Tag: DBT

Ultrasound and DBT Screening — Time to Call It Quits?

Posted on by Brian Casey

Ultrasound long ago carved out a role in breast cancer screening as a complementary tool to conventional 2D mammography. But is ultrasound still needed, now that U.S. breast screening programs have largely switched over to 3D digital breast tomosynthesis (DBT)? A new study in Academic Radiology raises questions. 

Conventional 2D mammography has well-known shortcomings, particularly in women with dense breast tissue that can obscure lesions. So alternative modalities like ultrasound, breast MRI, and contrast-enhanced mammography (CEM) are called in to help when needed.

  • Past research has shown that supplemental ultrasound can improve the cancer detection rate (CDR) in a 2D mammography screening program by 3-4 cancers per 1k women. 

But those studies were performed before the switch to DBT, which can often see around overlapping structures thanks to a gantry head that acquires multiple images as it pans across the breast. 

  • So is ultrasound still needed in screening programs using DBT? Researchers from Weill Cornell Medicine at New York-Presbyterian Hospital tested the hypothesis by examining 103k screening exams from 2014 to 2024 in which both DBT and ultrasound were used. 

In the study, researchers found that screening ultrasound after a negative DBT result…

  • Generated 1.9k biopsies, or 19 biopsies for every cancer the modality detected.
  • Produced an additional cancer detection rate of 1.0 per 1k women, compared to an additional CDR of 3-4 cancers for ultrasound in the 2D mammography era. 
  • Had an overall false-positive screening rate of 98.5%, a false-positive biopsy rate of 94.8%, and a positive predictive value of biopsies performed (PPV3) of just 5.2%.
  • Generated $652k false-positive screening ultrasound costs and $1.16M in ultrasound-guided biopsy costs.

The numbers are sobering and indicate that the days of ultrasound as a supplemental screening modality to DBT screening could be coming to a close. 

  • Instead, the researchers recommended that ultrasound screening be replaced by more sensitive modalities like breast MRI or CEM, both of which are fortunately more available now than during the 2D mammography era.

The Takeaway

The new study answers the question – in the negative – of whether supplementary ultrasound is still needed in the era of DBT screening. The positive subtext here is that the research confirms the improved detection performance of 3D compared to 2D mammography.

Mammo Modality Face-Off for Early Breast Cancer

Posted on by Brian Casey

When it comes to early breast cancer detection, which medical imaging modality is best: full-field digital mammography, digital breast tomosynthesis, or breast MRI? A new study in Clinical Radiology picks winners – and brings the receipts. 

Breast imagers are fortunate to have many technologies at their disposal, each with its own strengths and weaknesses. 

  • X-ray-based mammography tools like FFDM and DBT are easily available and relatively low cost, while breast MRI delivers the highest resolution but is expensive, less available, and more time-intensive to perform. 

So when does it make sense to use each modality? Researchers from China tested four techniques – FFDM, DBT, and breast MRI at 1.5T with accelerated and full protocols – in 329 patients with early-stage breast cancer (maximum tumor diameter ≤ 2 cm). 

  • They also analyzed results according to breast tissue density, as dense breast tissue is not only a cancer risk factor but can also obscure lesions on X-ray-based modalities.

Across the study sample, researchers found…

  • There was little difference in sensitivity between the four techniques for women with non-dense breast tissue, with FFDM, DBT, and accelerated breast MRI achieving 91% compared to 94% for full-protocol breast MRI.
  • But breast MRI pulled ahead in sensitivity for women with dense breast tissue, both with accelerated and full protocols (95% and 94%) beating DBT and FFDM (90% and 83%).
  • Accelerated breast MRI had performance comparable to the full protocol regardless of breast density, but at almost half the median scan time (8 vs. 15 minutes).
  • Accelerated and full-protocol breast MRI had the same specificity (94%), ahead of both DBT and FFDM (88% and 83%).

What to make of the results? Researchers said the findings in women with non-dense breast tissue reinforce that X-ray-based modalities are sufficient.

  • For women with dense breast tissue, accelerated breast MRI offers performance close enough to the full protocol that breast imaging practices can feel comfortable offering the faster exam.

