Are CT Scans Too Slow?

Is your imaging practice paying attention to the acquisition speed of your CT scans? A new study in AJR suggests that CT pulmonary angiography patients are being scanned at an average speed that’s 30% slower than optimal, resulting in unnecessary imaging artifacts. 

CT is radiology’s workhorse modality, but recent studies have found wide variation in CT scanning parameters, sometimes between scanners in the same health system or even the same facility. 

  • This can result in patients getting different levels of radiation dose for the same type of study, or differences in image quality that can make image comparisons more difficult. 

To even out the variation, imaging groups have proposed best-practice scanning protocols for different exams and anatomical regions. 

  • Most of these protocols focus on reducing radiation dose, but there are other elements – such as scan acquisition speed –  that are also important.

For CT pulmonary angiography exams, scans that are performed too slowly run the risk of motion artifacts caused by patients breathing.

  • Imaging sites, therefore, should try to optimize scan speed, which is determined by a mix of collimation, pitch, and gantry rotation time. 

Researchers in the new study — from UC San Francisco and University of Wisconsin — found that many sites were using a fixed scan speed for CTPA regardless of patient characteristics. 

  • They analyzed data for 167k CTPA scans acquired from 2016 to 2021, with data coming from 121 sites using 28 different scanner models from various manufacturers.

Researchers compared scan speeds to best-practice levels, revealing … 

  • Scans on average were 30% slower than the best-practice speed.
  • 87% of acquisitions were slower.
  • 62% were more than 20% slower.
  • Scan speeds varied widely by vendor and by scanner model.

Researchers concluded that CT sites weren’t optimizing their equipment and not implementing the fastest scan speeds available.  

  • As a result, they could be generating widespread motion artifacts, especially for smaller patients. 

The Takeaway

The new findings show that radiation dose isn’t the only CT scanning parameter that needs optimization. Imaging practices should take a look at their CT protocols to ensure they have the optimal settings, especially for CTPA scans of smaller patients. 

Mammography Rates Fall for Women in 40s

A new study on mammography screening confirms the worst fears of women’s health advocates: screening rates fell for women ages 40-49 after the USPSTF in 2009 withdrew its recommendation that younger women get biennial screening.

Breast screening has long been the most controversial cancer screening exam, with screening’s opponents claiming that its “harms” – such as breast biopsies and overdiagnosis – don’t justify its benefits.

  • The anti-mammography wave crested in 2009 when the USPSTF withdrew its screening recommendation for women ages 40-49 and older than 75, instead advising them to consult with their physicians. 

The change prompted confusion and anger that persisted until the task force in 2024 rescinded the 2009 guidance and returned to a broad recommendation in favor of biennial screening for women in their 40s (screening still isn’t recommended for women over 74).

  • This left the breast imaging community pondering the impact that 15 years of the more restrictive guidance had on breast screening rates.

Researchers address that question in a new study in JAMA Network Open, in which they analyzed screening records for 1.6M women, finding the probability of getting a biennial mammogram …

  • Fell -1.1 percentage points for all women ages 40-49.
  • Fell -3 percentage points for non-Hispanic Black women 40-49, the biggest decline among younger women.
  • Fell -4.8 percentage points for all women 75 years and older.
  • Fell -6.2 percentage points for Hispanic women over age 75, the biggest decline among all age groups.

The new research confirms other studies finding that the USPSTF 2009 guidance led to a small – but statistically significant – decline in overall breast screening rates. 

  • What’s new is its discovery of demographic variations in the magnitude of the change, an important finding given recent studies showing that Black women have a 39% higher breast cancer mortality rate

In fact, rising cancer risk in Black women was cited by the USPSTF as one of its reasons for changing its guidance in 2024. 

  • The USPSTF estimated that lowering screening’s starting age to 40 would avert 1.8 additional deaths per 1k Black women screened every two years

The Takeaway

Hopefully, we’ve seen the end of the “mammography wars” that led to the USPSTF’s 2009 guideline change. A better future is one in which breast screening decisions are made with consideration for factors like cancer risk in addition to just age.

