Tag: radiology

Will Congress Stop Medicare Cuts?

Posted on by Brian Casey

Radiologists find themselves once again in a familiar position, facing CMS cuts in Medicare and Medicaid physician payments for 2025. A new analysis by revenue cycle management company Healthcare Administrative Partners details the impact of the reductions, as well as other reimbursement changes set to take effect next year. 

CMS has been driving down radiology reimbursement for years, a trend widely seen as part of the agency’s effort to shift funding from medical specialties to primary care. 

  • That’s having an impact on physician pay, as a study last week found that private-practice diagnostic radiologists have seen inflation-adjusted salaries decline at a -1% annual rate since 2014. 

That trend is set to continue in 2025, with CMS publishing its final rule for the Medicare Physician Fee Schedule that affirms most of the changes it proposed in July. In the new article, HAP’s Sandy Coffta unpacks the changes, which include … 

  • A new conversion factor of $32.3465 (down from $33.2875).
  • Payment reductions of -2.8% for radiology and nuclear medicine, and -4.8% for interventional radiology.

But not all of the changes are negative. Other 2025 policies that affect radiology include …

  • Reimbursement for CT colonography for Medicare beneficiaries at a rate of $108.68 for the professional component.
  • New codes for reporting MRI safety procedures.
  • New quality category measures in the Merit-based Incentive Payment System.

CMS proposed similar cuts last year, but Congress swooped in at the last minute to roll them back with the Consolidated Appropriations Act, which applied a positive 2.93% upward adjustment. 

  • Several bills in Congress now would likewise stave off the 2025 reductions (H.R. 2474 and H.R. 10073), but time is running out to pass them before the current Congressional session expires on January 3, 2025. 

The Takeaway

Will Congress once again ride to the rescue and stave off Medicare reimbursement cuts, as it did a year ago? Or will things be different this time, given the political turbulence that’s shaking Washington, DC? We’ll find out in a few weeks.

Radiologist Salaries Lag Inflation

Posted on by Brian Casey

A new study in JACR confirms what many radiologists have suspected: salary growth for private-practice radiologists has lagged inflation over the last 10 years. While there were a few bright spots, the study mostly shows that radiologists are working harder for less pay. 

Radiology has long been one of the better-compensated medical specialties, often landing in the top 10 of disciplines with the highest average annual compensation. 

  • But radiology has also been a target for reimbursement cuts by the U.S. government as it tries to shift more Medicare and Medicaid payments to primary care practitioners.

As a result, previous studies have found that payments per Medicare beneficiary in radiology have actually declined. 

  • And another 2.83% cut is on the docket for 2025 unless Congress steps in before the end of the current legislative session to prevent cuts in the 2025 Medicare Physician Fee Schedule.

The new study analyzes radiologist compensation based on MGMA salary survey data from 2014 to 2023. 

  • Researchers compared salaries for both diagnostic and interventional radiologists, and also between private-practice and academic radiologists. 

Based on the data, they found …

  • Diagnostic radiologists saw median total compensation grow over the survey period, but at a faster rate for academic radiologists (32% vs. 18%). 
  • Academic radiologists enjoyed faster annualized salary growth (3.2% vs. 1.9%) and had an edge after adjustment for inflation (+0.3% vs. -1%).
  • Work RVUs (a measure of productivity) also grew but at a slightly higher rate for academic radiologists (21% vs. 20%). 
  • Interventional radiologists saw higher salary growth for both non-academic and academic physicians (41% and 35%). 

The findings indicate that the traditional salary gap between private-practice and academic radiologists may be narrowing.

  • The growth in wRVUs in a time of stagnant or declining salaries after inflation adjustment may confirm the suspicions of both types of radiologists: that they are working harder for less pay. 

The Takeaway

The findings could be a gut punch for private-practice diagnostic radiologists, who are finding that their salary gains aren’t keeping pace with inflation (sound familiar?). They also suggest that academic radiology could offer a refuge from the market and government forces that are reshaping the private sector.

Real-World Stroke AI Implementation

Posted on by Brian Casey

Time is brain. That simple saying encapsulates the urgency in diagnosing and treating stroke, when just a few hours can mean a huge difference in a patient’s recovery. A new study in Clinical Radiology shows the potential for Nicolab’s StrokeViewer AI software to improve stroke diagnosis, but also underscores the challenges of real-world AI implementation.

Early stroke research recommended that patients receive treatment – such as with mechanical thrombectomy – within 6-8 hours of stroke onset. 

  • CT is a favored modality to diagnose patients, and the time element is so crucial that some health networks have implemented mobile stroke units with ambulances outfitted with on-board CT scanners. 

