#428 – The Wire

  • The Cost of Follow-Ups: A recent KHN exposé brought attention to the downstream out-of-pocket costs created by the US’ policy of covering preventive care (e.g. cancer screening), but not follow-up diagnostics (biopsies, imaging, etc). The article highlighted recent progress with follow-up colonoscopies and CTCs, and ongoing legislative efforts to cover follow-up breast cancer diagnostics, but warned that these efforts will have to overcome pushback from payors.
  • Aidoc’s $110M Expansion: Aidoc closed a massive $110M Series D round, increasing its total funding to $250M, and revealing plans to further expand its AI Care Platform across hospital departments. Nine-figure funding totals have historically been reserved for care-connected imaging AI players (e.g. Viz.ai’s $251M & HeartFlow’s $577M) or healthcare startups outside of radiology, so this is a major milestone for the triage/detection side of AI (where Aidoc got its start). Meanwhile, an expansion to new hospital service lines and clinical workflows would be a major step for Aidoc’s long-term strategy.
  • O-RADS General Effectiveness: A recent JAMA study showed that the ACR Ovarian-Adnexal Reporting and Data Systems (O-RADS) ultrasound risk stratification system also performs well with low-risk populations. The study among non-selected, low-risk women (n = 913, w/ 1,014 adnexal lesions) found that O-RADS US 4 was the optimum cutoff for diagnosing cancer, with 90.6% sensitivity, 81.9% specificity, 31.4% PPV, and 99% NPV. Researchers have previously validated O-RADS in selected populations, but this research shows the system can also be applied to a general population of women seeking pelvic ultrasonography.
  • YNHH Home Hospital: Yale New Haven Health is partnering with Medically Home to launch a Home Hospital Program for local Medicare patients. Patients who would otherwise need to be hospitalized will instead receive a daily telehealth visit with a physician through a provided tablet, twice-daily in-person visits from a nurse, plus additional services (including mobile imaging). Although this isn’t really an imaging story, patient care’s continued shift beyond hospital walls definitely has imaging implications.
  • Cardiac MRI AI Measurements: UK researchers developed and evaluated a cardiac MRI AI model, finding that the model’s automated CMRI measurements correlated better than manual measurements for left ventricular stroke volume (r = 0.74 vs. 0.68), pulmonary vascular resistance (r = 0.62 vs. 0.41), and pulmonary artery pressure (r = 0.56 vs. 0.37) with 178 patients. Moreover, AI-measured right ventricular end-systolic volume, ejection fraction, and mass all predicted mortality in 920 patients with pulmonary arterial hypertension (hazard ratios: 1.40, 0.76, and 1.15) over a 3.8yr average follow-up period.
  • Hyperfine Down Under: Hyperfine announced that its Swoop portable MRI is now available in Australia and New Zealand, following the completion of its AU/NZ registration and notification process and the appointment of Quantum HealthCare as its local distributor. Multiple Swoop pilot research units have already been ordered across key Australia and New Zealand cities, laying the foundation for its upcoming commercial efforts.
  • Refining Lung Cancer Screening Candidates: A new Radiology Journal paper detailed an AI-based approach for improving lung cancer screening candidate selection, compared to the current USPSTF criteria. The research showed that excluding low- or indeterminate- risk candidates (identified with CXR-based AI) from a subset of USPSTF-eligible individuals (n = 7,835) reduced the proportion of candidates selected for LD-CT screening from 45.1% to 35.8%, while maintaining cancer inclusion rates (0.3% vs. 0.3%) and PPV (0.9% vs. 0.7%; P=0.85).
  • Infinitt & Brainreader: INFINITT North America announced plans to integrate Brainreader’s FDA-cleared Neuroreader software. Neuroreader can visualize and quantify 45 individual brain structures on MRIs in under 10 minutes, helping clinicians determine which regions are abnormal and to what extent.
  • AI Model Imbalances: When AI models are trained on datasets weighted towards patients with the condition they’re trying to predict, they often struggle to identify patients without the condition. A new study published in JAMIA found that efforts to correct these imbalances frequently do more harm than good. In an ovarian cancer study, the authors found that adding more examples of the minority outcome to fix the model led to a strong overestimation of patients in the minority group, further adding to the miscalibration and reducing the model’s clinical viability.
  • Another Call to Ditch the Disk: Former ACR Chair Geraldine McGinty, M.D., MBA, FACR took another stand against CD-based image sharing in a Journal of Digital Imaging editorial. Dr. McGinty outlined the “outdated” and “embarrassing” practice’s impact on repeat imaging volumes/costs, incidental findings, and diagnostic accuracy (due to lack of access to priors), calling for a multi-stakeholder effort and potential changes to regulations/reimbursements to address this issue. However, she admits that we might not be able to completely “Ditch the Disk” until using CDs becomes prohibited.
  • Healthcare Hiring Boost: The US healthcare sector recently saw a bump in hiring according to the May Jobs Report, adding 28k jobs throughout last month, including 16k hospital workers. Following hospitals, the subsectors with the largest workforce gains were ambulatory services, physician offices, and nursing care facilities, each adding ~6k employees. Despite the improvement, the healthcare workforce remains 1.3% (223k jobs) below pre-pandemic levels, compared to a 0.5% decline across all industries.

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-- The Imaging Wire team