PE Practice Purchases Tick Up

Private equity acquisitions of radiology practices ticked up in 2024 after two years of declines. A new paper in JACR sheds light on PE purchases in radiology, which have raised concerns about the corporatization of medical imaging in the U.S.

Private-sector radiology historically consisted of independent imaging practices run largely by radiologist-owners who contracted with hospitals to read imaging exams.

  • That model has begun to break down as radiology attracts investment from private equity investors eager to roll up what they see as a fragmented industry into larger companies that can leverage market power.

But what’s good for PE investors may not be good for radiologists – or for healthcare. 

  • Private equity investment in healthcare providers has raised concerns that investors may be putting profits before patients.

The new study documents the rate of private equity investment in radiology from 2013 to 2024, based on queries of the Pitchbook and CB Insights databases, finding …

  • There were 113 PE-led radiology acquisitions over the full study period (out of a total of 4.3k radiology practices in the U.S. in 2023). 
  • PE radiology acquisitions peaked at 18 in 2021, fell for the next two years, and ticked back up to 10 in 2024.
  • Most of the radiology practices being acquired employed 50-99 radiologists.
  • PE-led acquisitions were most common in the South.

So what’s to make of the numbers? A total of 113 acquisitions over 10 years isn’t that many (although the authors caution that acquisitions of multi-state or national practices and imaging chains would be counted as a single deal). 

  • And the researchers acknowledge that there’s little data on the impact of corporatization on healthcare quality, at least in radiology (although they do cite a study showing that PE ownership was associated with an 8.2% increase in radiology prices).  

The Takeaway

Private equity investment in radiology practices may still be in the early stages relative to other medical specialties, but radiologists will watch PE acquisitions closely for signs of how the trend may impact them. The new study serves as an important baseline for tracking future activity.   

Radiology’s VC Funding Boom?

Radiology venture capital funding appears to be gaining momentum in the first few weeks of 2025. This past week has seen the release of six funding rounds, led by a massive $260M Series B from preventive medicine firm Neko Health. 

Venture capital funding is a closely watched barometer for any industry built on innovation, and radiology is no exception, especially the imaging AI sector. 

  • Radiology venture capital funding got off to a particularly slow start in 2024, and by year end funding specifically for imaging AI was down 48% compared to 2023 ($335M vs. $646M according to Signify Research). This raised concerns about whether imaging startups might face a decline in VC investment – the equivalent of choking off their air supply before products in development could begin generating commercial sales. 

A CB Insights report earlier this month found that the nature of venture capital investment in digital health has indeed changed, with fewer but larger deals getting done.

  • This was widely seen as VC firms pivoting to quality, with investors demanding proof of progress in the clinical, regulatory, and commercial realms.

That brings us to the recent funding rounds …

  • Neko Health raised $260M that it will use to expand its Neko Body Scan from its current beachheads in Stockholm and London to other locations in Europe and the U.S.
  • Rad AI raised $60M in a round that follows on a $50M Series B less than a year ago as it moves to commercialize its AI-powered radiology reporting software. 
  • Quibim raised $50M in a Series A round to advance its work in imaging biomarkers through AI foundation models that analyze MRI, CT, and PET scans.
  • Annalise.ai parent Harrison.ai received $20M (USD) in funding from an Australian government investment fund to further develop its radiology and pathology AI.
  • Springbok Analytics raised $5M in a Series A round to fund its AI technology for analyzing muscle health from MRI scans.
  • Sycai Medical raised $3.1M for its AI for detecting abdominal cancers.

These six deals – combined with other recent funding rounds from Median Technologies, Core Sound, and BrainSightAI – show that January 2025 has already exceeded the five radiology venture capital deals recorded during the first four months of 2024.

The Takeaway

Do this week’s developments in radiology venture capital funding represent a boom, a boomlet, or just a string of coincidences? Whichever it is, startups would have to acknowledge that any interest from VC investors is better than the alternative.