AI is another technology that can help speed time to diagnosis. 

  • AI analysis of CT angiography scans can help identify cases of acute ischemic stroke missed by radiologists, in particular cases of large vessel occlusion, for which one study found a 20% miss rate. 

The U.K.’s National Health Service has been looking closely at AI to provide 24/7 LVO detection and improve accuracy in an era of workforce shortages.

  • StrokeView is a cloud-based AI solution that analyzes non-contrast CT, CT angiography, and CT perfusion scans and notifies clinicians when a suspected LVO is detected. Reports can be viewed via PACS or with a smartphone.  

In the study, NHS researchers shared their experiences with StrokeView, which included difficulties with its initial implementation but ultimately improved performance after tweaks to the software.  

  • For example, researchers encountered what they called “technical failures” in the first phase of implementation, mostly related to issues like different protocol names radiographers used for CTA scans that weren’t recognized by the software. 

Nicolab was notified of the issue, and the company performed training sessions with radiographers. A second implementation took place, and researchers found that across 125 suspected stroke cases  … 

  • Sensitivity was 93% in both phases of the study.
  • Specificity rose from the first to second implementation (91% to 94%).
  • The technical failure rate dropped (25% to 17%).
  • Only two cases of technical failure occurred in the last month of the study.

The Takeaway

The new study is a warts-and-all description of a real-world AI implementation. It shows the potential of AI to improve clinical care for a debilitating condition, but also that success may require additional work on the part of both clinicians and AI developers.

Time to Embrace X-Ray AI for Early Lung Cancer Detection

Posted on by Partner Content

Each year approximately 2 billion chest X-rays are performed globally. They are fast, noninvasive, and a relatively inexpensive radiological examination for front-line diagnostics in outpatient, emergency, or community settings. 

  • But beyond the simplicity of CXR lies a secret weapon in the fight against lung cancer: artificial intelligence. 

Be it serendipitous screening, opportunistic detection, or incidental identification, there is potential for AI incorporated into CXR to screen patients for disease when they are getting an unrelated medical examination. 

  • This could include the patient in the ER undergoing a CXR for suspected broken ribs after a fall, or an individual referred by their doctor for a CXR with suspected pneumonia. These people, without symptoms, may unknowingly have small yet growing pulmonary nodules. 

AI can find these abnormalities and flag them to clinicians as a suspicious finding for further investigation. 

  • This has the potential to find nodules earlier, in the very early stages of lung cancer when it is easier to biopsy or treat. 

Indeed, only 5.8% of eligible ex-smoking Americans undergo CT-based lung cancer screening. 

  • So the ability to cast the detection net wider through incidental pulmonary nodule detection has significant merits. 

Early global studies into the power of AI for incidental pulmonary nodules (IPNs) shows exciting promise.

  • The latest evidence shows one lung cancer detected for every 1,120 CXRs has major implications to diagnose and treat people earlier – and potentially save lives. 

The qXR-LN chest X-ray AI algorithm from Qure.ai is raising the bar for incidental pulmonary nodule detection. In a retrospective study performed on missed or mislabelled US CXR data, qXR-LN achieved an impressive negative predictive value of 96% and an AUC score of 0.99 for detection of pulmonary nodules. 

  • By acting as a second pair of eyes for radiologists, qXR-LN can help detect subtle anatomical anomalies that may otherwise go unnoticed, particularly in asymptomatic patients.

The FDA-cleared solution serves as a crucial second reader, assisting in the review of chest radiographs on the frontal projection. 

  • In another multicenter study involving 40 sites from across the U.S., the qXR-LN algorithm demonstrated an impressive AUC of 94% for scan-level nodule detection, highlighting its potential to significantly impact patient outcomes by identifying early signs of lung cancer that can be easily missed. 

The Takeaway 

By harnessing the power of AI for opportunistic lung cancer surveillance, healthcare providers can adopt a proactive approach to early detection, without significant new investment, and ultimately improving patient survival rates.

Qure.ai will be exhibiting at RSNA 2024, December 1-4. Visit booth #4941 for discussion, debate, and demonstrations.

Sources

AI-based radiodiagnosis using Chest X-rays: A review. Big Data Analytics for Social Impact, Volume 6 – 2023

Results from a feasibility study for integrated TB & lung cancer screening in Vietnam, Abstract presentation UNION CONF 2024: 2560   

Performance of a Chest Radiography AI Algorithm for Detection of Missed or Mislabelled Findings: A Multicenter Study. Diagnostics 12, no. 9 (2022): 2086

Qure.ai. Qure.ai’s AI-Driven Chest X-ray Solution Receives FDA Clearance for Enhanced Lung Nodule Detection. Qure.ai, January 7, 2024

Studies Support Breast Ultrasound for Screening

Posted on by Brian Casey

A pair of new research studies offers guidance on when and where to use ultrasound for breast screening. The publications highlight the important advances being made in one of radiology’s most versatile modalities. 

