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Seely JM, Domonkos V, Verma R. Auditing Abbreviated Breast MR Imaging: Clinical Considerations and Implications. Radiol Clin North Am 2024; 62:687-701. [PMID: 38777543 DOI: 10.1016/j.rcl.2023.12.010] [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
Abbreviated breast MR (AB-MR) imaging is a relatively new breast imaging tool, which maintains diagnostic accuracy while reducing image times compared with full-protocol breast MR (FP-MR) imaging. Breast imaging audits involve calculating individual and organizational metrics, which can be compared with established benchmarks, providing a standard against which performance can be measured. Unlike FP-MR imaging, there are no established benchmarks for AB-MR imaging but studies demonstrate comparable performance for cancer detection rate, positive predictive value 3, sensitivity, and specificity with T2. We review the basics of performing an audit, including strategies to implement if benchmarks are not being met.
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Affiliation(s)
- Jean M Seely
- Department of Radiology, The Ottawa Hospital, General Campus, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada.
| | - Victoria Domonkos
- Department of Radiology, The Ottawa Hospital, General Campus, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada
| | - Raman Verma
- Department of Radiology, The Ottawa Hospital, General Campus, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada. https://twitter.com/RamanVermaMD
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2
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Mann RM, Longo V. Contrast-enhanced Mammography versus MR Imaging of the Breast. Radiol Clin North Am 2024; 62:643-659. [PMID: 38777540 DOI: 10.1016/j.rcl.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
Breast MR imaging and contrast-enhanced mammography (CEM) are both techniques that employ intravenously injected contrast agent to assess breast lesions. This approach is associated with a very high sensitivity for malignant lesions that typically exhibit rapid enhancement due to the leakiness of neovasculature. CEM may be readily available at the breast imaging department and can be performed on the spot. Breast MR imaging provides stronger enhancement than the x-ray-based techniques and offers higher sensitivity. From a patient perspective, both modalities have their benefits and downsides; thus, patient preference could also play a role in the selection of the imaging technique.
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Affiliation(s)
- Ritse M Mann
- Department of Imaging, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Radiology, the Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Valentina Longo
- Department of Bioimaging, Radiation Oncology and Hematology, UOC of Radiodiagnostica Presidio Columbus, Fondazione Policlinico Universitario A. Gemelli IRCSS, Largo A. Gemelli 8, Rome 00168, Italy
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Li S, Lin Y, Liu G, Shao Z, Yang Y. Unveiling the potential of breast MRI: a game changer for BI-RADS 4A microcalcifications. Breast Cancer Res Treat 2024; 206:425-435. [PMID: 38664289 DOI: 10.1007/s10549-024-07320-y] [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: 02/06/2024] [Accepted: 03/28/2024] [Indexed: 06/19/2024]
Abstract
PURPOSE To assess the diagnostic performance of breast MRI for BI-RADS 4A microcalcifications on mammography and propose a potential clinical pathway to avoid unnecessary biopsies. METHODS Bibliometrics analysis of breast MRI and BI-RADS 4 was provided. A retrospective analysis was conducted on 139 women and 142 cases of BI-RADS 4A microcalcifications on mammography from Fudan University Shanghai Cancer Center. The mammographic BI-RADS level and the MRI reports were compared with the final pathological diagnosis. RESULTS Much attention has been given to breast MRI and BI-RADS 4 in the literature. However, studies on BI-RADS 4A are limited. Pathological results showed 117 cases (82.4%) were benign lesions, malignant cases of 25 (17.6%) in our study. The positive predictive values (PPV), specificity, sensitivity and negative predictive values (NPV) of MRI were 44.2% (23/52), 75.2% (88/117), 92.0% (23/25), and 97.8% (88/90), respectively. Therefore, 75.2% (88/117) of biopsies for benign lesions could potentially be avoided. There were 2.2% (2/90) malignant lesions missed. Logistic regression indicated that patients who are postmenopausal (HR = 2.655, p = 0.012), have a history of breast cancer (family history) (HR = 2.833, p = 0.029), and exhibit clustered microcalcifications (HR = 2.179, p = 0.046) are more likely to have a higher MRI BI-RADS level. CONCLUSIONS Breast MRI has the potential to improve the diagnosis of BI-RADS 4A microcalcifications on mammography. We propose a potential clinical pathway that patients with BI-RADS 4A on mammography who are premenopausal, have no personal history of breast cancer (family history) or have non-clustered distribution of calcifications can undergo MRI to avoid unnecessary biopsies.
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Affiliation(s)
- Shiping Li
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Fudan University, Shanghai Medical College, Shanghai, China
| | - Yihao Lin
- The First School of Medicine, Wenzhou Medical University, Wenzhou, China
| | - Guangyu Liu
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Fudan University, Shanghai Medical College, Shanghai, China
| | - Zhimin Shao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Fudan University, Shanghai Medical College, Shanghai, China
| | - Yinlong Yang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Fudan University, Shanghai Medical College, Shanghai, China.
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Kaiser C, Wilhelm T, Walter S, Singer S, Keller E, Baltzer PAT. Cancer detection rate of breast-MR in supplemental screening after negative mammography in women with dense breasts. Preliminary results of the MA-DETECT-Study after 200 participants. Eur J Radiol 2024; 176:111476. [PMID: 38710116 DOI: 10.1016/j.ejrad.2024.111476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 03/20/2024] [Accepted: 04/17/2024] [Indexed: 05/08/2024]
Abstract
BACKGROUND Due to increased cancer detection rates (CDR), breast MR (breast MRI) can reduce underdiagnosis of breast cancer compared to conventional imaging techniques, particularly in women with dense breasts. The purpose of this study is to report the additional breast cancer yield by breast MRI in women with dense breasts after receiving a negative screening mammogram. METHODS For this study we invited consecutive participants of the national German breast cancer Screening program with breast density categories ACR C & D and a negative mammogram to undergo additional screening by breast MRI. Endpoints were CDR and recall rates. This study reports interim results in the first 200 patients. At a power of 80% and considering an alpha error of 5%, this preliminary population size is sufficient to demonstrate a 4/1000 improvement in CDR. RESULTS In 200 screening participants, 8 women (40/1000, 17.4-77.3/1000) were recalled due to positive breast MRI findings. Image-guided biopsy revealed 5 cancers in 4 patients (one bilateral), comprising four invasive cancers and one case of DCIS. 3 patients revealed 4 invasive cancers presenting with ACR C breast density and one patient non-calcifying DCIS in a woman with ACR D breast density, resulting in a CDR of 20/1000 (95%-CI 5.5-50.4/1000) and a PPV of 50% (95%-CI 15.7-84.3%). CONCLUSION Our initial results demonstrate that supplemental screening using breast MRI in women with heterogeneously dense and very dense breasts yields an additional cancer detection rate in line with a prior randomized trial on breast MRI screening of women with extremely dense breasts. These findings are highly important as the population investigated constitutes a much higher proportion of women and yielded cancers particularly in women with heterogeneously dense breasts.
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Affiliation(s)
- Cgn Kaiser
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim-University of Heidelberg, Germany.
| | - T Wilhelm
- German National Screening Unit Radiologie Franken-Hohenlohe, BW, Germany
| | - S Walter
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim-University of Heidelberg, Germany
| | - S Singer
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim-University of Heidelberg, Germany
| | - E Keller
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim-University of Heidelberg, Germany
| | - P A T Baltzer
- Department of Biomedical Imaging and Image-guided therapy, Allgemeines Krankenhaus Wien, Medical University of Vienna, Austria
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5
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Pötsch N, Clauser P, Kapetas P, Baykara Ulusan M, Helbich T, Baltzer P. Enhancing the Kaiser score for lesion characterization in unenhanced breast MRI. Eur J Radiol 2024; 176:111520. [PMID: 38820953 DOI: 10.1016/j.ejrad.2024.111520] [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: 04/04/2024] [Revised: 05/15/2024] [Accepted: 05/19/2024] [Indexed: 06/02/2024]
Abstract
PURPOSE To adapt the methodology of the Kaiser score, a clinical decision rule for lesion characterization in breast MRI, for unenhanced protocols. METHOD In this retrospective IRB-approved cross-sectional study, we included 93 consecutive patients who underwent breast MRI between 2021 and 2023 for further work-up of BI-RADS 0, 3-5 in conventional imaging or for staging purposes (BI-RADS 6). All patients underwent biopsy for histologic verification or were followed for a minimum of 12 months. MRI scans were conducted using 1.5 T or 3 T scanners using dedicated breast coils and a protocol in line with international recommendations including DWI and ADC. Lesion characterization relied solely on T2w and DWI/ADC-derived features (such as lesion type, margins, shape, internal signal, surrounding tissue findings, ADC value). Statistical analysis was done using decision tree analysis aiming to distinguish benign (histology/follow-up) from malignant outcomes. RESULTS We analyzed a total of 161 lesions (81 of them non-mass) with a malignancy rate of 40%. Lesion margins (spiculated, irregular, or circumscribed) were identified as the most important criterion within the decision tree, followed by the ADC value as second most important criterion. The resulting score demonstrated a strong diagnostic performance with an AUC of 0.840, providing both rule-in and rule-out criteria. In an independent test set of 65 lesions the diagnostic performance was verified by two readers (AUC 0.77 and 0.87, kappa: 0.62). CONCLUSIONS We developed a clinical decision rule for unenhanced breast MRI including lesion margins and ADC value as the most important criteria, achieving high diagnostic accuracy.
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Affiliation(s)
- N Pötsch
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - P Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - P Kapetas
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - M Baykara Ulusan
- Department of Radiology, University of Health Sciences Istanbul Training and Research Hospital, Org. Abdurrahman Nafiz Gurman Cad, No:1 Fatih, İstanbul, Turkey
| | - T Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - P Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna and General Hospital, Waehringer Guertel 18-20, 1090 Vienna, Austria.
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Kočo L, Balkenende L, Appelman L, Moman MR, Sponsel A, Schimanski M, Prokop M, Mann RM. Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study. Invest Radiol 2024; 59:538-544. [PMID: 38193779 DOI: 10.1097/rli.0000000000001059] [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: 01/10/2024]
Abstract
OBJECTIVES This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized. MATERIALS AND METHODS A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables. RESULTS The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario. CONCLUSIONS This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.
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Affiliation(s)
- Lejla Kočo
- From the Department of Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (L.K., L.A., M.P., R.M.M.); Department of Radiology, The Netherlands Cancer Institute (Antoni van Leeuwenhoek), Amsterdam, the Netherlands (L.B., R.M.M.); Department of Radiology, Alexander Monro Hospital, Bilthoven, the Netherlands (L.A., M.R.M.); and Siemens Healthcare GmbH, Erlangen, Germany (A.S., M.S.)
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7
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Ray KM. Interval Cancers in Understanding Screening Outcomes. Radiol Clin North Am 2024; 62:559-569. [PMID: 38777533 DOI: 10.1016/j.rcl.2023.12.012] [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
Interval breast cancers are not detected at routine screening and are diagnosed in the interval between screening examinations. A variety of factors contribute to interval cancers, including patient and tumor characteristics as well as the screening technique and frequency. The interval cancer rate is an important metric by which the effectiveness of screening may be assessed and may serve as a surrogate for mortality benefit.
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Affiliation(s)
- Kimberly M Ray
- Department of Radiology and Biomedical Sciences, University of California, San Francisco, UCSF Medical Center, 1825 4th Street, L3185, Box 4034, San Francisco, CA 94107, USA.
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Ginzberg SP, Grady CB, Fayanju OM, Edmonds CE. Disparities in the Use of Preoperative Breast Magnetic Resonance Imaging After Breast Cancer Diagnosis. JCO Oncol Pract 2024:OP2300831. [PMID: 38950325 DOI: 10.1200/op.23.00831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/27/2024] [Accepted: 04/22/2024] [Indexed: 07/03/2024] Open
Abstract
PURPOSE Preoperative magnetic resonance imaging (MRI) after breast cancer diagnosis is increasingly used to improve locoregional staging, particularly among women with dense breasts, extensive ductal carcinoma in situ, and lobular histology. The goals of this study were to (1) assess whether use of preoperative MRI varies by race and insurance type; and (2) determine whether preoperative MRI is associated with downstream surgical management. MATERIALS AND METHODS We performed a retrospective cohort study of women with stage 0-III breast cancer who were treated with surgical resection within our academic health system (2016-2019). Patients were categorized by race and insurance type. The primary outcome was receipt of preoperative MRI. Secondary outcomes included surgery extent (lumpectomy v mastectomy) and receipt of a second operation. RESULTS A total of 1,410 women (27% Black, 73% White; 67% private insurance, 26% Medicare, 6% Medicaid) were included. Black patients were significantly less likely to undergo preoperative MRI than White patients (odds ratio [OR], 0.54 [95% CI, 0.38 to 0.76]; P < .001). There was no association between insurance type and preoperative MRI (Medicare v private: OR, 0.77 [95% CI, 0.52 to 1.15]; P = .208; Medicaid v private: OR, 0.67 [95% CI, 0.36 to 1.25]; P = .210). White patients who underwent preoperative MRI were less likely to undergo lumpectomy versus those who did not (OR, 0.53 [95% CI, 0.37 to 0.76]; P < .001). Likelihood of re-excision was lower for Black women who had undergone MRI versus those who had not (OR, 0.43 [95% CI, 0.20 to 0.93]; P = .031). CONCLUSION Black patients were less likely than White patients to undergo preoperative MRI, yet Black women who underwent MRI were less likely to require re-excision. Standardizing preoperative MRI use may mitigate provider- and system-level biases and promote more equitable care.
