Cleerly’s Anita Vadria, MS, PA-C on the importance of measuring non-calcified plaque.

I’m happy to share a special Imaging Wire interview detailing how Cleerly’s CCTA AI solution allowed one of its own team members to catch and treat his potentially life-threatening atherosclerosis.

Join me, Terry Schemmel, and Anita Vadria, MS, PA-C, as we discuss Terry’s journey as both a Cleery patient and team member, and how Cleery helps physicians identify and treat their high-risk asymptomatic patients.

Imaging Wire Sponsors

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Prostate Cancer Imaging

Prostate MR AI’s Experience Boost

A new European Radiology study showed that Siemens Healthineers’ AI-RAD Companion Prostate MR solution can improve radiologists’ lesion assessment accuracy (especially less-experienced rads), while reducing reading times and lesion grading variability. 

The researchers had four radiologists (two experienced, two inexperienced) assess lesions in 172 prostate MRI exams, with and without AI support, finding that AI-RAD Companion Prostate MR improved:

• The less-experienced radiologists’ performance, significantly (AUCs: 0.66 to 0.80 & 0.68 to 0.80)
• The experienced rads’ performance, modestly (AUCs: 0.81 to 0.86 & 0.81 to 0.84)
• Overall PI-RADS category and Gleason score correlations (r = 0.45 to 0.57)
• Median reading times (157 to 150 seconds)

The study also highlights Siemens Healthineers’ emergence as an AI research leader, leveraging its relationship / funding advantages over AI-only vendors and its (potentially) greater focus on AI research than its OEM peers to become one of imaging AI’s most-published vendors (here are some of its other recent studies).

The Takeaway

Given the role that experience plays in radiologists’ prostate MRI accuracy, and noting prostate MRI’s historical challenges with variability, this study makes a solid case for AI-RAD Companion Prostate MR’s ability to improve rads’ diagnostic performance (without slowing them down). It’s also a reminder that Siemens Healthineers is serious about supporting its homegrown AI portfolio through academic research.

The Multitenant Cloud 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.

Windsong’s Case for MEDRAD Stellant FLEX CT

Learn how Windsong Radiology Group used Bayer’s MEDRAD Stellant FLEX CT injection system to drive efficiencies and standardization across its imaging centers.

The Wire

• Ultra-Portable MRI Validation: A team of Spanish scientists developed and tested an ultra-portable and low-cost extremity MRI (72mT, 70cm wide, 250kg, <€50k), finding that it could produce diagnostic-quality exams in “previously unrealistic” settings. The researchers used the MRI to scan a volunteer’s knee in five different environmental and power source settings (the lab, a home, an office, outdoors with electricity, open air with a gas generator), producing diagnostic images in clinically viable scan times.

• Automated Cancer Coordination: A PLOS Digital Health study of 127 liver cancer patients at a VA hospital found that an automated system for reviewing radiology reports improved the timeliness of care. The EHR-linked system generated a queue of abnormal cases for review while allowing care coordinators to create lists of next steps / reminders. Over the course of the 5-year study, the system reduced mean time from diagnosis to treatment by 36 days, time from imaging to diagnosis by 51 days, and time from imaging to treatment by 87 days.

• ‘Staggering’ CVD Rise: A study published in JACC projects steep increases in cardiovascular disease in the coming decades, with major patient care (and likely imaging) implications. By the year 2060, the number of people with ischemic heart disease is forecast to increase by 31% (22M to 29M), heart failure by 33% (10M to 13M), myocardial infarction by 30% (12M to 16M), and stroke by 34% (11M to 15M). 

• Using Thyroid AI with Breast Lesions: Just as AI is starting to work with pathologies it’s trained to detect, a team of South Korean researchers explored using a thyroid ultrasound AI tool to assess breast cancer lesions. The thyroid ultrasound AI tool originally performed poorly with 1,042 breast lesions (0.678 AUC), but improved after fine-tuning training with 1,084 separate breast lesions (0.841 AUC). Despite these “not bad” results after fine-tuning, the authors concluded that an organ-specific approach to AI training “guarantees better diagnostic performance.”

• Mammography’s Healthcare Cost Barriers: A new JACR study highlighted a number of patient-reported healthcare cost barriers that appear to reduce mammography screening utilization. Survey data from 7.5k American women (69% screened within prev. 2yrs) revealed that women are less likely to attend mammography screening if they worry about the cost of medical bills, find affording dental care or eyeglasses “challenging,” or skip/reduce/delay their medication refills (odds ratios: 0.86, 0.65, 0.67, 0.69/0.63/0.71).

• Mayo Clinic + Mercy: Mayo Clinic and Mercy Health entered a 10-year partnership to share deidentified patient data from over 500M visits to develop novel AI algorithms focused on “personalized, predictive, and proactive medicine.” Most larger health systems do similar work with their own data, but this collaboration is designed to take advantage of Mayo Clinic and Mercy’s different populations and geographies to help reduce model bias while improving the accuracy of treatment recommendations.

