Risk-adjusted Breast Cancer Screening Strategies
The incidence of breast cancer is increasing worldwide. Population-based screening is available in many countries but is often not the most efficient use of resources. Therefore, interest in risk-adjusted screening programs has increased in recent years. 1 Models to predict the risk of a woman to develop breast cancer in her lifetime are taking the of individual breast density as well as inherited genetic variants into consideration. 2 In the future, the goal is to be able to make personalized screening authoritative recommendations on when a woman should start and stop screening and how often it should be performed. 1
What do our clinical experts have to say?
In the following videos, clinical experts present the role of breast imaging and artificial intelligence for risk-adjusted breast screening. A special focus is put on breast density and how to measure it objectively.
How did the pandemic harm breast screening programs and what should a return strategy look like?
The patient in the center: The way forward for women with dense breasts
Which breast imaging technologies challenge digital mammography in breast screening?
Risk-adjusted Breast Cancer Screening Strategies (ECR Symposium)
After an introduction by Associate Prof. Dr. Luis Pina (Pamplona/Spain), Dr. Ritse Mann (Nijmegen/Netherlands) and Prof. Dr. Francesco Sardanelli (Milan/Italy) give an overview about risk-adjusted breast cancer screening strategies (ECR Symposium, July 2020).
Personalized Breast Cancer Screening and the Role of Breast Density
Dense Breast and How to Overcome the Radiologist’s “Problem Child” Video
Volumetric Breast Density Analysis in Mammography and Tomosynthesis Video
Related abstracts
Volumetric breast density analysis in mammography and tomosynthesis: brief overview
Hanna Sartor; Malmö, Sweden
High breast density is associated with an increased risk of breast cancer. However, qualitative measurements of breast density by radiologists may vary and be subjective. Automated VBDA was developed to provide objective and reproducible measurements. To explore the possibilities and clinical use of VBDA, previous studies have described the agreement between different methods of measuring volumetric density (e.g., by software such as Volpara and Quantra) and radiologists’ assessments in mammography (e.g., qualitative measurements such as BI-RADS and a visual analogue scale) with varying results. DBT is a promising technique and a potential screening modality, and the possibility to measure breast density on DBT images is important. Our group has previously compared breast density that was measured by radiologists to measurements obtained from an automated VBDA tool from Siemens using the central projection image in DBT. The results suggested that VBDA could be used in DBT in addition to mammography. Taken together, the use of a robust VBDA is important and seems possible in both mammography and DBT, enabling it to be used in individualized screening programs and in breast cancer risk scores.
Learning objectives:
1. To understand the clinical basics of volumetric breast density analysis (VBDA) based on previous studies
2. To acknowledge the difference between radiologists’ assessment of breast density and software measurements
3. To discuss VBDA’s potential use for mammography and digital breast tomosynthesis (DBT) in clinical practice
How did the pandemic harm breast screening
programs and how should a return strategy look like?
Federica Pediconi, Rome, Italy
3 https://www.bcrf.org/breast-cancer-statistics-and-resources/
The biggest questions in breast screening
The patient in the center: The way forward for women with dense breasts
Panagiotis Kapetas, Vienna, Austria – FFDM & Ultrasound
Pascal Baltzer, Vienna, Austria – Abbreviated MRI protocols
Which breast imaging technologies challenge digital mammography in breast screening?
Mireille Broeders, Nijmegen, Netherlands
Sophia Zackrisson, Malmö, Sweden
Sylvia Heywang-Köbrunner, Munich, Germany
Learning objectives:
- What is needed to get new examination methods approved in screening guidelines?
- How will we assess the maturity level of DBT, ABVS and MRI for their potential impact in breast screening?
- Are there mature alternatives to breast imaging?
Risk-based screening and the potential of AI for patient stratification
Ritse Mann; Nijmegen, The Netherlands
Once a women’s risk of developing breast cancer is known, defining an optimal screening strategy becomes important. Such a strategy includes questions on the techniques to use for screening, but should also take into account from what age to screen women, and at what age to stop; when to use highly sensitive screening technologies and when to rely on highly specific ones and so on. This should be placed in perspective in relation to the overall health status of the screened women, and the relative risk of dying from other causes. Moreover, it should take into account relevant costs to both the patient and society.