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Affiliation(s)
- Sara P Ginzberg
- Department of Surgery, University of Pennsylvania Health System, Philadelphia, PA
- Penn Center for Cancer Care Innovation, University of Pennsylvania, Philadelphia, PA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
| | - Connor B Grady
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Oluwadamilola M Fayanju
- Department of Surgery, University of Pennsylvania Health System, Philadelphia, PA
- Penn Center for Cancer Care Innovation, University of Pennsylvania, Philadelphia, PA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Rena Rowan Breast Center, Penn Medicine, Philadelphia, PA
| | - Christine E Edmonds
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Radiology, University of Pennsylvania Health System, Philadelphia, PA
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Huck LC, Bode M, Zanderigo E, Wilpert C, Raaff V, Dethlefsen E, Wenkel E, Kuhl CK. Dedicated Photon-Counting CT for Detection and Classification of Microcalcifications: An Intraindividual Comparison With Digital Breast Tomosynthesis. Invest Radiol 2024:00004424-990000000-00226. [PMID: 38923436 DOI: 10.1097/rli.0000000000001097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Abstract
OBJECTIVES Clinical experience regarding the use of dedicated photon-counting breast CT (PC-BCT) for diagnosis of breast microcalcifications is scarce. This study systematically compares the detection and classification of breast microcalcifications using a dedicated breast photon-counting CT, especially designed for examining the breast, in comparison with digital breast tomosynthesis (DBT). MATERIALS AND METHODS This is a prospective intraindividual study on women with DBT screening-detected BI-RADS-4/-5 microcalcifications who underwent PC-BCT before biopsy. PC-BCT images were reconstructed with a noninterpolated spatial resolution of 0.15 × 0.15 × 0.15 mm (reconstruction mode 1 [RM-1]) and with 0.3 × 0.3 × 0.3 mm (reconstruction mode 2 [RM-2]), plus thin-slab maximum intensity projection (MIP) reconstructions. Two radiologists independently rated the detection of microcalcifications in direct comparison with DBT on a 5-point scale. The distribution and morphology of microcalcifications were then rated according to BI-RADS. The size of the smallest discernible microcalcification particle was measured. For PC-BCT, the average glandular dose was determined by Monte Carlo simulations; for DBT, the information provided by the DBT system was used. RESULTS Between September 2022 and July 2023, 22 participants (mean age, 61; range, 42-85 years) with microcalcifications (16 malignant; 6 benign) were included. In 2/22 with microcalcifications in the posterior region, microcalcifications were not detectable on PC-BCT, likely because they were not included in the PC-BCT volume. In the remaining 20 participants, microcalcifications were detectable. With high between-reader agreement (κ > 0.8), conspicuity of microcalcifications was rated similar for DBT and MIPs of RM-1 (mean, 4.83 ± 0.38 vs 4.86 ± 0.35) (P = 0.66), but was significantly lower (P < 0.05) for the remaining PC-BCT reconstructions: 2.11 ± 0.92 (RM-2), 2.64 ± 0.80 (MIPs of RM-2), and 3.50 ± 1.23 (RM-1). Identical distribution qualifiers were assigned for PC-BCT and DBT in 18/20 participants, with excellent agreement (κ = 0.91), whereas identical morphologic qualifiers were assigned in only 5/20, with poor agreement (κ = 0.44). The median size of smallest discernible microcalcification particle was 0.2 versus 0.6 versus 1.1 mm in DBT versus RM-1 versus RM-2 (P < 0.001), likely due to blooming effects. Average glandular dose was 7.04 mGy (PC-BCT) versus 6.88 mGy (DBT) (P = 0.67). CONCLUSIONS PC-BCT allows reliable detection of in-breast microcalcifications as long as they are not located in the posterior part of the breast and allows assessment of their distribution, but not of their individual morphology.
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Affiliation(s)
- Luisa Charlotte Huck
- From the Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany (L.C.H., M.B., E.Z., C.W., V.R., E.D., C.K.K.); Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany (C.W.); Department of Radiology, University Hospital Erlangen, Erlangen, Germany (E.W.); and Department of Radiology, Radiology München, München, Germany (E.W.)
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10
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Faheem M, Tam HZ, Nougom M, Suaris T, Jahan N, Lloyd T, Johnson L, Aggarwal S, Ullah M, Thompson EW, Brentnall AR. Role of Supplemental Breast MRI in Screening Women with Mammographically Dense Breasts: A Systematic Review and Meta-analysis. JOURNAL OF BREAST IMAGING 2024:wbae019. [PMID: 38912622 DOI: 10.1093/jbi/wbae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Indexed: 06/25/2024]
Abstract
BACKGROUND High mammographic density increases breast cancer risk and reduces mammographic sensitivity. We reviewed evidence on accuracy of supplemental MRI for women with dense breasts at average or increased risk. METHODS PubMed and Embase were searched 1995-2022. Articles were included if women received breast MRI following 2D or tomosynthesis mammography. Risk of bias was assessed using QUADAS-2. Analysis used independent studies from the articles. Fixed-effect meta-analytic summaries were estimated for predefined groups (PROSPERO: 230277). RESULTS Eighteen primary research articles (24 studies) were identified in women aged 19-87 years. Breast density was heterogeneously or extremely dense (BI-RADS C/D) in 15/18 articles and extremely dense (BI-RADS D) in 3/18 articles. Twelve of 18 articles reported on increased-risk populations. Following 21 440 negative mammographic examinations, 288/320 cancers were detected by MRI. Substantial variation was observed between studies in MRI cancer detection rate, partly associated with prevalent vs incident MRI exams (prevalent: 16.6/1000 exams, 12 studies; incident: 6.8/1000 exams, 7 studies). MRI had high sensitivity for mammographically occult cancer (20 studies with at least 1-year follow-up). In 5/18 articles with sufficient data to estimate relative MRI detection rate, approximately 2 in 3 cancers were detected by MRI (66.3%, 95% CI, 56.3%-75.5%) but not mammography. Positive predictive value was higher for more recent studies. Risk of bias was low in most studies. CONCLUSION Supplemental breast MRI following negative mammography in women with dense breasts has breast cancer detection rates of ~16.6/1000 at prevalent and ~6.8/1000 at incident MRI exams, considering both high and average risk settings.
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Affiliation(s)
- Michael Faheem
- Department of Breast Surgery, Barts Health NHS Trust, London, UK
| | - Hui Zhen Tam
- Wolfson Institute of Population Health, Centre for Evaluation and Methods, Queen Mary University of London, London, UK
| | - Magd Nougom
- Department of Breast Surgery, Barts Health NHS Trust, London, UK
| | - Tamara Suaris
- Department of Breast Radiology, Barts Health NHS Trust, London, UK
| | - Noor Jahan
- Department of Breast Radiology, Barts Health NHS Trust, London, UK
| | - Thomas Lloyd
- Department of Radiology, Princess Alexandra Hospital, Brisbane, Australia
| | - Laura Johnson
- Department of Breast Surgery, Barts Health NHS Trust, London, UK
| | - Shweta Aggarwal
- Department of Breast Surgery, Barts Health NHS Trust, London, UK
| | - MdZaker Ullah
- Department of Breast Surgery, Barts Health NHS Trust, London, UK
| | - Erik W Thompson
- Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Australia
| | - Adam R Brentnall
- Wolfson Institute of Population Health, Centre for Evaluation and Methods, Queen Mary University of London, London, UK
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11
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Keupers M, Woussen S, Postema S, Westerlinck H, Houbrechts K, Marshall N, Wildiers H, Cockmartin L, Bosmans H, Van Ongeval C. Limited impact of adding digital breast tomosynthesis to full field digital mammography in an elevated breast cancer risk population. Eur J Radiol 2024; 177:111540. [PMID: 38852327 DOI: 10.1016/j.ejrad.2024.111540] [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: 08/31/2023] [Revised: 05/16/2024] [Accepted: 05/28/2024] [Indexed: 06/11/2024]
Abstract
PURPOSE To investigate the impact of adding digital breast tomosynthesis (DBT) to full field digital mammography (FFDM) in screening asymptomatic women with an elevated breast cancer life time risk (BCLTR) but without known genetic mutation. METHODS This IRB-approved single-institution multi-reader study on prospectively acquired FFDM + DBT images included 429 asymptomatic women (39-69y) with an elevated BC risk on their request form. The BCLTR was calculated for each patient using the IBISrisk calculator v8.0b. The screening protocol and reader study consisted of 4-view FFDM + DBT, which were read by four independent radiologists using the BI-RADS lexicon. Standard of care (SOC) included ultrasound (US) and magnetic resonance imaging (MRI) for women with > 30 % BCLTR. Breast cancer detection rate (BCDR), sensitivity and positive predictive value were assessed for FFDM and FFDM + DBT and detection outcomes were compared with McNemar-test. RESULTS In total 7/429 women in this clinically elevated breast cancer risk group were diagnosed with BC using SOC (BCDR 16.3/1000) of which 4 were detected with FFDM. Supplemental DBT did not detect additional cancers and BCDR was the same for FFDM vs FFDM + DBT (9.3/1000, McNemar p = 1). Moderate inter-reader agreement for diagnostic BI-RADS score was found for both study arms (ICC for FFDM and FFDM + DBT was 0.43, resp. 0.46). CONCLUSION In this single institution study, supplemental screening with DBT in addition to standard FFDM did not increase BCDR in this higher-than-average BC risk group, objectively documented using the IBISrisk calculator.
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Affiliation(s)
- Machteld Keupers
- Department of Radiology, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium; Multidisciplinary Breast, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Sofie Woussen
- Department of Radiology, AZ Groeninge, President Kennedylaan 4, 8500 Kortrijk, Belgium.
| | - Sandra Postema
- Department of Radiology, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Hélène Westerlinck
- Department of Radiology, AZ Diest, Statiestraat 65, 3290 Diest, Belgium.
| | - Katrien Houbrechts
- Department of Medical Physics, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Nicholas Marshall
- Department of Medical Physics, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Hans Wildiers
- Multidisciplinary Breast, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Lesley Cockmartin
- Department of Medical Physics, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Hilde Bosmans
- Department of Medical Physics, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Chantal Van Ongeval
- Department of Radiology, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium; Multidisciplinary Breast, University Hospitals KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
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12
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Niell BL, Jochelson MS, Amir T, Brown A, Adamson M, Baron P, Bennett DL, Chetlen A, Dayaratna S, Freer PE, Ivansco LK, Klein KA, Malak SF, Mehta TS, Moy L, Neal CH, Newell MS, Richman IB, Schonberg M, Small W, Ulaner GA, Slanetz PJ. ACR Appropriateness Criteria® Female Breast Cancer Screening: 2023 Update. J Am Coll Radiol 2024; 21:S126-S143. [PMID: 38823941 DOI: 10.1016/j.jacr.2024.02.019] [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: 02/20/2024] [Accepted: 02/28/2024] [Indexed: 06/03/2024]
Abstract
Early detection of breast cancer from regular screening substantially reduces breast cancer mortality and morbidity. Multiple different imaging modalities may be used to screen for breast cancer. Screening recommendations differ based on an individual's risk of developing breast cancer. Numerous factors contribute to breast cancer risk, which is frequently divided into three major categories: average, intermediate, and high risk. For patients assigned female at birth with native breast tissue, mammography and digital breast tomosynthesis are the recommended method for breast cancer screening in all risk categories. In addition to the recommendation of mammography and digital breast tomosynthesis in high-risk patients, screening with breast MRI is recommended. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
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Affiliation(s)
- Bethany L Niell
- Panel Chair, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
| | | | - Tali Amir
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ann Brown
- Panel Vice Chair, University of Cincinnati, Cincinnati, Ohio
| | - Megan Adamson
- Clinica Family Health, Lafayette, Colorado; American Academy of Family Physicians
| | - Paul Baron
- Lenox Hill Hospital, Northwell Health, New York, New York; American College of Surgeons
| | | | - Alison Chetlen
- Penn State Health Hershey Medical Center, Hershey, Pennsylvania
| | - Sandra Dayaratna
- Thomas Jefferson University Hospital, Philadelphia, Pennsylvania; American College of Obstetricians and Gynecologists
| | | | | | | | | | - Tejas S Mehta
- UMass Memorial Medical Center/UMass Chan Medical School, Worcester, Massachusetts
| | - Linda Moy
- NYU Clinical Cancer Center, New York, New York
| | | | - Mary S Newell
- Emory University Hospital, Atlanta, Georgia; RADS Committee
| | - Ilana B Richman
- Yale School of Medicine, New Haven, Connecticut; Society of General Internal Medicine
| | - Mara Schonberg
- Harvard Medical School, Boston, Massachusetts; American Geriatrics Society
| | - William Small
- Loyola University Chicago, Stritch School of Medicine, Department of Radiation Oncology, Cardinal Bernardin Cancer Center, Maywood, Illinois; Commission on Radiation Oncology
| | - Gary A Ulaner
- Hoag Family Cancer Institute, Newport Beach, California; University of Southern California, Los Angeles, California; Commission on Nuclear Medicine and Molecular Imaging
| | - Priscilla J Slanetz
- Specialty Chair, Boston University School of Medicine, Boston, Massachusetts
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13
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Berg WA. USPSTF Breast Cancer Screening Guidelines Do Not Go Far Enough. JAMA Oncol 2024; 10:706-708. [PMID: 38687475 DOI: 10.1001/jamaoncol.2024.0905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Affiliation(s)
- Wendie A Berg
- Department of Radiology, UPMC Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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14
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Jones LI, Marshall A, Geach R, Elangovan P, O'Flynn E, Timlin T, McKeown-Keegan S, Rose J, Vinnicombe S, Taylor-Phillips S, Halling-Brown M, Dunn JA. Optimising the diagnostic accuracy of First post-contrAst SubtracTed breast MRI (FAST MRI) through interpretation-training: a multicentre e-learning study, mapping the learning curve of NHS Breast Screening Programme (NHSBSP) mammogram readers using an enriched dataset. Breast Cancer Res 2024; 26:85. [PMID: 38807211 PMCID: PMC11134713 DOI: 10.1186/s13058-024-01846-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 05/18/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Abbreviated breast MRI (FAST MRI) is being introduced into clinical practice to screen women with mammographically dense breasts or with a personal history of breast cancer. This study aimed to optimise diagnostic accuracy through the adaptation of interpretation-training. METHODS A FAST MRI interpretation-training programme (short presentations and guided hands-on workstation teaching) was adapted to provide additional training during the assessment task (interpretation of an enriched dataset of 125 FAST MRI scans) by giving readers feedback about the true outcome of each scan immediately after each scan was interpreted (formative assessment). Reader interaction with the FAST MRI scans used developed software (RiViewer) that recorded reader opinions and reading times for each scan. The training programme was additionally adapted for remote e-learning delivery. STUDY DESIGN Prospective, blinded interpretation of an enriched dataset by multiple readers. RESULTS 43 mammogram readers completed the training, 22 who interpreted breast MRI in their clinical role (Group 1) and 21 who did not (Group 2). Overall sensitivity was 83% (95%CI 81-84%; 1994/2408), specificity 94% (95%CI 93-94%; 7806/8338), readers' agreement with the true outcome kappa = 0.75 (95%CI 0.74-0.77) and diagnostic odds ratio = 70.67 (95%CI 61.59-81.09). Group 1 readers showed similar sensitivity (84%) to Group 2 (82% p = 0.14), but slightly higher specificity (94% v. 93%, p = 0.001). Concordance with the ground truth increased significantly with the number of FAST MRI scans read through the formative assessment task (p = 0.002) but by differing amounts depending on whether or not a reader had previously attended FAST MRI training (interaction p = 0.02). Concordance with the ground truth was significantly associated with reading batch size (p = 0.02), tending to worsen when more than 50 scans were read per batch. Group 1 took a median of 56 seconds (range 8-47,466) to interpret each FAST MRI scan compared with 78 (14-22,830, p < 0.0001) for Group 2. CONCLUSIONS Provision of immediate feedback to mammogram readers during the assessment test set reading task increased specificity for FAST MRI interpretation and achieved high diagnostic accuracy. Optimal reading-batch size for FAST MRI was 50 reads per batch. Trial registration (25/09/2019): ISRCTN16624917.
