Tag: radiology

MRI’s Value for Prostate Screening

Posted on by Brian Casey

Among cancer screening tests, prostate screening could be the most problematic. But a new study published this week in JAMA Network Open offers guidance on the role that MRI can play in making prostate screening more effective – and opening the door to population-based screening.

The problem with prostate screening is that PSA tests often discover disease that’s either indolent or slow-growing. 

  • This can lead to a cascade of interventions that are expensive and have harms of their own. 

But prostate cancer remains a common – and deadly – cancer, with 1.5M cases globally in 2022, and it’s the second most commonly occurring cancer in men after lung cancer.

  • Given these statistics, there has to be a way to perform prostate screening more effectively.

MRI offers one such alternative, and a clinical consensus has emerged that performing a single MRI scan after a positive PSA result can help stratify men before biopsy. 

  • In this scenario, men might not be referred to biopsy if their MRI scan is negative, and adoption of this protocol has helped reduce prostate biopsies in PSA-positive men while still detecting clinically significant cancer.   

But if one MRI scan is good, are repeat MRI scans even better? In the new study, Swedish researchers investigated this question in a secondary analysis of the STHLM3-MRI trial, which involved repeat screening of 1.5k men 2-3 years after an original prostate screening.

Of the group who got repeat PSA and MRI screening, 667 men had PSA levels of 3 ng/mL or higher, the threshold for MRI testing, with the repeat scans finding … 

  • 51 men (7.6%) had equivocal lesions (PI-RADS score of 3)
  • 33 men (4.9%) had suspicious lesions (PI-RADS score of 4)
  • Only 10 men (1.5%) had lesions with PI-RADS scores of 4 or greater

The findings led the authors to conclude that cancer detection was “limited” in the second round of PSA and MRI prostate screening, and detection of low-grade tumors was low.

The Takeaway

At first blush, STHLM3-MRI may seem like a negative study, but it actually helps frame the debate over prostate cancer screening and MRI’s role by omitting the need for multiple repeat scans. The results also give clinicians confidence that it’s safe to omit prostate biopsies in men who have a single negative MRI result – a key finding in reducing the downstream costs of any population-based screening program.

Real-World AI Experiences

Posted on by Brian Casey

Clinical studies showing that AI helps radiologists interpret medical images are great, but how well does AI work in the real world – and what do radiologists think about it? These questions are addressed in a new study in Applied Ergonomics that takes a deep dive into the real-world implementation of a commercially available AI algorithm at a German hospital. 

A slew of clinical studies supporting AI were published in 2023, from the MASAI study on AI for breast screening to smaller studies on applications like opportunistic screening or predicting who should get lung cancer screening. 

  • But even an AI algorithm with the best clinical evidence behind it could fall flat if it’s difficult to use and doesn’t integrate well with existing radiology workflow.

To gain insight into this issue, the new study tracked University Hospital Bonn’s implementation of Quantib’s Prostate software for interpreting and documenting prostate MRI scans (Quantib was acquired by RadNet in January 2022). 

  • Researchers described the solution as providing partial automation of prostate MRI workflow, such as helping segment the prostate, generating heat maps of areas of interest, and automatically producing patient reports based on lesions it identifies. 

Prostate was installed at the hospital in the spring of 2022, with nine radiology residents and three attending physicians interviewed before and after implementation, finding…

  • All but one radiologist had a positive attitude toward AI before implementation and one was undecided 
  • After implementation, seven said their attitudes were unchanged, one was disappointed, and one saw their opinion shift positively
  • Use of the AI was inconsistent, with radiologists adopting different workflows and some using it all the time with others only using it occasionally
  • Major concerns cited included workflow delays due to AI use, additional steps required such as sending images to a server, and unstable performance

The findings prompted the researchers to conclude that AI is likely to be implemented and used in the real world differently than in clinical trials. Radiologists should be included in AI algorithm development to provide insights into workflow where the tools will be used.

The Takeaway

The new study is unique in that – rather than focusing on AI algorithm performance – it concentrated on the experiences of radiologists using the software and how they changed following implementation. Such studies can be illuminating as AI developers seek broader clinical use of their tools. 

Breast Cancer in Younger Women Rises

Posted on by Brian Casey

Breast cancer rates have been rising in younger women – many of whom aren’t yet eligible for screening – and a new study in JAMA Network Open offers a perspective. 