Ultrasound is used in developed countries for supplementary breast cancer screening in women who may not be suitable for X-ray-based mammography due to issues like dense breast tissue.

  • Ultrasound is also being examined as a primary screening tool in developing regions like China and Africa, where access to mammography may be limited.

But despite growing use, there are still many questions about exactly when and where ultrasound is best employed in a breast screening role – and this week’s studies shed some light. 

First up is a study in Academic Radiology in which researchers compared second-look ultrasound to mammography in women with suspicious lesions found on breast MRI. 

  • Their goal was to find the best clinical path for working up MRI-detected lesions without performing too many unnecessary biopsies. 

In a group of 221 women, second-look ultrasound was largely superior to mammography with… 

  • Higher detection rates for mass lesions (56% vs. 17%).
  • A much higher detection rate for malignant mass lesions > 10 mm (89%).
  • But worse performance with malignant non-mass lesions (22% vs. 38%).

They concluded second-look ultrasound is a great tool for assessment and biopsy of MRI-detected lesions > 10 mm without calcifications. 

  • It’s not so great for suspicious non-mass lesions, which might be better sent to mammography for further workup. 

Breast ultrasound of non-mass lesions was also the focus of a second study, this one published in Radiology. 

  • Non-mass lesions are becoming more frequent as more women with dense breast tissue get supplemental screening, but incidence and malignancy rates are low. 

So how should they be managed? In a study of 993 women with non-mass lesions found on whole-breast handheld screening ultrasound, researchers classified by odds ratios the factors indicating malignancy…

  • Associated calcifications (OR=21.6).
  • Posterior shadowing (OR=6.9).
  • Segmental distribution (OR=6.2).
  • Mixed echogenicity (OR=5.0).
  • Larger size (2.6 vs. 1.9 mm).
  • Negative mammography (2.8% vs. 29%).

The Takeaway

Ultrasound’s value comes from its high prevalence, low cost, and ease of use, but in many ways clinicians are still exploring its optimal role in breast cancer screening. This week’s research studies should help.

CT Lung Screening’s Weak Link

Posted on by Brian Casey

CT lung cancer screening rates in the U.S. remain abysmally low, over a decade after the exam was recommended. Is part of lung screening’s problem its reliance on provider referrals? A new research letter in JAMA Network Open examines this question. 

Unlike breast screening, in which eligible women are able to self-refer themselves for exams, CT lung screening revolves around provider referrals to start the process. 

  • CMS requires a shared decision-making session that results in a written order from a practitioner for a CT lung screening exam in order to pay for screening through Medicare and Medicaid. 

When CMS created the rules in 2015, provider referrals and shared decision-making were seen as ways to get patients involved in their own care by making choices in coordination with their caregivers.

  • But many are starting to see the requirements as a barrier, especially given low CT lung screening rates in the U.S.

In the new article, researchers investigated how easy it would be for an eligible individual to secure a CT lung screening appointment by just calling hospitals – without a provider referral. 

  • They note that one-third of Americans don’t have primary care clinicians, and are often told to call hospitals directly to set up appointments.

So they did just that, placing phone calls to 527 hospitals asking to arrange CT lung screening appointments, finding …

  • 317 calls (60%) failed because the caller did not have a primary care provider’s order.
  • Only 51 hospitals (9.7%) were able to connect callers to any component of a lung cancer screening process. 

The study authors note that the provider referral requirement isn’t the only thing holding CT lung cancer screening back, as even patients with primary care providers aren’t getting screened, and managing nodule follow-up can also be challenging. 

  • But Medicare’s cumbersome reimbursement rules certainly don’t help bring new people into the fold.

The Takeaway

Given CT lung cancer screening’s undisputed life-saving value, there’s no reason to put unnecessary barriers in its way. The provider referral and shared decision-making requirements are lung screening’s weak link to securing greater adoption, and CMS should rescind them to put CT lung cancer screening on the path to greater adoption.

MRI Predicts Cognitive Decline

Posted on by Brian Casey

Early detection of cognitive decline is becoming increasingly important as new therapies become available for conditions like Alzheimer’s disease. A new 20-year study in JAMA Network Open shows that MRI can detect structural brain changes indicating future cognitive decline – years before symptoms occur. 