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Affiliation(s)
- Lyn I Jones
- North Bristol NHS Trust, Southmead Hospital, Southmead Road, Westbury on Trym, Bristol, BS10 5NB, UK.
| | - Andrea Marshall
- Warwick Clinical Trials Unit, University of Warwick, Coventry, CV4 7AL, UK
| | - Rebecca Geach
- North Bristol NHS Trust, Southmead Hospital, Southmead Road, Westbury on Trym, Bristol, BS10 5NB, UK
| | - Premkumar Elangovan
- Scientific Computing Department, Royal Surrey NHS Foundation Trust, Guildford, Surrey, GU2 7XX, UK
| | - Elizabeth O'Flynn
- St George's University Hospitals Foundation Trust, London, SW17 0QT, UK
| | - Tony Timlin
- North Bristol NHS Trust, Southmead Hospital, Southmead Road, Westbury on Trym, Bristol, BS10 5NB, UK
| | - Sadie McKeown-Keegan
- North Bristol NHS Trust, Southmead Hospital, Southmead Road, Westbury on Trym, Bristol, BS10 5NB, UK
| | - Janice Rose
- Independent Cancer Patients' Voice, London, EC1R 0LL, UK
| | - Sarah Vinnicombe
- Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, GL53 7AS, UK
| | | | - Mark Halling-Brown
- Scientific Computing Department, Royal Surrey NHS Foundation Trust, Guildford, Surrey, GU2 7XX, UK
| | - Janet A Dunn
- Warwick Clinical Trials Unit, University of Warwick, Coventry, CV4 7AL, UK
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15
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Hayward JH, Lee AY, Sickles EA, Ray KM. Prevalent vs Incident Screen: Why Does It Matter? JOURNAL OF BREAST IMAGING 2024; 6:232-237. [PMID: 38190264 DOI: 10.1093/jbi/wbad096] [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: 08/01/2023] [Indexed: 01/10/2024]
Abstract
There are important differences in the performance and outcomes of breast cancer screening in the prevalent compared to the incident screening rounds. The prevalent screen is the first screening examination using a particular imaging technique and identifies pre-existing, undiagnosed cancers in the population. The incident screen is any subsequent screening examination using that technique. It is expected to identify fewer cancers than the prevalent screen because it captures only those cancers that have become detectable since the prior screening examination. The higher cancer detection rate at prevalent relative to incident screening should be taken into account when analyzing the medical audit and effectiveness of new screening technologies.
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Affiliation(s)
- Jessica H Hayward
- Department of Radiology and Biomedical Imaging, Division of Breast Imaging, University of California, San Francisco, CA, USA
| | - Amie Y Lee
- Department of Radiology and Biomedical Imaging, Division of Breast Imaging, University of California, San Francisco, CA, USA
| | - Edward A Sickles
- Department of Radiology and Biomedical Imaging, Division of Breast Imaging, University of California, San Francisco, CA, USA
| | - Kimberly M Ray
- Department of Radiology and Biomedical Imaging, Division of Breast Imaging, University of California, San Francisco, CA, USA
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16
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Klassen CL, Viers LD, Ghosh K. Following the High-Risk Patient: Breast Cancer Risk-Based Screening. Ann Surg Oncol 2024; 31:3154-3159. [PMID: 38302622 DOI: 10.1245/s10434-024-14957-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 01/11/2024] [Indexed: 02/03/2024]
Abstract
Breast cancer (BC) is the most common cancer occurring in women in the USA today, and accounts for more than 40,000 deaths annually (Giaquinto in CA Cancer J Clin 72: 524-541, 2022). While breast cancer survival has improved over the past decades, incidence has increased, and diagnoses are being made at younger ages. This emphasizes the importance of risk evaluation, accurate prediction, and effective mitigation and risk reduction strategies. Enhanced screening can help detect cancers at an earlier stage, thus improving morbidity and mortality. This review addresses the recognition of women at high-risk for BC and monitoring strategies for those at high risk.
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Affiliation(s)
- Christine L Klassen
- Mayo School of Graduate Medical Education, Mayo Clinic- Rochester, Rochester, MN, USA.
| | - Lyndsay D Viers
- Mayo School of Graduate Medical Education, Mayo Clinic- Rochester, Rochester, MN, USA
| | - Karthik Ghosh
- Mayo School of Graduate Medical Education, Mayo Clinic- Rochester, Rochester, MN, USA
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17
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Endrikat J, Gutberlet M, Barkhausen J, Schöckel L, Bhatti A, Harz C, Hoffmann KT. Clinical Efficacy of Gadobutrol: Review of Over 25 Years of Use Exceeding 100 Million Administrations. Invest Radiol 2024; 59:345-358. [PMID: 37972293 DOI: 10.1097/rli.0000000000001041] [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: 11/19/2023]
Abstract
BACKGROUND Gadobutrol has been administered more than 100 million times worldwide, since February 1998, that is, over the last 25 years. Numerous clinical studies in a broad range of indications document the long-term experience with gadobutrol. OBJECTIVE The aim of this study was to provide a literature-based overview on gadobutrol's efficacy in 9 approved indications and use in children. MATERIALS AND METHODS Efficacy results in patients of all age groups including sensitivity, specificity, accuracy, and positive/negative predictive values were identified by a systematic literature search on Embase until December 31, 2022. Nine approved indications were considered: central nervous system (CNS), magnetic resonance angiography (MRA), breast, heart, prostate, kidney, liver, musculoskeletal, whole body, and various indications in children. RESULTS Sixty-five publications (10 phase III, 2 phase IV, 53 investigator-initiated studies) reported diagnostic efficacy results obtained from 7806 patients including 271 children, at 369 centers worldwide. Indication-specific sensitivity ranges were 59%-98% (CNS), 53%-100% (MRA), 80%-100% (breast), 64%-90% (heart), 64%-96% (prostate), 71-85 (kidney), 79%-100% (liver), 53%-98% (musculoskeletal), and 78%-100% (children). Indication-specific specificity ranges were 75%-100% (CNS), 64%-99% (MRA), 58%-98% (breast), and 47%-100% (heart). CONCLUSIONS The evaluated body of evidence, consisting of 65 studies with 7806 patients, including 271 children and 7535 adults, showed that gadobutrol is an efficacious magnetic resonance imaging contrast agent for all age groups in various approved indications throughout the whole body.
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Affiliation(s)
- Jan Endrikat
- From the Radiology, Bayer AG, Berlin, Germany (J.E., L.S., C.H.); Department of Gynecology, Obstetrics, and Reproductive Medicine, University Medical School of Saarland, Homburg/Saar, Germany (J.E.); Department of Diagnostic and Interventional Radiology, University of Leipzig, Heart Center, Leipzig, Germany (M.G.); Department of Radiology and Nuclear Medicine, University Hospital Schleswig Holstein-Campus Luebeck, Luebeck, Germany (J.B.); Bayer US LLC, Benefit-Risk Management Pharmacovigilance, Whippany, NJ (A.B.); and Department of Neuroradiology, University of Leipzig, Leipzig, Germany (K.-T.H.)
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18
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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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19
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Marcon M, Fuchsjäger MH, Clauser P, Mann RM. ESR Essentials: screening for breast cancer - general recommendations by EUSOBI. Eur Radiol 2024:10.1007/s00330-024-10740-5. [PMID: 38656711 DOI: 10.1007/s00330-024-10740-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 02/13/2024] [Accepted: 02/17/2024] [Indexed: 04/26/2024]
Abstract
Breast cancer is the most frequently diagnosed cancer in women accounting for about 30% of all new cancer cases and the incidence is constantly increasing. Implementation of mammographic screening has contributed to a reduction in breast cancer mortality of at least 20% over the last 30 years. Screening programs usually include all women irrespective of their risk of developing breast cancer and with age being the only determining factor. This approach has some recognized limitations, including underdiagnosis, false positive cases, and overdiagnosis. Indeed, breast cancer remains a major cause of cancer-related deaths in women undergoing cancer screening. Supplemental imaging modalities, including digital breast tomosynthesis, ultrasound, breast MRI, and, more recently, contrast-enhanced mammography, are available and have already shown potential to further increase the diagnostic performances. Use of breast MRI is recommended in high-risk women and women with extremely dense breasts. Artificial intelligence has also shown promising results to support risk categorization and interval cancer reduction. The implementation of a risk-stratified approach instead of a "one-size-fits-all" approach may help to improve the benefit-to-harm ratio as well as the cost-effectiveness of breast cancer screening. KEY POINTS: Regular mammography should still be considered the mainstay of the breast cancer screening. High-risk women and women with extremely dense breast tissue should use MRI for supplemental screening or US if MRI is not available. Women need to participate actively in the decision to undergo personalized screening. KEY RECOMMENDATIONS: Mammography is an effective imaging tool to diagnose breast cancer in an early stage and to reduce breast cancer mortality (evidence level I). Until more evidence is available to move to a personalized approach, regular mammography should be considered the mainstay of the breast cancer screening. High-risk women should start screening earlier; first with yearly breast MRI which can be supplemented by yearly or biennial mammography starting at 35-40 years old (evidence level I). Breast MRI screening should be also offered to women with extremely dense breasts (evidence level I). If MRI is not available, ultrasound can be performed as an alternative, although the added value of supplemental ultrasound regarding cancer detection remains limited. Individual screening recommendations should be made through a shared decision-making process between women and physicians.
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Affiliation(s)
- Magda Marcon
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
- Institute of Radiology, Hospital Lachen, Oberdorfstrasse 41, 8853, Lachen, Switzerland.
| | - Michael H Fuchsjäger
- Division of General Radiology, Department of Radiology, Medical University Graz, Auenbruggerplatz 9, 8036, Graz, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Research Group: Molecular and Gender Imaging, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Wien, Austria
| | - Ritse M Mann
- Department of Diagnostic Imaging, Radboud University Medical Centre, Geert Grotteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
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20
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Lo Gullo R, Brunekreef J, Marcus E, Han LK, Eskreis-Winkler S, Thakur SB, Mann R, Groot Lipman K, Teuwen J, Pinker K. AI Applications to Breast MRI: Today and Tomorrow. J Magn Reson Imaging 2024. [PMID: 38581127 DOI: 10.1002/jmri.29358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/07/2024] [Accepted: 03/09/2024] [Indexed: 04/08/2024] Open
Abstract
In breast imaging, there is an unrelenting increase in the demand for breast imaging services, partly explained by continuous expanding imaging indications in breast diagnosis and treatment. As the human workforce providing these services is not growing at the same rate, the implementation of artificial intelligence (AI) in breast imaging has gained significant momentum to maximize workflow efficiency and increase productivity while concurrently improving diagnostic accuracy and patient outcomes. Thus far, the implementation of AI in breast imaging is at the most advanced stage with mammography and digital breast tomosynthesis techniques, followed by ultrasound, whereas the implementation of AI in breast magnetic resonance imaging (MRI) is not moving along as rapidly due to the complexity of MRI examinations and fewer available dataset. Nevertheless, there is persisting interest in AI-enhanced breast MRI applications, even as the use of and indications of breast MRI continue to expand. This review presents an overview of the basic concepts of AI imaging analysis and subsequently reviews the use cases for AI-enhanced MRI interpretation, that is, breast MRI triaging and lesion detection, lesion classification, prediction of treatment response, risk assessment, and image quality. Finally, it provides an outlook on the barriers and facilitators for the adoption of AI in breast MRI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Roberto Lo Gullo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
| | - Joren Brunekreef
- AI for Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Eric Marcus
- AI for Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Lynn K Han
- Weill Cornell Medical College, New York-Presbyterian Hospital, New York City, New York, USA
| | - Sarah Eskreis-Winkler
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
| | - Sunitha B Thakur
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
| | - Ritse Mann
- AI for Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Kevin Groot Lipman
- AI for Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jonas Teuwen
- AI for Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Katja Pinker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
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21
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Shen S, Koonjoo N, Longarino FK, Lamb LR, Villa Camacho JC, Hornung TPP, Ogier SE, Yan S, Bortfeld TR, Saksena MA, Keenan KE, Rosen MS. Breast imaging with an ultra-low field MRI scanner: a pilot study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.01.24305081. [PMID: 38633799 PMCID: PMC11023648 DOI: 10.1101/2024.04.01.24305081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Breast cancer screening is necessary to reduce mortality due to undetected breast cancer. Current methods have limitations, and as a result many women forego regular screening. Magnetic resonance imaging (MRI) can overcome most of these limitations, but access to conventional MRI is not widely available for routine annual screening. Here, we used an MRI scanner operating at ultra-low field (ULF) to image the left breasts of 11 women (mean age, 35 years ±13 years) in the prone position. Three breast radiologists reviewed the imaging and were able to discern the breast outline and distinguish fibroglandular tissue (FGT) from intramammary adipose tissue. Additionally, the expert readers agreed on their assessment of the breast tissue pattern including fatty, scattered FGT, heterogeneous FGT, and extreme FGT. This preliminary work demonstrates that ULF breast MRI is feasible and may be a potential option for comfortable, widely deployable, and low-cost breast cancer diagnosis and screening.