Recent research in various populations has shown that breast MRI outperforms mammography screening, detecting cancer earlier, and reducing the interval cancer rate. Still selecting patients for such a technique remains a challenge, and it is simply not possible for us to offer the technique to all women at risk. Imaging characteristics may in fact contain a lot of useful information to gauge a woman’s short-term risk of developing breast cancer. Subtle findings, not enough for recall, may be used as an argument for more intensive screening or the application of supplemental screening techniques. It is therefore conceivable that patient selection for supplemental or alternative screening techniques may be performed using characterization of findings present with relatively inexpensive, moderately sensitive, but highly specific screening tools such as mammography. Al applications aimed at automated image analysis may aid in such image-based personification of the screening regimen.
Learning objectives:
- To be aware of the questions that arise in clinical practice when implementing personalized screening
- To understand the relative advantages of common screening techniques
- To appreciate the potential of AI-assisted imaging-based stratification of women to screening cohorts
Strategies for women at average risk:
The new guidelines on breast cancer screening and diagnosis from the European Commission Initiative on Breast Cancer (ECIBC)
Francesco Sardanelli; Milano, Italy
Six principles were followed: a) selection (open call) of an expert panel; b) systematic review of evidence; c) inclusion of patient advocates; d) transparency of conflicts of interest and use of GRADE evidence to determine frameworks; e) recommendations on outcomes relevant to women and rating of the certainty of evidence (CoE); f) stakeholder feedback. A panel of 28 members developed questions and recommendations informed by systematic reviews conducted between 03/2016 and 12/2018 on organized screening of average-risk asymptomatic women:
1) age 40−44, conditional recommendation for not implementing organized screening (moderate CoE);
2) age 45−49, conditional recommendation for digital mammography (DM) organized screening (moderate CoE);
3) aged 50−69, strong recommendation for DM organized screening (moderate CoE); 4) age 70−74, conditional recommendation for DM organized screening (moderate CoE);
5) aged 45−49, conditional recommendation for either biennial or triennial DM (very low CoE);
6-7) age 50−69, strong recommendation against annual DM (very low CoE) and conditional recommendation for biennial DM organized screening over triennial screening (very low CoE);
8-9) age 70−74, strong recommendation against annual DM screening (very low CoE) and conditional recommendation for triennial over biennial DM (very low CoE);
10-11) age 50−69, conditional recommendation for screening with DM alone over tomosynthesis and over DM+tomosynthesis (very low CoE);
12-14) high breast density and negative DM, conditional recommendation against screening with automated breast ultrasonography, handheld ultrasonography, or magnetic resonance imaging over DM alone (very low, low, and very low CoE, respectively).
Update of recommendations was planned.
References: Ann Intern Med 2019 (doi: 10.7326/M18-3445 and 10.7326/M19-2125).
Learning objectives:
1. To know the methodology of the new ECIBC guidelines
2. To be aware of the content of the recommendations of the new ECIBC guideline
3. To be able to implement these recommendations in clinical practice
Personalized breast cancer screening and the role of breast density
Mireille Broeders: Nijmegen, The Netherlands
Breast screening programs today generally offer a mammographic examination every two years to women in a specified age range. Ongoing research is exploring the added value of personalized risk-based screening (i.e., screening strategies tailored to a woman’s individual risk of breast cancer). A vital prerequisite for personalized risk-based screening is a comprehensive breast cancer risk prediction model. The next step is to develop screening regimens for women at varying levels of risk, which may be addressed in several ways: changing starting and stopping ages, changing screening intervals, as well as offering further imaging techniques in addition to digital mammography. Using modeling techniques, the harm-benefit ratios and cost-effectiveness can then be estimated to find the optimal screening strategies. In parallel, it is essential to understand the acceptability of personalized approaches, especially for women at low risk, and the challenges in communication and implementation.
Breast density is an important factor in this research area because it can contribute to risk prediction, but it will also play a role in finding the optimal screening strategy. Automated measures of breast density on digital mammography are being updated rapidly, which will facilitate getting this data for all women in the target population. However, the fact that DBT may replace digital mammography in the near future raises the following questions: How does DBT perform across breast density categories? What is the relationship between automated breast density measures on DBT and breast cancer risk? What is the role of additional imaging modalities when DBT is the screening test?
