DBT in Screening: Approaches to Reduce Reading Time
Digital breast tomosynthesis (DBT) is being intensively discussed for use European screening programs, while it’s already being widely adopted in the United States. Within DBT, reading time is of the essence and any effort to reduce it will be particularly important.
What do our clinical experts have to say?
Experts are describing a number of strategies for reducing the number of cases and images that need to be interpreted and are proposing various methods for decreasing the time required to interpret a case. Artificial intelligence is one of the latest developments that can reduce reading time and effort.
DBT in screening: Approaches to reduce reading time – Physicist’s perspective
DBT in screening: Approaches to reduce reading time – Radiologist’s perspective
Approaches to accelerating and standardize DBT reading in screening
AI in Breast Screening and Diagnostics – the Evidence and Clinical Implementation
Related Publications on Approaches to Reduce Reading Time with DBT in Screening
Van Winkel SL, Rodríguez-Ruiz A, Appelman L, Gubern-Mérida A, Karssemeijer N, Teuwen J, Wanders AJT, Sechopoulos I, Mann RM.
Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study. Eur Radiol. 2021 May 4
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
DBT in screening: Approaches to reduce reading time
Chantal Van Ongeval; Leuven, Belgium – Radiologist’s view
Ioannis Sechopoulos; Nijmegen, The Netherlands – Medical Physicist’s view
Prospective trials have shown the improvement in detection performance of digital breast tomosynthesis (DBT) compared to mammography at screening. However, these trials have also repeatedly shown that reading a DBT stack takes about twice as long as it does to interpret a 2D mammography image. This is one of the major roadblocks for DBT to be introduced for use in screening programs.
However, many strategies to reduce DBT reading time are being investigated. Some trials have investigated acquiring only the medio-lateral oblique (MLO) view during screening. Other trials have estimated the impact on performance of single-reading DBT cases, as opposed to current standard double reading. The capabilities of artificial intelligence (AI) to identify suspicious cases could be used to avoid the human reading of normal cases. These strategies effectively reduce the number of images to be read. Alternative methods that have been proposed to read an individual case faster include the use of thick slabs instead of thin slices to represent the entire breast, and the use of the synthetic mammogram as a guide to determining which areas of the DBT stack to review. Finally, AI -assisted navigating and reading could also have a substantial impact on reading time.
All these strategies, their technical requirements, and their potential impact on reading efficiency and detection performance will be discussed. The current evidence and availability for incorporating some of them will be presented, while the remaining advances and trials that need to be performed to prove the efficiency and safety of the others will also be reviewed.
Learning objectives
1. Describe the proposed strategies to reduce the number of cases and images that need to be interpreted.
2. Describe the methods proposed to decrease the time required to interpret a given case.
3. Discuss the remaining issues and future developments needed to implement these time-saving strategies in the clinic.
Approaches to accelerating and standardizing DBT reading in screening – what’s new?
Final results of the Malmö Breast Tomosynthesis Screening Trial
Sophia Zackrisson; Malmö, Sweden
The superiority of digital breast tomosynthesis (DBT) compared to digital mammography (DM) for cancer detection in screening is undoubted, as indicated by the results from several large, prospective screening trials. One of the challenges for implementation of DBT in screening is that longer reading times are reported for DBT, up to twice as long as for DM. In high-volume screen reading, ways to improve reading times with sustained sensitivity and specificity are warranted. The image protocols vary between trials, from two-view DM+DBT, two-view synthetic DM+DBT, and one-view DBT, although with quite similar results on detection and somewhat mixed effects on recalls. This presentation will include a discussion on what is the optimal image protocol. Further, does the use of narrow- versus wide-angle DBT make a difference? Do we need double reading with DBT? Will artificial intelligence systems replace one reader? Are thicker slices, slabbing, a way forward? How much does experience add? Finally, some of the final results from the Malmö Breast Tomosynthesis Screening Trial will be presented.
Learning objectives:
1. To become familiar with the different image protocols used in prospective trials
2. To acknowledge ways to accelerate and standardize DBT screen reading
Dense breast and how to overcome the radiologist’s ”problem child”
Luis Pina, Pamplona, Spain
In BI-RADS 2003, the composition was based on the overall density resulting in ACR category 1 ( <25% fibroglandular tissue), category 2 ( 25–50%), category 3 (50–75%) and category 4 (>75%). In BI-RADS 2013, the use of percentages is discouraged, because in individual cases it is more important to take into account the chance that a mass can be obscured by fibroglandular tissue than the percentage of breast density as an indicator for breast cancer risk. Four groups are used: a, b, c, and d. The patterns c and d are considered “dense.” Dense breasts reduce the sensitivity of mammography up to 50%. This is the main limitation of mammography. Fortunately, tomosynthesis can significantly increase the sensitivity of mammography, especially if wide angle is used (increment of detection rate up to +43%). Tomosynthesis is able to reduce the superimposition of tissue and the anatomic noise, allowing the detection of occult lesions. However, at least a small amount of fat surrounding the lesion is needed to be detected. Breast US is widely used as an adjunct to mammography and it improves the sensitivity in dense breasts. But US is a time-consuming, operator-dependent technique that detects too many benign lesions (false-positive results). This is why US cannot be used for population-based screening. MRI is not routinely used for the evaluation of dense breasts, although it can be very useful in some particular cases (preoperative planning, high-risk patients, etc.).