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22
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Ramli Hamid MT, Ab Mumin N, Abdul Hamid S, Ahmad Saman MS, Rahmat K. Abbreviated breast magnetic resonance imaging (MRI) or digital breast tomosynthesis for breast cancer detection in dense breasts? A retrospective preliminary study with comparable results. Clin Radiol 2024; 79:e524-e531. [PMID: 38267349 DOI: 10.1016/j.crad.2023.12.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 11/08/2023] [Accepted: 12/19/2023] [Indexed: 01/26/2024]
Abstract
AIM To compare the diagnostic performance of abbreviated breast magnetic resonance (AB-MR) imaging (MRI) and digital breast tomosynthesis (DBT) for breast cancer detection in Malaysian women with dense breasts, using histopathology as the reference standard. MATERIALS AND METHODS This was a single-centre cross-sectional study of 115 women with American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BIRADS) breast density C and D on DBT with breast lesions who underwent AB-MR from June 2018 to December 2021. AB-MR was performed on a 3 T MRI system with an imaging protocol consisting of three sequences: axial T1 fat-saturated unenhanced; axial first contrast-enhanced; and subtracted first contrast-enhanced with maximum intensity projection (MIP). DBT and AB-MR images were evaluated by two radiologists blinded to the histopathology and patient outcomes. Diagnostic accuracy (sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV]) was assessed. RESULT Of the 115 women, the mean age was 50.6 years. There were 48 (41.7%) Malay, 54 (47%) Chinese, and 12 (10.4%) Indian women. The majority (n=87, 75.7%) were from the diagnostic population. Sixty-one (53.1%) were premenopausal and 54 (46.9%) postmenopausal. Seventy-eight (72.4%) had an increased risk of developing breast cancer. Ninety-one (79.1%) women had density C and 24 (20.9%) had density D. There were 164 histopathology-proven lesions; 69 (42.1%) were malignant and 95 (57.9%) were benign. There were 62.8% (n=103/164) lesions detected at DBT. All the malignant lesions 100% (n=69) and 35.7% (n=34) of benign lesions were detected. Of the 61 lesions that were not detected, 46 (75.4%) were in density C, and 15 (24.6%) were in density D. The sensitivity, specificity, PPV, and NPV for DBT were 98.5%, 34.6%, 66.3%, and 94.7%, respectively. There were 65.2% (n=107/164) lesions detected on AB-MR, with 98.6% (n=68) malignant and 41.1% (39) benign lesions detected. The sensitivity, specificity, PPV, and NPV for AB-MR were 98.5%, 43.9%, 67.2%, and 96.2%, respectively. One malignant lesion (0.6%), which was a low-grade ductal carcinoma in-situ (DCIS), was missed on AB-MR. CONCLUSION The present findings suggest that both DBT and AB-MR have comparable effectiveness as an imaging method for detecting breast cancer and have high NPV for low-risk lesions in women with dense breasts.
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Affiliation(s)
- M T Ramli Hamid
- Department of Radiology, Faculty of Medicine University Teknologi MARA, Sungai Buloh, Selangor, Malaysia.
| | - N Ab Mumin
- Department of Radiology, Faculty of Medicine University Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - S Abdul Hamid
- Department of Radiology, Faculty of Medicine University Teknologi MARA, Sungai Buloh, Selangor, Malaysia.
| | - M S Ahmad Saman
- Department of Public Health, Faculty of Medicine, University Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - K Rahmat
- Department of Biomedical Imaging, University Malaya Research Imaging Centre, Kuala Lumpur, Malaysia
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23
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Kim JH, Kim SY, Cui C, Ji H, Yoen H, Cho N, Kim DH. Problem Solving MRI to Reduce False-Positive Biopsy Related to Breast US: Conductivity vs. DWI vs. Abbreviated Contrast-Enhanced MRI. J Magn Reson Imaging 2024; 59:1218-1228. [PMID: 37477575 DOI: 10.1002/jmri.28884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/21/2023] [Accepted: 06/21/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND While breast ultrasound (US) is a useful tool for diagnosing breast masses, it can entail false-positive biopsy results because of some overlapping features between benign and malignant breast masses and subjective interpretation. PURPOSE To evaluate the performance of conductivity imaging for reducing false-positive biopsy results related to breast US, as compared to diffusion-weighted imaging (DWI) and abbreviated MRI consisting of one pre- and one post-contrast T1-weighted imaging. STUDY TYPE Prospective. SUBJECTS Seventy-nine women (median age, 44 years) with 86 Breast Imaging Reporting and Data System (BI-RADS) category 4 masses as detected by breast US. FIELD STRENGTH/SEQUENCE 3-T, T2-weighted turbo spin echo sequence, DWI, and abbreviated contrast-enhanced MRI (T1-weighted gradient echo sequence). ASSESSMENT US-guided biopsy (reference standard) was obtained on the same day as MRI. The maximum and mean conductivity parameters from whole and single regions of interest (ROIs) were measured. Apparent diffusion coefficient (ADC) values were obtained from an area with the lowest signal within a lesion on the ADC map. The performance of conductivity, ADC, and abbreviated MRI for reducing false-positive biopsies was evaluated using the following criteria: lowest conductivity and highest ADC values among malignant breast lesions and BI-RADS categories 2 or 3 on abbreviated MRI. STATISTICAL TESTS One conductivity parameter with the maximum area under the curve (AUC) from receiver operating characteristics was selected. A P-value <0.05 was considered statistically significant. RESULTS US-guided biopsy revealed 65 benign lesions and 21 malignant lesions. The mean conductivity parameter of the single ROI method was selected (AUC = 0.74). Considering conductivity (≤0.10 S/m), ADC (≥1.60 × 10-3 mm2 /sec), and BI-RADS categories 2 or 3 reduced false-positive biopsies by 23% (15 of 65), 38% (25 of 65), and 43% (28 of 65), respectively, without missing malignant lesions. DATA CONCLUSION Conductivity imaging may show lower performance than DWI and abbreviated MRI in reducing unnecessary biopsies. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jun-Hyeong Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Soo-Yeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National College of Medicine, Seoul, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Chuanjiang Cui
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Hye Ji
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Heera Yoen
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Nariya Cho
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Radiology, Seoul National College of Medicine, Seoul, Republic of Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
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Coffey K, Berg WA, Dodelzon K, Jochelson MS, Mullen LA, Parikh JR, Hutcheson L, Grimm LJ. Breast Radiologists' Perceptions on the Detection and Management of Invasive Lobular Carcinoma: Most Agree Imaging Beyond Mammography Is Warranted. JOURNAL OF BREAST IMAGING 2024; 6:157-165. [PMID: 38340343 PMCID: PMC10983784 DOI: 10.1093/jbi/wbad112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Indexed: 02/12/2024]
Abstract
OBJECTIVE To determine breast radiologists' confidence in detecting invasive lobular carcinoma (ILC) on mammography and the perceived need for additional imaging in screening and preoperative settings. METHODS A 16-item anonymized survey was developed, and IRB exemption obtained, by the Society of Breast Imaging (SBI) Patient Care and Delivery Committee and the Lobular Breast Cancer Alliance. The survey was emailed to 2946 radiologist SBI members on February 15, 2023. The survey recorded demographics, perceived modality-specific sensitivity for ILC to the nearest decile, and opinions on diagnosing ILC in screening and staging imaging. Five-point Likert scales were used (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). RESULTS Response rate was 12.4% (366/2946). Perceived median (interquartile range) modality-specific sensitivities for ILC were MRI 90% (80-90), contrast-enhanced mammography 80% (70-90), molecular breast imaging 80% (60-90), digital breast tomosynthesis 70% (60-80), US 60% (50-80), and 2D mammography 50% (30-60). Only 25% (85/340) respondents were confident in detecting ILC on screening mammography in dense breasts, while 67% (229/343) were confident if breasts were nondense. Most agreed that supplemental screening is needed to detect ILC in women with dense breasts (272/344, 79%) or a personal history of ILC (248/341, 73%), with 34% (118/334) indicating that supplemental screening would also benefit women with nondense breasts. Most agreed that additional imaging is needed to evaluate extent of disease in women with newly diagnosed ILC, regardless of breast density (dense 320/329, 97%; nondense 263/329, 80%). CONCLUSION Most breast radiologists felt that additional imaging beyond mammography is needed to more confidently screen for and stage ILC.
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Affiliation(s)
- Kristen Coffey
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Wendie A Berg
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Maxine S Jochelson
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Lisa A Mullen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, MD, USA
| | - Jay R Parikh
- Division of Diagnostic Imaging, Department of Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Lars J Grimm
- Department of Radiology, Duke University, Durham, NC, USA
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Mundinger A, Mundinger C. Artificial Intelligence in Senology - Where Do We Stand and What Are the Future Horizons? Eur J Breast Health 2024; 20:73-80. [PMID: 38571686 PMCID: PMC10985572 DOI: 10.4274/ejbh.galenos.2024.2023-12-13] [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: 12/26/2023] [Accepted: 01/16/2024] [Indexed: 04/05/2024]
Abstract
Artificial Intelligence (AI) is defined as the simulation of human intelligence by a digital computer or robotic system and has become a hype in current conversations. A subcategory of AI is deep learning, which is based on complex artificial neural networks that mimic the principles of human synaptic plasticity and layered brain architectures, and uses large-scale data processing. AI-based image analysis in breast screening programmes has shown non-inferior sensitivity, reduces workload by up to 70% by pre-selecting normal cases, and reduces recall by 25% compared to human double reading. Natural language programs such as ChatGPT (OpenAI) achieve 80% and higher accuracy in advising and decision making compared to the gold standard: human judgement. This does not yet meet the necessary requirements for medical products in terms of patient safety. The main advantage of AI is that it can perform routine but complex tasks much faster and with fewer errors than humans. The main concerns in healthcare are the stability of AI systems, cybersecurity, liability and transparency. More widespread use of AI could affect human jobs in healthcare and increase technological dependency. AI in senology is just beginning to evolve towards better forms with improved properties. Responsible training of AI systems with meaningful raw data and scientific studies to analyse their performance in the real world are necessary to keep AI on track. To mitigate significant risks, it will be necessary to balance active promotion and development of quality-assured AI systems with careful regulation. AI regulation has only recently included in transnational legal frameworks, as the European Union's AI Act was the first comprehensive legal framework to be published, in December 2023. Unacceptable AI systems will be banned if they are deemed to pose a clear threat to people's fundamental rights. Using AI and combining it with human wisdom, empathy and affection will be the method of choice for further, fruitful development of tomorrow's senology.
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Affiliation(s)
- Alexander Mundinger
- Breast Imaging and Interventions; Breast Centre Osnabrück; FHH Niels-Stensen-Kliniken; Franziskus-Hospital Harderberg, Georgsmarienhütte, Germany
| | - Carolin Mundinger
- Department of Behavioural Biology, Institute for Neuro- and Behavioural Biology, University of Muenster, Muenster, Germany
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Camps-Herrero J, Pijnappel R, Balleyguier C. MR-contrast enhanced mammography (CEM) for follow-up of breast cancer patients: a "pros and cons" debate. Eur Radiol 2024:10.1007/s00330-024-10684-w. [PMID: 38488968 DOI: 10.1007/s00330-024-10684-w] [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: 08/10/2023] [Revised: 01/07/2024] [Accepted: 02/03/2024] [Indexed: 03/17/2024]
Abstract
Women with a personal history of breast cancer (PHBC) are at an increased risk of either a local recurrence or a new primary breast cancer. Thus, surveillance is essential for the detection of recurrent disease at the earliest possible stage, allowing for prompt treatment, and potentially improving overall survival. Nowadays, mammography follow-up is the only surveillance imaging technique recommended by international guidelines. Nevertheless, sensitivity of mammography is lower after breast cancer treatment, particularly during the first 5 years, due to increased density or post-treatment changes. Contrast-enhanced breast imaging techniques, such as MRI or contrast-enhanced mammography (CEM), are very sensitive to detect malignant enhancement, especially in dense breasts. This Special Report will provide arguments in favor of and against breast cancer follow-up with MRI or CEM, in a debate style between experts in Breast Imaging. Finally, the scientific points of pros and cons arguments will be summarized to help objectively decide the best follow-up strategy for women with a personal history of breast cancer. CLINICAL RELEVANCE STATEMENT: A personalized approach to follow-up imaging after conservative breast cancer treatment could optimize patient outcomes, using mammography as a baseline for most patients, and MRI or CEM selectively in patients with higher risks for a recurrence. KEY POINTS: • Women with a personal history of breast cancer are at an increased risk of either a local recurrence or a new primary breast cancer. • Breast cancer survivors may benefit from additional imaging with MRI/CEM, in case of increased risk of a second breast cancer, with dense breasts or a cancer diagnosis before age 50 years. • As survival after local recurrence seems to depend on the initial stage at diagnosis, imaging should be more focused on detecting tumors in the earliest stages.