Learning Objectives:
1. To understand the components of a personalized breast cancer screening program
2. To explore the role of automated breast density estimates in personalized breast cancer screening with tomosynthesis
Dense breast and how to overcome the radiologist’s ”problem child”
Luis Pina; Pamplona, Spain
Learning objectives:
- To become familiar with the limitations of mammography in dense breasts
- To learn the role of tomosynthesis to overcome the limitations of mammography in dense breasts
- To understand the role of breast US in dense breasts
Volumetric breast density analysis in mammography and tomosynthesis: brief overview
Hanna Sartor; Malmö, Sweden
High breast density is associated with an increased risk of breast cancer. However, qualitative measurements of breast density by radiologists may vary and be subjective. Automated VBDA was developed to provide objective and reproducible measurements. To explore the possibilities and clinical use of VBDA, previous studies have described the agreement between different methods of measuring volumetric density (e.g., by software such as Volpara and Quantra) and radiologists’ assessments in mammography (e.g., qualitative measurements such as BI-RADS and a visual analogue scale) with varying results. DBT is a promising technique and a potential screening modality, and the possibility to measure breast density on DBT images is important. Our group has previously compared breast density that was measured by radiologists to measurements obtained from an automated VBDA tool from Siemens using the central projection image in DBT. The results suggested that VBDA could be used in DBT in addition to mammography. Taken together, the use of a robust VBDA is important and seems possible in both mammography and DBT, enabling it to be used in individualized screening programs and in breast cancer risk scores.
Learning objectives:
1. To understand the clinical basics of volumetric breast density analysis (VBDA) based on previous studies
2. To acknowledge the difference between radiologists’ assessment of breast density and software measurements
3. To discuss VBDA’s potential use for mammography and digital breast tomosynthesis (DBT) in clinical practice
How did the pandemic harm breast screening
programs and how should a return strategy look like?
Federica Pediconi, Rome, Italy
3 https://www.bcrf.org/breast-cancer-statistics-and-resources/
The biggest questions in breast screening
The patient in the center: The way forward for women with dense breasts
Panagiotis Kapetas, Vienna, Austria – FFDM & Ultrasound
Pascal Baltzer, Vienna, Austria – Abbreviated MRI protocols
Which breast imaging technologies challenge digital mammography in breast screening?
Mireille Broeders, Nijmegen, Netherlands
Sophia Zackrisson, Malmö, Sweden
Sylvia Heywang-Köbrunner, Munich, Germany
Learning objectives:
- What is needed to get new examination methods approved in screening guidelines?
- How will we assess the maturity level of DBT, ABVS and MRI for their potential impact in breast screening?
- Are there mature alternatives to breast imaging?
Risk-based screening and the potential of AI for patient stratification
Ritse Mann; Nijmegen, The Netherlands
Once a women’s risk of developing breast cancer is known, defining an optimal screening strategy becomes important. Such a strategy includes questions on the techniques to use for screening, but should also take into account from what age to screen women, and at what age to stop; when to use highly sensitive screening technologies and when to rely on highly specific ones and so on. This should be placed in perspective in relation to the overall health status of the screened women, and the relative risk of dying from other causes. Moreover, it should take into account relevant costs to both the patient and society.
Recent research in various populations has shown that breast MRI outperforms mammography screening, detecting cancer earlier, and reducing the interval cancer rate. Still selecting patients for such a technique remains a challenge, and it is simply not possible for us to offer the technique to all women at risk. Imaging characteristics may in fact contain a lot of useful information to gauge a woman’s short-term risk of developing breast cancer. Subtle findings, not enough for recall, may be used as an argument for more intensive screening or the application of supplemental screening techniques. It is therefore conceivable that patient selection for supplemental or alternative screening techniques may be performed using characterization of findings present with relatively inexpensive, moderately sensitive, but highly specific screening tools such as mammography. Al applications aimed at automated image analysis may aid in such image-based personification of the screening regimen.
