M Gabriela Sava
- Wilbur O. and Ann Powers College of Business, Clemson University, Clemson, South Carolina; current affiliation: Department of Applied Statistics and Operations Research, Allen W. and Carol M. Schmidhorst College of Business, Bowling Green State University, Bowling Green, Ohio
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13
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Mahecha Carvajal ME, Mahecha Carvajal JE, Cardona Ortegón JD, Palazuelos G, Romero JA. Contrast-enhanced Mammography: Revisiting the Roots of Screening. Radiology 2023; 307:e230376. [PMID: 37367441 DOI: 10.1148/radiol.230376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023]
Affiliation(s)
| | | | - José David Cardona Ortegón
- Department of Diagnostic Imaging, Fundación Santa Fe de Bogotá, 116 Street # 9-02, Bogotá, Colombia 110111
| | - Gloria Palazuelos
- Department of Diagnostic Imaging, Fundación Santa Fe de Bogotá, 116 Street # 9-02, Bogotá, Colombia 110111
| | - Javier Andrés Romero
- Department of Diagnostic Imaging, Fundación Santa Fe de Bogotá, 116 Street # 9-02, Bogotá, Colombia 110111
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14
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Smith KA, Hunt KN, Rauch GM, Fowler AM. Molecular Breast Imaging in the Screening Setting. JOURNAL OF BREAST IMAGING 2023; 5:240-247. [PMID: 38416886 DOI: 10.1093/jbi/wbad011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Indexed: 03/01/2024]
Abstract
Early detection of breast cancer through screening mammography saves lives. However, the sensitivity of mammography for breast cancer detection is reduced in women with dense breast tissue. Imaging modalities for supplemental breast cancer screening include MRI, whole breast US, contrast-enhanced mammography, and molecular breast imaging (MBI). Molecular breast imaging with 99mTc-sestamibi is a functional imaging test to identify metabolically active areas in the breast with positioning analogous to mammography. Since 2011, there have been six large, published studies of screening MBI as a supplement to mammography involving over 6000 women from four different institutions. A multicenter, prospective clinical trial of 3000 women comparing breast cancer detection using screening digital breast tomosynthesis alone or in combination with MBI recently completed enrollment. This review focuses on the current evidence of MBI use for supplemental breast cancer screening, the strengths and limitations of MBI, and recent technological advances.
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Affiliation(s)
| | - Katie N Hunt
- Mayo Clinic, Department of Radiology, Rochester, MN, USA
| | - Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
- The University of Texas MD Anderson Cancer Center, Department of Abdominal Imaging, Houston, TX, USA
| | - Amy M Fowler
- University of Wisconsin School of Medicine and Public Health, Department of Radiology, Madison, WI, USA
- University of Wisconsin Carbone Cancer Center, Madison, WI, USA
- University of Wisconsin School of Medicine and Public Health, Department of Medical Physics, Madison, WI, USA
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15
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Weigel S, Heindel W, Hense HW, Decker T, Gerß J, Kerschke L. Breast Density and Breast Cancer Screening with Digital Breast Tomosynthesis: A TOSYMA Trial Subanalysis. Radiology 2023; 306:e221006. [PMID: 36194110 DOI: 10.1148/radiol.221006] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Digital breast tomosynthesis (DBT) plus synthesized mammography (SM) reduces the diagnostic pitfalls of tissue superimposition, which is a limitation of digital mammography (DM). Purpose To compare the invasive breast cancer detection rate (iCDR) of DBT plus SM versus DM screening for different breast density categories. Materials and Methods An exploratory subanalysis of the TOmosynthesis plus SYnthesized MAmmography (TOSYMA) study, a randomized, controlled, multicenter, parallel-group trial recruited within the German mammography screening program from July 2018 to December 2020. Women aged 50-69 years were randomly assigned (1:1) to DBT plus SM or DM screening examination. Breast density categories A-D were visually assessed according to the Breast Imaging Reporting and Data System Atlas. Exploratory analyses were performed of the iCDR in both study arms and stratified by breast density, and odds ratios and 95% CIs were determined. Results A total of 49 762 women allocated to DBT plus SM and 49 796 allocated to DM (median age, 57 years [IQR, 53-62 years]) were included. In the DM arm, the iCDR was 3.6 per 1000 screening examinations in category A (almost entirely fatty) (16 of 4475 screenings), 4.3 in category B (102 of 23 534 screenings), 6.1 in category C (116 of 19 051 screenings), and 2.3 in category D (extremely dense breasts) (six of 2629 screenings). The iCDR in the DBT plus SM arm was 2.7 per 1000 screening examinations in category A (12 of 4439 screenings), 6.9 in category B (154 of 22 328 screenings), 8.3 in category C (156 of 18 772 screenings), and 8.1 in category D (32 of 3940 screenings). The odds ratio for DM versus DBT plus SM in category D was 3.8 (95% CI: 1.5, 11.1). The invasive cancers detected with DBT plus SM were most often grade 2 tumors; in category C, it was 58% (91 of 156 invasive cancers), and in category D, it was 47% (15 of 32 invasive cancers). Conclusion The TOmosynthesis plus SYnthesized MAmmography trial revealed higher invasive cancer detection rates with digital breast tomosynthesis plus synthesized mammography than digital mammography in dense breasts, relatively and absolutely most marked among women with extremely dense breasts. ClinicalTrials.gov registration no.: NCT03377036 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.
