Northwestern Medical’s Mozziyar Etemadi, MD, PhD his goal to develop an amateur-ready fetal ultrasound solution.

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Imaging Incidentals

Incidental Evolution

Last week brought a wave of studies that either highlighted how findings in common imaging exams could add value in completely different clinical areas, or showed how incidentals could find a home in established clinical workflows. That might not be welcomed news among the many radiologists who view incidentals as a clinical slippery slope, but it’s another sign that the incidental evolution is gaining momentum.

Left Atrial Dementia Marker – A new JAMA study showed that echocardiographic left atrial function measurements can be used to identify individuals with higher dementia risks, in addition to supporting cardiovascular diagnosis. Analysis of 4,096 participants’ echo exams and 6-year outcomes (75yr avg. age; 531 developed dementia) revealed that lower left atrial function (e.g. reservoir strain, conduit strain, contractile strain, active emptying fraction, emptying fraction) has a statistically significant association with developing dementia (1.43 to 1.98 hazard ratios).

BACs and CVD – A Kaiser Permanente study added more evidence supporting breast arterial calcifications’ value as a cardiovascular disease risk factor. The researchers analyzed 5,059 women’s digital mammography exams (26.5% w/ BACs), finding that women with BACs had a 51% higher risk of developing atherosclerotic CVD and a 23% higher risk of developing any type of CVD over 6.5-years. This is far from the first study to tie BACs to CVD risk, but it came with a high level of credibility (large/observational study, published on Circulation) and generated quite a bit of media attention.

Auto CAC Pathway – A Journal of Digital Imaging study highlighted how coronary artery calcium scores (CAC scores) could be integrated into standard cardiovascular disease (CVD) risk systems, potentially streamlining CAC AI adoption. The researchers used an FDA-cleared AI model (believed to be from Nanox AI) to screen 14,135 patients’ existing CTs (470 who experienced CVD within 5yrs) and then combined their CAC scores with the ACC/AHA’s PCE risk system. The AI-augmented PCE predictions outperformed standard PCE predictions (sensitivity: 57% vs. 53%; specificity: 70% vs. 67%), without requiring additional scans or diagnostic workflows.

Northwestern Follows-Up – A new NEJM study highlighted the impressive results of Northwestern Medicine’s lung nodule follow-up system, which uses NLP to identify suspicious nodules and then initiates a follow-up workflow (prompts physicians, notifies patients, tracks follow-ups). Over 13 months, the system screened over 570k imaging studies, flagging 29k exams for follow-up (77.1% sensitivity, 99.5% specificity, 90.3% PPV), and tracked over 2,400 follow-ups to completion.

The Takeaway
Last week’s batch of studies serve as yet another reminder that common imaging exams could serve broader clinical roles the future, either by creating new risk-based incidental pathways (LA function for dementia; BAC for CVD), catching more undetected incidentals (AI CAC scoring), or by formalizing how incidentals are brought into clinical pathways (e.g. adding CAC to PCEs; leveraging NLP for follow-ups).

RMI Sees Clearly and Decides Confidently

See how adopting ClearRead CT allowed Michigan’s Regional Medical Imaging’s radiologists to complete their chest CT reads faster and more accurately in this Riverain Technologies case study.

Canon Across America

Canon Medical is making its way through the US on its 2022 Mobile Tour, bringing its products and solutions directly to hospitals and providers in 50 US cities. Tune in to see when Canon is coming to you and watch highlights from its tour stops along the way.

The Wire

• Amateur Ultrasound AI: Northwestern Medicine and Google are teaming up to develop a handheld ultrasound AI solution intended to help expand access to fetal ultrasound interpretations in low and middle-income countries. Since these exams would be performed by lightly trained health workers or even pregnant women, Northwestern and Google will compile a training database of “amateur” handheld ultrasound images (performed by Northwestern patients, family members, and novice clinicians), matched with professional images and diagnoses. Google Health will then use this database to develop an AI solution to accurately interpret amateur fetal ultrasound images.

• CDIs PCa Advantage: A University of Waterloo-led research team showed that Synthetic Correlated Diffusion Imaging (CDIs) could improve MRI prostate cancer screening. The researchers performed CDIs and standard prostate MRI techniques (T2w, DWI, DCE) on 200 patients, finding that CDIs differentiated cancerous and healthy tissue (0.916 AUC) and clinically significant and insignificant prostate cancer (0.755 AUC) far more accurately than the standard MRI techniques.

• Is Pricier Healthcare Worth It? A recent study from the National Bureau of Economic Research found that US hospitals with higher costs of care have lower overall mortality rates, with a 35% mortality difference between hospitals in the 20th and 80th cost percentiles. However, the reduction was driven by hospitals in competitive markets where patients have alternatives, while receiving care from pricier hospitals in less competitive markets where competition isn’t geographically feasible (reportedly 69% of all hospitals) has no detectable effect on mortality.

• Arterys & RMS’ BENELUX Alliance: Arterys and Belgium-based medtech developer and distributor, RMS Medical Devices, launched a partnership that will make Arterys’ AI platform available through RMS in Belgium, Netherlands, and Luxembourg. The alliance continues Arterys’ notable European channel expansion since the start of 2021, following partnerships with AMG Medtech (UK & Ireland), Wellbeing (UK), and Human Bytes (Nordic countries). 