Learning objectives:
- To be aware of the questions that arise in clinical practice when implementing personalized screening
- To understand the relative advantages of common screening techniques
- To appreciate the potential of AI-assisted imaging-based stratification of women to screening cohorts
Strategies for women at average risk:
The new guidelines on breast cancer screening and diagnosis from the European Commission Initiative on Breast Cancer (ECIBC)
Francesco Sardanelli; Milano, Italy
Six principles were followed: a) selection (open call) of an expert panel; b) systematic review of evidence; c) inclusion of patient advocates; d) transparency of conflicts of interest and use of GRADE evidence to determine frameworks; e) recommendations on outcomes relevant to women and rating of the certainty of evidence (CoE); f) stakeholder feedback. A panel of 28 members developed questions and recommendations informed by systematic reviews conducted between 03/2016 and 12/2018 on organized screening of average-risk asymptomatic women:
1) age 40−44, conditional recommendation for not implementing organized screening (moderate CoE);
2) age 45−49, conditional recommendation for digital mammography (DM) organized screening (moderate CoE);
3) aged 50−69, strong recommendation for DM organized screening (moderate CoE); 4) age 70−74, conditional recommendation for DM organized screening (moderate CoE);
5) aged 45−49, conditional recommendation for either biennial or triennial DM (very low CoE);
6-7) age 50−69, strong recommendation against annual DM (very low CoE) and conditional recommendation for biennial DM organized screening over triennial screening (very low CoE);
8-9) age 70−74, strong recommendation against annual DM screening (very low CoE) and conditional recommendation for triennial over biennial DM (very low CoE);
10-11) age 50−69, conditional recommendation for screening with DM alone over tomosynthesis and over DM+tomosynthesis (very low CoE);
12-14) high breast density and negative DM, conditional recommendation against screening with automated breast ultrasonography, handheld ultrasonography, or magnetic resonance imaging over DM alone (very low, low, and very low CoE, respectively).
Update of recommendations was planned.
References: Ann Intern Med 2019 (doi: 10.7326/M18-3445 and 10.7326/M19-2125).
Learning objectives:
1. To know the methodology of the new ECIBC guidelines
2. To be aware of the content of the recommendations of the new ECIBC guideline
3. To be able to implement these recommendations in clinical practice
Personalized breast cancer screening and the role of breast density
Mireille Broeders: Nijmegen, The Netherlands
Breast screening programs today generally offer a mammographic examination every two years to women in a specified age range. Ongoing research is exploring the added value of personalized risk-based screening (i.e., screening strategies tailored to a woman’s individual risk of breast cancer). A vital prerequisite for personalized risk-based screening is a comprehensive breast cancer risk prediction model. The next step is to develop screening regimens for women at varying levels of risk, which may be addressed in several ways: changing starting and stopping ages, changing screening intervals, as well as offering further imaging techniques in addition to digital mammography. Using modeling techniques, the harm-benefit ratios and cost-effectiveness can then be estimated to find the optimal screening strategies. In parallel, it is essential to understand the acceptability of personalized approaches, especially for women at low risk, and the challenges in communication and implementation.
Breast density is an important factor in this research area because it can contribute to risk prediction, but it will also play a role in finding the optimal screening strategy. Automated measures of breast density on digital mammography are being updated rapidly, which will facilitate getting this data for all women in the target population. However, the fact that DBT may replace digital mammography in the near future raises the following questions: How does DBT perform across breast density categories? What is the relationship between automated breast density measures on DBT and breast cancer risk? What is the role of additional imaging modalities when DBT is the screening test?
Learning Objectives:
1. To understand the components of a personalized breast cancer screening program
2. To explore the role of automated breast density estimates in personalized breast cancer screening with tomosynthesis
Dense breast and how to overcome the radiologist’s ”problem child”
Luis Pina; Pamplona, Spain
Learning objectives:
- To become familiar with the limitations of mammography in dense breasts
- To learn the role of tomosynthesis to overcome the limitations of mammography in dense breasts
- To understand the role of breast US in dense breasts
Volumetric breast density analysis in mammography and tomosynthesis: brief overview
Hanna Sartor; Malmö, Sweden
High breast density is associated with an increased risk of breast cancer. However, qualitative measurements of breast density by radiologists may vary and be subjective. Automated VBDA was developed to provide objective and reproducible measurements. To explore the possibilities and clinical use of VBDA, previous studies have described the agreement between different methods of measuring volumetric density (e.g., by software such as Volpara and Quantra) and radiologists’ assessments in mammography (e.g., qualitative measurements such as BI-RADS and a visual analogue scale) with varying results. DBT is a promising technique and a potential screening modality, and the possibility to measure breast density on DBT images is important. Our group has previously compared breast density that was measured by radiologists to measurements obtained from an automated VBDA tool from Siemens using the central projection image in DBT. The results suggested that VBDA could be used in DBT in addition to mammography. Taken together, the use of a robust VBDA is important and seems possible in both mammography and DBT, enabling it to be used in individualized screening programs and in breast cancer risk scores.
Learning objectives:
1. To understand the clinical basics of volumetric breast density analysis (VBDA) based on previous studies
2. To acknowledge the difference between radiologists’ assessment of breast density and software measurements
3. To discuss VBDA’s potential use for mammography and digital breast tomosynthesis (DBT) in clinical practice