The Takeaway

It’s no surprise that breast MRI beat both FFDM and DBT mammography for early breast cancer detection in women with dense breast tissue. But it is intriguing that there wasn’t much difference between breast MRI with either accelerated or full protocols. That’s good news for practices that want to make this powerful modality accessible to more women. 

AI Boosts DBT in Detecting More Breast Cancer

Posted on by Brian Casey

A real-world study of AI for DBT screening found that AI-assisted mammogram interpretation nearly doubled the breast cancer detection rate. Radiologists using iCAD’s ProFound AI software saw sharp improvements across multiple metrics. 

Mammography screening has quickly become one of the most promising use cases for AI. 

  • Multiple large-scale studies published in 2024 and 2025 have documented improved radiologist performance when using AI for mammogram interpretation, with the largest studies performed in Europe.

Another new technology changing mammography screening is digital breast tomosynthesis, which is being rapidly adopted in the U.S. 

  • DBT use in Europe is occurring more slowly, so questions have arisen about whether AI’s benefits for 2D mammography would also be found with 3D systems.

To investigate this question, researchers writing in Clinical Breast Cancer tested radiologist performance for DBT screening before and after implementation of iCAD’s ProFound V2.1 AI algorithm in 2020 at Indiana University. 

  • Interestingly, the pre-AI period included use of iCAD’s older PowerLook CAD software. 

Across the 16.7k DBT cases studied, those with AI saw …

  • A sharp improvement in cancer detection rate per 1k exams (6.1 vs. 3.7).
  • A decline in the abnormal interpretation rate (6.5% vs. 8.2%).
  • Higher PPV1 (rate that abnormal mammograms would be positive) (8.8% vs. 4.2%).
  • Higher PPV3 (rate that biopsies would be positive) (57% vs. 32%). 
  • Higher specificity (94% vs. 92%).
  • No statistically significant change in sensitivity.

The findings on sensitivity are curious given AI’s positive impact on other interpretation metrics.

  • Researchers postulated that there was higher breast cancer incidence in the post-AI implementation period, which could have been caused by AI finding cancers that were missed in the period without AI.

The Takeaway

The radiology world has seen multiple positive studies on AI for mammography, but most of these have come from Europe and involved 2D mammography not DBT. The new results suggest that AI’s benefits will also transfer to DBT, the technology that’s becoming the standard of care for breast screening in the U.S.

AI Detects Interval Cancer on Mammograms

Posted on by Brian Casey

In yet another demonstration of AI’s potential to improve mammography screening, a new study in Radiology shows that Lunit’s Insight MMG algorithm detected nearly a quarter of interval cancers missed by radiologists on regular breast screening exams. 

Breast screening is one of healthcare’s most challenging cancer screening exams, and for decades has been under attack by skeptics who question its life-saving benefit relative to “harms” like false-positive biopsies.  

  • But AI has the potential to change the cost-benefit equation by detecting a higher percentage of early-stage cancers and improving breast cancer survival rates. 

Indeed, 2024 has been a watershed year for mammography AI. 

U.K. researchers used Insight MMG (also used in the BreastScreen Norway trial) to analyze 2.1k screening mammograms, of which 25% were interval cancers (cancers occurring between screening rounds) and the rest normal. 

  • The AI algorithm generates risk scores from 0-100, with higher scores indicating likelihood of malignancy, and this study was set at a 96% specificity threshold, equivalent to the average 4% recall rate in the U.K. national breast screening program.

In analyzing the results, researchers found … 

  • AI flagged 24% of the interval cancers and correctly localized 77%.
  • AI localized a higher proportion of node-positive than node-negative cancers (24% vs. 16%).
  • Invasive tumors had higher median risk scores than noninvasive (62 vs. 33), with median scores of 26 for normal mammograms.

Researchers also tested AI at a lower specificity threshold of 90%. 

  • AI detected more interval cancers at this level, but in real-world practice this would bump up recall rates.  

It’s also worth noting that Insight MMG is designed for the analysis of 2D digital mammography, which is more common in Europe than DBT. 

  • For the U.S., Lunit is emphasizing its recently cleared Insight DBT algorithm, which may perform differently.  

