Intelerad’s Jonathan Robinson SIIM panel comment on the diverse use and understanding of many cloud imaging terms and technologies.

Imaging Wire Sponsors

Arterys  •  Bayer Radiology  •  Blackford Analysis  •  Canon Medical Systems  •  CARPL.ai  •  Change Healthcare  •  Fujifilm Healthcare  •  GE Healthcare  •  Intelerad  •  Novarad  •  Nuance  •  Riverain Technologies  •  Siemens Healthineers  •  United Imaging  •  Us2.ai

Informatics

SIIM 2022 Recap

The first in-person SIIM meeting since COVID hit is officially a wrap, delivering the latest in informatics and a family reunion vibe that might have surpassed any other imaging event. Here’s the top takeaways from the biggest imaging informatics conference of the year.

Crowds & Conversations – We understand there were 300 to 400 on-site attendees at SIIM 2022 (excluding exhibitors), with far more attendees in the educational sessions and afterparties than the exhibit hall booths. Still, it was clear that there’s no better place for informatics leaders and vendors to get together than SIIM.

Big Cloud – The shift to the cloud felt more inevitable than ever last week. The cloud was at the center of nearly every vendor and providers’ informatics roadmaps, while the AWS/GCP/Azure “healthcare cloud land grab” appears to be having an underrated influence on cloud adoption. That said, SIIM22’s cloud PACS conversations hadn’t changed much from previous years…

• Everyone still agrees about the cloud’s security and administrative upsides
• PACS vendors are still debating cloud native vs. cloud enabled (…and questioning whether providers know the difference or care as much as they do)
• Nobody is willing to adopt cloud at the expense of PACS performance
• And because of that, hybrid cloud remains the realistic starting point for many providers

Integrating AI – AI remained a major theme at SIIM, although most conversations focused on how to adopt and integrate AI (and then get ROI), rather than how AI can improve diagnosis. That probably explains why the exhibit hall featured far more AI distributors (AI marketplaces, PACS AI platforms, etc.) than AI developers, and it serves as a good reminder for AI vendors to continue improving their integration capabilities.

Productivity Hacks – Unsurprisingly, radiologist productivity was a common theme through the presentations and exhibit hall booths, ranging from the ultra-logical (fast PACS, administrative AI) to the ultra-ambitious (single-vendor unified imaging IT systems). 

Inconsistent Imaging – This might be old news to many of you, but I was amazed to learn how far many organizations are from achieving informatics best practice. I heard a lot about patched together workflows, outdated PACS versions, inconsistent site setups, antiquated imaging sharing, and narrowly-defined enterprise imaging. The silver lining to that is there’s plenty of room for improvement, but it also suggests that some imaging organizations will need a lot of work before they’re technologically prepared for the next-gen stuff we talked about all week.

The Takeaway

SIIM 2022 made it abundantly clear that there are seismic changes coming to imaging informatics, and even if those changes will probably take longer than some might hope, their impact might be greater than many of us expect. There’s also plenty of opportunities to improve radiology workflows in the short-term, and some of the smartest people in healthcare are ready to deliver these improvements.

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.

Qure.ai & CARPL.ai’s Real Time Validation

Faced with the task of monitoring the thousands of exams its algorithms analyze each day, Qure.ai leveraged CARPL.ai’s validation workflow to create a real-time performance dashboard. See how they did it here.

The Wire

• Pediatric Imaging Disparities: A large JAMA study (38 hospitals, 27 states, 12M ED visits) showed that US children’s hospitals that serve more Hispanic and Black patients have greater imaging utilization discrepancies. Black patients were consistently less likely to receive diagnostic imaging than White patients at every hospital, while there was a significant correlation between a hospital’s proportion of minority patients and the imaging utilization difference between White and Black patients (correlation coefficient, −0.37).

• An AI Education Lesson: A team from the University of British Columbia shared valuable insights into how best to teach future doctors about AI. After training 350 med students in a 5-week workshop, the authors identified a series of educational challenges (knowledge disparities, curricular depth vs. breadth, knowledge retention) and successes (addressing AI concerns, open-access resources, and multidisciplinary collaboration) that they encountered. Based on their experience, they recommend that future AI educators: (1) standardize their curricular structure, (2) create AI case studies, (3) use experiential learning, and (4) involve a diverse group of trainees.

• Pros & Cons of WBCT: A new Emergency Radiology study highlighted the pros and cons of implementing whole-body CT (WBCT) for lower-extremity trauma patients in the ED. The authors evaluated patient throughput during the six months before and after Indianapolis’ University Methodist Hospital adopted WBCT (n=58 & 58), finding that the protocol decreased the time patients spent in the ED (416 to 340 min) and reduced X-ray images per patient (2.8 to 0.8), but significantly increased overall imaging costs ($23.66 to $95.53) and radiation exposure (4.03 to 7.61 mRem).

• Aidoc in Barcelona: Aidoc announced a new AI partnership with Hospital Clínic de Barcelona (HCB), revealing plans to deploy three AI detection modules (ICH, PE, incidental PE) that will be used to improve HCB’s patient care and train its radiology residents. HCB joins 12 other European academic medical facilities using Aidoc AI, in addition to a growing number of North American institutions.

