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Vaz SC, Corion CLS, Goeman J, Zeillemaker AM, Hezemans R, de Geus-Oei LF, Pereira Arias-Bouda LM. Can Molecular Breast Imaging With Tc-99m Sestamibi Safely Rule Out Malignancy in Pathologic Nipple Discharge? Clin Nucl Med 2025:00003072-990000000-01693. [PMID: 40302123 DOI: 10.1097/rlu.0000000000005851] [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: 11/11/2024] [Accepted: 02/18/2025] [Indexed: 05/01/2025]
Abstract
PURPOSE Nipple discharge is the third most common breast-related complaint. It is recommended to exclude malignancy in pathologic nipple discharge (PND). Mammography and ultrasound are the first-line conventional diagnostic (CD) imaging. Although magnetic resonance is often used as a complementary modality, molecular breast imaging (MBI) with Tc-99m sestamibi may be a suitable alternative. Considering the lack of information on this subject and its clinical importance, this study aimed to evaluate the role of MBI in ruling out malignancy in patients with PND and negative/indeterminate CD. PATIENTS AND METHODS Retrospective cohort single-center study including all patients with PND evaluated by CD and MBI between 2012 and 2020. Pathology was considered the gold standard. Follow-up was used when pathology was not available. RESULTS Of the 96 cases of PND included, 78 were benign, and 18 (20%) corresponded to breast cancer (BC). Although CD and MBI were concordant in the BIRADS classification in 81% (78/96), half of BC were detected by MBI only. BC was located directly behind the nipple in a minority of patients (11%), meaning that MBI could significantly prevent futile central ductal excision. MBI presented higher sensitivity (83% vs. 33%) and negative predictive value (96% vs. 86%) than CD alone, with similar specificity (89% vs. 92%) and positive predictive value (63% vs. 50%). The area under the curve of MBI and CD was 0,86 (P-value<0.001 [95% CI: 0.75-0.97]) and 0.63 (P-value=0.091 [95% CI: 0.47-0.79]), respectively. CONCLUSIONS MBI showed good diagnostic accuracy for detecting BC in patients with PND with negative/indeterminate findings on CD imaging.
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Affiliation(s)
- Sofia C Vaz
- Nuclear Medicine-Radiopharmacology, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal
- Department of Radiology, Leiden University Medical Center, Leiden
| | | | - Jelle Goeman
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden
| | | | - Rachel Hezemans
- Department of Nuclear Medicine, Alrijne Hospital, Leiderdorp
| | - Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center, Leiden
- Biomedical Photonic Imaging Group, University of Twente, Enschede
- Department of Radiation Science & Technology, Delft University of Technology, Delft
| | - Lenka M Pereira Arias-Bouda
- Department of Radiology, Leiden University Medical Center, Leiden
- Department of Nuclear Medicine, Alrijne Hospital, Leiderdorp
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2
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Foshag K, Tsiouris AJ, Prince M, Reichman M. A review of gadolinium-based contrast agents in the setting of repeated MRI for high risk breast cancer screening. Clin Imaging 2025; 120:110420. [PMID: 39938355 DOI: 10.1016/j.clinimag.2025.110420] [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: 12/02/2024] [Revised: 01/26/2025] [Accepted: 02/02/2025] [Indexed: 02/14/2025]
Abstract
Women who are considered high risk for breast cancer are recommended to undergo supplemental breast cancer screening annually with MRI. There are primarily three safety concerns associated with gadolinium-based contrast agents which include allergic reactions, nephrogenic systemic fibrosis and gadolinium deposition. In this review, we discuss how these risks are affected by molecular structure, will specifically review the difference between the two commonly used agents, gadobutrol and gadoterate, and discuss the most recent FDA approved contrast agent on the market, gadopiclenol.
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Affiliation(s)
- Kelcie Foshag
- Weill Cornell Medicine at New York-Presbyterian Hospital, 525 East 68th Street, New York, NY 10065, United States of America.
| | - Apostolos John Tsiouris
- Weill Cornell Medicine at New York-Presbyterian Hospital, 525 East 68th Street, New York, NY 10065, United States of America.
| | - Martin Prince
- Weill Cornell Medicine at New York-Presbyterian Hospital, 525 East 68th Street, New York, NY 10065, United States of America.
| | - Melissa Reichman
- Weill Cornell Medicine at New York-Presbyterian Hospital, 525 East 68th Street, New York, NY 10065, United States of America.
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Gullo RL, Brunekreef J, Marcus E, Han LK, Eskreis-Winkler S, Thakur SB, Mann R, Lipman KG, Teuwen J, Pinker K. AI Applications to Breast MRI: Today and Tomorrow. J Magn Reson Imaging 2024; 60:2290-2308. [PMID: 38581127 PMCID: PMC11452568 DOI: 10.1002/jmri.29358] [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: 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, NY 10065, 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, NY, USA
| | - Sarah Eskreis-Winkler
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Sunitha B Thakur
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, 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, NY 10065, USA
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4
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Patel BK, Carnahan MB, Northfelt D, Anderson K, Mazza GL, Pizzitola VJ, Giurescu ME, Lorans R, Eversman WG, Sharpe RE, Harper LK, Apsey H, Cronin P, Kling J, Ernst B, Palmieri J, Fraker J, Mina L, Batalini F, Pockaj B. Prospective Study of Supplemental Screening With Contrast-Enhanced Mammography in Women With Elevated Risk of Breast Cancer: Results of the Prevalence Round. J Clin Oncol 2024; 42:3826-3836. [PMID: 39058970 DOI: 10.1200/jco.22.02819] [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: 12/15/2022] [Revised: 03/14/2024] [Accepted: 05/01/2024] [Indexed: 07/28/2024] Open
Abstract
PURPOSE Contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) have shown similar diagnostic performance in detection of breast cancer. Limited CEM data are available for high-risk breast cancer screening. The purpose of the study was to prospectively investigate the efficacy of supplemental screening CEM in elevated risk patients. MATERIALS AND METHODS A prospective, single-institution, institutional review board-approved observational study was conducted in asymptomatic elevated risk women age 35 years or older who had a negative conventional two-dimensional digital breast tomosynthesis screening mammography (MG) and no additional supplemental screening within the prior 12 months. RESULTS Four hundred sixty women were enrolled from February 2019 to April 2021. The median age was 56.8 (range, 35.0-79.2) years; 408 of 460 (88.7%) were mammographically dense. Biopsy revealed benign changes in 22 women (22/37, 59%), high-risk lesions in four women (4/37, 11%), and breast cancer in 11 women (11/37, 30%). Fourteen cancers (10 invasive, tumor size range 4-15 mm, median 9 mm) were diagnosed in 11 women. The overall supplemental cancer detection rate was 23.9 per 1,000 patients, 95% CI (12.0 to 42.4). All cancers were grade 1 or 2, ER+ ERBB2-, and node negative. CEM imaging screening offered high specificity (0.875 [95% CI, 0.844 to 0.906]), high NPV (0.998 [95% CI, 0.993 to 1.000), moderate PPV1 (0.164 [95% CI, 0.076 to 0.253), moderate PPV3 (0.275 [95% CI, 0.137 to 0.413]), and high sensitivity (0.917 [95% CI, 0.760 to 1.000]). At least 1 year of imaging follow-up was available on all patients, and one interval cancer was detected on breast MRI 4 months after negative screening CEM. CONCLUSION A pilot trial demonstrates a supplemental cancer detection rate of 23.9 per 1,000 in women at an elevated risk for breast cancer. Larger, multi-institutional, multiyear CEM trials in patients at elevated risk are needed for validation.