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Affiliation(s)
| | - Ruud Pijnappel
- Department of Radiology, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Corinne Balleyguier
- Imaging Department, Gustave Roussy Cancer Campus, Villejuif, France.
- BIOMAPS, UMR 1281, Université Paris-Saclay, 94800, Villejuif, France.
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Yılmaz E, Güldoğan N, Ulus S, Türk EB, Mısır ME, Arslan A, Arıbal ME. Diagnostic value of synthetic diffusion-weighted imaging on breast magnetic resonance imaging assessment: comparison with conventional diffusion-weighted imaging. Diagn Interv Radiol 2024; 30:91-98. [PMID: 37888786 PMCID: PMC10916533 DOI: 10.4274/dir.2023.232466] [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: 08/21/2023] [Accepted: 10/22/2023] [Indexed: 10/28/2023]
Abstract
PURPOSE To compare images generated by synthetic diffusion-weighted imaging (sDWI) with those from conventional DWI in terms of their diagnostic performance in detecting breast lesions when performing breast magnetic resonance imaging (MRI). METHODS A total of 128 consecutive patients with 135 enhanced lesions who underwent dynamic MRI between 2018 and 2021 were included. The sDWI and DWI signals were compared by three radiologists with at least 10 years of experience in breast radiology. RESULTS Of the 82 malignant lesions, 91.5% were hyperintense on sDWI and 73.2% were hyperintense on DWI. Of the 53 benign lesions, 71.7% were isointense on sDWI and 37.7% were isointense on DWI. sDWI provides accurate signal intensity data with statistical significance compared with DWI (P < 0.05). The diagnostic performance of DWI and sDWI to differentiate malignant breast masses from benign masses was as follows: sensitivity 73.1% [95% confidence interval (CI): 62-82], specificity 37.7% (95% CI: 24-52); sensitivity 91.5% (95% CI: 83-96), specificity 71.7% (95% CI: 57-83), respectively. The diagnostic accuracy of DWI and sDWI was 59.2% and 83.7%, respectively. However, when the DWI images were evaluated with apparent diffusion coefficient mapping and compared with the sDWI images, the sensitivity was 92.68% (95% CI: 84-97) and the specificity was 79.25% (95% CI: 65-89) with no statistically significant difference. The inter-reader agreement was almost perfect (P < 0.001). CONCLUSION Synthetic DWI is superior to DWI for lesion visibility with no additional acquisition time and should be taken into consideration when conducting breast MRI scans. The evaluation of sDWI in routine MRI reporting will increase diagnostic accuracy.
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Affiliation(s)
- Ebru Yılmaz
- Acıbadem Altunizade Hospital Breast Center, Department of Radiology, İstanbul, Türkiye
| | - Nilgün Güldoğan
- Acıbadem Altunizade Hospital Breast Center, Department of Radiology, İstanbul, Türkiye
| | - Sıla Ulus
- Acıbadem Ataşehir Hospital, Department of Radiology, İstanbul, Türkiye
| | - Ebru Banu Türk
- Acıbadem Altunizade Hospital Breast Center, Department of Radiology, İstanbul, Türkiye
| | - Mustafa Enes Mısır
- Acıbadem Mehmet Ali Aydınlar University, Department of Radiology, İstanbul, Türkiye
| | - Aydan Arslan
- University of Health Sciences Türkiye, Ümraniye Training and Research Hospital, Clinic of Radiology, İstanbul, Türkiye
| | - Mustafa Erkin Arıbal
- Acıbadem Mehmet Ali Aydınlar University, Department of Radiology, İstanbul, Türkiye
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28
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Kuhl CK. Abbreviated Breast MRI: State of the Art. Radiology 2024; 310:e221822. [PMID: 38530181 DOI: 10.1148/radiol.221822] [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: 03/27/2024]
Abstract
Abbreviated MRI is an umbrella term, defined as a focused MRI examination tailored to answer a single specific clinical question. For abbreviated breast MRI, this question is: "Is there evidence of breast cancer?" Abbreviated MRI of the breast makes maximum use of the fact that the kinetics of breast cancers and of benign tissue differ most in the very early postcontrast phase; therefore, abbreviated breast MRI focuses on this period. The different published approaches to abbreviated MRI include the following three subtypes: (a) short protocols, consisting of a precontrast and either a single postcontrast acquisition (first postcontrast subtracted [FAST]) or a time-resolved series of postcontrast acquisitions with lower spatial resolution (ultrafast [UF]), obtained during the early postcontrast phase immediately after contrast agent injection; (b) abridged protocols, consisting of FAST or UF acquisitions plus selected additional pulse sequences; and (c) noncontrast protocols, where diffusion-weighted imaging replaces the contrast information. Abbreviated MRI was proposed to increase tolerability of and access to breast MRI as a screening tool. But its widening application now includes follow-up after breast cancer and even diagnostic assessment. This review defines the three subtypes of abbreviated MRI, highlighting the differences between the protocols and their clinical implications and summarizing the respective evidence on diagnostic accuracy and clinical utility.
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Affiliation(s)
- Christiane K Kuhl
- From the Department of Diagnostic and Interventional Radiology, University Hospital Aachen, RWTH Pauwelsstr 30, 52074 Aachen, Germany
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29
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Li Y, Zhang Y, Yu Q, He C, Yuan X. Intelligent scoring system based on dynamic optical breast imaging for early detection of breast cancer. BIOMEDICAL OPTICS EXPRESS 2024; 15:1515-1527. [PMID: 38495695 PMCID: PMC10942703 DOI: 10.1364/boe.515135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/06/2024] [Accepted: 01/31/2024] [Indexed: 03/19/2024]
Abstract
Early detection of breast cancer can significantly improve patient outcomes and five-year survival in clinical screening. Dynamic optical breast imaging (DOBI) technology reflects the blood oxygen metabolism level of tumors based on the theory of tumor neovascularization, which offers a technical possibility for early detection of breast cancer. In this paper, we propose an intelligent scoring system integrating DOBI features assessment and a malignancy score grading reporting system for early detection of breast cancer. Specifically, we build six intelligent feature definition models to depict characteristics of regions of interest (ROIs) from location, space, time and context separately. Similar to the breast imaging-reporting and data system (BI-RADS), we conclude the malignancy score grading reporting system to score and evaluate ROIs as follows: Malignant (≥ 80 score), Likely Malignant (60-80 score), Intermediate (35-60 score), Likely Benign (10-35 score), and Benign (<10 score). This system eliminates the influence of subjective physician judgments on the assessment of the malignant probability of ROIs. Extensive experiments on 352 Chinese patients demonstrate the effectiveness of the proposed system compared to state-of-the-art methods.
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Affiliation(s)
- Yaoyao Li
- Hangzhou Institute of Technology, Xidian University, Qiannong Dong Road No. 8, Hangzhou, Zhejiang, 311231, China
| | - Yipei Zhang
- Hangzhou Institute of Technology, Xidian University, Qiannong Dong Road No. 8, Hangzhou, Zhejiang, 311231, China
| | - Qiang Yu
- Hangzhou Institute of Technology, Xidian University, Qiannong Dong Road No. 8, Hangzhou, Zhejiang, 311231, China
| | - Chenglong He
- Hangzhou Institute of Technology, Xidian University, Qiannong Dong Road No. 8, Hangzhou, Zhejiang, 311231, China
| | - Xiguo Yuan
- Hangzhou Institute of Technology, Xidian University, Qiannong Dong Road No. 8, Hangzhou, Zhejiang, 311231, China
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Jing X, Dorrius MD, Zheng S, Wielema M, Oudkerk M, Sijens PE, van Ooijen PMA. Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks. Eur Radiol 2024; 34:2084-2092. [PMID: 37658141 PMCID: PMC10873226 DOI: 10.1007/s00330-023-10184-3] [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: 05/10/2023] [Revised: 06/20/2023] [Accepted: 07/21/2023] [Indexed: 09/03/2023]
Abstract
OBJECTIVES To develop a deep learning-based method for contrast-enhanced breast lesion detection in ultrafast screening MRI. MATERIALS AND METHODS A total of 837 breast MRI exams of 488 consecutive patients were included. Lesion's location was independently annotated in the maximum intensity projection (MIP) image of the last time-resolved angiography with stochastic trajectories (TWIST) sequence for each individual breast, resulting in 265 lesions (190 benign, 75 malignant) in 163 breasts (133 women). YOLOv5 models were fine-tuned using training sets containing the same number of MIP images with and without lesions. A long short-term memory (LSTM) network was employed to help reduce false positive predictions. The integrated system was then evaluated on test sets containing enriched uninvolved breasts during cross-validation to mimic the performance in a screening scenario. RESULTS In five-fold cross-validation, the YOLOv5x model showed a sensitivity of 0.95, 0.97, 0.98, and 0.99, with 0.125, 0.25, 0.5, and 1 false positive per breast, respectively. The LSTM network reduced 15.5% of the false positive prediction from the YOLO model, and the positive predictive value was increased from 0.22 to 0.25. CONCLUSIONS A fine-tuned YOLOv5x model can detect breast lesions on ultrafast MRI with high sensitivity in a screening population, and the output of the model could be further refined by an LSTM network to reduce the amount of false positive predictions. CLINICAL RELEVANCE STATEMENT The proposed integrated system would make the ultrafast MRI screening process more effective by assisting radiologists in prioritizing suspicious examinations and supporting the diagnostic workup. KEY POINTS • Deep convolutional neural networks could be utilized to automatically pinpoint breast lesions in screening MRI with high sensitivity. • False positive predictions significantly increased when the detection models were tested on highly unbalanced test sets with more normal scans. • Dynamic enhancement patterns of breast lesions during contrast inflow learned by the long short-term memory networks helped to reduce false positive predictions.
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Affiliation(s)
- Xueping Jing
- Department of Radiation Oncology, and Data Science Center in Health (DASH), Machine Learning Lab, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.
| | - Monique D Dorrius
- Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Sunyi Zheng
- School of Engineering, Artificial Intelligence and Biomedical Image Analysis Lab, Westlake University, No.18 Shilongshan, Road Cloud Town, Xihu District, Hangzhou, 310024, Zhejiang, China
| | - Mirjam Wielema
- Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Matthijs Oudkerk
- Faculty of Medical Sciences, University of Groningen, and Institute of Diagnostic Accuracy, Wiersmastraat 5, 9713 GH, Groningen, The Netherlands
| | - Paul E Sijens
- Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Peter M A van Ooijen
- Department of Radiation Oncology, and Data Science Center in Health (DASH), Machine Learning Lab, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
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Tian R, Lu G, Zhao N, Qian W, Ma H, Yang W. Constructing the Optimal Classification Model for Benign and Malignant Breast Tumors Based on Multifeature Analysis from Multimodal Images. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01036-7. [PMID: 38381383 DOI: 10.1007/s10278-024-01036-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 01/28/2024] [Accepted: 02/02/2024] [Indexed: 02/22/2024]
Abstract
The purpose of this study was to fuse conventional radiomic and deep features from digital breast tomosynthesis craniocaudal projection (DBT-CC) and ultrasound (US) images to establish a multimodal benign-malignant classification model and evaluate its clinical value. Data were obtained from a total of 487 patients at three centers, each of whom underwent DBT-CC and US examinations. A total of 322 patients from dataset 1 were used to construct the model, while 165 patients from datasets 2 and 3 formed the prospective testing cohort. Two radiologists with 10-20 years of work experience and three sonographers with 12-20 years of work experience semiautomatically segmented the lesions using ITK-SNAP software while considering the surrounding tissue. For the experiments, we extracted conventional radiomic and deep features from tumors from DBT-CCs and US images using PyRadiomics and Inception-v3. Additionally, we extracted conventional radiomic features from four peritumoral layers around the tumors via DBT-CC and US images. Features were fused separately from the intratumoral and peritumoral regions. For the models, we tested the SVM, KNN, decision tree, RF, XGBoost, and LightGBM classifiers. Early fusion and late fusion (ensemble and stacking) strategies were employed for feature fusion. Using the SVM classifier, stacking fusion of deep features and three peritumoral radiomic features from tumors in DBT-CC and US images achieved the optimal performance, with an accuracy and AUC of 0.953 and 0.959 [CI: 0.886-0.996], a sensitivity and specificity of 0.952 [CI: 0.888-0.992] and 0.955 [0.868-0.985], and a precision of 0.976. The experimental results indicate that the fusion model of deep features and peritumoral radiomic features from tumors in DBT-CC and US images shows promise in differentiating benign and malignant breast tumors.
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Affiliation(s)
- Ronghui Tian
- College of Medicine and Biological Information Engineering, Northeastern University, No. 195 Chuangxin Road, Hunnan District, Shenyang, 110819, Liaoning Province, China
| | - Guoxiu Lu
- College of Medicine and Biological Information Engineering, Northeastern University, No. 195 Chuangxin Road, Hunnan District, Shenyang, 110819, Liaoning Province, China
- Department of Nuclear Medicine, General Hospital of Northern Theatre Command, No. 83 Wenhua Road, Shenhe District, Shenyang, 110016, Liaoning Province, China
| | - Nannan Zhao
- Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, No. 44 Xiaoheyan Road, Dadong District, Shenyang, 110042, Liaoning Province, China
| | - Wei Qian
- College of Medicine and Biological Information Engineering, Northeastern University, No. 195 Chuangxin Road, Hunnan District, Shenyang, 110819, Liaoning Province, China
| | - He Ma
- College of Medicine and Biological Information Engineering, Northeastern University, No. 195 Chuangxin Road, Hunnan District, Shenyang, 110819, Liaoning Province, China
| | - Wei Yang
- Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, No. 44 Xiaoheyan Road, Dadong District, Shenyang, 110042, Liaoning Province, China.