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Affiliation(s)
- Stefanie Weigel
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Walter Heindel
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Hans-Werner Hense
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Thomas Decker
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Joachim Gerß
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Laura Kerschke
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
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- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
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16
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Deep Learning Models for Automated Assessment of Breast Density Using Multiple Mammographic Image Types. Cancers (Basel) 2022; 14:cancers14205003. [PMID: 36291787 PMCID: PMC9599904 DOI: 10.3390/cancers14205003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/09/2022] [Accepted: 10/10/2022] [Indexed: 11/24/2022] Open
Abstract
Simple Summary The DL model predictions in automated breast density assessment were independent of the imaging technologies, moderately or substantially agreed with the clinical reader density values, and had improved performance as compared to inclusion of commercial software values. Abstract Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. Each participant underwent up to 3 screening examinations and completed a questionnaire at each screening encounter. Pre-trained EfficientNetB0 DL models with or without clinical history were optimized. The DL models were evaluated using BI-RADS (fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense) versus binary (non-dense or dense) density classification. Pre-trained EfficientNetB0 model performances were compared using inter-observer and commercial software (Volpara) variabilities. Results show that the average Fleiss’ Kappa score between-observers ranged from 0.31–0.50 and 0.55–0.69 for the BI-RADS and binary classifications, respectively, showing higher uncertainty among experts. Volpara-observer agreement was 0.33 and 0.54 for BI-RADS and binary classifications, respectively, showing fair to moderate agreement. However, our proposed pre-trained EfficientNetB0 DL models-observer agreement was 0.61–0.66 and 0.70–0.75 for BI-RADS and binary classifications, respectively, showing moderate to substantial agreement. Overall results show that the best breast density estimation was achieved using for-presentation FFDM and DBT images without added clinical information. Pre-trained EfficientNetB0 model can automatically assess breast density from any images modality type, with the best results obtained from for-presentation FFDM and DBT, which are the most common image archived in clinical practice.
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17
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Yong-Hing CJ, Gordon PB, Appavoo S, Fitzgerald SR, Seely JM. Addressing Misinformation About the Canadian Breast Screening Guidelines. Can Assoc Radiol J 2022; 74:388-397. [PMID: 36048585 DOI: 10.1177/08465371221120798] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Screening mammography has been shown to reduce breast cancer mortality by 41% in screened women ages 40-69 years. There is misinformation about breast screening and the Canadian breast screening guidelines. This can decrease confidence in screening mammography and can lead to suboptimal recommendations. We review some of this misinformation to help radiologists and referring physicians navigate the varied international and provincial guidelines. We address the ages to start and stop breast screening. We explore how these recommendations may vary for specific populations such as patients who are at increased risk, transgender patients and minorities. We identify who would benefit from supplemental screening and review the available supplemental screening modalities including ultrasound, MRI, contrast-enhanced mammography and others. We describe emerging technologies including the potential use of artificial intelligence for breast screening. We provide background on why screening policies vary across the country between provinces and territories. This review is intended to help radiologists and referring physicians understand and navigate the varied international and provincial recommendations and guidelines and make the best recommendations for their patients.