The Takeaway

As with the MASAI and BreastScreen Norway results, the new study points to an exciting role for AI in making mammography screening more accurate with less drain on radiologist resources. But as with those studies, the new results must be interpreted against Europe’s double-reading paradigm, which differs from the single-reading protocol used in the U.S. 

DBT Detects Earlier Cancers in Swedish Tomo Study

Posted on by Brian Casey

A new analysis of a landmark DBT study from Sweden offers more support for the effectiveness of tomosynthesis mammography screening. Published in Radiology, researchers found that DBT screening seems to detect earlier cancers, most likely before they become more aggressive. 

Most U.S. mammography practices have embraced DBT since its approval in 2011, such that 48% of all certified mammography units are DBT and 90% of all facilities have at least one tomosynthesis unit. 

  • But doubts about DBT have persisted, particularly by mammography skeptics who charge that the technology was adopted without conducting randomized controlled trials to prove its value. 

But apart from RCTs, there have been plenty of observational studies in which DBT showed a benefit, one of them being the Malmö Breast Tomosynthesis Screening Trial of almost 15k women in Sweden.

  • First results from MBTST were published in 2018 and showed that single-view DBT screening had a 34% higher cancer detection rate per 1k women than digital mammography (8.7 vs. 6.5), but with a higher recall rate as well (3.6% vs. 2.5%).

In the new study, researchers wanted to see if DBT’s screening benefits persisted over two subsequent screening rounds with conventional digital mammography. 

  • Their assumption was that the cancer detection rate would be lower in subsequent rounds, and there would be fewer slow-growing, less aggressive cancers – a sign of early cancer detection. 

Their analysis found …

  • The cancer detection rate per 1k women was lower in the first (4.6) and second (5.3) rounds compared to the original MBTST
  • Recall rate was 2.1% – also lower 
  • The odds ratio of cancer detection was lower than MBTST in the first (OR=0.46) and second (OR=0.53) follow-up rounds 
  • Invasive cancers were less prevalent in the first round compared to the second round (66% vs. 83%) 

What do the results mean? The implication is that because DBT detected cancers in the initial screening round, there was lower cancer prevalence and less aggressive cancer in follow-up rounds, an effect that wore off as time went on.

The Takeaway

There may never be a randomized controlled trial of DBT due to the ethical problem of denying a live-saving technology to women in a control group. But studies like the MBTST follow-up are important in adding to the body of evidence showing that DBT actually does work.

Breast Screening’s New Gold Standard?

Posted on by Brian Casey

A new study in Radiology on the use of digital breast tomosynthesis for breast screening makes the case that DBT has so many advantages over conventional 2D digital mammography that it should be considered the gold standard for breast screening. 

Unlike 2D mammography, DBT systems scan around the breast in an arc, acquiring multiple breast images that are combined into 3D volumes. The technique is believed to be more effective in revealing pathology that might be obscured on 2D projections.

Previous research already demonstrated the effectiveness of DBT for certain uses, but the new study is notable for its large patient population, as well as its focus on general screening rather than subgroups like women with cancer risk factors such as dense breast tissue.

Researchers led by Dr. Emily Conant of the University of Pennsylvania reviewed DBT’s performance in five large U.S. healthcare systems, with a total study population of over 1 million women. 

The advantages of DBT were notable:

  • Higher cancer detection rate: 5.5 vs. 4.5 per 1k women screened
  • Lower recall rate:  8.9% vs. 10.3%
  • Higher recall PPV: 5.9% vs. 4.3%.

On the negative side, DBT had higher biopsy rates, of 17.6 biopsies per 1,000 women versus 14.5 biopsies for 2D digital mammography. But PPV of biopsy for both techniques was largely the same. 

Researchers note that breast cancer mortality rates have fallen 41% since 1989, a development attributed to earlier diagnosis and better treatment. DBT could help accelerate this trend as it finds more cancers relative to 2D digital mammography.

The Takeaway

This study reinforces the idea that DBT is now the gold standard for breast screening. While mammography vendors have already seen high market penetration for DBT systems, the new study is likely to convince any remaining holdouts that 3D mammography is a necessary technology for any breast imaging facility. 

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