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Affiliation(s)
- Bhavika K Patel
- Department of Radiology, Mayo Clinic in Arizona, Phoenix, AZ
| | | | - Donald Northfelt
- Department of Medical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Karen Anderson
- Department of Medical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Gina L Mazza
- Department of Quantitative Health Sciences, Mayo Clinic in Arizona, Phoenix, AZ
| | | | | | - Roxanne Lorans
- Department of Radiology, Mayo Clinic in Arizona, Phoenix, AZ
| | | | | | - Laura K Harper
- Department of Radiology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Heidi Apsey
- Division of Women's Health Internal Medicine, Mayo Clinic in Arizona, Phoenix, AZ
| | - Patricia Cronin
- Department of Surgical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Juliana Kling
- Division of Women's Health Internal Medicine, Mayo Clinic in Arizona, Phoenix, AZ
| | - Brenda Ernst
- Department of Medical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | | | - Jessica Fraker
- Department of Surgical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Lida Mina
- Department of Medical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Felipe Batalini
- Department of Medical Oncology, Mayo Clinic in Arizona, Phoenix, AZ
| | - Barbara Pockaj
- Division of Women's Health Internal Medicine, Mayo Clinic in Arizona, Phoenix, AZ
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Cha E, Oluyemi ET, Ambinder EB, Myers KS. Clinical Outcomes of Benign Concordant MRI-Guided Breast Biopsies. Clin Breast Cancer 2024; 24:597-603. [PMID: 39013683 DOI: 10.1016/j.clbc.2024.06.009] [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: 01/12/2024] [Revised: 06/06/2024] [Accepted: 06/13/2024] [Indexed: 07/18/2024]
Abstract
INTRODUCTION MRI-guided biopsy is the standard of care for breast imaging findings seen only by MRI. Although a non-zero false-negative rate of MRI-guided breast biopsy has been reported by multiple studies, there are varied practice patterns for imaging follow-up after a benign concordant MRI guided biopsy. This study assessed the outcomes of benign concordant MRI-guided biopsies at a single institution. PATIENTS AND METHODS This IRB-approved, retrospective study included patients with MRI-guided biopsies of breast lesions from November 1, 2014, to August 31, 2020. Only image-concordant breast lesions with benign histopathology and those follow up with MRI imaging or excision were included in the study. RESULTS Out of 275 lesions in 216 patients that met the inclusion criteria, 274 lesions were followed with MRI (range, 5-79 months; average, 25.5 months) and showed benign or stable features upon follow-up. One out of 275 lesions (0.4%), a 6 mm focal nonmass enhancement, was ultimately found to represent malignancy after initial MRI-guided biopsy yielded fibrocystic changes. The lesion was stable at a 6-month follow-up MRI but increased in size at 18 months. Repeat biopsy by ultrasound guidance yielded invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS). CONCLUSION Breast MRI-guided biopsy has a low false-negative rate. Our single malignancy from a total of 275 lesions gives a false negative rate of 0.4%. This data also supports a longer follow-up interval than the commonly performed 6-month follow-up, in order to assess for interval change.
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Affiliation(s)
- Eumee Cha
- Johns Hopkins University School of Medicine, Baltimore, MD
| | - Eniola T Oluyemi
- Johns Hopkins School of Medicine, Department of Radiology, Baltimore, MD
| | - Emily B Ambinder
- Johns Hopkins School of Medicine, Department of Radiology, Baltimore, MD
| | - Kelly S Myers
- Johns Hopkins School of Medicine, Department of Radiology, Baltimore, MD.
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Kim HJ, Choi WJ, Gwon HY, Jang SJ, Chae EY, Shin HJ, Cha JH, Kim HH. Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software. Eur Radiol 2024; 34:3924-3934. [PMID: 37938383 DOI: 10.1007/s00330-023-10422-8] [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: 09/15/2023] [Revised: 09/15/2023] [Accepted: 10/14/2023] [Indexed: 11/09/2023]
Abstract
OBJECTIVES To evaluate the improvement of mammography interpretation for novice and experienced radiologists assisted by two commercial AI software. METHODS We compared the performance of two AI software (AI-1 and AI-2) in two experienced and two novice readers for 200 mammographic examinations (80 cancer cases). Two reading sessions were conducted within 4 weeks. The readers rated the likelihood of malignancy (range, 1-7) and the percentage probability of malignancy (range, 0-100%), with and without AI assistance. Differences in AUROC, sensitivity, and specificity were analyzed. RESULTS Mean AUROC increased in both novice (0.86 to 0.90 with AI-1 [p = 0.005]; 0.91 with AI-2 [p < 0.001]) and experienced readers (0.87 to 0.92 with AI-1 [p < 0.001]; 0.90 with AI-2 [p = 0.004]). Sensitivities increased from 81.3 to 88.8% with AI-1 (p = 0.027) and to 91.3% with AI-2 (p = 0.005) in novice readers, and from 81.9 to 90.6% with AI-1 (p = 0.001) and to 87.5% with AI-2 (p = 0.016) in experienced readers. Specificity did not decrease significantly in both novice (p > 0.999, both) and experienced readers (p > 0.999 with AI-1 and 0.282 with AI-2). There was no significant difference in the performance change depending on the type of AI software (p > 0.999). CONCLUSION Commercial AI software improved the diagnostic performance of both novice and experienced readers. The type of AI software used did not significantly impact performance changes. Further validation with a larger number of cases and readers is needed. CLINICAL RELEVANCE STATEMENT Commercial AI software effectively aided mammography interpretation irrespective of the experience level of human readers. KEY POINTS • Mammography interpretation remains challenging and is subject to a wide range of interobserver variability. • In this multi-reader study, two commercial AI software improved the sensitivity of mammography interpretation by both novice and experienced readers. The type of AI software used did not significantly impact performance changes. • Commercial AI software may effectively support mammography interpretation irrespective of the experience level of human readers.
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Affiliation(s)
- Hee Jeong Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea
| | - Woo Jung Choi
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea.
| | - Hye Yun Gwon
- Department of Radiology, Hallym University Sacred Heart Hospital, 22, Gwanpyeong-Ro 170-Gil, Dongan-Gu, Anyang-Si, Gyeonggi-Do, 14068, South Korea
| | - Seo Jin Jang
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea
| | - Eun Young Chae
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea
| | - Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea
| | - Joo Hee Cha
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea
| | - Hak Hee Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea
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Fan M, Cao X, Lü F, Xie S, Yu Z, Chen Y, Lü Z, Li L. Generative adversarial network-based synthesis of contrast-enhanced MR images from precontrast images for predicting histological characteristics in breast cancer. Phys Med Biol 2024; 69:095002. [PMID: 38537294 DOI: 10.1088/1361-6560/ad3889] [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: 11/27/2023] [Accepted: 03/27/2024] [Indexed: 04/16/2024]
Abstract
Objective. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a sensitive tool for assessing breast cancer by analyzing tumor blood flow, but it requires gadolinium-based contrast agents, which carry risks such as brain retention and astrocyte migration. Contrast-free MRI is thus preferable for patients with renal impairment or who are pregnant. This study aimed to investigate the feasibility of generating contrast-enhanced MR images from precontrast images and to evaluate the potential use of synthetic images in diagnosing breast cancer.Approach. This retrospective study included 322 women with invasive breast cancer who underwent preoperative DCE-MRI. A generative adversarial network (GAN) based postcontrast image synthesis (GANPIS) model with perceptual loss was proposed to generate contrast-enhanced MR images from precontrast images. The quality of the synthesized images was evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The diagnostic performance of the generated images was assessed using a convolutional neural network to predict Ki-67, luminal A and histological grade with the area under the receiver operating characteristic curve (AUC). The patients were divided into training (n= 200), validation (n= 60), and testing sets (n= 62).Main results. Quantitative analysis revealed strong agreement between the generated and real postcontrast images in the test set, with PSNR and SSIM values of 36.210 ± 2.670 and 0.988 ± 0.006, respectively. The generated postcontrast images achieved AUCs of 0.918 ± 0.018, 0.842 ± 0.028 and 0.815 ± 0.019 for predicting the Ki-67 expression level, histological grade, and luminal A subtype, respectively. These results showed a significant improvement compared to the use of precontrast images alone, which achieved AUCs of 0.764 ± 0.031, 0.741 ± 0.035, and 0.797 ± 0.021, respectively.Significance. This study proposed a GAN-based MR image synthesis method for breast cancer that aims to generate postcontrast images from precontrast images, allowing the use of contrast-free images to simulate kinetic features for improved diagnosis.