• Contrast Incident Reporting: A new JACR study detailed MGH’s successful rollout of a tool that supports radiologists’ imaging contrast reaction documentation process (CISaR; Contrast Incident Support and Reporting). Analysis of 431 CT and MRI contrast reactions from before and after MGH adopted CISaR showed that it significantly increased the share of reactions with radiologist documentation (from 50% to 89%) and documentation completeness (>95% reports complete), while achieving full adoption within nine months of its introduction.

• Off Label AI: A team of researchers from UC Berkeley and University of Texas revealed that images in many open-source databases were preprocessed to support specific AI use cases, and therefore are likely to produce unexpected results when used with other AI models. The authors realized this after they were unable to replicate an image reconstruction study that used a preprocessed MRI dataset. They then performed a number of tests that revealed MRI image reconstruction algorithms can produce 25% to 48% higher quality images when they use preprocessed images (vs. raw).

• SPADE Ultrasound: Researchers from The Technion – Israel Institute of Technology unveiled their new ‘SPADE’ ultrasound detector technology (Silicon-Photonics Acoustic Detector), which leverages optical components to support smaller ultrasound systems with better image quality (can be built into 1 mm devices, can image 10-20 micrometer objects). The new SPADE detectors could support new endoscopic and vascular ultrasound applications, noting that the extremely small transducers required for these use cases traditionally have low image quality.

• PE AI with Low Quality CTPAs: A new MGH study showed that Aidoc’s pulmonary embolism AI solution maintains its accuracy with both suboptimal and optimal quality CTPA images (n = 104 & 226), detecting PE with similar sensitivity (100% vs. 96%), specificity (89% vs. 92%), and AUCs (0.89 vs. 0.87). Although it’s rare to see AI studies focused on performance with low-quality exams, this could be an important capability considering that another recent study showed that the same Aidoc solution was particularly helpful catching missed PE cases in CTPAs with lower contrast injection quality.

• 177Lu-PSMA-617 Cleared: The FDA cleared Novartis’ 177Lu-PSMA-617 (Pluctivo) prostate cancer treatment for patients with PSMA–positive metastatic castration-resistant prostate cancer (mCRPC). The approval should be welcomed by these patients and their care teams (reduces risk of death by 38% and progression by 60%) and should lead to more PET scans given that it relies on PET to identify and treat patients.

• Prioritizing Abnormal Brain MRIs: A King’s College-led team developed a deep learning-based framework for triaging and prioritizing brain MRIs, finding that it could significantly reduce abnormal case reporting times. The team trained the model with 70k labeled T2 and axial diffusion-weighted MRIs and tested it against 800 MRIs, finding that it was able to quickly (<5 seconds) and accurately (>0.9 AUCs) identify abnormal brain MRIs, with good generalization across the two hospitals networks (ΔAUC ≤ 0.02). A simulation study showed that the model would have significantly reduced the two networks’ average abnormal exam reporting times (28 days to 14 days & 9 days to 5 days).

The Multitenant Advantage

Check out this Change Healthcare video explaining the difference between single-tenant and multitenant cloud architecture, and how multitenant solutions can improve your efficiency and flexibility.

The Resource Wire

• Thinking about adding PET/CT to your clinical offerings but don’t have the patient volume to support a full-time scanner? Check out Siemens Healthineers’ fleet of Biograph mobile PET/CT solutions to learn how we can provide reliable, high-quality imaging with a focus on the patient experience – no matter the location.

• Are you sure your imaging archive is safe and recoverable? See how Intelerad’s Cloud DR disaster recovery solution mitigates the many risks facing your archive by securely storing copies of every image.

• Trying to figure out how your IT resources can handle increased AI adoption? This Blackford paper details how the cloud is helping radiology organizations scale their computing resources to support multiple AI applications or algorithms.

• Memorial MRI and Diagnostic of Katy, Texas just became the latest home of a United Imaging MRI system. See the install in action.

• With radiologist workloads growing in volume and complexity, having the wrong PACS can lead to radiologist burnout. This helpful Fujifilm post shows how having the right PACS that functions as a centralized and integrated enterprise imaging system can be part of the solution.

• See how Us2.ai cuts echocardiography’s manual work, subjectivity, and turnaround times to automate the fight against heart disease.

• We talk a lot about radiology practices’ AI adoption, but usually don’t have much evidence to back it up. That changes with this new Arterys report detailing how and why 30 US radiology groups became imaging AI adopters.

• See how Nanox AI’s population health solutions are helping health systems and payers to improve the quality and cost of care through early disease detection.

• This Bayer case study details how radiation benchmarking programs can help push CT dose exposure reduction initiatives from achieving compliance to driving quality.

• Do your radiologists want faster and less manual access to imaging studies? See how the Indiana Health Information Exchange (IHIE), the largest inter-organizational clinical data repository in the US, cut its imaging study retrieval time by 94% when it adopted Nuance PowerShare.

• See how Ochsner Health overcame its CT imaging challenges by leveraging University of Wisconsin’s CT imaging protocols across its fleet of GE Healthcare scanners.

• Evaluating your patient engagement strategy? Check out this Imaging Wire Show featuring Novarad’s Paul Shumway for a great conversation about how new technologies are helping imaging providers safely and securely improve patient engagement.