Learning objectives:
1. To become familiar with the limitations of mammography in dense breasts
2. To learn the role of tomosynthesis in overcoming the limitations of mammography in dense breasts
3. 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
DBT in screening: Approaches to reduce reading time
Chantal Van Ongeval; Leuven, Belgium – Radiologist’s view
Ioannis Sechopoulos; Nijmegen, The Netherlands – Medical Physicist’s view
Prospective trials have shown the improvement in detection performance of digital breast tomosynthesis (DBT) compared to mammography at screening. However, these trials have also repeatedly shown that reading a DBT stack takes about twice as long as it does to interpret a 2D mammography image. This is one of the major roadblocks for DBT to be introduced for use in screening programs.
However, many strategies to reduce DBT reading time are being investigated. Some trials have investigated acquiring only the medio-lateral oblique (MLO) view during screening. Other trials have estimated the impact on performance of single-reading DBT cases, as opposed to current standard double reading. The capabilities of artificial intelligence (AI) to identify suspicious cases could be used to avoid the human reading of normal cases. These strategies effectively reduce the number of images to be read. Alternative methods that have been proposed to read an individual case faster include the use of thick slabs instead of thin slices to represent the entire breast, and the use of the synthetic mammogram as a guide to determining which areas of the DBT stack to review. Finally, AI -assisted navigating and reading could also have a substantial impact on reading time.
All these strategies, their technical requirements, and their potential impact on reading efficiency and detection performance will be discussed. The current evidence and availability for incorporating some of them will be presented, while the remaining advances and trials that need to be performed to prove the efficiency and safety of the others will also be reviewed.
Learning objectives
1. Describe the proposed strategies to reduce the number of cases and images that need to be interpreted.
2. Describe the methods proposed to decrease the time required to interpret a given case.
3. Discuss the remaining issues and future developments needed to implement these time-saving strategies in the clinic.
Approaches to accelerating and standardizing DBT reading in screening – what’s new?
Final results of the Malmö Breast Tomosynthesis Screening Trial
Sophia Zackrisson; Malmö, Sweden
The superiority of digital breast tomosynthesis (DBT) compared to digital mammography (DM) for cancer detection in screening is undoubted, as indicated by the results from several large, prospective screening trials. One of the challenges for implementation of DBT in screening is that longer reading times are reported for DBT, up to twice as long as for DM. In high-volume screen reading, ways to improve reading times with sustained sensitivity and specificity are warranted. The image protocols vary between trials, from two-view DM+DBT, two-view synthetic DM+DBT, and one-view DBT, although with quite similar results on detection and somewhat mixed effects on recalls. This presentation will include a discussion on what is the optimal image protocol. Further, does the use of narrow- versus wide-angle DBT make a difference? Do we need double reading with DBT? Will artificial intelligence systems replace one reader? Are thicker slices, slabbing, a way forward? How much does experience add? Finally, some of the final results from the Malmö Breast Tomosynthesis Screening Trial will be presented.
Learning objectives:
1. To become familiar with the different image protocols used in prospective trials
2. To acknowledge ways to accelerate and standardize DBT screen reading
Dense breast and how to overcome the radiologist’s ”problem child”
Luis Pina, Pamplona, Spain
In BI-RADS 2003, the composition was based on the overall density resulting in ACR category 1 ( <25% fibroglandular tissue), category 2 ( 25–50%), category 3 (50–75%) and category 4 (>75%). In BI-RADS 2013, the use of percentages is discouraged, because in individual cases it is more important to take into account the chance that a mass can be obscured by fibroglandular tissue than the percentage of breast density as an indicator for breast cancer risk. Four groups are used: a, b, c, and d. The patterns c and d are considered “dense.” Dense breasts reduce the sensitivity of mammography up to 50%. This is the main limitation of mammography. Fortunately, tomosynthesis can significantly increase the sensitivity of mammography, especially if wide angle is used (increment of detection rate up to +43%). Tomosynthesis is able to reduce the superimposition of tissue and the anatomic noise, allowing the detection of occult lesions. However, at least a small amount of fat surrounding the lesion is needed to be detected. Breast US is widely used as an adjunct to mammography and it improves the sensitivity in dense breasts. But US is a time-consuming, operator-dependent technique that detects too many benign lesions (false-positive results). This is why US cannot be used for population-based screening. MRI is not routinely used for the evaluation of dense breasts, although it can be very useful in some particular cases (preoperative planning, high-risk patients, etc.).
Learning objectives:
1. To become familiar with the limitations of mammography in dense breasts
2. To learn the role of tomosynthesis in overcoming the limitations of mammography in dense breasts
3. 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