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Affiliation(s)
- Ming Fan
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
| | - Xuan Cao
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
| | - Fuqing Lü
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
| | - Sangma Xie
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
| | - Zhou Yu
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
| | - Yuanlin Chen
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
| | - Zhong Lü
- Affiliated Dongyang Hospital of Wenzhou Medical University,People's Republic of China
| | - Lihua Li
- Institute of Intelligent Biomedicine, Hangzhou Dianzi University,Hangzhou 310018, Zhejiang, People's Republic of China
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Kubota K, Nakashima K, Nakashima K, Kataoka M, Inoue K, Goto M, Kanbayashi C, Hirokaga K, Yamaguchi K, Suzuki A. The Japanese breast cancer society clinical practice guidelines for breast cancer screening and diagnosis, 2022 edition. Breast Cancer 2024; 31:157-164. [PMID: 37973686 PMCID: PMC10901949 DOI: 10.1007/s12282-023-01521-x] [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: 09/12/2023] [Accepted: 10/24/2023] [Indexed: 11/19/2023]
Abstract
This article provides updates to readers based on the newly published Japanese Breast Cancer Society Clinical Practice Guidelines for Breast Cancer Screening and Diagnosis, 2022 Edition. These guidelines incorporate the latest evaluation of evidence from studies of diagnostic accuracy. For each clinical question, outcomes for benefits and harms were established, and qualitative or quantitative systematic reviews were conducted. Recommendations were determined through voting by a multidisciplinary group, and guidelines were documented to facilitate shared decision-making among patients and medical professionals. The guidelines address screening, surveillance, and pre- and postoperative diagnosis of breast cancer. In an environment that demands an integrated approach, decisions are needed on how to utilize modalities, such as mammography, ultrasound, MRI, and PET/CT. Additionally, it is vital to understand the appropriate use of new technologies, such as tomosynthesis, elastography, and contrast-enhanced ultrasound, and to consider how best to adapt these methods for individual patients.
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Affiliation(s)
- Kazunori Kubota
- Department of Radiology, Dokkyo Medical University Saitama Medical Center, 2-1-50 Minami-koshigaya, Koshigaya, Saitama, 343-8555, Japan.
- The Japanese Breast Cancer Society Clinical Practice Guidelines Breast Cancer Screening and Diagnosis Subcommittee, Tokyo, Japan.
| | - Kazutaka Nakashima
- Department of General Surgery, Kawasaki Medical School General Medical Center, Okayama, Japan
| | - Kazuaki Nakashima
- The Japanese Breast Cancer Society Clinical Practice Guidelines Breast Cancer Screening and Diagnosis Subcommittee, Tokyo, Japan
- Division of Breast Imaging and Breast Interventional Radiology, Shizuoka Cancer Center, Shizuoka, Japan
| | - Masako Kataoka
- The Japanese Breast Cancer Society Clinical Practice Guidelines Breast Cancer Screening and Diagnosis Subcommittee, Tokyo, Japan
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kenich Inoue
- The Japanese Breast Cancer Society Clinical Practice Guidelines Breast Cancer Screening and Diagnosis Subcommittee, Tokyo, Japan
- Breast Cancer Center, Shonan Memorial Hospital, Kanagawa, Japan
| | - Mariko Goto
- The Japanese Breast Cancer Society Clinical Practice Guidelines Breast Cancer Screening and Diagnosis Subcommittee, Tokyo, Japan
- Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Chizuko Kanbayashi
- The Japanese Breast Cancer Society Clinical Practice Guidelines Breast Cancer Screening and Diagnosis Subcommittee, Tokyo, Japan
- Department of Breast Oncology, Niigata Cancer Center Hospital, Niigata, Japan
| | - Koichi Hirokaga
- Department of Breast Surgery, Hyogo Cancer Center, Hyogo, Japan
| | - Ken Yamaguchi
- Department of Radiology, Faculty of Medicine, Saga University, Saga, Japan
| | - Akihiko Suzuki
- Division of Breast and Endocrine Surgery, Tohoku Medical and Pharmaceutical University, Sendai, Japan
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9
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Arian A, Seyed-Kolbadi FZ, Yaghoobpoor S, Ghorani H, Saghazadeh A, Ghadimi DJ. Diagnostic accuracy of intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) MRI to differentiate benign from malignant breast lesions: A systematic review and meta-analysis. Eur J Radiol 2023; 167:111051. [PMID: 37632999 DOI: 10.1016/j.ejrad.2023.111051] [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: 03/11/2023] [Revised: 08/01/2023] [Accepted: 08/14/2023] [Indexed: 08/28/2023]
Abstract
PURPOSE Magnetic resonance imaging (MRI) can reduce the need for unnecessary invasive diagnostic tests by nearly half. In this meta-analysis, we investigated the diagnostic accuracy of intravoxel incoherent motion modeling (IVIM) and dynamic contrast-enhanced (DCE) MRI in differentiating benign from malignant breast lesions. METHOD We systematically searched PubMed, EMBASE, and Scopus. We included English articles reporting diagnostic accuracy for both sequences in differentiating benign from malignant breast lesions. Articles were assessed by quality assessment of diagnostic accuracy studies-2 (QUADAS-2) questionnaire. We used a bivariate effects model for standardized mean difference (SMD) analysis and diagnostic test accuracy analysis. RESULTS Ten studies with 537 patients and 707 (435 malignant and 272 benign) lesions were included. The D, f, Ktrans, and Kep mean values significantly differ between benign and malignant lesions. The pooled sensitivity (95 % confidence interval) and specificity were 86.2 % (77.9 %-91.7 %) and 70.3 % (56.5 %-81.1 %) for IVIM, and 93.8 % (85.3 %-97.5 %) and 68.1 % (52.7 %-80.4 %) for DCE, respectively. Combined IVIM and DCE depicted the highest area under the curve of 0.94, with a sensitivity and specificity of 91.8 % (82.8 %-96.3 %) and 87.6 % (73.8 %-94.7 %), respectively. CONCLUSIONS Combined IVIM and DCE had the highest diagnostic accuracy, and multiparametric MRI may help reduce unnecessary benign breast biopsy.
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Affiliation(s)
- Arvin Arian
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran; Cancer Research Institute, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Zahra Seyed-Kolbadi
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran; Evidence-Based Medicine Study Center, Hormozgan University of Medical Sciences, Bandar Abass, Iran
| | - Shirin Yaghoobpoor
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran; Student Research Committee, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hamed Ghorani
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amene Saghazadeh
- Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran; Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Delaram J Ghadimi
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Quantitative MR Imaging and Spectroscopy Group (QMISG), Tehran University of Medical Sciences, Tehran, Iran.
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Nicosia L, Bozzini AC, Pesapane F, Rotili A, Marinucci I, Signorelli G, Frassoni S, Bagnardi V, Origgi D, De Marco P, Abiuso I, Sangalli C, Balestreri N, Corso G, Cassano E. Breast Digital Tomosynthesis versus Contrast-Enhanced Mammography: Comparison of Diagnostic Application and Radiation Dose in a Screening Setting. Cancers (Basel) 2023; 15:2413. [PMID: 37173880 PMCID: PMC10177523 DOI: 10.3390/cancers15092413] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/15/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
This study aims to evaluate the Average Glandular Dose (AGD) and diagnostic performance of CEM versus Digital Mammography (DM) as well as versus DM plus one-view Digital Breast Tomosynthesis (DBT), which were performed in the same patients at short intervals of time. A preventive screening examination in high-risk asymptomatic patients between 2020 and 2022 was performed with two-view Digital Mammography (DM) projections (Cranio Caudal and Medio Lateral) plus one Digital Breast Tomosynthesis (DBT) projection (mediolateral oblique, MLO) in a single session examination. For all patients in whom we found a suspicious lesion by using DM + DBT, we performed (within two weeks) a CEM examination. AGD and compression force were compared between the diagnostic methods. All lesions identified by DM + DBT were biopsied; then, we assessed whether lesions found by DBT were also highlighted by DM alone and/or by CEM. We enrolled 49 patients with 49 lesions in the study. The median AGD was lower for DM alone than for CEM (3.41 mGy vs. 4.24 mGy, p = 0.015). The AGD for CEM was significantly lower than for the DM plus one single projection DBT protocol (4.24 mGy vs. 5.55 mGy, p < 0.001). We did not find a statistically significant difference in the median compression force between the CEM and DM + DBT. DM + DBT allows the identification of one more invasive neoplasm one in situ lesion and two high-risk lesions, compared to DM alone. The CEM, compared to DM + DBT, failed to identify only one of the high-risk lesions. According to these results, CEM could be used in the screening of asymptomatic high-risk patients.