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Affiliation(s)
- Charlotte J Yong-Hing
- Faculty of Medicine, Department of Radiology, 8166University of British Columbia, Vancouver, BC, Canada
| | - Paula B Gordon
- Faculty of Medicine, Department of Radiology, 8166University of British Columbia, Vancouver, BC, Canada
| | - Shushiela Appavoo
- Department of Radiology and Diagnostic Imaging, 3158University of Alberta, Edmonton, AB, Canada
| | - Sabrina R Fitzgerald
- Faculty of Medicine, Department of Radiology, 7938University of Toronto, Toronto, ON, Canada
| | - Jean M Seely
- Faculty of Medicine, Department of Radiology, University of Ottawa, Ottawa, ON, Canada.,Ottawa Hospital Research Institute, Ottawa, ON, Canada.,Ontario Breast Screening Program, Ottawa, ON, Canada
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18
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Lee SH, Moon WK. Glandular Tissue Component on Breast Ultrasound in Dense Breasts: A New Imaging Biomarker for Breast Cancer Risk. Korean J Radiol 2022; 23:574-580. [PMID: 35617993 PMCID: PMC9174505 DOI: 10.3348/kjr.2022.0099] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/04/2022] [Accepted: 04/10/2022] [Indexed: 11/15/2022] Open
Affiliation(s)
- Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.
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19
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The Impact of Dense Breasts on the Stage of Breast Cancer at Diagnosis: A Review and Options for Supplemental Screening. Curr Oncol 2022; 29:3595-3636. [PMID: 35621681 PMCID: PMC9140155 DOI: 10.3390/curroncol29050291] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/23/2022] [Accepted: 04/25/2022] [Indexed: 11/16/2022] Open
Abstract
The purpose of breast cancer screening is to find cancers early to reduce mortality and to allow successful treatment with less aggressive therapy. Mammography is the gold standard for breast cancer screening. Its efficacy in reducing mortality from breast cancer was proven in randomized controlled trials (RCTs) conducted from the early 1960s to the mid 1990s. Panels that recommend breast cancer screening guidelines have traditionally relied on the old RCTs, which did not include considerations of breast density, race/ethnicity, current hormone therapy, and other risk factors. Women do not all benefit equally from mammography. Mortality reduction is significantly lower in women with dense breasts because normal dense tissue can mask cancers on mammograms. Moreover, women with dense breasts are known to be at increased risk. To provide equity, breast cancer screening guidelines should be created with the goal of maximizing mortality reduction and allowing less aggressive therapy, which may include decreasing the interval between screening mammograms and recommending consideration of supplemental screening for women with dense breasts. This review will address the issue of dense breasts and the impact on the stage of breast cancer at the time of diagnosis, and discuss options for supplemental screening.
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20
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Breast MRI for "the Masses". Eur Radiol 2022; 32:4034-4035. [PMID: 35420302 DOI: 10.1007/s00330-022-08782-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 03/02/2022] [Accepted: 03/26/2022] [Indexed: 11/04/2022]
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21
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Gordon PB, Berg WA. Corrections: Breast cancer screening guidelines for young women of color. Cancer 2022; 128:849-850. [PMID: 34730844 DOI: 10.1002/cncr.33988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 10/08/2021] [Indexed: 11/11/2022]
Affiliation(s)
- Paula B Gordon
- Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Wendie A Berg
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
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22
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Covington MF. Rethinking the ACR Appropriateness Criteria® Supplemental Breast Cancer Screening Based on Breast Density. J Am Coll Radiol 2022; 19:595. [DOI: 10.1016/j.jacr.2021.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 11/17/2021] [Indexed: 10/19/2022]
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23
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24
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Covington MF, Parent EE, Dibble EH, Rauch GM, Fowler AM. Advances and Future Directions in Molecular Breast Imaging. J Nucl Med 2021; 63:17-21. [PMID: 34887334 DOI: 10.2967/jnumed.121.261988] [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: 06/01/2021] [Revised: 11/16/2021] [Indexed: 12/11/2022] Open
Abstract
Molecular breast imaging (MBI) using 99mTc-sestamibi has advanced rapidly over the past decade. Technical advances allow lower-dose, higher-resolution imaging and biopsy capability. MBI can be used for supplemental breast cancer screening with mammography for women with dense breasts, as well as to assess neoadjuvant therapy response, evaluate disease extent, and predict breast cancer risk. This article highlights the current state of the art and future directions in MBI.
