Canon’s Meaningful RSNA Innovations

After taking a virtual approach to RSNA last year, Canon Medical Systems made its presence felt at RSNA 2022, unveiling an interactive “digital patient journey” booth that featured an interesting mix of new products and business model innovations. 

SP MRIs – Canon unveiled SP-suffix configurations of its Vantage Orian and Galan MRIs (1.5T & 3T), adding new features intended to enhance MRI team efficiency (tablet UX interface, intelligent Ceiling Camera), while making a number of its image quality and productivity-focused solutions standard (AiCE DLR, Fast 3D acceleration, ForeSee View automation).

Mobile XR – The new Mobirex i9 brings a rare update to Canon’s U.S. mobile X-ray lineup, launching with an emphasis on its small size, mobile/flexible design, and its use of Canon’s next-gen CXDI-Elite wireless detectors.

Mobile MI – In a different type of mobile expansion, Canon launched a mobile version of its Cartesion Prime Digital PET/CT, which seems to be a good fit for mobile coaches given its Air Cooled technology and small footprint (fits in 3.15×7.1 meters).

Future Proof Packages – Canon rolled out its interesting new Non-Obsolescence Program, which allows CT and MRI customers to purchase an up-front package that gives them access to all future hardware, software, and service options as they become available. The program covers five years of upgrades, and is priced well below what users would pay if they ordered each item individually.

Glassbeam Clinsights – Canon’s Inclusive Analytics Suite added Glassbeam Clinsights Utilization Analytics, which analyzes DICOM and HL7 data to help Canon service customers understand imaging utilization and productivity levels across their fleets (multi-modalities and vendors).

GE Focuses on Efficiency at RSNA 2022

GE Healthcare had yet another busy RSNA, highlighted by several major launches, and its continued focus on helping imaging teams work more efficiently.

MRI Efficiency – GE’s biggest RSNA launches were in its MRI lineup, and those new launches placed a direct target on workflow, resource, and cost efficiency.

  • GE launched its SIGNA Experience MRI platform, which positions the new SIGNA One user interface as a “cornerstone” for managing a range of GE MRI technologies (AI, DLIR, technologist workflow solutions, AIR Coils), and simplifying MRI operations.
  • GE also unveiled its forthcoming SIGNA Victor MRI (1.5T, 60cm), which will feature the new SIGNA Experience platform, and consumes significantly less power and helium (-10% & -70%).

Future-Forward CT – While GE Healthcare’s CT booth was highlighted by the modular/scalable Revolution Apex platform that launched at RSNA 2021, this year’s event brought news that GE’s latest photon counting CT prototype is beginning clinical evaluations at the University of Wisconsin–Madison (its first U.S. evaluations).

Partnership Plays – GE also announced a pair of partnerships that expand its capabilities beyond the scanners and solutions that it’s known for.

  • GE Healthcare unveiled its OmnifyXR Interventional Suite augmented reality solution, which it co-developed with MediView to support IR visualization and remote collaboration.
  • GE also entered the contrast media injector segment, signing an agreement with ulrich medical that will allow GE to sell the GE-branded CT Motion multi-dose syringeless CT contrast injector in the US.

Much More – GE Healthcare has been busy throughout 2022, so although the other products in its booth were still quite new, they’ve already been detailed in recent Imaging Wire issues. That includes the Definium 656 HD X-ray system, Omni Legend PET/CT, LOGIQ Fortis ultrasound, and the PACS-based intelligent workload management solution.

The Imaging Wire’s RSNA 2022 Reflections

RSNA 2022 is officially a wrap. We hope you had a blast if you made it, and had a great week if you stayed home. We also hope you enjoy our recap of radiology’s most important event in at least three years.

Crowds & Conversations – RSNA’s attendance and overall energy continued to trend upward, as most of the 31k people on-site were super engaged and truly excited to be there. Although attendance was still well below RSNA 2019 (~49k on-site), it was a big jump from last year (~23k on-site), and infinitely better than 2020’s virtual RSNA.

Much Rad Love – If you had “I’m not a radiologist but…” on your RSNA bingo card you’d be in a good spot, because the exhibit hall was full of non-rads talking about how to help radiology teams be more effective and more satisfied.

Focus on Productivity – Perhaps due to all that vendor empathy, just about every new product (hardware and software) focused on eliminating steps / clicks / interruptions, improving workflow integration, alleviating burnout and labor challenges, and better matching diagnostic processes.

Getting Cloudy – There’s no debate that imaging’s shift to the cloud was one of RSNA’s top trends, as informatics vendors continued to strengthen their cloud capabilities and expand their list of cloud-based customers (especially if you include hybrid). There were, however, plenty of debates about who’s cloud tech is truly native and who’s aren’t.