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Affiliation(s)
- Luca Nicosia
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Anna Carla Bozzini
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Filippo Pesapane
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Anna Rotili
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Irene Marinucci
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Giulia Signorelli
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Samuele Frassoni
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy
| | - Daniela Origgi
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, Via Ripamonti 435, 20141 Milan, Italy
| | - Paolo De Marco
- Medical Physics Unit, IEO European Institute of Oncology IRCCS, Via Ripamonti 435, 20141 Milan, Italy
| | - Ida Abiuso
- Radiology Department, Università Degli Studi di Torino, 10124 Turin, Italy
| | - Claudia Sangalli
- Data Management, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Nicola Balestreri
- Department of Radiology, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
| | - Giovanni Corso
- Division of Breast Surgery, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
- European Cancer Prevention Organization, 20122 Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
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11
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Iima M, Le Bihan D. The road to breast cancer screening with diffusion MRI. Front Oncol 2023; 13:993540. [PMID: 36895474 PMCID: PMC9989267 DOI: 10.3389/fonc.2023.993540] [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: 07/13/2022] [Accepted: 01/10/2023] [Indexed: 02/23/2023] Open
Abstract
Breast cancer is the leading cause of cancer in women with a huge medical, social and economic impact. Mammography (MMG) has been the gold standard method until now because it is relatively inexpensive and widely available. However, MMG suffers from certain limitations, such as exposure to X-rays and difficulty of interpretation in dense breasts. Among other imaging methods, MRI has clearly the highest sensitivity and specificity, and breast MRI is the gold standard for the investigation and management of suspicious lesions revealed by MMG. Despite this performance, MRI, which does not rely on X-rays, is not used for screening except for a well-defined category of women at risk, because of its high cost and limited availability. In addition, the standard approach to breast MRI relies on Dynamic Contrast Enhanced (DCE) MRI with the injection of Gadolinium based contrast agents (GBCA), which have their own contraindications and can lead to deposit of gadolinium in tissues, including the brain, when examinations are repeated. On the other hand, diffusion MRI of breast, which provides information on tissue microstructure and tumor perfusion without the use of contrast agents, has been shown to offer higher specificity than DCE MRI with similar sensitivity, superior to MMG. Diffusion MRI thus appears to be a promising alternative approach to breast cancer screening, with the primary goal of eliminating with a very high probability the existence of a life-threatening lesion. To achieve this goal, it is first necessary to standardize the protocols for acquisition and analysis of diffusion MRI data, which have been found to vary largely in the literature. Second, the accessibility and cost-effectiveness of MRI examinations must be significantly improved, which may become possible with the development of dedicated low-field MRI units for breast cancer screening. In this article, we will first review the principles and current status of diffusion MRI, comparing its clinical performance with MMG and DCE MRI. We will then look at how breast diffusion MRI could be implemented and standardized to optimize accuracy of results. Finally, we will discuss how a dedicated, low-cost prototype of breast MRI system could be implemented and introduced to the healthcare market.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat á l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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12
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Xie H, Lei Y, Wang T, Roper J, Axente M, Bradley JD, Liu T, Yang X. Magnetic resonance imaging contrast enhancement synthesis using cascade networks with local supervision. Med Phys 2022; 49:3278-3287. [PMID: 35229344 PMCID: PMC11747766 DOI: 10.1002/mp.15578] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/03/2021] [Accepted: 02/22/2022] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Gadolinium-based contrast agents (GBCAs) are widely administrated in MR imaging for diagnostic studies and treatment planning. Although GBCAs are generally thought to be safe, various health and environmental concerns have been raised recently about their use in MR imaging. The purpose of this work is to derive synthetic contrast enhance MR images from unenhanced counterpart images, thereby eliminating the need for GBCAs, using a cascade deep learning workflow that incorporates contour information into the network. METHODS AND MATERIALS The proposed workflow consists of two sequential networks: (1) a retina U-Net, which is first trained to derive semantic features from the non-contrast MR images in representing the tumor regions; and (2) a synthesis module, which is trained after the retina U-Net to take the concatenation of the semantic feature maps and non-contrast MR image as input and to generate the synthetic contrast enhanced MR images. After network training, only the non-contrast enhanced MR images are required for the input in the proposed workflow. The MR images of 369 patients from the multimodal brain tumor segmentation challenge 2020 (BraTS2020) dataset were used in this study to evaluate the proposed workflow for synthesizing contrast enhanced MR images (200 patients for five-fold cross-validation and 169 patients for hold-out test). Quantitative evaluations were conducted by calculating the normalized mean absolute error (NMAE), structural similarity index measurement (SSIM), and Pearson correlation coefficient (PCC). The original contrast enhanced MR images were considered as the ground truth in this analysis. RESULTS The proposed cascade deep learning workflow synthesized contrast enhanced MR images that are not visually differentiable from the ground truth with and without supervision of the tumor contours during the network training. Difference images and profiles of the synthetic contrast enhanced MR images revealed that intensity differences could be observed in the tumor region if the contour information was not incorporated in network training. Among the hold-out test patients, mean values and standard deviations of the NMAE, SSIM, and PCC were 0.063±0.022, 0.991±0.007 and 0.995±0.006, respectively, for the whole brain; and were 0.050±0.025, 0.993±0.008 and 0.999±0.003, respectively, for the tumor contour regions. Quantitative evaluations with five-fold cross-validation and hold-out test showed that the calculated metrics can be significantly enhanced (p-values ≤ 0.002) with the tumor contour supervision in network training. CONCLUSION The proposed workflow was able to generate synthetic contrast enhanced MR images that closely resemble the ground truth images from non-contrast enhanced MR images when the network training included tumor contours. These results suggest that it may be possible to minimize the use of GBCAs in cranial MR imaging studies.
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Affiliation(s)
- Huiqiao Xie
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Yang Lei
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Tonghe Wang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Justin Roper
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Marian Axente
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Jeffrey D Bradley
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Tian Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
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13
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Lotz M, Ghebremichael M, Chervinsky K, Zorc T, Brenner C, Bousvaros G, Pories SE. Effective Surveillance of High-Risk Women. Clin Breast Cancer 2022; 22:e263-e269. [PMID: 34429241 DOI: 10.1016/j.clbc.2021.07.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 06/28/2021] [Accepted: 07/24/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND This study addresses the effectiveness of risk models and screening breast magnetic resonance imaging (MRI) in women who have atypical hyperplasia (AH), lobular carcinoma in situ (LCIS), or a family history of breast cancer, but not a genetic mutation. PATIENTS AND METHODS A retrospective review of 444 women who had 458 breast screening MRIs at a community teaching hospital over a 12-month period between March 25, 2014 and March 31, 2015 was performed. The patients underwent high risk screening with breast MRIs alternating with mammograms every 6 months. After excluding patients with prior breast or ovarian cancer, genetic mutations, and chest wall radiation, 200 remaining patients constituted the study cohort. Over the following 5 years, the patients were screened with MRIs alternating with mammograms every 6 months. A total of 961 total MRI screenings were performed over the entire 5-year period of the study. RESULTS A total of 200 women fit the study criteria. Of these 103 had a prior history of AH or LCIS. Over the 5-year period, 60 women dropped out of the screening regimen, 6 patients were diagnosed with breast cancer on screening MRIs, and 2 additional patients were diagnosed with breast cancer on screening mammograms. Surprisingly, the highest Tyrer-Cuzick (T-C) scores did not correlate with increased development of breast cancers in our population. CONCLUSIONS This study shows that there is wide variation in the results of risk assessment models. Risk models may overestimate breast cancer risk, suggesting that re-evaluation of current risk assessment and screening protocols is warranted.