Longitudinal research has shown that subtle changes in body structure – be they in the heart, brain, or other organs – can predict future disease risk, in some cases decades in advance.

  • That enables the possibility of targeted treatments or behavioral interventions to reduce risk before sick patients experience a cascade of expensive and invasive therapies. 

Mild cognitive impairment is an excellent example. MCI can be a transition to more serious diseases like Alzheimer’s, and previous research has connected it to vascular risk factors that are signs of brain atrophy. 

  • In the current paper, researchers analyzed MRI scans acquired as part of the BIOCARD cohort, a longitudinal study started in 1995 in which cognitively normal participants got baseline brain MRI scans and follow-up exams. 

In a group of 185 BIOCARD participants, researchers tracked how many transitioned to MCI over a mean follow-up period of 20 years, then compared structural brain changes on MRI, finding …

  • 60 participants (32%) progressed to MCI, eight of whom later developed dementia (4.3%).
  • Those with white-matter atrophy on MRI had an 86% higher chance of progression to MCI, the highest rate of any variable studied.
  • Participants with enlargement of the ventricles on MRI had 71% higher risk.
  • Other variables like diabetes and amyloid pathology also had higher risk, but not at the rate of the MRI-detected variables. 

The findings indicate that white-matter volume is closely associated with cognitive function in aging, and that people with higher rates of change are more likely to develop MCI. 

  • The association of diabetes with MCI was not a shock, but researchers said they were surprised there was no association from risk factors like hypertension, dyslipidemia, and smoking.

The Takeaway

The new findings demonstrate the power of MRI to predict pathology years in advance – the question is how and whether to put this knowledge into clinical practice. One could almost see structural brain scans incorporated into whole-body MRI screening exams (if anyone’s listening).

ABUS Flies Solo for Breast Screening

Posted on by Brian Casey

Is breast ultrasound ready for use as a primary breast screening modality – without mammography? Maybe not in developed countries, but researchers in China gave automated breast ultrasound a try, with results that are worth checking out in a new study in AJR. 

Mammography is unquestionably the primary imaging modality for first-line breast screening, with other technologies like ultrasound and MRI taking a supplemental role, such as for working up questionable cases or for women with dense breast tissue.

  • But the standard mammography-dominated paradigm might not be suitable for some resource-challenged countries that have yet to build an installed base of X-ray-based mammography systems. 

One of these countries is China, which not only has fewer mammography systems in rural areas but also has a population of women who have denser breast tissue, which can cause problems with conventional mammography. 

  • As a result, the Chinese National Breast Cancer Screening Program has adopted ultrasound as its primary screening modality, with women ages 35-69 eligible for screening breast ultrasound every 2-3 years. Mammography is reserved for additional workup. 

But handheld ultrasound has challenges of its own. It’s operator-dependent, and image interpretation requires experienced radiologists – also in short supply in some Chinese regions.

  • So the AJR researchers performed a study of 6k women who were screened with GE HealthCare’s Invenia ABUS 2.0 scanner, which uses ultrasound to scan women lying in the supine position. Images were sent via teleradiology to expert radiologists at a remote institution.

How did ABUS perform as a primary screening modality? The researchers found that after a single round of screening …

  • ABUS had a cancer detection rate of 4.0 cancers per 1k women (4.4 for women 40-69).
  • Sensitivity was 92% and specificity was 88%.
  • Abnormal interpretation rate was 12%.
  • 96% of detected cancers were invasive, and 74% were node-negative.
  • Two interval cancers were detected (rate of 0.33 per 1k).

How do the numbers compare to mammography? 

  • The cancer detection rate in the Breast Cancer Surveillance Consortium study was 5.1 cancers per 1k women, so not far off. 

The Takeaway

The results offer an interesting look at an alternative to the mammography-first breast screening paradigm used in developed countries, where ABUS is mostly used as a supplemental technology. For resource-challenged areas around the world, ABUS with teleradiology could solve multiple problems at once.

PSMA-PET Reduces Prostate Deaths

Posted on by Brian Casey

Using PSMA-PET instead of conventional imaging to stage patients with recurrent prostate cancer could reduce deaths by 13% and lead to improved quality of life. The new paper in JAMA Network Open confirms the value of PSMA imaging compared to traditional imaging approaches. 

Recurrent prostate cancer is one of the trickiest cancers to manage, especially as biochemical recurrence can occur in up to half of patients getting local treatment. 

  • PSA tests work well for detecting rising prostate antigen levels that could signify recurrence, but it can be difficult to locate recurrent cancer with existing imaging tools like CT and bone scans.