Breast cancer mortality has dropped consistently over the last several decades, with a recent study in JAMA attributing the decline to the combination of screening and treatment. 

The problem is that even the most liberal breast screening guidelines recommend that average-risk women don’t start getting screened until age 40. 

  • This leaves younger women at risk of developing cancers that may present as more advanced disease.

The new study delves into this phenomenon, with researchers examining data from 218k women ages 20-49 who were diagnosed with invasive breast cancer from 2000-2019. Researchers found that cancer incidence …

  • Increased 0.79% annually across all women
  • Accelerated “dramatically” starting in 2016 
  • Rates per 100k women were similar for non-Hispanic Black and White women (71 & 70) across all age groups
  • But were sharply lower for Hispanic women (53)
  • Rates for Black women 20-29 and 30-39 were the highest among race and age cohorts (8 and 51)
  • Rates varied by hormone receptor status

The lower incidence rate for Hispanic women was an intriguing finding that researchers attributed to younger age at the birth of their first child, higher maternal parity, and longer periods of breastfeeding – all factors that may be changing with lower fertility rates.

  • The higher incidence rates for younger Black women are particularly problematic as these women also are more likely to present with advanced disease, which leads to higher mortality rates.

The Takeaway

The new study provides background to what’s become one of the more disturbing trends in public health. While incidence rates in younger women are still much lower than in older women, the rise raises the question of whether health interventions such as risk assessment and targeted screening – such as for younger Black women – are necessary.

Imaging and COVID Vaccine Effectiveness

Posted on by Brian Casey

In the debate over how long the protection from COVID-19 vaccines last, radiology has now entered the chat. A new study in Radiology shows that people with COVID who got vaccinated more than eight months before COVID diagnosis had more severe clinical findings on imaging exams. 

The rapid development of COVID vaccines and their rollout worldwide has been one of the biggest public health success stories of the last 100 years. 

  • Still, even the most effective vaccines lose their potency over time, and COVID vaccines are no different. 

The question is, how long does the COVID vaccine’s protection last? 

  • Previous research documented a decline during the Delta and Omicron waves in vaccine effectiveness against hospitalization, from 92% to 79% after 224-251 days, and a drop in efficacy against death from 91% to 86% after 168-195 days in those with severe COVID.

To shed more light on the issue, researchers in South Korea performed imaging exams on 4.2k patients with COVID from June 2021 to December 2022. 

  • They correlated the severity of clinical outcomes like pneumonia visible on imaging exams to the length of time between patient diagnosis and when they had been vaccinated. 

Compared to those vaccinated in the last 90 days before COVID diagnosis, people vaccinated more than 240 days …

  • Had almost twice odds of severe outcomes (OR = 1.94)
  • Had higher odds of severe pneumonia on chest radiographs (OR = 1.65)
  • But there was no difference in the odds of severe outcome between those vaccinated in the last 90 days and those vaccinated 91-240 days before diagnosis

In an interesting wrinkle to the study, the researchers found no statistically significant difference in odds of severe pneumonia visible on chest CT scans between those vaccinated more than 90 days before diagnosis and those vaccinated within 90 days.

  • The authors proposed that the low use of CT for pneumonia assessment in their study population (20%) and its use primarily for critically ill patients could have introduced bias into the results. 

The Takeaway

The new findings shed light on the declining potency of COVID vaccines over time and could inform public debate over the length of time between boosters. The research also dovetails with other studies showing that the vaccine’s effectiveness does indeed begin to wane at six months.

Out-of-Network Radiology Claims Fall

Posted on by Brian Casey

Is out-of-network billing – when a patient receives care outside their insurance network – still a problem in radiology? A new study in JACR shows that out-of-network commercial claims have dropped dramatically since 2007.

Out-of-network healthcare has been the focus of a number of legislative efforts in recent years as lawmakers try to protect patients from the financial sting of getting a big bill for services rendered outside their provider’s network.

  • Probably the centerpiece of this effort is the federal No Surprises Act, which went into effect in January 2022; not only did it cap the amount that patients can be billed for out-of-network services, but it created an independent dispute resolution mechanism for adjudicating disagreement between providers and payors over how much they should be paid.

The IDR mechanism has been the focus of legal wrangling in recent months, but the new study in JACR indicates that it might not be getting much use after all, at least in radiology.