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Affiliation(s)
- Margaret Lotz
- Hoffman Breast Center, Mount Auburn Hospital, Cambridge, MA
| | - Musie Ghebremichael
- Harvard Medical School, Boston, MA; The Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA
| | | | - Thomas Zorc
- Hoffman Breast Center, Mount Auburn Hospital, Cambridge, MA
| | | | | | - Susan E Pories
- Hoffman Breast Center, Mount Auburn Hospital, Cambridge, MA; Harvard Medical School, Boston, MA.
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14
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Neal CH. Screening Breast MRI and Gadolinium Deposition: Cause for Concern? JOURNAL OF BREAST IMAGING 2022; 4:10-18. [PMID: 38422412 DOI: 10.1093/jbi/wbab074] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Indexed: 03/02/2024]
Abstract
Gadolinium-based contrast agents (GBCAs) have been used worldwide for over 30 years and have enabled lifesaving diagnoses. Contrast-enhanced breast MRI is frequently used as supplemental screening for women with an elevated lifetime risk of breast cancer. Data have emerged that indicate a fractional amount of administered gadolinium is retained in the bone, skin, solid organs, and brain tissues of patients with normal renal function, although there are currently no reliable data regarding the clinical or biological significance of this retention. Linear GBCAs are associated with a higher risk of gadolinium retention than macrocyclic agents. Over the course of their lives, screened women may receive high cumulative doses of GBCA. Therefore, as breast MRI screening utilization increases, thoughtful use of GBCA is indicated in this patient population.
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Affiliation(s)
- Colleen H Neal
- ProMedica Toledo Hospital, ProMedica Breast Care, Toledo, OH, USA
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15
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Lee SC, Hovanessian-Larsen L, Stahl D, Cen S, Lei X, Desai B, Yamashita M. Accuracy of contrast-enhanced spectral mammography compared with MRI for invasive breast cancers: Prospective study in population of predominantly underrepresented minorities. Clin Imaging 2021; 80:364-370. [PMID: 34509973 DOI: 10.1016/j.clinimag.2021.08.015] [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: 04/07/2021] [Revised: 07/01/2021] [Accepted: 08/23/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES This prospective study compares contrast-enhanced spectral mammography (CESM) with contrast-enhanced breast MRI in assessing the extent of newly diagnosed breast cancer in a multiethnic cohort. METHODS This study includes 41 patients with invasive breast cancer detected by mammography or conventional ultrasound imaging from May 2017 to March 2020. CESM and MRI scans were performed prior to any treatment. Results are compared with each other and to histopathology. Detection of the malignant lesion was assessed by sensitivity, specificity, PPV, NPV. Consistency of malignant tumor size measurement was compared between modalities using Intraclass Correlation Coefficient (ICC). RESULTS In a multiethnic cohort with over 65% Hispanic and African-American women, the sensitivity of detecting malignant lesions for CESM is 93.1% (77.23%, 99.15%) and MRI is 96.55% (82.24%, 99.91%). The PPV for CESM 96.43% (81.65%, 99.91%) is better compared to MRI 82.35% (65.47%, 93.24%). CESM is as effective as MRI in evaluating index cancers and multifocal/multicentric/contralateral disease. CESM has greater specificity and PPV since MRI tends to overcall benign lesions. There is a good agreement of tumor size between CESM to surgery and MRI to surgery with ICC of 0.85 (95% CI 0.69, 0.93) and 0.87 (95% CI 0.74, 0.94), respectively. There is good agreement of malignancy detection between CESM and MRI with Kappa of 0.74 (95% CI 0.52, 0.95). CONCLUSIONS CESM is an effective imaging modality for evaluating the extent of disease in newly diagnosed invasive breast cancers and a good alternative to MRI in a multiethnic population.
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Affiliation(s)
- Sandy C Lee
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Linda Hovanessian-Larsen
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Daniel Stahl
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Steven Cen
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Xiaomeng Lei
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Bhushan Desai
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
| | - Mary Yamashita
- Department of Radiology, Keck School of Medicine, University of Southern California, 1200 North State Street, 3rd Floor Room 3750A, Los Angeles, CA 90033, United States of America.
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16
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Bonelli LA, Calabrese M, Belli P, Corcione S, Losio C, Montemezzi S, Pediconi F, Petrillo A, Zuiani C, Camera L, Carbonaro LA, Cozzi A, De Falco Alfano D, Gristina L, Panzeri M, Poirè I, Schiaffino S, Tosto S, Trecate G, Trimboli RM, Valdora F, Viganò S, Sardanelli F. MRI versus Mammography plus Ultrasound in Women at Intermediate Breast Cancer Risk: Study Design and Protocol of the MRIB Multicenter, Randomized, Controlled Trial. Diagnostics (Basel) 2021; 11:diagnostics11091635. [PMID: 34573983 PMCID: PMC8469187 DOI: 10.3390/diagnostics11091635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 08/27/2021] [Accepted: 08/31/2021] [Indexed: 12/28/2022] Open
Abstract
In women at high/intermediate lifetime risk of breast cancer (BC-LTR), contrast-enhanced magnetic resonance imaging (MRI) added to mammography ± ultrasound (MX ± US) increases sensitivity but decreases specificity. Screening with MRI alone is an alternative and potentially more cost-effective strategy. Here, we describe the study protocol and the characteristics of enrolled patients for MRIB feasibility, multicenter, randomized, controlled trial, which aims to compare MRI alone versus MX+US in women at intermediate breast cancer risk (aged 40-59, with a 15-30% BC-LTR and/or extremely dense breasts). Two screening rounds per woman were planned in ten centers experienced in MRI screening, the primary endpoint being the rate of cancers detected in the 2 arms after 5 years of follow-up. From July 2013 to November 2015, 1254 women (mean age 47 years) were enrolled: 624 were assigned to MX+US and 630 to MRI. Most of them were aged below 50 (72%) and premenopausal (45%), and 52% used oral contraceptives. Among postmenopausal women, 15% had used hormone replacement therapy. Breast and/or ovarian cancer in mothers and/or sisters were reported by 37% of enrolled women, 79% had extremely dense breasts, and 41% had a 15-30% BC-LTR. The distribution of the major determinants of breast cancer risk profiles (breast density and family history of breast and ovarian cancer) of enrolled women varied across centers.
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Affiliation(s)
- Luigina Ada Bonelli
- Unit of Clinical Epidemiology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy;
- Correspondence: ; Tel.: +39-010-5558502
| | - Massimo Calabrese
- Unit of Diagnostic Senology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy; (M.C.); (L.G.); (S.T.); (F.V.)
| | - Paolo Belli
- Department of Radiological, Radiotherapic and Hematological Sciences, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Università Cattolica del Sacro Cuore, 00168 Roma, Italy;
| | - Stefano Corcione
- Breast Imaging Unit, Arcispedale Sant’Anna, Azienda Ospedaliero-Universitaria di Ferrara, 44124 Cona, Italy; (S.C.); (D.D.F.A.)
| | - Claudio Losio
- Unit of Senology, IRCCS Ospedale San Raffaele, 20132 Milano, Italy; (C.L.); (M.P.)
| | - Stefania Montemezzi
- Unit of Radiology BT, Azienda Ospedaliera Universitaria Integrata, 37126 Verona, Italy; (S.M.); (L.C.)
| | - Federica Pediconi
- Department of Radiological, Oncological and Pathological Sciences, Università degli Studi “La Sapienza”, 00161 Roma, Italy;
| | - Antonella Petrillo
- Radiology Unit, Istituto Nazionale dei Tumori IRCCS Fondazione G. Pascale, 80131 Napoli, Italy;
| | - Chiara Zuiani
- Institute of Radiology, Azienda Ospedaliera Universitaria “Santa Maria della Misericordia”, Università degli Studi di Udine, 33100 Udine, Italy;
| | - Lucia Camera
- Unit of Radiology BT, Azienda Ospedaliera Universitaria Integrata, 37126 Verona, Italy; (S.M.); (L.C.)
| | - Luca Alessandro Carbonaro
- Unit of Radiology, IRCCS Policlinico San Donato, 20097 San Donato Milanese, Italy; (L.A.C.); (S.S.); (F.S.)