PET using a new generation of PSMA tracers offers a better solution thanks to tracers that target the PSMA protein that builds up on the surface of prostate cancer cells.

  • Previous studies have shown that PSMA-PET is more sensitive and specific for detecting recurrent prostate cancer, especially at lower PSA levels – but the modality’s long-term effects haven’t been explored. 

In the new study, researchers wanted to investigate the impact of switching to PSMA-PET on mortality and quality of life using statistical modeling to predict outcomes from three imaging approaches …

  • Conventional imaging with CT and bone scan.
  • CT and bone scan followed by PSMA-PET for negative or equivocal cases.
  • PSMA-PET alone.

They then projected outcomes for a hypothetical population of 1k patients with biochemically recurrent prostate cancer, defined as a persistent or rising PSA of 0.20 ng/mL after prostatectomy or PSA 2.0 ng/mL or higher following radiation therapy. They found …

  • PSMA-PET had the lowest number of prostate cancer deaths at 512, compared to conventional imaging plus PSMA-PET (520) or just conventional imaging (587).
  • PSMA-PET diagnosed 611 patients with metastasis compared to 630 with conventional imaging plus PSMA-PET and 297 with only conventional imaging.
  • PSMA-PET yielded 824 more quality-adjusted life years per 1k patients than conventional imaging.

The Takeaway

The findings are not only good news for patients with recurrent prostate cancer, they are also a boon for developers of commercially available PSMA-PET radiotracers like Lantheus Medical Imaging’s Pylarify (approved in 2021), Telix Pharmaceuticals’ Illuccix (approved in 2021), and Blue Earth Diagnostics’ Posluma (approved in 2023). 

Using AI-Powered Automation to Help Solve Today’s Radiology Crisis

Posted on by Partner Content

Reimbursement cuts. Radiologist and staff shortages. Rising costs. Surging imaging volumes. Overwhelming staff workloads. Shrinking margins. 

Sound familiar?

Radiology departments, imaging centers, and radiology practices are facing a perfect storm of challenges to deliver high-quality patient care while remaining profitable and competitive. 

  • This familiar narrative emphasizes the need for change and to embrace automation, AI, and technology solutions that automate routine tasks. 

RADIN Health has developed an innovative, cloud-based (SaaS), all-in-one technology stack based on the firsthand experience of radiologist Alejandro Bugnone, MD, CEO and medical director of Total Medical Imaging (TMI), a teleradiology group that reads for imaging centers and hospital systems nationally.  

  • Dr. Bugnone and his team of radiologists were similarly suffering from supply and demand imbalance, reimbursement cuts, increasing study volumes, and customer pressures to maintain their margin. 

As a software developer and seasoned radiologist, Dr. Bugnone was equally frustrated by the lack of a comprehensive, end-to-end technology solution in the market to address these same issues for his teleradiology practice.  

  • In evaluating numerous RIS, PACS, AI voice recognition, and workflow management solutions, his team found that each required expensive interfaces, separate company fees, and ongoing support, yet as an ecosystem still did not deliver a seamless experience that would provide a return on investment. 

An alternative is a system based on straight-through processing, a concept first pioneered in the financial services industry in which automation electronically processes transactions without manual intervention. 

“I knew there had to be a better way forward. I founded RADIN Health for healthcare and teleradiology practices [like TMI], imaging centers, and radiology departments based on straight-through processing, similar to how Wall Street sped up financial transactions without any human intervention,” Dr. Bugnone said. 

RADIN Health is a cloud-based platform that combines RIS, PACS, dictation AI, and workflow management into an all-in-one software solution. 

  • It leverages artificial intelligence, machine learning, OCR/AI, natural language processing (NLP), and other intellectual property.

Dr. Bugnone said TMI has achieved remarkable efficiencies with RADIN. 

“Our results at TMI have been staggering since implementing RADIN over the past 18 months for our complex teleradiology practice,” Dr. Bugnone noted. “With RADIN DICTATION AI, our radiologists have increased their productivity and efficiency, reducing dictation times 30% to 50%.” 

By adding RADIN SELECT, TMI reduced its SLAs more than 50% and FTEs by 70% for managing operational workflow tasks, all while adding 35% in study volumes.  

  • RADIN’s all-in-one technology solution has enabled Total Medical Imaging to meet the challenges of the radiology crisis without hiring new personnel – simply by unlocking the efficiency of their existing staff. 

“We have enjoyed significant growth in 2024 without the need to hire additional staff,” Dr. Bugnone concluded.

Watch the video below to see how RADIN’s all-in-one solution can help your practice.

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