Researchers from the ACR’s Harvey L. Neiman Health Policy Institute analyzed 80M commercial claims for radiology services from 2007 to 2021, finding…

  • Out-of-network radiology claims fell dramatically (to 1.1% vs. 13%)
  • Out-of-network claims fell for inpatient stays (to 1.4% vs. 10%)
  • Claims also fell for emergency visits (to 0.4% vs. 3.9%)
  • By modality, most claims were for X-ray (57%), followed by ultrasound and CT (15% each) 
  • By 2021, radiologists practiced almost exclusively in-network

What’s the reason for the dramatic decline? The study authors credit good-faith negotiations between radiology practices and commercial payors, as well as the impact of state surprise billing laws (the study period occurred before the federal No Surprises Act went into effect).

  • Other possible factors include consolidation among practices, hospitals, and payors; expansion of academic centers into communities; and the COVID-19 pandemic.   

The Takeaway

The JACR study is welcome news for both patients and radiology practices. Patients are less likely to be hit with surprise medical charges, while practices are less likely to have to fight through the IDR process to resolve claims. In the end, everybody wins – even insurance companies.

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. 

AI Models Go Head-to-Head in Project AIR Study

Posted on by Brian Casey

One of the biggest challenges in assessing the performance of different AI algorithms is the varying conditions under which AI research studies are conducted. A new study from the Netherlands published this week in Radiology aims to correct that by testing a variety of AI algorithms head-to-head under similar conditions. 

There are over 200 AI algorithms on the European market (and even more in the US), many of which address the same clinical condition. 

  • Therefore, hospitals looking to acquire AI can find it difficult to assess the diagnostic performance of different models. 

The Project AIR initiative was launched to fill the gap in accurate assessment of AI algorithms by creating a Consumer Reports-style testing environment that’s consistent and transparent.

  • Project AIR researchers have assembled a validated database of medical images for different clinical applications, against which multiple AI algorithms can be tested; to ensure generalizability, images have come from different institutions and were acquired on equipment from different vendors. 

In the first test of the Project AIR concept, a team led by Kicky van Leeuwen of Radboud University Medical Centre in the Netherlands invited AI developers to participate, with nine products from eight vendors validated from June 2022 to January 2023: two models for bone age prediction and seven algorithms for lung nodule assessment (one vendor participated in both tests). Results included:

  • For bone age analysis, both of the tested algorithms (Visiana and Vuno) showed “excellent correlation” with the reference standard, with an r correlation coefficient of 0.987-0.989 (1 = perfect agreement)
  • For lung nodule analysis, there was a wider spread in AUC between the algorithms and human readers, with humans posting a mean AUC of 0.81
  • Researchers found superior performance for Annalise.ai (0.90), Lunit (0.93), Milvue (0.86), and Oxipit (0.88)

What’s next on Project AIR’s testing agenda? Van Leeuwen told The Imaging Wire that the next study will involve fracture detection. Meanwhile, interested parties can follow along on leaderboards for both bone age and lung nodule use cases. 

The Takeaway

Head-to-head studies like the one conducted by Project AIR may make many AI developers squirm (several that were invited declined to participate), but they are a necessary step toward building clinician confidence in the performance of AI algorithms that needs to take place to support the widespread adoption of AI. 

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.

Top 10 Radiology Stories of 2023

Posted on by Brian Casey

What were the top 10 radiology stories of 2023 in The Imaging Wire? From worklist cherry-picking to a wearable breast ultrasound scanner – and with lots of AI in between – this year’s top 10 list demonstrates the fascinating new developments going on every day in medical imaging.

1. The Perils of Worklist Cherry-Picking

If you’re a radiologist, chances are at some point in your career you’ve cherry-picked the worklist. But picking easy, high-RVU imaging studies to read before your colleagues isn’t just rude – it’s bad for patients and bad for healthcare. That’s according to a study in Journal of Operations Management that analyzed radiology cherry-picking in the context of operational workflow and efficiency. 

2. Tipping Point for Breast AI? 

Have we reached a tipping point when it comes to AI for breast screening? A study in Radiology demonstrated the value of AI for interpreting screening mammograms. 

3. Autonomous AI for Medical Imaging is Here. Should We Embrace It? 

What is autonomous artificial intelligence, and is radiology ready for this new technology? In this paper, we explored one of the most exciting autonomous AI applications, ChestLink from Oxipit. 