- Department of Radiology, Grande Ospedale Metropolitano Niguarda, 20162 Milano, Italy
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, 20122 Milano, Italy
| | - Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milano, Italy; (A.C.); (R.M.T.)
| | - Daniele De Falco Alfano
- Breast Imaging Unit, Arcispedale Sant’Anna, Azienda Ospedaliero-Universitaria di Ferrara, 44124 Cona, Italy; (S.C.); (D.D.F.A.)
- Mammography Center, Radiology Unit, Policlinico Sant’Orsola–Malpighi, 40138 Bologna, Italy
| | - Licia Gristina
- Unit of Diagnostic Senology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy; (M.C.); (L.G.); (S.T.); (F.V.)
| | - Marta Panzeri
- Unit of Senology, IRCCS Ospedale San Raffaele, 20132 Milano, Italy; (C.L.); (M.P.)
| | - Ilaria Poirè
- Unit of Clinical Epidemiology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy;
| | - Simone Schiaffino
- Unit of Radiology, IRCCS Policlinico San Donato, 20097 San Donato Milanese, Italy; (L.A.C.); (S.S.); (F.S.)
| | - Simona Tosto
- Unit of Diagnostic Senology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy; (M.C.); (L.G.); (S.T.); (F.V.)
| | - Giovanna Trecate
- Department of Diagnostic Imaging, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy; (G.T.); (S.V.)
| | - Rubina Manuela Trimboli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milano, Italy; (A.C.); (R.M.T.)
- Breast Imaging and Screening Unit, Department of Radiology, Humanitas Clinical and Research Center—IRCCS, 20089 Rozzano, Italy
| | - Francesca Valdora
- Unit of Diagnostic Senology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy; (M.C.); (L.G.); (S.T.); (F.V.)
| | - Sara Viganò
- Department of Diagnostic Imaging, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milano, Italy; (G.T.); (S.V.)
| | - Francesco Sardanelli
- Unit of Radiology, IRCCS Policlinico San Donato, 20097 San Donato Milanese, Italy; (L.A.C.); (S.S.); (F.S.)
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milano, Italy; (A.C.); (R.M.T.)
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17
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Woolen SA, Troost JP, Khalatbari S, Pujara AC, McDonald JS, McDonald RJ, Shankar P, Lewin AA, Melsaether AN, Westphal SM, Patterson KH, Nettles A, Welby JP, Patel PP, Kiros N, Piccoli L, Davenport MS. Prospective multicenter assessment of patient preferences for properties of gadolinium-based contrast media and their potential socioeconomic impact in a screening breast MRI setting. Eur Radiol 2021; 31:9139-9149. [PMID: 34047845 PMCID: PMC8160413 DOI: 10.1007/s00330-021-07982-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 02/19/2021] [Accepted: 04/01/2021] [Indexed: 12/01/2022]
Abstract
Objective It is unknown how patients prioritize gadolinium-based contrast media (GBCM) benefits (detection sensitivity) and risks (reactions, gadolinium retention, cost). The purpose of this study is to measure preferences for properties of GBCM in women at intermediate or high risk of breast cancer undergoing annual screening MRI. Methods An institutional reviewed board-approved prospective discrete choice conjoint survey was administered to patients at intermediate or high risk for breast cancer undergoing screening MRI at 4 institutions (July 2018–March 2020). Participants were given 15 tasks and asked to choose which of two hypothetical GBCM they would prefer. GBCMs varied by the following attributes: sensitivity for cancer detection (80–95%), intracranial gadolinium retention (1–100 molecules per 100 million administered), severe allergic-like reaction rate (1–19 per 100,000 administrations), mild allergic-like reaction rate (10–1000 per 100,000 administrations), out-of-pocket cost ($25–$100). Attribute levels were based on published values of existing GBCMs. Hierarchical Bayesian analysis was used to derive attribute “importance.” Preference shares were determined by simulation. Results Response (87% [247/284]) and completion (96% [236/247]) rates were excellent. Sensitivity (importance = 44.3%, 95% confidence interval = 42.0–46.7%) was valued more than GBCM-related risks (mild allergic-like reaction risk (19.5%, 17.9–21.1%), severe allergic-like reaction risk (17.0%, 15.8–18.1%), intracranial gadolinium retention (11.6%, 10.5–12.7%), out-of-pocket expense (7.5%, 6.8–8.3%)). Lower income participants placed more importance on cost and less on sensitivity (p < 0.01). A simulator is provided that models GBCM preference shares by GBCM attributes and competition. Conclusions Patients at intermediate or high risk for breast cancer undergoing MRI screening prioritize cancer detection over GBCM-related risks, and prioritize reaction risks over gadolinium retention. Key Points • Among women undergoing annual breast MRI screening, cancer detection sensitivity (attribute “importance,” 44.3%) was valued more than GBCM-related risks (mild allergic reaction risk 19.5%, severe allergic reaction risk 17.0%, intracranial gadolinium retention 11.6%, out-of-pocket expense 7.5%). • Prospective four-center patient preference data have been incorporated into a GBCM choice simulator that allows users to input GBCM properties and calculate patient preference shares for competitor GBCMs. • Lower-income women placed more importance on out-of-pocket cost and less importance on cancer detection (p < 0.01) when prioritizing GBCM properties. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-07982-y.
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Affiliation(s)
- Sean A Woolen
- Department of Radiology and Biomedical Imaging, UCSF, 350 Parnassus, San Francisco, CA, 94117, USA.
