Tag: breast screening

Why Has Breast Cancer Mortality Fallen?

Posted on by Brian Casey

There’s no question that breast cancer mortality has fallen dramatically over the last several decades. The question is why. 

Proponents of cancer screening believe that early detection has played a major role by finding cancer and enabling treatment to start before it spreads. 

  • But that position is disputed by a vocal minority of skeptics who believe that better cancer treatments deserve most of the credit. 

A case in point was the Bretthauer et al study published in 2023, which claimed that there was no evidence to support screening’s beneficial impact on all-cause mortality. 

  • This despite a demonstrated long-term decline in mortality for the cancers targeted by the four major population-based screening programs: breast, cervical, prostate, and lung. 

A new study in JAMA offers clarity in the debate by placing a numeric value on the tools that have contributed to lower breast cancer mortality. Researchers led by Jennifer Caswell-Jin, MD, of Stanford University used simulation models based on CISNET data to analyze breast cancer mortality from 1975 to 2019, drawing the following conclusions:

  • Screening and treatment together produced a 58% decline in breast cancer mortality, from a death rate of 48/100,000 women to 27/100,000
  • 47% of the reduction was due to treatment of stage I to III cancer 
  • 29% was due to treatment for metastatic breast cancer 
  • 25% was associated with mammography screening 

The authors also discovered that the biggest improvement in breast cancer survival after metastatic recurrence (3.2 vs. 1.9 years) happened between 2000-2019. 

The Takeaway

The new results in Caswell-Jin et al should be seen as another victory for the screening community. In addition to setting a numeric figure for screening’s value, they also demonstrate the synergistic effect when screening and treatment work together to target breast cancer before it has a chance to spread. Efforts to separate the two are quixotic at best and dangerous to women at worst. 

Top 12 Radiology Trends for 2024

Posted on by Brian Casey

What will be the top radiology trends for 2024? We talked to key opinion leaders across the medical imaging spectrum to get their opinions on the technologies, clinical applications, and regulatory developments that will shape the specialty for the next 12 months.

AI – Generative AI to Reduce Radiology’s Workload: “New generative AI methods will summarize complex medical records, draft radiology reports from images, and explain radiology reports to patients using language they understand. These innovative systems will reduce our workload and will provide more time for us to connect with our colleagues and our patients.” — Curtis Langlotz, MD, PhD, Stanford University and president, RSNA 2024

AI – Generative AI Will Get Multimodal: “In 2024, we can expect continued innovations in generative AI with a greater emphasis on integrating GenAI into existing and new radiology and patient-facing applications with growing interests in retrieval-augmented generation, fine-tuning, smaller models, multi-model routing, and AI assistants. Medicine being multimodal, the term ‘multimodal’ will become more ubiquitous.” — Woojin Kim, MD, CMIO at Rad AI

AI – Will AI Really Reduce Radiology Burnout? “Burnout will continue to be a huge issue in radiology with no solution in sight. AI vendors will offer algorithms as solutions to burnout with catchy slogans such as ‘buy our lung nodule detector and become the radiologist your parents wanted you to be.’ Their enthusiasm will cause even more burnout.” — Saurabh Jha, MBBS, AKA RogueRad, Hospital of the University of Pennsylvania

Breast Imaging – Prepare Now for Density Reporting: “The FDA ‘dense breast’ reporting standard to patients becomes effective on September 10, 2024, and breast imaging centers should be prepared for new patient questions and conversations. A plan for a consistent approach to recommending supplemental screening and facilitating ordering of additional imaging from referring providers should be put into action.” — JoAnn Pushkin, executive director, DenseBreast-info.org

Breast Imaging – Density Reporting to Spur Earlier Detection: “In March 2023, FDA issued a national requirement for reporting breast density to patients and referring providers after mammography. Facilities performing mammograms must meet the September 2024 deadline incorporating breast density type and associated breast cancer risk in their reporting. This change can lead to earlier breast cancer detection as these patients will be informed of supplemental screening as it relates to their breast density and [will] choose to pursue it.” — Stamatia Destounis, MD, Elizabeth Wende Breast Care and chair, ACR Breast Imaging Commission

CT – Lung Cancer Screening to Build Momentum: “Uptake of LDCT screening for lung cancer will increase in the US and worldwide. AI-enabled cardiac evaluation, even on non-gated scans, will allow for prediction of illnesses such as AFib and heart failure.  Quantifying measurement error across platforms will become an important aspect of nodule management.” — David Yankelevitz, MD, Icahn School of Medicine at Mount Sinai Health System