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Ebaid NY, Assy MM, Eldin AMA. Diagnostic validity of abbreviated breast MRI in the diagnosis of breast cancer: a comparative study to the full breast MRI protocol using BI-RADS. Pol J Radiol 2024; 89:e80-e87. [PMID: 38510549 PMCID: PMC10953509 DOI: 10.5114/pjr.2024.135474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 01/25/2024] [Indexed: 03/22/2024] Open
Abstract
Purpose This work aimed to determine the diagnostic performance of the magnetic resonance imaging (MRI) breast abbreviated protocol (AP) in diagnosing malignant breast lesions using BI-RADS compared with the diagnostic accuracy of the full diagnostic protocol (FDP). Material and methods A prospective single-centre study was conducted. A total of 125 female patients with suspicious breast masses underwent MRI with the AP and the FDP. The images of AP and FDP were independently interpreted by 2 radiologists with 10 years of experience in breast imaging, and any disagreement was resolved with a third one. Using the histopathological examination as a reference test, the diagnostic effectiveness of both FDP and AP in breast cancer screening was calculated. ROC curve was utilised to estimate the optimal BI-RADS cut-off for prediction of malignancy. The difference in image interpretation time between both protocols was estimated using the Mann-Whitney test. Moreover, the inter-test agreement between both protocols was assessed using Cohen's κ test. Results The study included 83 malignant and 42 benign lesions. AP indicated a specificity, sensitivity, and accuracy of 90.5%, 96.4%, and 94.4%, while the FDP showed a specificity, sensitivity, and accuracy of 92.9%, 100%, and 97.6%, respectively. BI-RADS 3 category was the best cut-off for prediction of malignancy. There was a significant difference between both protocols concerning the interpretation time (p < 0.001). There was excellent agreement between both protocols, with a κ of 0.915. Conclusions Breast MRI AP may be employed instead of FDP to identify breast cancer with similar diagnostic performance. Moreover, it reduces the interpretation time and the scan cost.
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Affiliation(s)
- Noha Yahia Ebaid
- Department of Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Mostafa Mohamad Assy
- Department of Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Ahmed M. Alaa Eldin
- Department of Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt
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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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Mullen LA. Can digital breast tomosynthesis decrease interval cancers in a breast cancer screening program? Eur Radiol 2024:10.1007/s00330-024-10635-5. [PMID: 38319429 DOI: 10.1007/s00330-024-10635-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 01/14/2024] [Accepted: 01/20/2024] [Indexed: 02/07/2024]
Affiliation(s)
- Lisa A Mullen
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Suite 4120, 601 N. Caroline St., Baltimore, MD, 21287, USA.
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Chen L, Wu T, Fan R, Qian YS, Liu JF, Bai J, Zheng B, Liu XL, Zheng D, Du LT, Jiang GQ, Wang YC, Fan XT, Deng GH, Wang CY, Shen F, Hu HP, Zhang QZ, Ye YN, Zhang J, Gao YH, Xia J, Yan HD, Liang MF, Yu YL, Sun FM, Gao YJ, Sun J, Zhong CX, Wang Y, Wang H, Kong F, Chen JM, Wen H, Wu BM, Wang CX, Wu L, Hou JL, Wang HY. Cell-free DNA testing for early hepatocellular carcinoma surveillance. EBioMedicine 2024; 100:104962. [PMID: 38184937 PMCID: PMC10808903 DOI: 10.1016/j.ebiom.2023.104962] [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: 09/11/2023] [Revised: 12/17/2023] [Accepted: 12/24/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Liver cirrhosis (LC) is the highest risk factor for hepatocellular carcinoma (HCC) development worldwide. The efficacy of the guideline-recommended surveillance methods for patients with LC remains unpromising. METHODS A total of 4367 LCs not previously known to have HCC and 510 HCCs from 16 hospitals across 11 provinces of China were recruited in this multi-center, large-scale, cross-sectional study. Participants were divided into Stage Ⅰ cohort (510 HCCs and 2074 LCs) and Stage Ⅱ cohort (2293 LCs) according to their enrollment time and underwent Tri-phasic CT/enhanced MRI, US, AFP, and cell-free DNA (cfDNA). A screening model called PreCar Score was established based on five features of cfDNA using Stage Ⅰ cohort. Surveillance performance of PreCar Score alone or in combination with US/AFP was evaluated in Stage Ⅱ cohort. FINDINGS PreCar Score showed a significantly higher sensitivity for the detection of early/very early HCC (Barcelona stage A/0) in contrast to US (sensitivity of 51.32% [95% CI: 39.66%-62.84%] at 95.53% [95% CI: 94.62%-96.38%] specificity for PreCar Score; sensitivity of 23.68% [95% CI: 14.99%-35.07%] at 99.37% [95% CI: 98.91%-99.64%] specificity for US) (P < 0.01, Fisher's exact test). PreCar Score plus US further achieved a higher sensitivity of 60.53% at 95.08% specificity for early/very early HCC screening. INTERPRETATION Our study developed and validated a cfDNA-based screening tool (PreCar Score) for HCC in cohorts at high risk. The combination of PreCar Score and US can serve as a promising and practical strategy for routine HCC care. FUNDING A full list of funding bodies that contributed to this study can be found in Acknowledgments section.
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Affiliation(s)
- Lei Chen
- National Center of Liver Cancer, Navel Medical University, Shanghai, 210822, PR China; International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute/Hospital, Shanghai, 200438, PR China.
| | - Tong Wu
- National Center of Liver Cancer, Navel Medical University, Shanghai, 210822, PR China; Department of Radiation Oncology, General Hospital of Northern Theater Command, Shenyang, l10016, PR China
| | - Rong Fan
- Department of Infectious Diseases, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, PR China; Hepatology Unit, Shenzhen Hospital, Southern Medical University, Shenzhen, PR China
| | - Yun-Song Qian
- Hepatology Department, Ningbo Hwamei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, PR China
| | - Jing-Feng Liu
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, PR China
| | - Jian Bai
- Berry Oncology Corporation, Beijing, 100102, PR China
| | - Bo Zheng
- National Center of Liver Cancer, Navel Medical University, Shanghai, 210822, PR China; International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute/Hospital, Shanghai, 200438, PR China
| | - Xiao-Long Liu
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, PR China
| | - Dan Zheng
- Department of Gastroenterology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, PR China
| | - Lu-Tao Du
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Jinan 250033, Shandong, PR China; Shandong Provincial Clinical Medicine Research Center for Clinical Laboratory, Jinan, 250033, PR China
| | - Guo-Qing Jiang
- Department of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, 225001, PR China
| | - Ying-Chao Wang
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, PR China
| | - Xiao-Tang Fan
- Department of Hepatology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830000, PR China
| | - Guo-Hong Deng
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, PR China
| | - Chun-Ying Wang
- Xuzhou Infectious Diseases Hospital, Xuzhou, 221004, PR China
| | - Feng Shen
- Department of Hepatic Surgery IV, Eastern Hepatobiliary Surgery Institute, Second Military Medical University, Shanghai, 200438, PR China
| | - He-Ping Hu
- Department of Hepatobiliary Medicine, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai, 210822, PR China
| | | | - Yi-Nong Ye
- The Department of Infectious Disease, The First People's Hospital of Foshan, Foshan City, 528000, PR China
| | - Jing Zhang
- Berry Oncology Corporation, Beijing, 100102, PR China
| | - Yan-Hang Gao
- The First Hospital of Jilin University, Jilin, 130021, PR China
| | - Jie Xia
- Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, PR China
| | - Hua-Dong Yan
- Hepatology Department, Ningbo Hwamei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, PR China
| | - Min-Feng Liang
- The Department of Infectious Disease, The First People's Hospital of Foshan, Foshan City, 528000, PR China
| | - Yan-Long Yu
- Chifeng Clinical Medical School of Inner Mongolia Medical University, Chifeng, 024000, PR China
| | - Fu-Ming Sun
- Berry Oncology Corporation, Beijing, 100102, PR China
| | - Yu-Jing Gao
- Xuzhou Infectious Diseases Hospital, Xuzhou, 221004, PR China
| | - Jian Sun
- Department of Infectious Diseases, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, PR China
| | - Chun-Xiu Zhong
- Department of Infectious Diseases, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, PR China
| | - Yin Wang
- Berry Oncology Corporation, Beijing, 100102, PR China
| | - Hui Wang
- Department of Hepatobiliary Medicine, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai, 210822, PR China
| | - Fei Kong
- The First Hospital of Jilin University, Jilin, 130021, PR China
| | - Jin-Ming Chen
- Chifeng Clinical Medical School of Inner Mongolia Medical University, Chifeng, 024000, PR China
| | - Hao Wen
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830000, PR China
| | - Bo-Ming Wu
- Hepatology Department, Ningbo Hwamei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, PR China
| | - Chuan-Xin Wang
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Jinan 250033, Shandong, PR China; Shandong Provincial Clinical Medicine Research Center for Clinical Laboratory, Jinan, 250033, PR China.
| | - Lin Wu
- Berry Oncology Corporation, Beijing, 100102, PR China.
| | - Jin-Lin Hou
- Department of Infectious Diseases, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, PR China; Hepatology Unit, Shenzhen Hospital, Southern Medical University, Shenzhen, PR China.
| | - Hong-Yang Wang
- National Center of Liver Cancer, Navel Medical University, Shanghai, 210822, PR China; International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute/Hospital, Shanghai, 200438, PR China; Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer (SMMU), Ministry of Education, Shanghai, 200438, PR China; Shanghai Key Laboratory of Hepatobiliary Tumor Biology (EHBH), Shanghai, 200438, PR China.
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Enogieru IE, Comstock CE, Grimm LJ. Breast Cancer Screening and Treatment Clinical Trials Updated for 2023. JOURNAL OF BREAST IMAGING 2024; 6:14-22. [PMID: 38243862 DOI: 10.1093/jbi/wbad089] [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: 07/05/2023] [Indexed: 01/22/2024]
Abstract
There are many active or recently completed breast cancer screening and treatment trials in 2023 that have the potential to fundamentally change the way breast radiologists practice medicine. Breast cancer screening trials may provide evidence to support supplemental screening beyond mammography to include US, contrast-enhanced mammography, and breast MRI. Furthermore, there are multiple efforts to support risk-adaptive screening strategies that would personalize screening modalities, frequencies, and ages of initiation. For breast cancer treatment, aims to reduce overtreatment may provide nonsurgical treatment options for women with low-risk breast cancer. Breast radiologists must be familiar with the study designs, major inclusion and exclusion criteria, and principal endpoints in order to determine when and how the study results should influence clinical care. As multidisciplinary team members, breast radiologists will have major roles in the success or failure of these trials as they transition from research to actual clinical practice.
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Affiliation(s)
- Imarhia E Enogieru
- Department of Radiology, Duke University Medical Center, Durham, NC, USA
| | | | - Lars J Grimm
- Department of Radiology, Duke University Medical Center, Durham, NC, USA
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Hirsch L, Huang Y, Makse HA, Martinez DF, Hughes M, Eskreis-Winkler S, Pinker K, Morris E, Parra LC, Sutton EJ. [WITHDRAWN] Predicting breast cancer with AI for individual risk-adjusted MRI screening and early detection. ARXIV 2024:arXiv:2312.00067v2. [PMID: 38076513 PMCID: PMC10705586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
This paper has been withdrawn by Lukas Hirsch. Major revisions and rewriting in progress.
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Ghuman N, Ambinder EB, Oluyemi ET, Sutton E, Myers KS. Clinical and Imaging Features of MRI Screen-Detected Breast Cancer. Clin Breast Cancer 2024; 24:45-52. [PMID: 37821332 DOI: 10.1016/j.clbc.2023.09.012] [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: 07/13/2023] [Revised: 08/28/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND Supplemental screening with breast MRI is recommended annually for patients who have greater than 20% lifetime risk for breast cancer. While there is robust data regarding features of mammographic screen-detected breast cancers, there is limited data regarding MRI-screen-detected cancers. PATIENTS AND METHODS Screening breast MRIs performed between August 1, 2016 and July 30, 2022 identified 50 screen-detected breast cancers in 47 patients. Clinical and imaging features of all eligible cancers were recorded. RESULTS During the study period, 50 MRI-screen detected cancers were identified in 47 patients. The majority of MRI-screen detected cancers (32/50, 64%) were invasive. Pathology revealed ductal carcinoma in situ (DCIS) in 36% (18/50), invasive ductal carcinoma (IDC) in 52% (26/50), invasive lobular carcinoma in 10% (5/50), and angiosarcoma in 2% (1/50). The majority of patients (43/47, 91%) were stage 0 or 1 at diagnosis and there were no breast cancer-related deaths during the follow-up periods. Cancers presented as masses in 50% (25/50), nonmass enhancement in 48% (25/50), and a focus in 2% (1/50). DCIS was more likely to present as nonmass enhancement (94.4%, 17/18), whereas invasive cancers were more likely to present as masses (75%, 24/32) (P < .001). All cancers that were stage 2 at diagnosis were detected either on a baseline exam or more than 4 years since the prior MRI exam. CONCLUSION MRI screen-detected breast cancers were most often invasive cancers. Cancers detected by MRI screening had an excellent prognosis in our study population. Invasive cancers most commonly presented as a mass.