| | - Jonathan P Troost
- Michigan Institute for Clinical & Health Research, Michigan Medicine, Ann Arbor, MI, USA
| | - Shokoufeh Khalatbari
- Michigan Institute for Clinical & Health Research, Michigan Medicine, Ann Arbor, MI, USA
| | - Akshat C Pujara
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Prasad Shankar
- Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA
- Michigan Radiology Quality Collaborative, Michigan Medicine, Ann Arbor, MI, USA
| | - Alana A Lewin
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
| | | | - Steven M Westphal
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Katherine H Patterson
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ashley Nettles
- Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA
| | - John P Welby
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Neud Kiros
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Lisa Piccoli
- Department of Radiology, Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
| | - Matthew S Davenport
- Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA
- Michigan Radiology Quality Collaborative, Michigan Medicine, Ann Arbor, MI, USA
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18
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Suh J, Kim JH, Kim SY, Cho N, Kim DH, Kim R, Kim ES, Jang MJ, Ha SM, Lee SH, Chang JM, Moon WK. Noncontrast-Enhanced MR-Based Conductivity Imaging for Breast Cancer Detection and Lesion Differentiation. J Magn Reson Imaging 2021; 54:631-645. [PMID: 33894088 DOI: 10.1002/jmri.27655] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/01/2021] [Accepted: 04/01/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND There is increasing interest in noncontrast-enhanced MRI due to safety concerns for gadolinium contrast agents. PURPOSE To investigate the clinical feasibility of MR-based conductivity imaging for breast cancer detection and lesion differentiation. STUDY TYPE Prospective. SUBJECTS One hundred and ten women, with 112 known cancers and 17 benign lesions (biopsy-proven), scheduled for preoperative MRI. FIELD STRENGTH/SEQUENCE Non-fat-suppressed T2-weighted turbo spin-echo sequence (T2WI), dynamic contrast-enhanced MRI and diffusion-weighted imaging (DWI) at 3T. ASSESSMENT Cancer detectability on each imaging modality was qualitatively evaluated on a per-breast basis: the conductivity maps derived from T2WI were independently reviewed by three radiologists (R1-R3). T2WI, DWI, and pre-operative digital mammography were independently reviewed by three other radiologists (R4-R6). Conductivity and apparent diffusion coefficient (ADC) measurements (mean, minimum, and maximum) were performed for 112 cancers and 17 benign lesions independently by two radiologists (R1 and R2). Tumor size was measured from surgical specimens. STATISTICAL TESTS Cancer detection rates were compared using generalized estimating equations. Multivariable logistic regression analysis was performed to identify factors associated with cancer detectability. Discriminating ability of conductivity and ADC was evaluated by using the areas under the receiver operating characteristic curve (AUC). RESULTS Conductivity imaging showed lower cancer detection rates (20%-32%) compared to T2WI (62%-71%), DWI (85%-90%), and mammography (79%-88%) (all P < 0.05). Fatty breast on MRI (odds ratio = 11.8, P < 0.05) and invasive tumor size (odds ratio = 1.7, P < 0.05) were associated with cancer detectability of conductivity imaging. The maximum conductivity showed comparable ability to the mean ADC in discriminating between cancers and benign lesions (AUC = 0.67 [95% CI: 0.59, 0.75] vs. 0.84 [0.76, 0.90], P = 0.06 (R1); 0.65 [0.56, 0.73] vs. 0.82 [0.74, 0.88], P = 0.07 (R2)). DATA CONCLUSION Although conductivity imaging showed suboptimal performance in breast cancer detection, the quantitative measurement of conductivity showed the potential for lesion differentiation. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- June Suh
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - 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
| | - Nariya Cho
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Rihyeon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun Sil Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Myoung-Jin Jang
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Min Ha
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Su Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jung Min Chang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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19
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Rahbar H, Partridge SC. Editorial on "Diffusion-Weighted Double-Echo Steady-State with a 3D Cones Trajectory for Non-Contrast-Enhanced Breast MRI". J Magn Reson Imaging 2021; 53:1606-1607. [PMID: 33554380 DOI: 10.1002/jmri.27524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 11/06/2022] Open
Affiliation(s)
- Habib Rahbar
- Department of Radiology, Seattle Cancer Care Alliance, University of Washington School of Medicine, Seattle, Washington, USA
| | - Savannah C Partridge
- Department of Radiology, Seattle Cancer Care Alliance, University of Washington School of Medicine, Seattle, Washington, USA
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20
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Spear GG, Mendelson EB. Automated breast ultrasound: Supplemental screening for average-risk women with dense breasts. Clin Imaging 2020; 76:15-25. [PMID: 33548888 DOI: 10.1016/j.clinimag.2020.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 11/24/2020] [Accepted: 12/17/2020] [Indexed: 11/25/2022]
Abstract
OBJECTIVE We review ultrasound (US) options for supplemental breast cancer screening of average risk women with dense breasts. CONCLUSION Performance data of physician-performed handheld US (HHUS), technologist-performed HHUS, and automated breast ultrasound (AUS) indicate that all are appropriate for adjunctive screening. Volumetric 3D acquisitions, reduced operator dependence, protocol standardization, reliable comparison with previous studies, independence of performance and interpretation, and whole breast depiction on coronal view may favor selection of AUS. Important considerations are workflow adjustments for physicians and staff.
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Affiliation(s)
- Georgia Giakoumis Spear
- NorthShore University HealthSystem, The University of Chicago Pritzker School of Medicine, United States of America.
| | - Ellen B Mendelson
- Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America
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21
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Cozzi A, Schiaffino S, Giorgi Rossi P, Sardanelli F. Breast cancer screening: in the era of personalized medicine, age is just a number. Quant Imaging Med Surg 2020; 10:2401-2407. [PMID: 33269240 DOI: 10.21037/qims-2020-26] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy
| | - Simone Schiaffino
- Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy
| | - Paolo Giorgi Rossi
- Epidemiology Unit, Azienda USL - IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy.,Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy
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22
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Cozzi A, Buragina G, Spinelli D, Schiaffino S, Zanardo M, Di Leo G, Carbonaro LA, Sardanelli F. Accuracy and inter-reader agreement of breast MRI for cancer staging using 0.08 mmol/kg of gadobutrol. Clin Imaging 2020; 72:154-161. [PMID: 33249403 DOI: 10.1016/j.clinimag.2020.11.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 10/13/2020] [Accepted: 11/08/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Evidence on gadolinium brain accumulation after contrast-enhanced MRI prompted research in dose reduction. PURPOSE To estimate accuracy and inter-reader reproducibility of tumor size measurement in breast MRI using 0.08 mmol/kg of gadobutrol. METHODS We retrospectively analyzed all women who underwent 1.5-T breast MRI for cancer staging at our department with 0.08 mmol/kg of gadobutrol. Two readers (R1 and R2, 12 and 3 years-experience) measured the largest lesion diameter. Accuracy was estimated both as correlation with pathology and rate of absolute (>5 mm) overestimation and underestimation, inter-reader reproducibility using the Bland-Altman method. Data are given as median and interquartile range. RESULTS Thirty-six patients were analyzed (median age 56 years, 49-66) for a total of 38 lesions, 24 (63%) mass enhancement, 14 (37%) non-mass enhancement. Histopathological median size (mm) of all lesions was 15 (9-25): 13 (9-19) for mass lesions, 19 (11-39) for non-mass lesions. On MRI, R1 measured (mm) 14 (10-22) for all lesions, 13 (10-19) for mass lesions, 19 (11-49) for non-mass lesions. MRI-pathology correlation was very high for all lesion categories (ρ ≥ 0.766). On MRI, R1 overestimated lesion size in 6 cases (16%), and underestimated in 3 (8%); R2, overestimated 7 cases (18%) and underestimated 3 cases (8%). At inter-reader reproducibility analysis (mm): bias 0.9, coefficient of reproducibility 13 for all lesions; -0.1 and 6 for mass lesions; 2.5 and 20 for non-mass lesions. CONCLUSIONS Breast MRI may be performed using 0.08 mmol/kg of gadobutrol with high accuracy and acceptable inter-reader agreement.
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Affiliation(s)
- Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.
| | - Giuseppe Buragina
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milano, Italy.
| | - Diana Spinelli
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milano, Italy.
| | - Simone Schiaffino
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy.
| | - Moreno Zanardo
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.
| | - Giovanni Di Leo
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy.
| | | | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy.
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23
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Cyr AE, Sharma R. Forewarned Is Forearmed: Can Better Patient Counseling Increase MRI Utilization in High-Risk Women? Ann Surg Oncol 2020; 27:3567-3569. [DOI: 10.1245/s10434-020-08910-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 07/08/2020] [Indexed: 11/18/2022]
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24
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Zanardo M, Sardanelli F, Rainford L, Monti CB, Murray JG, Secchi F, Cradock A. Technique and protocols for cardiothoracic time-resolved contrast-enhanced magnetic resonance angiography sequences: a systematic review. Clin Radiol 2020; 76:156.e9-156.e18. [PMID: 33008622 DOI: 10.1016/j.crad.2020.08.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 08/24/2020] [Indexed: 12/21/2022]
Abstract
AIM To review contrast medium administration protocols used for cardiothoracic applications of time-resolved, contrast-enhanced magnetic resonance angiography (MRA) sequences. MATERIALS AND METHODS A systematic search of the literature (Medline/EMBASE) was performed to identify articles utilising time-resolved MRA sequences, focusing on type of sequence, adopted technical parameters, contrast agent (CA) issues, and acquisition workflow. Study design, year of publication, population, magnetic field strength, type, dose, and injection parameters of CA, as well as technical parameters of time-resolved MRA sequences were extracted. RESULTS Of 117 retrieved articles, 16 matched the inclusion criteria. The study design was prospective in 9/16 (56%) articles, and study population ranged from 5 to 185 patients, for a total of 506 patients who underwent cardiothoracic time-resolved MRA. Magnetic field strength was 1.5 T in 13/16 (81%), and 3 T in 3/16 (19%) articles. The administered CA was gadobutrol (Gadovist) in 6/16 (37%) articles, gadopentetate dimeglumine (Magnevist) in 5/16 (31%), gadobenate dimeglumine (MultiHance) in 2/16 (13%), gadodiamide (Omniscan) in 2/16 (13%), gadofosveset trisodium (Ablavar, previously Vasovist) in 1/16 (6%). CA showed highly variable doses among studies: fixed amount or based on patient body weight (0.02-0.2 mmol/kg) and was injected with a flow rate ranging 1-5 ml/s. Sequences were TWIST in 13/16 (81%), TRICKS in 2/16 (13%), and CENTRA 1/16 articles (6%). CONCLUSION Time-resolved MRA sequences were adopted in different clinical settings with a large spectrum of technical approaches, mostly in association with different CA dose, type, and injection method. Further studies in relation to specific clinical indications are warranted to provide a common standardised acquisition protocol.