CT – Photon-Counting CT to Expand: “In 2024, we will continue to see many papers published on photon-counting CT, strengthening the body of scientific evidence as to its many strengths. Results from clinical trials involving multiple manufacturers’ systems will also increase in number, perhaps leading to more commercial systems entering the market.” — Cynthia McCollough, PhD, director, CT Clinical Innovation Center, Mayo Clinic

Enterprise Imaging – Time is Ripe for Cloud and AI: “Healthcare has an opportunity for change in 2024, and imaging is ripe for disruption, with burnout, staffing challenges, and new technology needs. Many organizations are expanding their enterprise imaging strategy and are asking how and where they can take the plunge into cloud and AI. Vendors have got the message; now it’s time to push the gas and deliver.” — Monique Rasband, VP of strategy & research, imaging/oncology at KLAS

Imaging IT – Data Brokerage to Go Mainstream: “A new market will hit the mainstream in 2024 – radiology data brokerage. As data-hungry LLMs scale up and the use of companion diagnostics in lifesciences proliferates, health systems will look to cash in on curated radiology data. This will also be an even bigger driver for migration to cloud-based imaging IT.” — Steve Holloway, managing director, Signify Research     

MRI – Prostate MRI to Reduce Biopsies: “Prostate MRI in conjunction with PSMA PET will explode in 2024 and reduce the number of unnecessary biopsies for patients.” — Stephen Pomeranz, MD, CEO of ProScan Imaging and chair, Naples Florida Community Hospital Network 

Theranostics – New Radiotracers to Drive Diagnosis & Treatment: “Through 2024, nuclear medicine theranostics will increasingly be integrated into standard global practice. With many new radiopharmaceuticals in development, theranostics promise early diagnosis and precision treatment for a broadening range of cancers, expanding options for patients resistant to traditional therapies. Treatments will be enhanced by personalized dosimetry, artificial intelligence, and combination therapies.” — Helen Nadel, MD, Stanford University and president, SNMMI 2023-2024

Radiology Operations – Reimbursement Challenges Continue: “In 2024, we will continue to experience recruitment challenges coupled with decreases in reimbursement. Now, more than ever, every radiologist needs to be diligent in advocating for the specialty, focus on business plan diversification, and ensure all services rendered are optimally documented and billed.” — Rebecca Farrington, chief revenue officer, Healthcare Administrative Partners 

The Takeaway
To paraphrase Robert F. Kennedy, radiology is indeed living in interesting times – times of “danger and uncertainty,” but also times of unprecedented creativity and innovation. In 2024, radiology will get a much better glimpse of where these trends are taking us.

AI’s Impact on Breast Screening

Posted on by Brian Casey

One of the most exciting radiology use cases for AI is in breast screening. At last week’s RSNA 2023 show, a paper highlighted the technology’s potential for helping breast imagers focus on cases more likely to have cancer.

Looking for cancers on screening mammography has been compared to finding a needle in a haystack, and as such it’s considered to be one of the areas where AI can best help. 

  • One of the earliest use cases was in identifying suspicious breast lesions during radiologist interpretation (remember computer-aided detection?), but more recently researchers have focused on using AI as a triage tool, by identifying cases most likely to be normal that could be removed from the radiologist’s urgent worklist. Studies have found that 30-40% of breast screening cases could be read by AI alone or triaged to a low-suspicion list.

But what impact would AI-based breast screening triage have on radiologist metrics such as recall rate? 

  • To answer this question, researchers from NYU Langone Health prospectively tested their homegrown AI algorithm for analyzing DBT screening cases.

The algorithm was trained to identify extremely low-risk cases that could be triaged from the worklist while more complex cases where the AI was uncertain were sent to radiologists, who knew in advance the cases they were reading were more complicated. In 11.7k screening mammograms, researchers examined recall rates over two periods, one before AI triage and one after, finding: 

  • The overall recall rate went from 13% before the triage period to 15% after 
  • Recall rates for complex cases went from 17% to 20%
  • Recall rates for extremely low-risk studies went from 6% to 5%
  • There were no statistically significant differences in any of the comparisons
  • No change in median self-reported perceived difficulty of reading from the triage lists compared to non-triage list, regardless of years of experience

In future work, the NYU Langone researchers will continue their study to look at AI’s impact on cancer detection rate, biopsy rate, positive predictive value, and other metrics.