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Affiliation(s)
- Matthew F Covington
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute and University of Utah Department of Radiology and Imaging Sciences, Salt Lake City, Utah;
| | | | - Elizabeth H Dibble
- Warren Alpert Medical School of Brown University/Rhode Island Hospital Department of Diagnostic Imaging, Providence, Rhode Island
| | - Gaiane M Rauch
- M.D. Anderson Cancer Center, Departments of Abdominal and Breast Imaging, Houston, Texas; and
| | - Amy M Fowler
- University of Wisconsin School of Medicine and Public Health, Departments of Radiology and Medical Physics and the University of Wisconsin Carbone Cancer Center, Madison, Wisconsin
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25
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Fishman MDC, Rehani MM. Monochromatic X-rays: The future of breast imaging. Eur J Radiol 2021; 144:109961. [PMID: 34562745 DOI: 10.1016/j.ejrad.2021.109961] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/03/2021] [Accepted: 09/15/2021] [Indexed: 12/16/2022]
Abstract
PURPOSE To present details about the innovative and disruptive technology of monochromatic X-rays and its application to breast imaging. METHODS To analyze results of studies done using a prototype system for breast imaging that generates monochromatic X-rays through fluorescence emission. To assess signal-to-noise ratio (SNR) as a measure of image quality at different doses in breast phantoms of different sizes and review the comparison of parameters with a standard mammography system. RESULTS Monochromatic X-rays reduce the radiation dose per mammogram by a factor of 5 to 10 times. For phantom simulating thick breast (9 cm), the SNR for monochromatic system was 2.6 times higher and the dose 4.2 times lower than the respective values obtained with the conventional system within the same 5 mm × 5 mm square area of the 100% glandular step wedge. For the conventional broadband system to equal the SNR of the monochromatic system, it would require a dose of 19 mGy, 29 times higher than the dose delivered by the monochromatic system. Contrast-enhanced digital mammography with monochromatic X-rays is shown to provide a simpler and more effective technique at substantially lower radiation dose. CONCLUSIONS Lowering radiation dose by a factor of 5 to 10 while maintaining image quality implies a major reduction in total exposure from breast cancer screening and dramatically less risk of radiation-induced cancers in at-risk women. The high SNRs for very thick breast phantoms provide strong evidence that screening with lower breast compression is possible while maintaining image quality.
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Affiliation(s)
- Michael D C Fishman
- Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
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26
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Gordon PB, Berg WA. Is It Really Time to Close the Chapter on Screening Breast US? Radiology 2021; 301:E414. [PMID: 34402667 DOI: 10.1148/radiol.2021210104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Paula B Gordon
- Faculty of Medicine, University of British Columbia, 750 W Broadway, Suite 505, Vancouver, BC, Canada V5Z 1H4
| | - Wendie A Berg
- Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pa
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27
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Implementation of Abbreviated Breast MRI for Screening: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2021; 218:202-212. [PMID: 34378397 DOI: 10.2214/ajr.21.26349] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Abbreviated breast MRI (AB-MRI) is being rapidly adopted to harness the high sensitivity of screening MRI while addressing issues related to access, cost, and workflow. The successful implementation of an ABI-MRI program requires collaboration across administrative, operational, financial, technical, and clinical providers. Institutions must be thoughtful in defining AB-MRI patient eligibility and providing recommendations for screening intervals, as existing practices are heterogeneous. Similarly, there is no universally accepted AB-MRI protocol, though guiding principles should harmonize abbreviated and full protocols while being mindful of scan duration and table time. The interpretation of AB-MRI will be a new experience for many radiologists and may require a phased rollout as well as a careful audit of performance metrics over time to ensure benchmark metrics are achieved. AB-MRI finances, which are driven by patient self-payment, will require buy-in from hospital administration with the recognition that downstream revenues will be needed to support initial costs. Finally, successful startup of an AB-MRI program requires active engagement with the larger community of patients and referring providers. As AB-MRI becomes more widely accepted and available, best practices and community standards will continue to evolve to ensure high quality patient care.