Hospital Slashes Mammography Backlog

A Michigan hospital was able to reduce its backlog of screening mammograms and speed up report turnaround time through a series of steps that included batched workflow and elimination of paper forms. Researchers describe their work in a new paper in Current Problems in Diagnostic Radiology

Mammography screening has always been a big challenge for breast radiologists, who typically read hundreds of normal mammograms before encountering an actual breast cancer. 

  • These challenges have only gotten worse with rising exam volumes and the well-documented shortage of radiologists, a combination that can lead to growing backlogs and longer report turnaround times. 

At the University of Michigan Health System, turnaround times for mammography reports had ballooned to 8.3 days, prompting researchers to investigate ways to make the breast imaging service more efficient. 

Study authors identified three main areas that slowed mammography TAT …

  • Interruptions during radiologist reading shifts.
  • Paper-based workflow. 
  • Cumbersome report dictation workflow.

So they developed a program called “Uninterrupted with Assistant” that eliminated the facility’s traditional reading model – eight-hour reading shifts in which radiologists were also responsible for other tasks like breast MRI and interventional procedures. 

  • Instead, they implemented four-hour shifts where radiologists batch-read mammograms without interruption. They were also aided by a clerical staff member as a “live transcriptionist” who reviewed charts and drafted pre-dictated reports in real time. 

The mammography service also ditched its paper workflow in favor of having patients complete intake forms on tablets, while technologists entered data on computers.

  • Finally, they updated their reporting to a standard template with pre-populated fields, based on FDA- and MQSA-approved verbiage. 

They then tested the Uninterrupted with Assistant program over 32 weeks in 2021, finding that during the program … 

  • Mean report turnaround time fell 39% (51 vs. 83 hours).
  • The institution’s TAT goal of less than 72 hours was achieved more often (93% vs. 35%).
  • Radiologists experienced fewer distractions (2.0 vs. 5.6 on a 10-point scale). 

The Takeaway

Batch reading isn’t new (neither is mammography worklist software), but combining the two with a ride-along assistant in the reading room creates a powerful productivity package. The Michigan model is an experience that can be emulated by other mammography centers struggling to improve efficiency and clear their backlog. 

AI Enables Single-Click Cardiac MRI

Cardiac MRI is one of the most powerful imaging tools for assessing heart function, but it’s difficult and time-consuming to perform. Could automated AI planning offer a solution? A new research paper shows how AI-based software can speed up cardiac MRI workflow

Cardiac MRI has a variety of useful clinical applications, generating high-resolution images for tissue characterization and functional assessment without the ionizing radiation of angiography or CT.

  • But cardiac MR also requires highly trained MR technologists to perform complex tasks like finding reference cardiac planes, adjusting parameters for every sequence, and interacting with patients – all challenges in today’s era of workforce shortages. 

Cardiac MRI’s complexity also increases the number of clicks required by technologists to plan exams. 

  • This can introduce scan errors and produces inter-operator variability between exams. 

Fortunately, vendors are developing AI-based software that automates cardiac MR planning – in this case, Siemens Healthineers’ myExam Cardiac Assist and AI Cardiac Scan Companion. 

  • The solution enables single-click cardiac MR planning with a pre-defined protocol that includes auto-positioning to identify the center of the heart and shift the scanner table to isocenter, as well as positioning localizers to perform auto-align without manual intervention. 

How well does it work in the real world? Researchers tested the AI software against conventional manual cardiac MR exam planning in 82 patients from August 2023 to February 2024, finding that automated protocols had … 

  • A lower mean rate of procedure errors (0.45 vs. 1.13).
  • A higher rate of error-free exams (71% vs. 45%).
  • Shorter duration of free-breathing studies (30 vs. 37 minutes).
  • But similar duration of breath-hold exams (42 vs. 44 minutes, p=0.42).
  • While reducing the error gap between more and less experienced technologists. 