The Takeaway

The NYU Langone study puts a US spin on research like MASAI from Sweden, in which AI was able to reduce radiologists’ breast screening workload by 44%. Given the differences in screening protocols between the US and Europe, it’s important to assess how AI affects workload between the regions.

Further work is needed in this ongoing study, but early results indicate that AI can triage complex cases without having an undue impact on recall rate or self-perceived difficulty in interpreting exams – a surrogate measure for burnout.

Uneven Success Against Breast Cancer

Posted on by Brian Casey

The decline in breast cancer mortality has been one of public health’s major success stories. But when you look at it from a global perspective, it’s the best of times and the worst of times. 

That’s because success in fighting breast cancer has been uneven around the world. While countries in North America, Western Europe, and Oceania have seen dramatic declines in breast cancer mortality and advanced-stage disease, other regions continue to be plagued by what really is becoming a survivable disease for most women. 

A new study in JAMA Oncology points out these disparities, documenting major differences in rates of advanced breast disease between countries in what researchers said was the most comprehensive review to date of global differences in breast cancer stage at diagnosis. 

  • Researchers conducted a meta-analysis of 133 studies covering 2.4M women across 81 nations over the past two decades, documenting differences in rates of advanced breast disease at diagnosis both over time and between countries. 

While most high-income nations have seen declines in rates of distant metastatic disease over the past 20 years, advanced-stage disease remains stubbornly common in lower middle-income countries. Researchers found: 

  • Rates of distant metastatic disease varied across countries by region, with sub-Saharan Africa the highest and North America the lowest (6-31% vs. 0-6%)
  • Lower socioeconomic status was tied to more advanced disease when women in the most disadvantaged group were compared to least disadvantaged (3-11% vs. 2-8%)
  • There were pronounced disparities even in high-resource countries with established screening programs, as rates of metastatic disease were twice as high in women of low socioeconomic status (SES) compared to high SES women, such as in the US (8% vs. 4%) 
  • Older women had a much higher prevalence of advanced disease across different countries compared to younger women (range of 4-34% vs. 2-16%), a phenomenon that could be because most screening programs stop at age 75
  • 40% of countries did not meet the Global Breast Cancer Initiative goal of having 60% or more of patients diagnosed at stage I or II

The Takeaway

The new findings indicate that it’s too soon to take a victory lap in the battle against breast cancer. While progress at higher socioeconomic levels in high-income countries has been impressive, breast cancer remains a scourge among more disadvantaged women and across wide regions of the world.

Can AI Direct Breast MRI?

Posted on by Brian Casey

A deep learning algorithm trained to analyze mammography images did a better job than traditional risk models in predicting breast cancer risk. The study shows the AI model could direct the use of supplemental screening breast MRI for women who need it most. 

Breast MRI has emerged (along with ultrasound) as one of the most effective imaging modalities to supplement conventional X-ray-based mammography. Breast MRI performs well regardless of breast tissue density, and can even be used for screening younger high-risk women for whom radiation is a concern. 

But there are also disadvantages to breast MRI. It’s expensive and time-consuming, and clinicians aren’t always sure which women should get it. As a result, breast MRI is used too often in women at average risk and not often enough in those at high risk. 

In the current study in Radiology, researchers from MGH compared the Mirai deep learning algorithm to conventional risk-prediction models. Mirai was developed at MIT to predict five-year breast cancer risk, and the first papers on the model emerged in 2019; previous studies have already demonstrated the algorithm’s prowess for risk prediction. 

Mirai was used to analyze mammograms and develop risk scores for 2.2k women who also received 4.2k screening breast MRI exams from 2017-2020 at four facilities. Researchers then compared the performance of the algorithm to traditional risk tools like Tyrer-Cuzick and NCI’s Breast Cancer Risk Assessment (BCRAT), finding that … 

  • In women Mirai identified as high risk, the cancer detection rate per 1k on breast MRI was far higher compared to those classified as high risk by Tyrer-Cuzick and BCRAT (20.6 vs. 6.0 & 6.8)
  • Mirai had a higher PPV for predicting abnormal findings on breast MRI screening (14.6% vs. 5.0% & 5.5%)
  • Mirai scored higher in PPV of biopsies recommended (32.4% vs. 12.7% & 11.1%) and PPV for biopsies performed (36.4% vs. 13.5% & 12.5%)

The Takeaway
Breast imaging has become one of the AI use cases with the most potential, based on recent studies like PERFORMS and MASAI, and the new study shows Mirai could be useful in directing women to breast MRI screening. Like the previous studies, the current research is pointing to a near-term future in which AI and deep learning can make breast screening more accurate and cost-effective than it’s ever been before. 