• MGB’s CT Contrast Intervention: An AJR study detailed how Mass General Brigham’s EHR-based interventions helped it reduce contrast-enhanced CT volumes during the recent shortage. The first EHR intervention on May 10th informed referrers of the shortage and recommended alternative modalities, while the second intervention on May 16th required referrers to enter detailed clinical information. As a result, MGB’s contrast-enhanced body CT volumes fell from 561 patients per weekday, to 531 after the first intervention, and 491 after the second, even though its overall CT volumes remained steady (1,350, 1,323, 1,314).

• Siemens Supports AvoMD: AvoMD named Siemens Healthineers as a supporter of its app that will make the CAD-RADS 2.0 guidelines available to referring clinicians at the point of care. AvoMD’s app combines the Society of Cardiovascular Computed Tomography’s clinical expertise with AvoMD’s decision support technology in an effort to streamline CV care. Siemens is providing financial backing to offset costs associated with app development. 

• Aidence Efficiency & Consistency: An EJR study highlighted Aidence’s Veye Lung Nodules solution’s ability to improve radiologists’ lung nodule reporting efficiency and consistency. The researchers had two radiologists assess 50 chest CT cases, finding that Veye Lung Nodules reduced the radiologists’ reading times by 33.4 % and 42.6 % (226min to 151min, 321min to 184min), while improving their agreement rate (kappa: 0.61 to 0.84).

• Four Strikes and You’re Out: A 2,000 consumer survey from ModMed found that 73% of patients keep a “mental scorecard” of their doctor visits, and allow an average of four strikes on poor experiences before picking a new provider. Timeliness and modern technology use were the top factors contributing to a good experience, although 67% said friendliness of staff influences their provider choice and one-third said they’ve switched providers due to an unpleasant encounter with office staff. This study might not apply to most radiologists, but it seems very applicable to imaging centers.

• Inappropriate ENT Imaging: A new Insights into Imaging study revealed particularly high inappropriate otolaryngology imaging volumes at two Spanish hospitals. A review of 538 otolaryngology imaging orders found that just 42% were appropriate, while all other exams were inappropriate, not adequately justified, or not included in the guidelines (34%, 12%, 12%). Primary care physicians were most likely to order inappropriate exams (78%), while sinus X-ray orders were most likely to be inappropriate (60.7%).

What it Means to be Built for the Modern World

Find out what built for the modern world means — and why it matters — in this Aunt Minnie profile on United Imaging’s more modern approach to vertical integration, leadership, and culture.

The Resource Wire

• Considering your short and long-term AI plan? Check out Canon Medical’s State of AI Roundtable, sharing insights into how imaging AI is being used, where it’s needed most, and how AI might assume a core role in medical imaging.

• Discover how Enlitic’s Curie|ENDEX application transforms medical imaging data to a standard nomenclature to form a foundation for successful artificial intelligence strategies.

• Hyperfine’s MRI accessibility advantage doesn’t stop at image acquisition. See how Hyperfine’s BrainInsight AI tools give clinicians the quantitative biomarker information needed to streamline patient care and reduce the burden of manual brain MRI measurements.

• Working on your organization’s AI strategy? This Blackford Analysis post outlines the key considerations for creating your AI goals and strategy, including some you might not have considered. 

• Check out this patient case study showing how the Arterys Chest I MSK AI allowed radiologists at CSE in Paris to identify a fracture that was missed in three previous interpretations.

• What’s Next in Image Management? Check out this interview with Intelerad president Morris Panner, discussing key takeaways from SIIM 2022, new insights into AI adoption, and emerging goals for enhancing radiology workflow efficiency.

• Ready to address burnout on your team? This Novarad report details the main burnout drivers within imaging teams, and the steps radiology leaders can take to prevent burnout.

• After setting ambitious regulatory and commercialization goals, Lunit leveraged CARPL.ai’s platform and operational guidance to complete the clinical trials needed for its INSIGHT CXR and MMG AI tools’ FDA clearances.

• Siemens Healthineers’ NAEOTOM Alpha made headlines as the world’s first photon-counting CT system, a technology that’s poised to redefine CT imaging. Check out this whitepaper detailing how the NAEOTOM Alpha’s unique resolution, contrast-to-noise ratio, and spectral sensitivity advantages could change CT forever.

• This Riverain Technologies case study details how Einstein Medical Center adopted ClearRead CT enterprise-wide (all 13 CT scanners) and how the solution allowed Einstein radiologists to identify small nodules faster and more reliably.

• “When will I be back?” is athletes’ first question following a sports-related injury, and New York’s Hospital for Special Surgery increasingly relies on GE Healthcare MR technology for its answers. See how HSS is leveraging GE’s MR scanners, coils, and solutions to achieve more accurate assessments and better patient experiences.

• Check out this Imaging Wire Show featuring Us2.ai’s co-founders, James Hare and Carolyn Lam MBBS, PhD, detailing Us2.ai’s unique origins, impressive capabilities, and big goals to automate echocardiography reporting across the world.