In their discussion of the study’s significance, the researchers note that most of the recent literature on AI in medical imaging has focused on its use for image reconstruction, analysis, and reporting.

  • Meanwhile, there’s been relatively little attention paid to one of radiology’s biggest pain points – exam preparation and planning. 

The Takeaway

The new study’s results are exciting in that they offer not only a method for performing cardiac MR more easily (potentially expanding patient access), but also address the persistent shortage of technologists. What’s not to like?

VC Investors Pivot to Quality

Venture capital investors in digital health firms pivoted to quality in 2024, with fewer deals done but a higher median deal size compared to 2023. That’s according to a new report from market analysis firm CB Insights that also documented a record high for both the number and value of AI-focused deals.

Digital health investment has fluctuated in the years since the COVID-19 pandemic, with the number of deals hitting a peak in 2021 but then receding. 

  • The first half of 2024 was particularly slow in the radiology AI sector, but funding seemed to accelerate in the second half, with more and larger deals getting done.

So where did venture capital funding for digital health end up for all of 2024? The CB Insights report found that relative to 2023 there was …

  • A 23% drop in the number of digital health funding rounds, to 1.2k deals, the lowest number since 2014, versus 1.6k deals.
  • A 3% increase in the total dollar value of investments, to $15.6B versus $15.1B.
  • A median deal size of $5.3M, up 39% versus $3.8M.
  • AI-focused companies secured 42% of funding and 31% of deals, up from 37% and 26%. 
  • The biggest imaging-related deal was a $106M Series C round raised by cardiac AI developer Cleerly.

The numbers are a sign of VC investors looking for quality companies that meet heightened benchmarks.

  • Investors want demonstrated progress in terms of clinical validation, commercial traction, and regulatory readiness before they’ll sign checks. 

The Takeaway

The new report illustrates the opportunities and challenges of the current investment environment for digital health. AI developers will find the wind shifting in their favor, but they will need to do their homework and show real progress in the clinical, commercial, and regulatory spaces before securing venture capital investment.

AI Guides Lung Ultrasound

Healthcare professionals with no experience in lung ultrasound were able to acquire diagnostic-quality scans comparable to those of experts thanks to AI guidance in a new paper in JAMA Cardiology

Ultrasound is one of the most versatile and cost-effective imaging modalities, but it is operator-dependent and many of its more challenging clinical applications require highly trained personnel. 

  • Echocardiography AI has already been shown to help novice healthcare personnel improve their skill to that of expert users – could AI also have applications in other areas, like lung ultrasound? 

To find out, researchers used Caption Health’s AI technology to guide lung ultrasound scans in 176 patients with clinical concerns for pulmonary edema from July to December 2023. 

  • Patients were scanned twice, once by an expert in lung ultrasound without AI guidance and once by a healthcare professional (registered nurses or medical assistants without formal ultrasound training) who received a short training session with lung guidance AI software. 

In analyzing the results, the researchers found …

  • Nearly all the scans acquired by healthcare professionals with AI assistance were of diagnostic quality. 
  • There was no statistically significant difference in quality between scans acquired by healthcare personnel and those of experts (98% vs. 97%, p=0.31).
  • AI-aided personnel actually performed better than experts in the lung area around the heart (91% vs. 77%), perhaps due to AI guidance. 
  • At 15 minutes, median scan acquisition times were longer than those reported in the literature (six and eight minutes). 

The findings could have major implications around access-to-care issues, with handheld ultrasound scanners distributed to low-resource areas where AI-guided healthcare professionals could perform scans sent to tertiary care centers for interpretation. 

The Takeaway

The new study demonstrates an exciting use case for AI in ultrasound that builds on previous research in echo AI. By giving more healthcare professionals access to the power of ultrasound, it promises to democratize access to care in many resource-challenged areas.  

Opportunistic Screening’s AI Milestone

A new study lays the groundwork for AI-based opportunistic screening – the detection of disease using medical images acquired for other indications. In a paper in AJR, researchers show how their homegrown AI algorithm was able to analyze abdominal CT scans and link body composition measurements to the presence of disease.