Tipping Point for Breast AI?

Posted on by Brian Casey

Have we reached a tipping point when it comes to AI for breast screening? This week another study was published – this one in Radiology – demonstrating the value of AI for interpreting screening mammograms. 

Of all the medical imaging exams, breast screening probably could use the most help. Reading mammograms has been compared to looking for a needle in a haystack, with radiologists reviewing thousands of images before finding a single cancer. 

AI could help in multiple ways, either at the radiologist’s side during interpretation or by reviewing mammograms in advance, triaging the ones most likely to be normal while reserving suspicious exams for closer attention by radiologists (indeed, that was the approach used in the MASAI study in Sweden in August).

In the new study, UK researchers in the PERFORMS trial compared the performance of Lunit’s INSIGHT MMG AI algorithm to that of 552 radiologists in 240 test mammogram cases, finding that …

  • AI was comparable to radiologists for sensitivity (91% vs. 90%, P=0.26) and specificity (77% vs. 76%, P=0.85). 
  • There was no statistically significant difference in AUC (0.93 vs. 0.88, P=0.15)
  • AI and radiologists were comparable or no different with other metrics

Like the MASAI trial, the PERFORMS results show that AI could play an important role in breast screening. To that end, a new paper in European Journal of Radiology proposes a roadmap for implementing mammography AI as part of single-reader breast screening programs, offering suggestions on prospective clinical trials that should take place to prove breast AI is ready for widespread use in the NHS – and beyond. 

The Takeaway

It certainly does seem that AI for breast screening has reached a tipping point. Taken together, PERFORMS and MASAI show that mammography AI works well enough that “the days of double reading are numbered,” at least where it is practiced in Europe, as noted in an editorial by Liane Philpotts, MD. 

While double-reading isn’t practiced in the US, the PERFORMS protocol could be used to supplement non-specialized radiologists who don’t see that many mammograms, Philpotts notes. Either way, AI looks poised to make a major impact in breast screening on both sides of the Atlantic.

Screening Foes Strike Back

Posted on by Brian Casey

Opponents of population-based cancer screening aren’t going away anytime soon. Just weeks after publication of a landmark study claiming that cancer screening has saved $7T over 25 years, screening foes published a counterattack in JAMA Internal Medicine casting doubt on whether screening has any value at all. 

Population-based cancer screening has been controversial since the first programs were launched decades ago. 

  • A vocal minority of skeptics continues to raise concerns about screening, despite the fact that mortality rates have dropped and survival rates have increased for the four cancers targeted by population screening.

This week’s JAMA Internal Medicine featured a series of articles that cast doubt on screening. In the main study, researchers performed a meta-analysis of 18 randomized clinical trials (RCTs) covering 2.1M people for six major screening tests, including mammography, CT lung cancer screening, and colon and PSA tests. 

  • The authors, led by Norwegian gastroenterologist Michael Bretthauer, MD, PhD, concluded that only flexible sigmoidoscopy for colon cancer produced a gain in lifetimes. They conclude that RCTs to date haven’t included enough patients who were followed over enough years to show screening has an effect on all-cause mortality.

But a deeper dive into the study produces interesting revelations. For CT lung cancer screening, Bretthauer et al didn’t include the landmark National Lung Screening Trial, an RCT that showed a 20% mortality reduction from screening.

  • With respect to breast imaging, the researchers only included three studies, even though there have been eight major mammography RCTs performed. And one of the three included was the controversial Canadian National Breast Screening Study, originally conducted in the 1980s.

When it comes to colon screening, Bretthauer included his own controversial 2022 NordICC study in his meta-analysis. 

  • The NordICC study found that if a person is invited to colon screening but doesn’t follow through, they don’t experience a mortality benefit. But those who actually got colon screening saw a 50% mortality reduction.  

Other articles in this week’s JAMA Internal Medicine series were penned by researchers well known for their opposition to population-based screening, including Gilbert Welch, MD, and Rita Redberg, MD.