4. Undermining the Argument for NPPs

If you think you’ve been seeing more non-physician practitioners (NPPs) reading medical imaging exams, you’re not alone. A study in Current Problems in Diagnostic Radiology found that the rate of NPP interpretations went up almost 27% over four years. 

5. Reimbursement Drives AI Adoption

It’s no secret that insurance reimbursement drives adoption of new medical technology. But an analysis in NEJM AI showed exactly how reimbursement is affecting the diffusion into clinical practice of perhaps the newest medical technology – artificial intelligence. 

6. Radiation and Cancer Risk

New research on the cancer risk of low-dose ionizing radiation could have disturbing implications for those who are exposed to radiation on the job – including medical professionals. In a study in BMJ, researchers found that nuclear workers exposed to occupational levels of radiation had a cancer mortality risk that was higher than previously estimated.

7. Cardiac Imaging in 2040

What will cardiac imaging look like in 2040? It will be more automated and preventive, and CT will continue to play a major – and growing – role. That’s according to an April 11 article in Radiology in which Dr. David Bluemke and Dr. João Lima looked into the future and offered a top 10 list of major developments in cardiovascular imaging in 2040.

8. When AI Goes Wrong

What impact do incorrect AI results have on radiologist performance? That question was the focus of a study in European Radiology in which radiologists who received incorrect AI results were more likely to make wrong decisions on patient follow-up – even though they would have been correct without AI’s help.

9. The 35 Best Radiology Newsletters, Blogs, and Websites to Follow

We dedicated March 6th’s top story to the people and publications that we rely on to find the most interesting medical imaging stories. Assuming that you already subscribe to The Imaging Wire, these are the 35 other newsletters, websites, blogs, and accounts to follow if you want to know what’s happening in radiology.

10. Breast Ultrasound Gets Wearable

Wearable devices are all the rage in personal fitness – could wearable breast ultrasound be next? MIT researchers have developed a patch-sized wearable breast ultrasound device that’s small enough to be incorporated into a bra for early cancer detection. They described their work in a paper in Science Advances.

The Takeaway

The Imaging Wire’s list of top 10 articles for 2023 shows that, while artificial intelligence featured prominently during the year, there was much more to radiology than just AI. We hope you enjoyed reading our content this year as much as we enjoyed bringing it to you.

Lunit’s Deal for Volpara and AI Consolidation

Posted on by Brian Casey

Is the long-awaited consolidation of the healthcare AI sector gaining steam? In a deal valued at close to $200M, South Korean AI developer Lunit announced a bid to acquire Volpara Health, a developer of software for calculating breast density and cancer risk. 

At first glance, the alliance seems to be a match made in heaven. Lunit is a well-regarded AI developer that has seen impressive results in clinical trials of its Insight family of algorithms for indications ranging from mammography to chest imaging. 

  • Most recently, Lunit received FDA clearance for its Insight DBT software, marking its entry into the US breast screening market, and it also raised $150M in a public stock offering. 

Volpara has a long pedigree as a developer of breast imaging software, although it has shied away from image analysis applications to instead focus on breast center operations and risk assessment, in particular by calculating breast density. 

  • Thus, combining Lunit’s concentration in image analysis with Volpara’s focus on operations and risk assessment enables the combined company to offer a wider breadth of products to breast centers.

Lunit will also be able to take advantage of the marketing and sales structure that Volpara has built in the US mammography sector (97% of Volpara’s sales come from the US, where it has an installed base of 2k sites). Volpara expects 2024 sales of $30M and is cash-flow positive.

The question is whether the acquisition is a sign of things to come in the AI market. 

  • As commercial AI sales have been slow to develop, AI firms have largely funded their operations through venture capital firms – which are notoriously impatient in their quest for returns.

In fact, observers at the recent RSNA 2023 meeting noted that there were very few new start-up entrants into the AI space, and many AI vendors had smaller booths. 

  • And previous research has documented a slowdown in VC funding for AI developers that is prompting start-up firms to seek partners to provide more comprehensive offerings while also focusing on developing a road to profitability. 

The Takeaway

It’s not clear yet whether the Lunit/Volpara deal is a one-off combination or the start of a renewed consolidation trend in healthcare AI. Regardless of what happens, this alliance unites two of the stronger players in the field and has exciting potential for the years to come. 

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