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Affiliation(s)
- M Zanardo
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy.
| | - F Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy
| | - L Rainford
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
| | - C B Monti
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
| | - J G Murray
- Department of Radiology, Mater Misericordiae University Hospital, Dublin 7, Ireland
| | - F Secchi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy
| | - A Cradock
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
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25
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Blair VR, McLeod M, Carneiro F, Coit DG, D'Addario JL, van Dieren JM, Harris KL, Hoogerbrugge N, Oliveira C, van der Post RS, Arnold J, Benusiglio PR, Bisseling TM, Boussioutas A, Cats A, Charlton A, Schreiber KEC, Davis JL, Pietro MD, Fitzgerald RC, Ford JM, Gamet K, Gullo I, Hardwick RH, Huntsman DG, Kaurah P, Kupfer SS, Latchford A, Mansfield PF, Nakajima T, Parry S, Rossaak J, Sugimura H, Svrcek M, Tischkowitz M, Ushijima T, Yamada H, Yang HK, Claydon A, Figueiredo J, Paringatai K, Seruca R, Bougen-Zhukov N, Brew T, Busija S, Carneiro P, DeGregorio L, Fisher H, Gardner E, Godwin TD, Holm KN, Humar B, Lintott CJ, Monroe EC, Muller MD, Norero E, Nouri Y, Paredes J, Sanches JM, Schulpen E, Ribeiro AS, Sporle A, Whitworth J, Zhang L, Reeve AE, Guilford P. Hereditary diffuse gastric cancer: updated clinical practice guidelines. Lancet Oncol 2020; 21:e386-e397. [PMID: 32758476 DOI: 10.1016/s1470-2045(20)30219-9] [Citation(s) in RCA: 250] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 03/26/2020] [Accepted: 03/31/2020] [Indexed: 02/07/2023]
Abstract
Hereditary diffuse gastric cancer (HDGC) is an autosomal dominant cancer syndrome that is characterised by a high prevalence of diffuse gastric cancer and lobular breast cancer. It is largely caused by inactivating germline mutations in the tumour suppressor gene CDH1, although pathogenic variants in CTNNA1 occur in a minority of families with HDGC. In this Policy Review, we present updated clinical practice guidelines for HDGC from the International Gastric Cancer Linkage Consortium (IGCLC), which recognise the emerging evidence of variability in gastric cancer risk between families with HDGC, the growing capability of endoscopic and histological surveillance in HDGC, and increased experience of managing long-term sequelae of total gastrectomy in young patients. To redress the balance between the accessibility, cost, and acceptance of genetic testing and the increased identification of pathogenic variant carriers, the HDGC genetic testing criteria have been relaxed, mainly through less restrictive age limits. Prophylactic total gastrectomy remains the recommended option for gastric cancer risk management in pathogenic CDH1 variant carriers. However, there is increasing confidence from the IGCLC that endoscopic surveillance in expert centres can be safely offered to patients who wish to postpone surgery, or to those whose risk of developing gastric cancer is not well defined.
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Affiliation(s)
- Vanessa R Blair
- Department of Surgery, University of Auckland, Auckland, New Zealand; St Marks Breast Centre, Auckland, New Zealand
| | - Maybelle McLeod
- Kimihauora Health and Research Clinic, Mt Maunganui, New Zealand
| | - Fátima Carneiro
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | - Daniel G Coit
- Memorial Sloan Kettering Cancer Center and Weill Cornell Medical School, New York, NY, USA
| | | | - Jolanda M van Dieren
- Department of Gastrointestinal Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | - Nicoline Hoogerbrugge
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Carla Oliveira
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | | | - Julie Arnold
- New Zealand Familial Gastrointestinal Cancer Service, Auckland Hospital, Auckland, New Zealand
| | - Patrick R Benusiglio
- Consultation d'Oncogénétique, Unité Fonctionnelle d'Oncogénétique, Département de Génétique, DMU BioGeM, Groupe Hospitalier Pitié-Salpêtrière, Sorbonne Université, Paris, France
| | - Tanya M Bisseling
- Department of Gastroenterology, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Alex Boussioutas
- Department of Medicine, Royal Melbourne Hospital and Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Annemieke Cats
- Department of Gastrointestinal Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Amanda Charlton
- Department of Histopathology, Auckland Hospital, Auckland, New Zealand
| | | | - Jeremy L Davis
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | | | - James M Ford
- Division of Oncology, Departments of Medicine and Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Kimberley Gamet
- Genetic Health Service New Zealand Northern Hub, Auckland Hospital, Auckland, New Zealand
| | - Irene Gullo
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | - Richard H Hardwick
- Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, UK
| | - David G Huntsman
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Pardeep Kaurah
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada; Hereditary Cancer Program, British Columbia Cancer, Vancouver, BC, Canada
| | - Sonia S Kupfer
- Section of Gastroenterology, Nutrition and Hepatology, University of Chicago, Chicago, IL, USA
| | - Andrew Latchford
- St Mark's Hospital, London, UK; Department of Cancer and Surgery, Imperial College, London, UK
| | | | - Takeshi Nakajima
- Department of Clinical Genetic Oncology, Cancer Institute Hospital, Tokyo, Japan
| | - Susan Parry
- New Zealand Familial Gastrointestinal Cancer Service, Auckland Hospital, Auckland, New Zealand
| | - Jeremy Rossaak
- Department of Surgery, Tauranga Hospital, Tauranga, New Zealand
| | - Haruhiko Sugimura
- Department of Tumor Pathology, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Magali Svrcek
- Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Department of Pathology, Hôpital Saint-Antoine, Paris, France
| | - Marc Tischkowitz
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Toshikazu Ushijima
- Division of Epigenomics, National Cancer Centre Research Institute, Tokyo, Japan
| | - Hidetaka Yamada
- Department of Tumor Pathology, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | | | - Adrian Claydon
- Department of Gastroenterology, Tauranga Hospital, Tauranga, New Zealand
| | - Joana Figueiredo
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | - Karyn Paringatai
- Te Tumu School of Māori, Pacific and Indigenous Studies, University of Otago, Dunedin, New Zealand
| | - Raquel Seruca
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | - Nicola Bougen-Zhukov
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Tom Brew
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | | | - Patricia Carneiro
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | | | | | - Erin Gardner
- Kimihauora Health and Research Clinic, Mt Maunganui, New Zealand
| | - Tanis D Godwin
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Katharine N Holm
- Department of Biochemistry and Molecular Medicine, University of California Davis School Of Medicine, Davis, CA, USA
| | - Bostjan Humar
- Laboratory of the Swiss Hepato-Pancreato-Biliary and Transplantation Centre, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Caroline J Lintott
- Genetic Health Service New Zealand South Island Hub, Christchurch Hospital, Christchurch, New Zealand
| | | | | | - Enrique Norero
- Esophagogastric Surgery Unit, Digestive Surgery Department, Hospital Dr Sotero del Rio, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Yasmin Nouri
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Joana Paredes
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | - João M Sanches
- Institute for Systems and Robotics, Instituto Superior Técnico, Lisbon, Portugal
| | - Emily Schulpen
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Ana S Ribeiro
- Instituto de Investigação e Inovação em Saúde & Institute of Molecular Pathology and Immunology of the University of Porto, Department of Pathology, University of Porto, Porto, Portugal
| | - Andrew Sporle
- Healthier Lives National Science Challenge, University of Otago, Dunedin, New Zealand
| | - James Whitworth
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Liying Zhang
- Department of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Anthony E Reeve
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Parry Guilford
- Cancer Genetics Laboratory, Te Aho Matatū, Department of Biochemistry, University of Otago, Dunedin, New Zealand.
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