The Takeaway

There’s an old saying in statistics: “If you torture the data long enough, it will confess to anything.” Among major academic journals, JAMA Internal Medicine – which Redberg guided for 14 years as editor until she stepped down in June – has consistently been the most hostile toward screening and new medical technology.

In the end, the arguments being made by screening’s foes would carry more weight if they were coming from researchers and journals that haven’t already demonstrated a longstanding, ingrained bias against population-based cancer screening.

Value of Cancer Screening

Posted on by Brian Casey

A new study claims that medical screening for diseases like breast and cervical cancer has saved lives and generated value of at least $7.5T (yes, trillion) over the last 25 years. The findings, published in BMC Health Services Research, are a stunning rebuke to critics of screening exams.

While the vast majority of doctors and public health officials support evidence-based screening, a vocal minority of skeptics continues to raise questions about screening’s efficacy. These critics emphasize the “harms” of screening, such as overdiagnosis and patient anxiety – an accusation often levied against breast screening. 

Screening’s critics also target the downstream costs of medical tests intended to confirm suspicious findings. They argue that a single screen-detected finding can lead to a cascade of additional healthcare spending that drives up medical costs.

But the new study offers a counter-argument, putting a dollar figure on how much screening exams have saved by detecting disease earlier, when it can be treated more effectively. 

The research focused on the four main cancer screening tests – breast, cervical, colon, and lung cancer – analyzing the impact of preventive screening on life-years saved and its economic impact from 1996 to 2020, finding …

  • Americans enjoyed at least 12M more years of life thanks to cancer screening
  • The economic value of these life-years added up to at least $7.5T
  • If everyone who qualified for screening exams got them, it would save at least another 3.3M life-years and $1.7T in economic impact
  • Cervical cancer screening had by far the biggest economic impact ($5.2T-$5.7T), followed by breast ($0.8T-$1.9T), colorectal ($0.4T-$1T), and finally lung ($40B). 

Lung cancer’s paltry value was due to a small eligible population and low screening adherence rates. This finding is underscored by a new article in STAT that ponders why CT lung cancer screening rates are so low, with one observer calling it the “redheaded stepchild” of screening tests.  

The Takeaway
Screening skeptics have been taking it on the chin lately (witness the USPSTF’s U-turn on mammography for younger women) and the new findings will be another blow. We may continue to see a dribble of papers on the “harms” of overdiagnosis, but the momentum is definitely shifting in screening’s favor – to the benefit of patients.

Taking Ultrasound Beyond Breast Density

Posted on by Brian Casey

When should breast ultrasound be used as part of mammography screening? It’s often used in cases of dense breast tissue, but other factors should also come into play, say researchers in a new study in Cancer. 

Conventional X-ray mammography has difficulties when used for screening women with dense breast tissue, so supplemental modalities like ultrasound and MRI are called into play. But focusing too much on breast density alone could mean that many women who are at high risk of breast cancer don’t get the additional imaging they need.

To study this issue, researchers analyzed the risk of mammography screening failures (defined as interval invasive cancer or advanced cancer) in ~825k screening mammograms in ~377k women, and more than ~38k screening ultrasound studies in ~29k women. All exams were acquired from 2014 to 2020 at 32 healthcare facilities across the US.

Researchers then compared the mammography failure rate in women who got ultrasound and mammography to those who got mammography alone. Their findings included: 

  • Ultrasound was appropriately targeted at women with heterogeneously or extremely dense breasts, with 95.3% getting scans
  • However, based on their complete risk factor profile, women with dense breasts who got ultrasound had only a modestly higher risk of interval breast cancer compared to women who only got mammography (23.7% vs. 18.5%) 
  • More than half of women undergoing ultrasound screening had low or average risk of an interval breast cancer based on their risk factor profile, despite having dense breasts
  • The risk of advanced cancer was very close between the two groups (32.0% vs. 30.5%), suggesting that a large fraction of women at risk of advanced cancer are getting only mammography screening with no supplemental imaging

The Takeaway 

On the positive side, ultrasound is being widely used in women with dense breast tissue, indicating success in identifying these women and getting them the supplemental imaging they need. But the high rate of advanced cancer in women who only received mammography indicates that consideration of other risk factors – such as family history of breast cancer and body mass index – is necessary beyond just breast tissue density to identify women in need of supplemental imaging. 

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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