Opportunistic screening is a sort of holy grail for radiology, with the potential to help radiologists find pathology from scans ordered for other clinical indications

  • Some researchers specifically are focusing on analysis of body composition characteristics derived from CT scans like muscle, fat, and bone that could be biomarkers for hidden pathology – and AI is key because it can process mountains of patient data without getting tired.

In the new paper, researchers from the NIH and the University of Wisconsin tested the concept of AI-based body composition analysis on a massive database of 118k patients who got abdominal CT scans from 2000 to 2021. 

  • They analyzed the scans with their own internally developed AI tool that measures 13 features of body composition, from volume and attenuation in different organs to area of subcutaneous adipose tissue. 

Their goal was to correlate the AI measurements with actual presence of disease, as well as other factors that could affect body composition like age and sex. They found …

  • AI-based body composition metrics varied by age and sex, confirming previous studies.
  • AI metrics also correlated with the four systemic diseases studied, specifically cancer, cardiovascular disease, diabetes mellitus, and cirrhosis.
  • The predictive power of different metrics varied by disease, from a high of 13 measures for diabetes to a low of nine for cancer. 

What’s the real-world impact of the study? 

  • In addition to validating the concept of AI-based opportunistic screening on a broad scale, the findings could be used to establish a set of normal values for body composition that also take into account the impact of systemic disease on these measurements.

The Takeaway

The new study is a bit technical, but it’s an important milestone on the path to opportunistic screening. It not only demonstrates the concept’s feasibility, but also begins to establish the normal values needed to actually implement screening programs in the real world.

Top Radiology Trends for 2025

There’s no question that 2025 will be a watershed year for radiology. AI is on the cusp of going mainstream, the radiologist shortage won’t go away, and a number of new U.S. regulatory initiatives promise to reshape the field. 

As we did in 2024, The Imaging Wire asked key opinion leaders in medical imaging to provide their predictions on the technologies, clinical applications, and regulatory developments that will shape the specialty for the next 12 months.

AI Blurs Lines with Generative Models: “Providers will interchangeably use both general-purpose and custom-built GenAI models for regulated (e.g., draft reporting) and unregulated (e.g., EHR summaries) tasks. This will blur current lines for medical device determination, shift performance testing from regulators to providers, and encourage regulators to define comprehensive clearance pathways for GenAI.” – Keith Dreyer, DO, PhD, and Bernardo Bizzo, MD, PhD, Mass General Brigham/Harvard Medical School

AI Focus on Reporting and Synthetic Data: “There will be continued interest in using generative AI for reporting and synthetic data alongside ongoing discussions about bias, fairness, and regulations. We can expect an increasing focus on automated draft report generation. I look forward to seeing the community explore radiology use cases for test-time compute and agentic AI.” Woojin Kim, MD, CMIO, Rad AI

Breast Density Reporting Now in Effect: “The FDA ‘dense breast’ reporting standard is now in effect; needed next is standardization of insurance coverage. Individual state insurance laws are inconsistent, and while a federal Find It Early Act did not pass in 2024, supporters will likely reintroduce the legislation in 2025 to ensure health plans cover screening/diagnostic breast imaging with no out-of-pocket costs for women with dense breasts or at higher risk for breast cancer.” – JoAnn Pushkin, executive director, DenseBreast-info

Breast Screening Based on Risk: “The future direction of breast screening will likely include AI to analyze mammograms and other screening imaging studies as well as patient health data rather than family history and lifestyle choices, allowing more accurate risk assessment. Patients will receive tailored screening recommendations, and imaging may include breast MRI, DBT with AI assistance, and other technologies to identify small high-grade aggressive tumors. Genetic testing results will help identify patients at high elevated risk, providing patients with accurate, clear information about their individual risk and engaging them with shared decision-making regarding benefits and harms of screening opportunities.” – Stamatia Destounis, MD, managing partner, Elizabeth Wende Breast Care 