AI’s Two Sides – It seems like many folks are still in AI’s “trough of disillusionment,” as conversations often drifted towards problems with AI’s performance, use cases, funding climate, and provider ROI. However, AI adoption has never been wider, AI products have never worked better, and there are plenty of AI trends to be excited about…

  • AI is becoming less narrow
  • AI workflow integration keeps getting better
  • More radiologists are interested in AI
  • There’s solid traction with operational and efficiency AI
  • We’re not talking about AI replacing radiologists (as much)

Modality Progress – Although there were only a handful of completely new scanners at RSNA, the major OEMs showed continued advancements in MR (image quality, low-helium, low-field, reconstruction, coils) and CT (spectral, photon-counting, upgradability), while nearly all scanners took big strides in operator efficiency.

The Takeaway

Radiology faces plenty of challenges, but it’s populated by some of the smartest people in medicine/medtech who are working hard to solve those challenges. Hats off to the RSNA team for getting all the smart people together every year to push those solutions forward.

The Mammography AI Generalizability Gap

The “radiologists with AI beat radiologists without AI” trend might have achieved mainstream status in Spring 2020, when the DM DREAM Challenge developed an ensemble of mammography AI solutions that allowed radiologists to outperform rads who weren’t using AI.

The DM DREAM Challenge had plenty of credibility. It was produced by a team of respected experts, combined eight top-performing AI models, and used massive training and validation datasets (144k & 166k exams) from geographically distant regions (Washington state, USA & Stockholm, Sweden).

However, a new external validation study highlighted one problem that many weren’t thinking about back then. Ethnic diversity can have a major impact on AI performance, and the majority of women in the two datasets were White.

The new study used an ensemble of 11 mammography AI models from the DREAM study (the Challenge Ensemble Model; CEM) to analyze 37k mammography exams from UCLA’s diverse screening program, finding that:

  • The CEM model’s UCLA performance declined from the previous Washington and Sweden validations (AUROCs: 0.85 vs. 0.90 & 0.92)
  • The CEM model improved when combined with UCLA radiologist assessments, but still fell short of the Sweden AI+rads validation (AUROCs: 0.935 vs. 0.942)
  • The CEM + radiologists model also achieved slightly lower sensitivity (0.813 vs. 0.826) and specificity (0.925 vs. 0.930) than UCLA rads without AI 
  • The CEM + radiologists method performed particularly poorly with Hispanic women and women with a history of breast cancer

The Takeaway

Although generalization challenges and the importance of data diversity are everyday AI topics in late 2022, this follow-up study highlights how big of a challenge they can be (regardless of training size, ensemble approach, or validation track record), and underscores the need for local validation and fine-tuning before clinical adoption. 

It also underscores how much we’ve learned in the last three years, as neither the 2020 DREAM study’s limitations statement nor critical follow-up editorials mentioned data diversity among the study’s potential challenges.

Developing the Eighth Modality

Radiology has adopted seven mainstream modalities over its 127 years, and 4DMedical is determined to create the eighth imaging modality with its new XV Scanner.

The XV Scanner would be the first dedicated lung imaging system, giving radiologists four-dimensional and color-coded visibility into patients’ lung airflow and blood flow, and potentially a new way to assess lung diseases. 

  • The XV Scanner integrates fluoroscopy with advanced analytics software, producing qualitative and quantitative 4D lung function metrics 
  • It simultaneously acquires images from different angles, then measures lung tissue motion, and calculates ventilation at each breathing stage and every lung location
  • XV scans take 5 seconds to perform and deliver less radiation than a typical chest X-ray

4DMedical’s XV technology is also backed by a growing number of positive clinical studies, solid post-IPO funding, and an impressive expansion across Australian imaging giant I-Med Radiology’s 250 locations.

Although the XV Scanner hardware is still forthcoming, 4DMedical will initially launch XV software that can be installed on existing fluoroscopy systems (FDA cleared for ventilation, later adding perfusion) and will also support existing CTs in the future. 

  • Software-only might prove to be a logical starting point, providing 4DMedical with a low-friction way to demonstrate XV’s impact on patient care and test whether this impact is great enough to entice imaging departments to add a whole new scanner to their fleets.

The Takeaway

Creating medical imaging’s eighth mainstream modality might be among the most ambitious goals you’ll hear at RSNA 2022, but if the XV Scanner proves to be much better than existing lung imaging techniques, radiology might have to make room for one more.

AWS Targets Storage and Speed with HealthLake Imaging

AWS took a major step to bolster its cloud value proposition with the launch of Amazon HealthLake Imaging, a new HIPAA-eligible capability that addresses some of cloud imaging’s most common pain points. We sat down with AWS AI leader, Dr. Taha Kass-Hout, at HLTH 2022 last week to explore Amazon HealthLake Imaging’s potential impact on radiology.