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28
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Seely JM, Peddle SE, Yang H, Chiarelli AM, McCallum M, Narasimhan G, Zakaria D, Earle CC, Fung S, Bryant H, Nicholson E, Politis C, Berg W. Breast Density and Risk of Interval Cancers: The Effect of Annual Versus Biennial Screening Mammography Policies in Canada. Can Assoc Radiol J 2021; 73:90-100. [PMID: 34279132 DOI: 10.1177/08465371211027958] [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: 12/12/2022] Open
Abstract
Regular screening mammography reduces breast cancer mortality. However, in women with dense breasts, the performance of screening mammography is reduced, which is reflected in higher interval cancer rates (ICR). In Canada, population-based screening mammography programs generally screen women biennially; however, some provinces and territories offer annual mammography for women with dense breast tissue routinely and/or on recommendation of the radiologist. This study compared the ICRs in those breast screening programs with a policy of annual vs. those with biennial screening for women with dense breasts. Among 148,575 women with dense breasts screened between 2008 to 2010, there were 288 invasive interval breast cancers; screening programs with policies offering annual screening for women with dense breasts had fewer interval cancers 63/70,814 (ICR 0.89/1000, 95% CI: 0.67-1.11) compared with those with policies of usual biennial screening 225/77,761 (ICR 1.45 /1000 (annualized), 95% CI: 1.19-1.72) i.e. 63% higher (p = 0.0016). In screening programs where radiologists' screening recommendations were able to be analyzed, a total of 76,103 women were screened, with 87 interval cancers; the ICR was lower for recommended annual (65/69,650, ICR 0.93/1000, 95% CI: 0.71, 1.16) versus recommended biennial screening (22/6,453, ICR 1.70/1000 (annualized), 95%CI: 0.70, 2.71)(p = 0.0605). Screening program policies of annual as compared with biennial screening in women with dense breasts had the greatest impact on reducing interval cancer rates. We review our results in the context of current dense breast notification in Canada.
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Affiliation(s)
- Jean Morag Seely
- Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.,Department of Radiology and Surgery, University of Ottawa, Ottawa, Ontario, Canada.,Department of Medical Imaging, The Ottawa Hospital, Ottawa, Ontario, Canada
| | | | - Huiming Yang
- Alberta Health Services, Edmonton, Alberta, Canada
| | | | - Megan McCallum
- Government of the Northwest Territories, Yellowknife, Northwest Territories, Canada
| | | | | | - Craig C Earle
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada.,Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Sharon Fung
- Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Heather Bryant
- Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Erika Nicholson
- Canadian Partnership Against Cancer, Halifax, Nova Scotia, Canada
| | - Chris Politis
- Canadian Partnership Against Cancer, Toronto, Ontario, Canada
| | - Wendie Berg
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,UPMC Magee-Womens Hospital, Pittsburgh, PA, USA
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29
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Monticciolo DL, Malak SF, Friedewald SM, Eby PR, Newell MS, Moy L, Destounis S, Leung JWT, Hendrick RE, Smetherman D. Breast Cancer Screening Recommendations Inclusive of All Women at Average Risk: Update from the ACR and Society of Breast Imaging. J Am Coll Radiol 2021; 18:1280-1288. [PMID: 34154984 DOI: 10.1016/j.jacr.2021.04.021] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 11/25/2022]
Abstract
Breast cancer remains the most common nonskin cancer, the second leading cause of cancer deaths, and the leading cause of premature death in US women. Mammography screening has been proven effective in reducing breast cancer deaths in women age 40 years and older. A mortality reduction of 40% is possible with regular screening. Treatment advances cannot overcome the disadvantage of being diagnosed with an advanced-stage tumor. The ACR and Society of Breast Imaging recommend annual mammography screening beginning at age 40, which provides the greatest mortality reduction, diagnosis at earlier stage, better surgical options, and more effective chemotherapy. Annual screening results in more screening-detected tumors, tumors of smaller sizes, and fewer interval cancers than longer screening intervals. Screened women in their 40s are more likely to have early-stage disease, negative lymph nodes, and smaller tumors than unscreened women. Delaying screening until age 45 or 50 will result in an unnecessary loss of life to breast cancer and adversely affects minority women in particular. Screening should continue past age 74 years, without an upper age limit unless severe comorbidities limit life expectancy. Benefits of screening should be considered along with the possibilities of recall for additional imaging and benign biopsy and the less tangible risks of anxiety and overdiagnosis. Although recall and biopsy recommendations are higher with more frequent screening, so are life-years gained and breast cancer deaths averted. Women who wish to maximize benefit will choose annual screening starting at age 40 years and will not stop screening prematurely.