• Pandemic Cancer Screenings: A survey of 480k US adults led by the American Cancer Society found that preventative cancer screenings dropped by as much as 80% during the first few months of the pandemic (vs. 2018), with full-year 2020 screenings declining 6% for breast cancer, 11% for cervical cancer, and 16% for colorectal cancer.

• GE Adds Q-IT’s Helix Suite: GE Healthcare led off SIIM 2022 with the addition of Q-IT’s Helix Radiology Performance Suit workload management solution to the GE PACS portfolio. Developed by Q-IT (a subsidiary of large rad practice Quantum Imaging) the Helix Suite uses predictive analytics to prioritize and assign exams on the worklist based on real-time assessments of a practice’s available radiologists and their skill sets. Quantum Imaging found that Helix can boost radiologists’ reading capacity by up to 20%, with similar improvements to super STAT and STAT/ED turnaround times (16.7%  & 20.5%).

• Shields Cyberattack: Major New England imaging center and ASC company, Shields Health Care Group (30 locations), disclosed that a cyberattack exposed 2M of its patients’ information. Shields confirmed that the individuals’ full names, social security numbers, dates of birth, home addresses, provider information, diagnoses, billing information, medical record number, patient IDs, and more were accessible and/or removed from its systems. Although health system ransomware attacks justifiably get all the publicity, at least seven US practices and imaging centers have disclosed security incidents since the start of 2021.

• COPD AI 5yr Predictions: Korea-based researchers developed a chest X-ray-based deep learning algorithm that predicted COPD patients’ 5-year survival rates more accurately than conventional methods. When tested using three external CXR datasets (n=394, 416, 317), the algorithm predicted 5-year outcomes more accurately than “forced expiratory volume in 1 second” measurements (FEV1) with two of three cohorts (AI vs. FEV1 AUCs: 0.73 vs. 0.63; 0.67 vs. 0.60; 0.76 vs. 0.77).

• Mirada’s Growth Round: Mirada Medical completed a $17M growth round (total funding now $26M) after private equity firm Apposite Capital doubled down on its original 2019 investment. Mirada develops AI autocontouring software for personalized radiation oncology treatment planning, and the fresh funding should help it expand its partnerships, product lineup, and customer base.

• YOLO BC Predictions: Aiming to reduce mammography screening false-negatives, University of Louisville researchers developed a You-Only-Look-Once (YOLO)-based AI model that can predict which patients with “normal” prior mammograms would have cancerous screenings roughly one-year later. The authors used two image-to-image translation techniques (Pix2Pix and CycleGANs) to create synthetic mammograms from 413 patients’ “normal” priors and current cancer-positive exams. The YOLO-based model was able to detect and classify different types of abnormalities with 88%-95% accuracy in current exams, and 36%-50% accuracy in prior exams.

• GE & NCCS AI Alliance: GE Healthcare announced a research collaboration with National Cancer Centre Singapore (NCCS) focused on developing new AI-powered data analytics and clinical workflows solutions that will be used to create more personalized cancer treatment methods. The collaboration will combine GE’s imaging and monitoring expertise with NCCS’s expertise in R&D, testing, and consultation.

The Future of Radiology Starts on June 30th

Reserve your spot for AI Visions 2022, featuring live discussions from the top radiology and AI leaders and the global launch of Bayer’s Calantic Digital Solutions AI marketplace.

The Resource Wire

• Enterprise Imaging has come a long way, and it has a long way to go. This Intelerad white paper details the five pillars organizations should prioritize in order to realize the full potential of EI’s next evolution.

• See how Canon Medical’s AiCE image reconstruction solution allows Cartesion Prime digital PET/CT users to further improve image quality and reduce scan times.

• Ready to Update Your PACS? This Novarad blog outlines the product, vendor, future-proofing, and support considerations to help make sure you select the right system.

• Precision medicine startup BAMF Health just installed United Imaging’s uEXPLORER scanner, making it the first total-body PET/CT used for theranostics in the US. See how this combination will allow BAMF Health to deliver more effective and efficient theranostics treatments.

• Us2.ai recently announced the global launch of its flagship echocardiography AI solution, leveraging a new $15M Series A round, and its unique abilities to completely automate echo reporting (complete editable/explainable reports in 2 minutes) and analyze every chamber of the heart (vs. just left ventricle with some vendors).

• Creating your AI adoption plan? This Arterys report details what clinical, efficiency, and regulatory factors to look for in radiology AI vendors.

• Working out your AI business case? Check out this helpful Blackford Analysis post outlining the three steps to help you justify AI adoption. 

• Is your organization ready to move enterprise imaging to the cloud? Check out this Change Healthcare and ACHE webinar detailing cloud-native imaging’s benefits, best practices, and ROI.

• Pediatric patients can’t always accurately describe their orthopedic-related pain. Read how Lorenzo Biassnoi, MD, describes how SPECT/CT can help in this SPECT/CT and pediatric orthopedic surgery story.

• 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.

• 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 SPECT/CT substantially improved health outcomes for non-small-cell lung cancer treatment planning compared to planar imaging, while remaining highly cost-effective, in this GE Healthcare-supported study.