Weekly AI digest
Radiology & medical imaging AI · week of 9 to 15 August 2026
187 peer-reviewed papers · 5 industry and regulatory items · conference and KOL highlights. Adapted from my weekly intelligence report. Full report: FR (PDF) · EN (PDF) · RU (PDF).
Governance takeaway
What to do about it this week
If mammography AI is live in your department, split recall monitoring by pathway this month. A year-long alternating-month deployment doubled cancer detection without slowing reading, but abnormal interpretations rose only in diagnostic mammography, 18.7% versus 12.1%, while screening stayed flat. A single pooled recall metric would have hidden that shift.
Add abnormal interpretation rate by pathway to your monthly monitoring file; the same file becomes the seed of your EU AI Act Article 72 post-market record.
Regulation & AI Act watch
Medicare approves add-on payment for Aidoc CT body triage
CMS finalized a New Technology Add-on Payment of up to $137.53 per eligible inpatient case for CARE CT Body Multi-Triage from 1 October 2026, a triage clearance that prioritizes worklists rather than diagnosing, granted through a pathway that waives proof of substantial clinical improvement and closes from FY2028. The question to answer before relying on it: what do your own override and concordance rates show, since reimbursement changes the economics but not the local validation burden.Twelve US health systems form Diagnostic AI Consortium
Twelve systems covering roughly 20 million patients a year committed to shared standards for evaluating, deploying and governing diagnostic AI, with Aidoc as technical infrastructure and results promised for 2027. Watch whether standards built on one vendor's platform prove portable, and whether outcome measurement stays independent of the infrastructure provider being measured.Leica Biosystems clears first AI-assisted QC software for digital pathology
Aperio iQC DX is cleared to detect six acquisition artifacts on-scanner in clinical digital pathology, with no published performance study cited. Ask the vendor for per-artifact sensitivity and specificity and the measured impact on rescan rates before treating automated QC as a control.CliniComp clears an EHR-integrated PACS viewer
A viewer clearance as a Medical Image Management and Processing System carries no detection or triage claim, whatever the surrounding language about native AI prioritization implies. Ask which AI functions sit inside the cleared intended use and which are unregulated workflow features.Coreline Soft and Optellum declare intent to collaborate on the lung pathway
The proposed integration would wire FDA-cleared nodule detection into a separately cleared risk-scoring platform. Detection and risk scoring are separate claims on separate evidence; combining them in one workflow does not create a cleared end-to-end pathway.
Evidence you can use
Selected from 187 papers indexed in PubMed this week.
Impact of AI assistance on reading time, cancer detection rate, and abnormal interpretation rate in screening and diagnostic mammography: a prospective alternating-month study
European Radiology, 13 August 2026Prompt Configurations for Multimodal Large Language Models in Diagnosing and Staging Osteonecrosis of the Femoral Head: Multimodel Retrospective Observational Diagnostic Study
Journal of Medical Internet Research, 10 August 2026Vendor-Agnostic Multisite Automated Dual-Energy X-Ray Absorptiometry Reporting Using Artificial Intelligence-Based Optical Character Recognition: Impact on Workflow Efficiency and Accuracy
Journal of the American College of Radiology, 13 August 2026Adapted foundation models for breast MRI triaging in contrast-enhanced and non-contrast-enhanced protocols
European Radiology, 13 August 2026Deep-learning triage of three-dimensional pathology datasets for comprehensive and efficient pathologist assessments
Nature Biomedical Engineering, 12 August 2026Deep Learning-Based Enhancement of Already Diagnostic-Quality MRI for Alzheimer's Disease Classification: Effects on Model Performance and Training Data Requirements
Journal of Magnetic Resonance Imaging, 13 August 2026Prediction of Central Lymph Node Metastasis in Papillary Thyroid Microcarcinoma Using a Deep Learning Radiomics Model Based on SAM3 Automatic Segmentation of Ultrasound Images: A Multicenter Cohort Study
Academic Radiology, 12 August 2026From voxel discovery to regional interaction: A multi-level interpretable framework for Alzheimer's disease diagnosis
Medical Image Analysis, 12 August 2026
Post-market signal
SIIM published a recap of its webinar on post-production monitoring of deployed radiology AI, and it reads as a field report on what Article 72-style obligations look like in practice. Penn Medicine runs a governance committee spanning demo approval through post-deployment monitoring; Dasa tracks drift on an in-house MRI denoising model by watching input voxel distributions and input-output similarity over time; and Greensboro Radiology has declined FDA-cleared tools over poor real-world performance, monitoring deployed algorithms by comparing predictions against radiologist impressions extracted from reports. The shared message: clearance is the start of the evidence obligation, not the end.
A Clinical Imaging survey of 215 Society of Breast Imaging members adds the deployer-side view. About half worked in organizations with breast detection AI live, yet only a minority reported measurable improvement in callback rate, biopsy rate or burnout; recall rates fell around 35% among current users against non-user expectations, unnecessary biopsies only about 9%. Adoption is running ahead of measured benefit, which is exactly why departments should track their own deltas rather than projected ones.
Playbook snippet
One step for your AI committee
Anchor: EU AI Act Article 72 (post-market monitoring); ISO/IEC 42001 performance evaluation clause.
Step: Sample 20 AI outputs per month against the final signed report and track one number: the concordance rate. Plot it monthly and act on the trend, not on any single dip.
Why: Drift is invisible in aggregate accuracy and visible in a monthly line; a series started now is history you will already own when the monitoring obligation bites.
Worked example: Lakhani P et al. audited 400 AI-drafted DXA reports against the source images, not the prior reports, across four sites: 99.9 to 100% numerical accuracy, and the audit surfaced a 45% completeness rate in the human baseline at community sites. JACR, PMID 42595274, DOI 10.1016/j.jacr.2026.08.007.
From the field
The ACR published its detailed summary of the CMS FY2027 IPPS final rule on 13 August: a 2.3% hospital payment update, roughly $779 million in new-technology case payments, and the end of the alternative NTAP pathway from FY2028, after which every technology seeking add-on payment must demonstrate substantial clinical improvement. The evidence bar for US inpatient reimbursement just moved up.
The American Board of Radiology set out its AI position in a 12 August update: no AI in certification decisions or exam content, human experts retain scoring, and governance structures come before any adoption. A certification body publishing its human-oversight boundary is itself a governance signal for the specialty.
Curt Langlotz spent the week amplifying work on confidence-based control of clinical report generation, where an operating point on the false-positive curve gates what an LLM writes into the draft, alongside Stanford AIMI's pediatric echocardiography model in Circulation and the Nature Health analysis of 617,827 health conversations with Microsoft Copilot.
Daniel Pinto dos Santos flagged the joint EuSoMII and MICCAI session on the future of AI in medical imaging at October's EuSoMII Annual Meeting in Heraklion, themed on safe integration of AI tools in practice, while Amine Korchi pointed to voice AI agents for practice administration as the segment of medical AI with the lowest deployment friction.
Source articles are indexed in PubMed with verified DOIs. Manuscript-stage work is excluded. The full weekly report is produced in French.
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