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Affiliation(s)
- Debra L Monticciolo
- Vice-chair for Research, Department of Radiology, and Section Chief, Breast Imaging, Texas A&M University Health Sciences, Baylor Scott & White Healthcare-Central Texas, Temple, Texas.
| | | | - Sarah M Friedewald
- Chief of Breast and Women's Imaging; Vice Chair of Operations, Department of Radiology; Medical Director, Lynn Sage Comprehensive Breast Center, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Peter R Eby
- Chief of Breast Imaging, Radiology Representative to the Cancer Committee, Virginia Mason Medical Center, Seattle, Washington
| | - Mary S Newell
- Associate Division Director; Associate Director of Breast Center, Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia
| | - Linda Moy
- Laura and Isaac Perlutter Cancer Center, NYU School of Medicine, New York City, New York
| | - Stamatia Destounis
- Chair of Clinical Research and Medical Outcomes Department, Elizabeth Wende Breast Care, Rochester, New York
| | - Jessica W T Leung
- Deputy Chair of Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - R Edward Hendrick
- Department of Radiology, University of Colorado School of Medicine, Aurora, Colorado
| | - Dana Smetherman
- Department Chair and Associate Medical Director of the Medical Specialties, Department of Radiology, Ochsner Medical Center, New Orleans, Louisiana
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30
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Gao Y, Liu B, Zhu Y, Chen L, Tan M, Xiao X, Yu G, Guo Y. Detection and recognition of ultrasound breast nodules based on semi-supervised deep learning: a powerful alternative strategy. Quant Imaging Med Surg 2021; 11:2265-2278. [PMID: 34079700 PMCID: PMC8107344 DOI: 10.21037/qims-20-12b] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Accepted: 01/18/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND The successful recognition of benign and malignant breast nodules using ultrasound images is based mainly on supervised learning that requires a large number of labeled images. However, because high-quality labeling is expensive and time-consuming, we hypothesized that semi-supervised learning could provide a low-cost and powerful alternative approach. This study aimed to develop an accurate semi-supervised recognition method and compared its performance with supervised methods and sonographers. METHODS The faster region-based convolutional neural network was used for nodule detection from ultrasound images. A semi-supervised classifier based on the mean teacher model was proposed to recognize benign and malignant nodule images. The general performance of the proposed method on two datasets (8,966 nodules) was reported. RESULTS The detection accuracy was 0.88±0.03 and 0.86±0.02, respectively, on two testing sets (1,350 and 2,220 nodules). When 800 labeled training nodules were available, the proposed semi-supervised model plus 4,396 unlabeled nodules performed better than the supervised learning model (area under the curve (AUC): 0.934±0.026 vs. 0.83±0.050; 0.916±0.022 vs. 0.815±0.049). The performance of the semi-supervised model trained on 800 labeled and 4,396 unlabeled nodules was close to that of the supervised learning model trained on a massive number of labeled nodules (n=5,196) (AUC: 0.934±0.026 vs. 0.952±0.027; 0.916±0.022 vs. 0.918±0.017). Moreover, the semi-supervised model was better than the average accuracy of five human sonographers (AUC: 0.922 vs. 0.889). CONCLUSIONS The semi-supervised model can achieve excellent performance for nodule recognition and be useful for medical sciences. The method reduced the number of labeled images required for training, thus significantly alleviating the difficulty in data preparation of medical artificial intelligence.