Amazon HealthLake Imaging allows healthcare organizations to run multiple applications from a single authoritative copy of an image’s data that’s stored in the cloud, while giving each on-site application customizable metadata-level image access (e.g., patient ID, modality), and returning specially-encoded/compressed images to facilitate faster transfer. As a result…

  • Healthcare providers can cut their image storage TCO by 40% by eliminating the storage creep that comes from saving the same images to the cloud multiple times
  • Radiologists can retrieve and load imaging data from the cloud with sub-second latencies
  • Image viewers and AI algorithms can present or analyze the contents of a DICOM study faster, because they don’t have to load unnecessary image data
  • Researchers and developers can create de-identified image copies, without copying pixel data (and having to store that extra data)
  • AI development teams can access DICOM metadata in a developer-friendly format

Although AWS already plays a major role in radiology, this is one of very few imaging-targeted launch announcements that we’ve seen from the cloud giant. It also comes one month after Google Cloud similarly made its most public cloud imaging announcement in recent memory. 

  • Considering that medical imaging is responsible for roughly 90% of healthcare data, the recent surge in cloud imaging announcements suggests that the cloud leaders are increasing their focus on imaging as a way to add, keep, and grow their healthcare cloud accounts.

The Takeaway

It’s not every day that a storage provider launches a solution specifically intended to cut their clients’ storage costs nearly in half, but this seems like a logical move for AWS, considering that storage costs and performance lag are two of cloud imaging’s biggest challenges. It makes even more sense considering imaging’s role in overall healthcare cloud adoption, where we are in the healthcare cloud landgrab, and the fact that Amazon’s core principals start with “Customer Obsessed.”

Siemens Healthineers Targets MRI at Shape 2023

Siemens Healthineers kicked-off RSNA announcements season with its Shape 23 event, highlighted by a pair of forthcoming MRIs that should serve as the cornerstones of its high-end lineup for years to come.

Magnetom Cima.X – Siemens reinforced its already-solid 3T MR lineup with its new Magnetom Cima.X, calling it the company’s “strongest 3T MRI system ever.”

The Magnetom Cima.X owes that “strongest 3T” title to its new Gemini Gradients, which achieve 200 mT/m amplitude and 200 T/m/s slew rate performance. That’s a 2.5x increase from Siemens’ previous 3T MRIs and it’s higher than any other clinically released whole-body MRI. 

The Magnetom Cima.X also features Siemens Healthineers’ …

  • Benchmark 3T magnet
  • Deep Resolve AI image reconstruction for up to 50% faster scans
  • Open Recon for integrating custom reconstruction and post-processing solutions
  • BioMatrix Technology to automatically adjust exams based on patient biovariability
  • myExam Companion for streamlining technologist workflows

Magnetom Terra.X – Siemens’ new Magnetom Terra.X 7T MR is the long-awaited successor to the Magnetom Terra (the first FDA-cleared 7T MR), bringing improved clinical and research performance. The Magnetom Terra.X leverages Siemens’ new Ultra IQ Technology to achieve even greater image quality and visualization of small structures, Deep Resolve for image reconstruction-based speed and image enhancements, and Open Recon to support custom reconstructions.

The Takeaway

Although both MRIs are still under development, their starring role in Siemens Healthineers’ big RSNA event underscores their significance to Siemens’ high-end MRI lineup, and gives a glimpse of features to expect in future 1.5T and 3T MR launches. That’s especially notable given that Siemens’ last two RSNA announcements focused on its new low-field 0.55T MRIs, and it hasn’t launched any high-field systems in over three years.

The Medical Imaging Economy

With economic warning signs flashing brighter by the day, and hospitals continuing to struggle, it’s hard not to be concerned about medical imaging’s economic situation. However, the major imaging companies’ latest round of earnings suggest that there might be more reasons to remain confident. 