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Affiliation(s)
- Naveen Ghuman
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD.
| | - Emily B Ambinder
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Eniola T Oluyemi
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD
| | | | - Kelly S Myers
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD
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Tollens F, Baltzer PA, Froelich MF, Kaiser CG. Economic evaluation of breast MRI in screening - a systematic review and basic approach to cost-effectiveness analyses. Front Oncol 2023; 13:1292268. [PMID: 38130995 PMCID: PMC10733447 DOI: 10.3389/fonc.2023.1292268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/20/2023] [Indexed: 12/23/2023] Open
Abstract
Background Economic evaluations have become an accepted methodology for decision makers to allocate resources in healthcare systems. Particularly in screening, where short-term costs are associated with long-term benefits, and adverse effects of screening intermingle, cost-effectiveness analyses provide a means to estimate the economic value of screening. Purpose To introduce the methodology of economic evaluations and to review the existing evidence on cost-effectiveness of MR-based breast cancer screening. Materials and methods The various concepts and techniques of economic evaluations critical to the interpretation of cost-effectiveness analyses are briefly introduced. In a systematic review of the literature, economic evaluations from the years 2000-2022 are reviewed. Results Despite a considerable heterogeneity in the reported input variables, outcome categories and methodological approaches, cost-effectiveness analyses report favorably on the economic value of breast MRI screening for different risk groups, including both short- and long-term costs and outcomes. Conclusion Economic evaluations indicate a strongly favorable economic value of breast MRI screening for women at high risk and for women with dense breast tissue.
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Affiliation(s)
- Fabian Tollens
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Pascal A.T. Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Vienna General Hospital, Medical University of Vienna, Vienna, Austria
| | - Matthias F. Froelich
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Clemens G. Kaiser
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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Wilpert C, Neubauer C, Rau A, Schneider H, Benkert T, Weiland E, Strecker R, Reisert M, Benndorf M, Weiss J, Bamberg F, Windfuhr-Blum M, Neubauer J. Accelerated Diffusion-Weighted Imaging in 3 T Breast MRI Using a Deep Learning Reconstruction Algorithm With Superresolution Processing: A Prospective Comparative Study. Invest Radiol 2023; 58:842-852. [PMID: 37428618 DOI: 10.1097/rli.0000000000000997] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
OBJECTIVES Diffusion-weighted imaging (DWI) enhances specificity in multiparametric breast MRI but is associated with longer acquisition time. Deep learning (DL) reconstruction may significantly shorten acquisition time and improve spatial resolution. In this prospective study, we evaluated acquisition time and image quality of a DL-accelerated DWI sequence with superresolution processing (DWI DL ) in comparison to standard imaging including analysis of lesion conspicuity and contrast of invasive breast cancers (IBCs), benign lesions (BEs), and cysts. MATERIALS AND METHODS This institutional review board-approved prospective monocentric study enrolled participants who underwent 3 T breast MRI between August and December 2022. Standard DWI (DWI STD ; single-shot echo-planar DWI combined with reduced field-of-view excitation; b-values: 50 and 800 s/mm 2 ) was followed by DWI DL with similar acquisition parameters and reduced averages. Quantitative image quality was analyzed for region of interest-based signal-to-noise ratio (SNR) on breast tissue. Apparent diffusion coefficient (ADC), SNR, contrast-to-noise ratio, and contrast (C) values were calculated for biopsy-proven IBCs, BEs, and for cysts. Two radiologists independently assessed image quality, artifacts, and lesion conspicuity in a blinded independent manner. Univariate analysis was performed to test differences and interrater reliability. RESULTS Among 65 participants (54 ± 13 years, 64 women) enrolled in the study, the prevalence of breast cancer was 23%. Average acquisition time was 5:02 minutes for DWI STD and 2:44 minutes for DWI DL ( P < 0.001). Signal-to-noise ratio measured in breast tissue was higher for DWI STD ( P < 0.001). The mean ADC values for IBC were 0.77 × 10 -3 ± 0.13 mm 2 /s in DWI STD and 0.75 × 10 -3 ± 0.12 mm 2 /s in DWI DL without significant difference when sequences were compared ( P = 0.32). Benign lesions presented with mean ADC values of 1.32 × 10 -3 ± 0.48 mm 2 /s in DWI STD and 1.39 × 10 -3 ± 0.54 mm 2 /s in DWI DL ( P = 0.12), and cysts presented with 2.18 × 10 -3 ± 0.49 mm 2 /s in DWI STD and 2.31 × 10 -3 ± 0.43 mm 2 /s in DWI DL . All lesions presented with significantly higher contrast in the DWI DL ( P < 0.001), whereas SNR and contrast-to-noise ratio did not differ significantly between DWI STD and DWI DL regardless of lesion type. Both sequences demonstrated a high subjective image quality (29/65 for DWI STD vs 20/65 for DWI DL ; P < 0.001). The highest lesion conspicuity score was observed more often for DWI DL ( P < 0.001) for all lesion types. Artifacts were scored higher for DWI DL ( P < 0.001). In general, no additional artifacts were noted in DWI DL . Interrater reliability was substantial to excellent (k = 0.68 to 1.0). CONCLUSIONS DWI DL in breast MRI significantly reduced scan time by nearly one half while improving lesion conspicuity and maintaining overall image quality in a prospective clinical cohort.
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Affiliation(s)
- Caroline Wilpert
- From the Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany (C.W., C.N., A.R., H.S., M.B., JW, F.B., M.W.-B., J.N.); MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (T.B., E.W.); EMEA Scientific Partnerships, Siemens Healthcare GmbH, Erlangen, Germany (R.S.); Medical Physics, Department of Radiology, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany (M.R.); and Department of Stereotactic and Functional Neurosurgery, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany (M.R.)
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Fischer U, Diekmann F, Helbich T, Preibsch H, Püsken M, Wenkel E, Wienbeck S, Fallenberg EM. [Use of contrast-enhanced mammography for diagnosis of breast cancer]. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:916-924. [PMID: 37889284 PMCID: PMC10692004 DOI: 10.1007/s00117-023-01222-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/27/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Contrast-enhanced mammography (CEM) is an imaging method that is able to improve visualization of intramammary tumors after peripheral venous administration of an iodine-containing contrast medium (ICM). OBJECTIVES AND METHODS The current significance of CEM is discussed. RESULTS Studies were able to show an advantage of CEM in the diagnosis of breast cancer compared to mammography, especially for women with dense breasts. Indications for CEM currently depend on the availability of magnetic resonance imaging (MRI). If MRI is available, CEM is indicated in those cases when MRI cannot be performed. Use of CEM for breast cancer screening is currently viewed critically. This view can change when results and updated assessments of large CEM studies in Europe and USA become available. Patients must be informed about the use of an ICM. As ICM administration for CEM is carried out in a similar manner to established imaging methods, the authors expect the use of ICM for CEM to be unproblematic as long as general contraindications are adhered to. CONCLUSIONS In the future, CEM could have greater importance for the diagnosis of breast cancer, as this imaging method has diagnostic advantages compared to conventional mammography. A great advantage of CEM is its availability. For those who use breast MRI, CEM is helpful when MRI is not feasible due to contraindications or other reasons.
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Affiliation(s)
- Uwe Fischer
- Diagnostisches Brustzentrum Göttingen, Göttingen, Deutschland.
| | - Felix Diekmann
- Institut für Radiologische Diagnostik, Krankenhaus St. Joseph-Stift, Schwachhauser Heerstr. 54, 28209, Bremen, Deutschland
| | - Thomas Helbich
- Universitätsklinik für Radiologie und Nuklearmedizin, Abteilung für Allgemeine und Pädiatrische Radiologie, Medizinische Universität Wien/AKH WIEN, Währinger Gürtel 18-20, 1090, Wien, Österreich
| | - Heike Preibsch
- Diagnostische und Interventionelle Radiologie, Universitätsklinikum Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Deutschland
| | - Michael Püsken
- Institut für Diagnostische und Interventionelle Radiologie, Uniklinik Köln, Kerpener Str. 62, 50937, Köln, Deutschland
| | - Evelyn Wenkel
- Medizinische Fakultät, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Deutschland
- Radiologie München, München, Deutschland
| | - Susanne Wienbeck
- Radiologie Schwarzer Bär MVZ, Schwarzer Bär 8, 30449, Hannover, Deutschland
- Institut für Diagnostische und Interventionelle Radiologie, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Deutschland
| | - Eva Maria Fallenberg
- Institut für diagnostische und interventionelle Radiologie, School of Medicine & Klinikum rechts der Isar Technische Universität München (TUM), Ismaninger Str. 22, 81675, München, Deutschland
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Carnahan MB, Harper L, Brown PJ, Bhatt AA, Eversman S, Sharpe RE, Patel BK. False-Positive and False-Negative Contrast-enhanced Mammograms: Pitfalls and Strategies to Improve Cancer Detection. Radiographics 2023; 43:e230100. [PMID: 38032823 DOI: 10.1148/rg.230100] [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: 12/02/2023]
Abstract
Contrast-enhanced mammography (CEM) is a relatively new breast imaging modality that uses intravenous contrast material to increase detection of breast cancer. CEM combines the structural information of conventional mammography with the functional information of tumor neovascularity. Initial studies have demonstrated that CEM and MRI perform with similar accuracies, with CEM having a slightly higher specificity (fewer false positives), although larger studies are needed. There are various reasons for false positives and false negatives at CEM. False positives at CEM can be caused by benign lesions with vascularity, including benign tumors, infection or inflammation, benign lesions in the skin, and imaging artifacts. False negatives at CEM can be attributed to incomplete or inadequate visualization of lesions, marked background parenchymal enhancement (BPE) obscuring cancer, lack of lesion contrast enhancement due to technical issues or less-vascular cancers, artifacts, and errors of lesion perception or characterization. When possible, real-time interpretation of CEM studies is ideal. If additional views are necessary, they may be obtained while contrast material is still in the breast parenchyma. Until recently, a limitation of CEM was the lack of CEM-guided biopsy capability. However, in 2020, the U.S. Food and Drug Administration cleared two devices to support CEM-guided biopsy using a stereotactic biopsy technique. The authors review various causes of false-positive and false-negative contrast-enhanced mammograms and discuss strategies to reduce these diagnostic errors to improve cancer detection while mitigating unnecessary additional imaging and procedures. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Molly B Carnahan
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
| | - Laura Harper
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
| | - Parker J Brown
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
| | - Asha A Bhatt
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
| | - Sarah Eversman
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
| | - Richard E Sharpe
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
| | - Bhavika K Patel
- From the Department of Radiology, Mayo Clinic Arizona, 5777 E Mayo Blvd, Phoenix, AZ 85054 (M.B.C., L.H., P.J.B., S.E., R.E.S., B.K.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (A.A.B.)
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Coffey K, Mango V. Revisiting Screening in Women With a Family History of Breast Cancer. JOURNAL OF BREAST IMAGING 2023; 5:635-645. [PMID: 38141237 DOI: 10.1093/jbi/wbad069] [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: 05/31/2023] [Indexed: 12/25/2023]
Abstract
Women with a family history (FH) of breast cancer and without known genetic susceptibility represent a unique population whose lifetime probability of developing breast cancer varies widely depending on familial factors, breast density, and the risk assessment tool used. Recently updated guidelines from the American College of Radiology recommend supplemental annual screening with contrast-enhanced MRI or contrast-enhanced mammography for women with an FH who are high risk (≥20% lifetime risk) or have dense breasts. To date, most screening studies addressing outcomes in women with FH have largely included those also with confirmed or suspected gene mutations, in whom the lifetime risk is highest, with limited data for women at average to intermediate risk who are not known to be genetically susceptible and may not benefit as much from the same screening approaches. Further research focusing specifically on women with FH as the only breast cancer risk factor is warranted to refine risk assessment and optimize a multimodality personalized screening approach.
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Affiliation(s)
- Kristen Coffey
- Memorial Sloan Kettering Cancer Center, Department of Radiology, New York, NY, USA
| | - Victoria Mango
- Memorial Sloan Kettering Cancer Center, Department of Radiology, New York, NY, USA
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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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McCarthy AM, Fernandez Perez C, Beidas RS, Bekelman JE, Blumenthal D, Mack E, Bauer AM, Ehsan S, Conant EF, Wheeler BC, Guerra CE, Nunes LW, Gabriel P, Doucette A, Wileyto EP, Buttenheim AM, Asch DA, Rendle KA, Shelton RC, Fayanju OM, Ware S, Plag M, Hyland S, Gionta T, Shulman LN, Schnoll R. Protocol for a pragmatic stepped wedge cluster randomized clinical trial testing behavioral economic implementation strategies to increase supplemental breast MRI screening among patients with extremely dense breasts. Implement Sci 2023; 18:65. [PMID: 38001506 PMCID: PMC10668465 DOI: 10.1186/s13012-023-01323-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Increased breast density augments breast cancer risk and reduces mammography sensitivity. Supplemental breast MRI screening can significantly increase cancer detection among women with dense breasts. However, few women undergo this exam, and screening is consistently lower among racially minoritized populations. Implementation strategies informed by behavioral economics ("nudges") can promote evidence-based practices by improving clinician decision-making under conditions of uncertainty. Nudges directed toward clinicians and patients may facilitate the implementation of supplemental breast MRI. METHODS Approximately 1600 patients identified as having extremely dense breasts after non-actionable mammograms, along with about 1100 clinicians involved with their care at 32 primary care or OB/GYN clinics across a racially diverse academically based health system, will be enrolled. A 2 × 2 randomized pragmatic trial will test nudges to patients, clinicians, both, or neither to promote supplemental breast MRI screening. Before implementation, rapid cycle approaches informed by clinician and patient experiences and behavioral economics and health equity frameworks guided nudge design. Clinicians will be clustered into clinic groups based on existing administrative departments and care patterns, and these clinic groups will be randomized to have the nudge activated at different times per a stepped wedge design. Clinicians will receive nudges integrated into the routine mammographic report or sent through electronic health record (EHR) in-basket messaging once their clinic group (i.e., wedge) is randomized to receive the intervention. Independently, patients will be randomized to receive text message nudges or not. The primary outcome will be defined as ordering or scheduling supplemental breast MRI. Secondary outcomes include MRI completion, cancer detection rates, and false-positive rates. Patient sociodemographic information and clinic-level variables will be examined as moderators of nudge effectiveness. Qualitative interviews conducted at the trial's conclusion will examine barriers and facilitators to implementation. DISCUSSION This study will add to the growing literature on the effectiveness of behavioral economics-informed implementation strategies to promote evidence-based interventions. The design will facilitate testing the relative effects of nudges to patients and clinicians and the effects of moderators of nudge effectiveness, including key indicators of health disparities. The results may inform the introduction of low-cost, scalable implementation strategies to promote early breast cancer detection. TRIAL REGISTRATION ClinicalTrials.gov NCT05787249. Registered on March 28, 2023.