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Affiliation(s)
- Yanhua Gao
- Department of Medical Imaging, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- Department of Ultrasound, The Third Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Bo Liu
- Department of Ultrasound, The Third Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Yuan Zhu
- Department of Ultrasound, The Third Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Lin Chen
- Department of Pathology, The Third Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Miao Tan
- Department of Surgery, The Third Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Xiaozhou Xiao
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, China
| | - Gang Yu
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, China
| | - Youmin Guo
- Department of Medical Imaging, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Mesurolle B, El Khoury M, Travade A, Bagard C, Pétrou A, Monghal C. Is there any added value to substitute the 2D digital MLO projection for a MLO tomosynthesis projection and its synthetic view when a 2D standard digital mammography is used in a one-stop-shop immediate reading mammography screening? Eur Radiol 2021; 31:9529-9539. [PMID: 34047846 DOI: 10.1007/s00330-021-07999-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 04/01/2021] [Accepted: 04/13/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVES Breast cancer screening consists of batch interpretation of two-view (cranio-caudal CC- and medio-lateral oblique MLO) digital mammography (DM) per breast. The DM-MLO view was substituted by an MLO-digital breast tomosynthesis (DBT) and its synthetic (2D-synthetic mammography (SM)-MLO) view. The performance of this hybrid protocol was evaluated in a one-stop-shop screening visit, providing immediate reading and additional work up. METHODS Retrospective, observational review, comparing the cancer detection rate (CDR), breast US rates, and biopsy rates in 13,048 women screened with DM from June 2015 to November 2016 and 8639 women screened with SM-DBT/DM from January 2017 to July 2018. Chi-square tests or Fisher's exact tests were used to compare proportions between the two screening imaging methods. RESULTS SM + DBT/DM significantly increased the overall CDR (10.8‰) versus DM (7.5‰) (p = 0.0120) with more invasive lobular carcinoma (14% versus 4%) (p = 0.0357) detected and overall more invasive cancers among women with breast density type B (p = 0.0411) and those aged between 60 and 70 (p = 0.0306). This was achieved at the expense of additional sonographic examinations performed (33.5% in DBT group versus 26.7% in DM group) (p < 0.0001), more BI-RADS category III assigned (1.8% in SM-DBT/DM group versus 1.5% in DM group) (p = 0.0443) and more biopsy rates (3.0 % in SM-DBT/DM group versus 1.7% in DM group) (p < 0.0001). CONCLUSIONS Hybrid mammographic protocol replacing 2D-MLO by DBT-MLO and SM-MLO views in a one-stop-shop screening visit improved CDR, at the expense of more sonographic examinations, biopsies, and BI-RADS III lesions. Breast US alone detected 9.2% of all breast cancers in this cohort. KEY POINTS • Hybrid protocol including MLO (DBT + SM) with 2D DM CC may improve CDR compared to standard 4 views 2D DM in a screening program providing immediate interpretation. • Adding screening breast US, when perceived necessary, in the same visit of a screening mammography, increases cancer detection rate of 9.2%. • Based on our results, hybrid protocol including DBT + SM in MLO plane and DM in CC plane could be safely implemented as a transition towards DBT and SM alone, without any compromise in the cancer detection ability. Our results may vary according to the properties of machines from different vendors.
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Affiliation(s)
- Benoît Mesurolle
- Department of Radiology, Elsan, Centre République, 99 avenue de la République, BP 304, 63023, Clermont-Ferrand Cedex 2, France.
| | - Mona El Khoury
- Department of Radiology, Centre Hospitalier Universitaire de Montréal, 1051 Rue Sanguinet, Montréal, QC, H2X 3H4, Canada
| | - Armelle Travade
- Department of Radiology, Elsan, Centre République, 99 avenue de la République, BP 304, 63023, Clermont-Ferrand Cedex 2, France
| | - Christine Bagard
- Department of Radiology, Elsan, Centre République, 99 avenue de la République, BP 304, 63023, Clermont-Ferrand Cedex 2, France
| | - Agnès Pétrou
- Department of Radiology, Elsan, Centre République, 99 avenue de la République, BP 304, 63023, Clermont-Ferrand Cedex 2, France
| | - Camille Monghal
- Department of Radiology, Elsan, Centre République, 99 avenue de la République, BP 304, 63023, Clermont-Ferrand Cedex 2, France
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32
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Grimm LJ. Radiomics: A Primer for Breast Radiologists. JOURNAL OF BREAST IMAGING 2021; 3:276-287. [PMID: 38424774 DOI: 10.1093/jbi/wbab014] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Indexed: 03/02/2024]
Abstract
Radiomics has a long-standing history in breast imaging with computer-aided detection (CAD) for screening mammography developed in the late 20th century. Although conventional CAD had widespread adoption, the clinical benefits for experienced breast radiologists were debatable due to high false-positive marks and subsequent increased recall rates. The dramatic growth in recent years of artificial intelligence-based analysis, including machine learning and deep learning, has provided numerous opportunities for improved modern radiomics work in breast imaging. There has been extensive radiomics work in mammography, digital breast tomosynthesis, MRI, ultrasound, PET-CT, and combined multimodality imaging. Specific radiomics outcomes of interest have been diverse, including CAD, prediction of response to neoadjuvant therapy, lesion classification, and survival, among other outcomes. Additionally, the radiogenomics subfield that correlates radiomics features with genetics has been very proliferative, in parallel with the clinical validation of breast cancer molecular subtypes and gene expression assays. Despite the promise of radiomics, there are important challenges related to image normalization, limited large unbiased data sets, and lack of external validation. Much of the radiomics work to date has been exploratory using single-institution retrospective series for analysis, but several promising lines of investigation have made the leap to clinical practice with commercially available products. As a result, breast radiologists will increasingly be incorporating radiomics-based tools into their daily practice in the near future. Therefore, breast radiologists must have a broad understanding of the scope, applications, and limitations of radiomics work.