  • Agfa – Agfa’s two imaging divisions had very different Q3s, as HealthCare IT posted solid revenue and earnings growth (+25.7% to $64M; +63.4% to $4.1M EBIT), and Radiology Solutions saw modest revenue growth and a big earnings decline (+1.5% to $121M; -69.3% to $2.9M EBIT).
  • Canon – Canon Medical Systems continued its upswing, posting solid revenue (+9% to $908.5M) and operating profit (+7.5% to $46M) growth amid rising orders and strong post-COVID demand.
  • Fujifilm – Fujifilm’s Healthcare unit posted yet another positive quarter, as imaging drove big increases to revenue (+17.1% to $1.7B) and operating income (+24.4% to $236M). 
  • GE HealthCare – GE HealthCare posted its third straight quarter of revenue growth (+10% to $4.6B), while inflation led to slightly lower profit ($700M).
  • Hologic – The semiconductor shortage caused Hologic’s breast imaging revenue to fall yet again (-20.2% to $212M), while the company’s overall net income plummeted (-63.9% to $118.7M).
  • Konica Minolta – Konica Minolta’s Healthcare revenue increased for the second straight quarter (+14% to $254M), although the division continued to operate at a loss (-$18M).  
  • Philips – Philips’ Diagnosis & Treatment division’s comparable sales fell for the third straight quarter (-2% to $2.37B) due to component shortages, while division profit also declined (Adjusted EBITA -31.6% to $216M).
  • RadNet – RadNet posted another quarter of rising revenues (+5.2% to $350M), although the labor shortage and related payroll inflation cut into its profitability (Adjusted EBITDA -16.1% to $45.8M).
  • Siemens Healthineers – Siemens’ imaging business remained the company’s (and industry’s) top performer, as strong MRI and CT sales drove yet another quarter of revenue growth (+8.1% to $3.35B) and solid margins (Adjusted EBIT +22.4% to $776M).

Although several companies noted economic and inflation headwinds, nearly every earnings report forecasted positive Q4s and 2023s, as supply chain challenges subside and the post-COVID demand surge continues. 

The Takeaway

There are plenty of reasons to be concerned about the economy. However, most companies still reported solid healthcare/imaging financials, and most factors that hurt Q3 performances are likely to improve throughout 2023. Plus, healthcare is historically insulated from economic downturns. 

That doesn’t mean that the next year (or two) will be easy, but it does suggest that medical imaging could fare better than many sectors of the overall economy.

The Case for 18F-NaF PET/CT Bone Metastases Detection

Results from the MITNEC-A1 trial are in, and they further support using 18F-NaF PET/CT to detect bone metastases in patients with prostate and breast cancer, while bolstering its case for replacing 99mTc-MDP as the “bone imaging radiopharmaceutical of choice.”

The prospective, multicenter, single-cohort, phase 3 trial enrolled 261 breast and prostate cancer patients (57 & 204) who had high risk or suspected bone metastasis, scanning each participant with 18F-NaF PET/CT and 99mTc-MDP SPECT. 

Two experts interpreted the scans, which were later compared to 24-month follow-up results, revealing that 42% of the patients had bone metastases (109), and finding that 18F-NaF PET/CT diagnosed bone metastases with far higher…

  • Accuracy – 84.3% vs. 77.4%
  • Sensitivity – 78.9% vs. 63.3%
  • Negative Predictive Value – 85.4% vs. 76.9%

The MITNEC-A1 trial stands on the shoulders of a growing list of studies that support 18F-NaF PET/CT for bone metastases detection, and these latest results make the transition to 18F-NaF PET/CT “appealing” to this study’s authors. 

The next step in that transition process will likely be exploring 18F-NaF PET/CT’s cost-effectiveness versus bone scintigraphy with 99mTc-MDP SPECT, potentially leading to more widespread adoption.

The Takeaway

It’s historically been a challenge to detect prostate and breast cancer bone metastases. Although there’s more research to be done, it appears that 18F-NaF PET/CT might help overcome that challenge, and become bone imaging’s new radiopharmaceutical of choice.

RadNet’s UK Lung Cancer Screening Acquisition

RadNet advanced its AI-led cancer screening strategy, acquiring a 75% stake in Heart & Lung Health, a UK-based teleradiology network with a direct connection to the NHS’ lung cancer screening program.

Heart & Lung Health (HLH) has a network of over 70 cardiothoracic radiologists, and provides teleradiology reporting services for the NHS and a variety of UK hospitals and academic institutions.

Acquiring a UK telerad company might seem out of character for RadNet, which has historically focused its M&A on US-based imaging centers (and more recently global AI developers), only mentioned Europe once in its 2021 annual report, and exited the teleradiology business in 2020. However…

  • HLH is the leading reporting provider for NHS England Targeted Lung Health Check (TLHC), an AI-enabled lung cancer screening pilot program that might pave the way for a UK-wide program. 
  • TLHC requires all radiologists to use AI with their LDCT screening interpretations, suggesting that AI might also be required in a future UK-wide program.
  • HLH uses RadNet’s Aidence subsidiary’s lung cancer AI tools, and HLH will work with Aidence to further develop its solutions.

The Takeaway

RadNet started 2022 by acquiring two major cancer screening AI companies (Aidence and Quantib), which combined with its DeepHealth breast cancer AI business to support its ambitious new strategy to become a population-scale cancer screening leader. 

That goal might have seemed like a longshot to some, given AI’s uncertain path forward and RadNet’s geographic concentration in just seven US states. However, last week’s HLH acquisition showed that RadNet remains very committed to AI-driven cancer screening leadership, and its strategy might not be as geographically-challenged as some initially thought.

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