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Affiliation(s)
- Anne Marie McCarthy
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA.
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA.
| | | | - Rinad S Beidas
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Justin E Bekelman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Daniel Blumenthal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mack
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anna-Marika Bauer
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah Ehsan
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emily F Conant
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Carmen E Guerra
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Linda W Nunes
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter Gabriel
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Abigail Doucette
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - E Paul Wileyto
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Alison M Buttenheim
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Asch
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Katharine A Rendle
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA
| | - Rachel C Shelton
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Oluwadamilola M Fayanju
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Sue Ware
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Martina Plag
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Hyland
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tracy Gionta
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lawrence N Shulman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Robert Schnoll
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
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Liu Y, Jia X, Zhao J, Peng Y, Yao X, Hu X, Cui J, Chen H, Chen X, Wu J, Hong N, Wang S, Wang Y. A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI. J Magn Reson Imaging 2023. [PMID: 37933890 DOI: 10.1002/jmri.29111] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/17/2023] [Accepted: 10/17/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning. PURPOSE To develop an unenhanced radiomics model with using non-gadolinium based sequences for detecting breast cancer based on T2-weighted (T2W) and diffusion-weighted (DW) MRI. STUDY TYPE Retrospective analysis followed by retrospective and prospective cohorts study. POPULATION 1760 patients: Of these, 1293 for model construction (n = 775 for training and 518 for validation). The remaining patients for model testing in internal retrospective (n = 167), internal prospective (n = 188), and external retrospective (n = 112) cohorts. FIELD STRENGTH/SEQUENCE 3.0T MR scanners from two institution. T2WI, DWI, and first contrast-enhanced T1-weighted sequence. ASSESSMENT AUCs in distinguishing breast cancer were compared between combined model with gadolinium agent sequence and unenhanced model. Subsequently, the AUCs in testing cohorts of unenhanced model was compared with two radiologists' diagnosis for this research. Finally, patient subgroup analysis in testing cohorts was performed based on clinical subgroups and different types of malignancies. STATISTICAL TESTS Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, weighted kappa test, and DeLong's test. RESULTS The unenhanced radiomics model performed best under Gaussian process (GP) classifiers (AUC: training, 0.893; validation, 0.848) compared to support vector machine (SVM) and logistic, showing favorable prediction in testing cohorts (AUCs, 0.818-0.840). The AUCs for the unenhanced radiomics model were not statistically different in five cohorts from those of the combined radiomics model (P, 0.317-0.816), as well as the two radiologists (P, 0.181-0.918). The unenhanced radiomics model was least successful in identifying ductal carcinoma in situ, whereas did not show statistical significance in other subgroups. DATA CONCLUSION An unenhanced radiomics model based on T2WI and DWI has comparable diagnostic accuracy to the combined model using the gadolinium agent. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yulu Liu
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Xiaoxuan Jia
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Jiaqi Zhao
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, China
| | - Yuan Peng
- Department of Breast Surgery, Peking University People's Hospital, Beijing, China
| | - Xun Yao
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Xuege Hu
- Department of Breast Surgery, Peking University People's Hospital, Beijing, China
| | - Jingjing Cui
- Department of Research and Development, United Imaging Intelligence (Beijing) Co., Ltd., Beijing, China
| | - Haoquan Chen
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Xiufeng Chen
- Department of General Surgery, Beijing Aerospace General Hospital, Beijing, China
| | - Jing Wu
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Shu Wang
- Department of Breast Surgery, Peking University People's Hospital, Beijing, China
| | - Yi Wang
- Department of Radiology, Peking University People's Hospital, Beijing, China
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Obermann M, Nohava L, Frass-Kriegl R, Soanca O, Ginefri JC, Felblinger J, Clauser P, Baltzer PA, Laistler E. Panoramic Magnetic Resonance Imaging of the Breast With a Wearable Coil Vest. Invest Radiol 2023; 58:799-810. [PMID: 37227137 PMCID: PMC10581436 DOI: 10.1097/rli.0000000000000991] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/21/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND Breast cancer, the most common malignant cancer in women worldwide, is typically diagnosed by x-ray mammography, which is an unpleasant procedure, has low sensitivity in women with dense breasts, and involves ionizing radiation. Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality and works without ionizing radiation, but is currently constrained to the prone imaging position due to suboptimal hardware, therefore hampering the clinical workflow. OBJECTIVES The aim of this work is to improve image quality in breast MRI, to simplify the clinical workflow, shorten measurement time, and achieve consistency in breast shape with other procedures such as ultrasound, surgery, and radiation therapy. MATERIALS AND METHODS To this end, we propose "panoramic breast MRI"-an approach combining a wearable radiofrequency coil for 3 T breast MRI (the "BraCoil"), acquisition in the supine position, and a panoramic visualization of the images. We demonstrate the potential of panoramic breast MRI in a pilot study on 12 healthy volunteers and 1 patient, and compare it to the state of the art. RESULTS With the BraCoil, we demonstrate up to 3-fold signal-to-noise ratio compared with clinical standard coils and acceleration factors up to 6 × 4. Panoramic visualization of supine breast images reduces the number of slices to be viewed by a factor of 2-4. CONCLUSIONS Panoramic breast MRI allows for high-quality diagnostic imaging and facilitated correlation to other diagnostic and interventional procedures. The developed wearable radiofrequency coil in combination with dedicated image processing has the potential to improve patient comfort while enabling more time-efficient breast MRI compared with clinical coils.
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Phillips J, Mehta TS, Portnow LH, Fishman MDC, Zhang Z, Pisano ED. Comparison of Contrast-enhanced Mammography with MRI Utilizing an Enriched Reader Study: A Breast Cancer Study (CONTRRAST Trial). Radiology 2023; 309:e230530. [PMID: 37962503 DOI: 10.1148/radiol.230530] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Despite growing interest in using contrast-enhanced mammography (CEM) for breast cancer screening as an alternative to breast MRI, limited literature is available. Purpose To determine whether CEM is noninferior to breast MRI or abbreviated breast MRI (AB MRI) and superior to two-dimensional mammography in an asymptomatic population simulating those who would present for screening and then undergo diagnostic work-up. Materials and Methods This enriched reader study used CEM and MRI data prospectively collected from asymptomatic individuals at a single institution from December 2014 to March 2020. Case sets were obtained at screening, as part of work-up for a screening-detected finding, or before biopsy of a screening-detected abnormality. All images were anonymized and randomized, and all 12 radiologists interpreted them. For CEM interpretation, readers were first shown low-energy images as a surrogate for digital mammography and asked to give a forced Breast Imaging Reporting and Data System score for up to three abnormalities. The highest score was used as the case score. Readers then reviewed the full CEM examination and scored it similarly. After a minimum 1-month washout, the readers similarly interpreted AB MRI and full MRI examinations. Receiver operating characteristic analysis, powered to test CEM noninferiority to full MRI, was performed. Results The study included 132 case sets (14 negative, 74 benign, and 44 malignant; all female participants; mean age, 54 years ± 12 [SD]). The mean areas under the receiver operating characteristic curve (AUCs) for digital mammography, CEM, AB MRI, and full MRI were 0.79, 0.91, 0.89, and 0.91, respectively. CEM was superior to digital mammography (P < .001). No evidence of a difference in AUC was found between CEM and AB MRI and MRI. Conclusion In an asymptomatic study sample, CEM was noninferior to full MRI and AB MRI and was superior to digital mammography. Clinical trial registration no. NCT03482557 and NCT02275871 © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Jordana Phillips
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Tejas S Mehta
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Leah H Portnow
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Michael D C Fishman
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Zheng Zhang
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
| | - Etta D Pisano
- From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, TCC 4th Floor, Boston, MA 02215 (J.P.); Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (T.S.M.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (L.H.P.); Department of Radiology, Boston University Medical Center, Boston, Mass (J.P., M.D.C.F.); Takeda Pharmaceuticals, Cambridge, Mass (Z.Z.); and Department of Radiology, Penn Medicine, Philadelphia, Pa (E.D.P.)
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Mi J, Zhang H, Cao W, Yuan C. FTO, PIK3CB serve as potential markers to complement CEA and CA15-3 for the diagnosis of breast cancer. Medicine (Baltimore) 2023; 102:e35361. [PMID: 37861518 PMCID: PMC10589555 DOI: 10.1097/md.0000000000035361] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 09/01/2023] [Indexed: 10/21/2023] Open
Abstract
The diagnostic efficacy of carcinoembryonic antigen (CEA) and carbohydrate antigen 15-3 (CA15-3) is limited in breast cancer (BC), highlighting the necessity of exploring novel biomarkers to improve for BC diagnosis. Therefore, we assessed the diagnostic value of fat mass and obesity-associated protein (FTO), phosphatidylinositol-4,5-biphosphate 3-kinase catalytic subunit β (PIK3CB) as a potential complementary biomarker to CEA and CA153 in breast cancer by measuring serum FTO,PIK3CB levels. FTO, PIK3CB, CEA and CA15-3 levels were measured in 112 BC patients and 64 healthy controls using enzyme-linked immunosorbent assay or electrochemiluminescence immunoassay. Spearman's rank correlation analysis was conducted to assess the correlation between the levels of the 2 markers. The relationships between FTO, PIK3CB, CEA, CA15-3 and clinical characteristics were evaluated. Receiver operating characteristic curve (ROC) analysis was performed to assess the diagnostic value of FTO, PIK3CB, CEA and CA15-3 of BC. Serum FTO, PIK3CB, CEA and CA15-3 levels were significantly increased in BC. There was no correlation between FTO, PIK3CB and CEA, CA15-3. FTO and PIK3CB demonstrated significant diagnostic performance for breast cancer, with FTO achieving a specificity of 90.63%. The diagnostic performance of 2-four biomarker combinations was significantly superior to individual CEA or CA153, with a combined panel of 4 biomarkers yielding an area under the curve (AUC) of 0.918, sensitivity of 81.25% and specificity of 85.94%. In early-stage breast cancer (I + II), the combination of FTO, PIK3CB, CEA and CA153 yielded an AUC of 0.895, sensitivity of 77.22% and specificity of 85.71%. FTO and PIK3CB can be served as potential biomarkers to complement CEA and CA15-3 for BC diagnosis. Combining FTO, PIK3CB, CEA and CA15-3 improves the diagnostic efficiency of breast cancer.
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Affiliation(s)
- Jintao Mi
- College of Medical Technology,Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Hongsheng Zhang
- College of Medical Technology,Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Weiwei Cao
- Department of Clinical Laboratory, People’s Hospital of Deyang City, Deyang, China
| | - Chengliang Yuan
- Department of Clinical Laboratory, People’s Hospital of Deyang City, Deyang, China
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Eskreis-Winkler S, Sung JS, Dixon L, Monga N, Jindal R, Simmons A, Thakur S, Sevilimedu V, Sutton E, Comstock C, Feigin K, Pinker K. High-Temporal/High-Spatial Resolution Breast Magnetic Resonance Imaging Improves Diagnostic Accuracy Compared With Standard Breast Magnetic Resonance Imaging in Patients With High Background Parenchymal Enhancement. J Clin Oncol 2023; 41:4747-4755. [PMID: 37561962 PMCID: PMC10602549 DOI: 10.1200/jco.22.00635] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 01/05/2023] [Accepted: 06/16/2023] [Indexed: 08/12/2023] Open
Abstract
PURPOSE To compare breast magnetic resonance imaging (MRI) diagnostic performance using a standard high-spatial resolution protocol versus a simultaneous high-temporal/high-spatial resolution (HTHS) protocol in women with high levels of background parenchymal enhancement (BPE). MATERIALS AND METHODS We conducted a retrospective study of contrast-enhanced breast MRIs performed at our institution before and after the introduction of the HTHS protocol. We compared diagnostic performance of the HTHS and standard protocol by comparing cancer detection rate (CDR) and positive predictive value of biopsy (PPV3) among women with high BPE (ie, marked or moderate). RESULTS Among women with high BPE, the HTHS protocol demonstrated increased CDR (23.6 per 1,000 patients v 7.9 per 1,000 patients; P = 0. 013) and increased PPV3 (16.0% v 6.3%; P = .021) compared with the standard protocol. This corresponded to a 9.8% (95% CI, 1.29 to 18.3) decrease in the proportion of unnecessary biopsies among high-BPE patients and an additional cancer yield of 15.7 per 1,000 patients (95% CI, 1.3 to 18.3). CONCLUSION Among women with high BPE, HTHS MRI improved diagnostic performance, leading to an additional cancer yield of 15.7 cancers per 1,000 women and concomitantly decreasing unnecessary biopsies by 9.8%. A multisite prospective trial is warranted to confirm these findings and to pave the way for more widespread clinical implementation.
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Affiliation(s)
| | - Janice S. Sung
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Linden Dixon
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Natasha Monga
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ragni Jindal
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Sunitha Thakur
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Varadan Sevilimedu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Elizabeth Sutton
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Kimberly Feigin
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Katja Pinker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
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