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Affiliation(s)
- Lars J Grimm
- Duke University, Department of Radiology, Durham, NC, USA
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Seitzman RL, Pushkin J, Berg WA. Effect of an educational intervention on women's healthcare provider knowledge gaps about breast density, breast cancer risk, and screening. Menopause 2021; 28:909-917. [PMID: 33906202 DOI: 10.1097/gme.0000000000001780] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES We sought to assess the effect of an educational intervention, based on DenseBreast-info.org website content, on women's healthcare provider knowledge of breast density, its risk and screening implications, and comfort level discussing these topics with patients. METHODS US-based women's healthcare providers participated in a web-based pretest/posttest study from May 14, 2019 to September 30, 2019. Pretest included demographics; comfort/knowledge discussing breast density impact on risk and screening; and educational material. Posttest contained the same knowledge and comfort questions. We assessed mean pretest/posttest score and comfort level differences (paired t tests) and pretest/posttest knowledge gap differences (McNemar test). We evaluated associations of baseline characteristics with pretest score and score improvement using multiple linear regression, and associations with knowledge gaps using logistic regression. RESULTS Of 177 providers analyzed, 74.0% (131/177) were physicians and 71.8% (127/177) practiced obstetrics/gynecology. Average test score increased from 40.9% (5.7/14) responses correct pretest to 72.1% (10.1/14) posttest (P < 0.001). Pretest, 56.5% (100/177) knew women with extremely dense breasts have four-to-six-fold greater breast cancer risk than those with fatty breasts; 29.4% (52/177) knew risk increases with increasing glandular tissue; only 5.6% (10/177) knew 3D/tomosynthesis does not improve cancer detection in extremely dense breasts over 2D mammography; and 70.6% (125/177) would consider supplemental ultrasound after mammography in an average-risk 50-year old with dense breasts. Postintervention, these knowledge gaps resolved or reduced (all P < 0.005) and comfort in discussing breast density implications increased (all P < 0.001). CONCLUSIONS Important knowledge gaps about implications of breast density exist among women's healthcare providers, which can be effectively addressed with web-based education.
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Affiliation(s)
| | | | - Wendie A Berg
- DenseBreast-info, Inc., Deer Park, NY
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
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Rahbar H, Partridge SC. Editorial on "Diffusion-Weighted Double-Echo Steady-State with a 3D Cones Trajectory for Non-Contrast-Enhanced Breast MRI". J Magn Reson Imaging 2021; 53:1606-1607. [PMID: 33554380 DOI: 10.1002/jmri.27524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 11/06/2022] Open
Affiliation(s)
- Habib Rahbar
- Department of Radiology, Seattle Cancer Care Alliance, University of Washington School of Medicine, Seattle, Washington, USA
| | - Savannah C Partridge
- Department of Radiology, Seattle Cancer Care Alliance, University of Washington School of Medicine, Seattle, Washington, USA
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Hooley R, Butler R. Digital Breast Tomosynthesis May Not Provide Optimal Surveillance of Breast Cancer Survivors. Radiology 2020; 298:317-318. [PMID: 33355509 DOI: 10.1148/radiol.2020204219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Regina Hooley
- From the Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520
| | - Reni Butler
- From the Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar St, PO Box 208042, New Haven, CT 06520
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