MRI Safety Comes of Age: “2025 will be the year of MRI safety’s ‘coming of age.’ New CPT codes to reimburse providers for the additional effort required to ensure safe scanning of patients with implants are the first time a formal structure has been established to ensure at least some MRI safety. This CPT change isn’t a stand-alone revolution, but a bellwether of the ‘young adulthood’ of MRI safety and changes yet to come.” Tobias Gilk, founder, Gilk Radiology Consultants

New Era for CT Colonography: “A new era for CT colonography started on January 1, 2025, when CMS started coverage for colorectal cancer screening. Adding CTC as an option for CRC screening will ultimately save lives since it identifies precursor polyps as well as cancer. Expanding screening CTC to some of our most vulnerable patients – including African Americans, who have higher rates of colorectal cancer – will help to improve health disparities. Radiologists need to be prepared to handle increased CTC volumes to assure efficient and effective patient care.” – Judy Yee, MD, Montefiore Medical Center/Albert Einstein College of Medicine

Patients Discover AI for Medical Images:Patients will use consumer-grade, multi-modal generative AI chatbots like ChatGPT to interpret their medical images and verify radiology reports for missed findings. Because they are not marketed for medical use, regulators will struggle to enforce oversight and could announce enforcement discretion for consumer use of these general-purpose AI models.” – Keith Dreyer, DO, PhD, and Bernardo Bizzo, MD, PhD, Mass General Brigham/Harvard Medical School

Radiologist Shortage Deepens:  “Maintaining proper staffing to support increasing volume will be the number one priority for private practices with hospital-based services in 2025. The shortage of radiologists is deepening, and with the demand for staffing growing so is the compensation package necessary to attract candidates. Private practices serving hospitals with weaker payor mix profiles will continue to seek financial support from their hospital partners to remain competitive in the market, not only to recruit new radiologists but also to retain current staff.” – Daniel Corbett, chief of business development, Radiology Business Solutions

Radiology in the Spotlight – for Better or Worse: “2025 will be the first year of Trump 2.0. Elon Musk and Vivek Ramaswamy will be busy beavering through the federal government. All attention will be on healthcare costs again. Radiology will be in the spotlight with calls to curb utilization, adopt AI, abolish fee-for-service, and adopt alternative payment models.” –  Saurabh Jha, MBBS, AKA RogueRad, Hospital of the University of Pennsylvania

Radiology’s Tough Economy Triggers Action: “I expect the global imaging market to look quite different at the end of 2025 versus the start, as tough economic conditions trigger action: M&A of small and mid-size hardware innovators; consolidation in imaging AI with category leaders emerging; the growing influence of non-imaging actors (pharma and life sciences, imaging service providers, big tech); price competition biting for the largest hardware vendors in emerging markets; and speculatively, at least one multi-billion top 20 vendor ‘mega-merger.’ Buckle up!” – Steve Holloway, CEO, Signify Research     

Regulation and Reimbursement: “Reimbursement decreases and recruitment challenges persist in 2025. While it remains critical that radiologists continue to advocate for the specialty and diversify their business plans, it’s becoming increasingly important for hospital-based groups to understand the fair market value of their services and potentially negotiate for additional support.” – Sandy Coffta, VP of client services, Healthcare Administrative Partners

Reimbursement Aids Nuclear Medicine Access: “In 2025, CMS reimbursement policy adjustments are expected to increase nuclear medicine usage and patient access. Ongoing clinical trials will likely drive approval of new radiopharmaceutical therapies and theranostics. With the radiopharmaceutical market projected to reach $12.4B, we expect improved access to nuclear medicine diagnostics and treatments in oncology, neurology, and cardiac imaging.” – Cathy Sue Cutler, PhD, SNMMI president and chair/Brookhaven National Laboratory

The Takeaway 

Making predictions is never easy, and that’s particularly true in a discipline as dynamic as radiology. Whatever happens in 2025, you’ll be sure to read all about it in The Imaging Wire

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