Tag: structured reporting

Vizamyl’s New PET Label: Quantify & Monitor Amyloid—What It Means for Imaging Teams

 

What changed—and why it matters

The FDA has expanded the label for flutemetamol F 18 (Vizamyl), enabling quantification of amyloid plaque burden and long-term therapy monitoring in Alzheimer’s disease. This shift moves amyloid PET beyond a qualitative “positive/negative” decision toward objective, longitudinal assessment that can inform treatment choice, dose intervals, and discontinuation decisions. Business Wire

Professional groups report the update aligns amyloid PET with the clinical era of disease-modifying anti-amyloid therapies (e.g., lecanemab, donanemab), clarifying roles for baseline confirmation, on-treatment monitoring, and response tracking in routine care. Notably, SNMMI stated the FDA granted supplemental indications—including quantitative measurement and use for therapy monitoring—to three amyloid PET agents (flutemetamol F-18/Vizamyl, florbetapir F-18, and florbetaben F-18). SNMMI

Operational updates for radiology leaders

  • Protocols & quant pipelines: Build or validate a quant workflow (SUVr or comparable metrics) that’s scanner-calibrated and reproducible across sites. If you operate multi-vendor fleets, document harmonization steps in your SOPs.
  • Structured reports: Add fields for quantified burden at baseline, change from baseline, and interpretive guidance tied to therapeutic decisions (initiation, continuation, or discontinuation).
  • Scheduling & throughput: Expect rising referral volume from neurology and geriatrics as therapy monitoring enters routine practice; protect access with extended hours or overflow capacity.
  • Quality & governance: Define thresholds for biologically meaningful change, reader training for quant review, and reconciliation rules when quant and visual impressions diverge.

For additional context, trade coverage underscores that the updated label formally removes previous limitations around therapy monitoring and permits quant analysis in routine reporting. Empr

How Vesta Teleradiology helps

Vesta’s subspecialty neuro and nuclear medicine radiologists provide:

  • Amyloid PET expertise: Visual+quant reads with structured templates aligned to your therapy pathway.
  • Coverage when you need it: After-hours, weekends, or daytime overflow—without sacrificing turnaround time.
  • Interoperability: Seamless delivery to your PACS/RIS and EMR; clear flags for therapy decisions and recall intervals.
  • QA you can see: Peer review, consistency checks across readers, and optional double-reads during program ramp-up.

If you’re standing up or scaling amyloid PET services, we can supply immediate subspecialty coverage and templates tuned to your neurologists’ needs.

 

FDA’s 2025 AI Draft Guidance: A Buyer’s Checklist for Imaging Leaders

In January 2025, the U.S. Food and Drug Administration released a draft guidance for AI-enabled medical devices that lays out expectations across the total product life cycle—design, validation, bias mitigation, transparency, documentation, and post-market performance monitoring. For imaging leaders, it’s a clear signal to tighten procurement criteria and operational guardrails before piloting AI in CT, MRI, mammo, ultrasound, or PET.

As teams lock in Q4 budgets and head into RSNA season, the FDA’s AI lifecycle draft (Jan 2025) and the now-final PCCP (Dec 2024) have reset what buyers should expect from AI in imaging—devices, software, and workflows. Vendors are updating claims and governance; this issue distills a practical buyer’s checklist—multisite validation with subgroup results, drift monitoring and version control, clear in-viewer transparency—and how pairing those tools with Vesta’s subspecialty coverage and QA turns promise into measurable gains across CT/MRI/US/mammography.

A practical buyer’s checklist

Use this when evaluating AI for your service lines:

  1. Intended use fit: Verify indications, inputs/outputs, and claims match your pathway and patient mix.
  2. Validation depth: Prefer multisite, diverse datasets; stratified results; pre-specified endpoints; documented data lineage and splits.
  3. Bias mitigation: Demand subgroup performance (sex, age, race/ethnicity when available), scanner/vendor variability analyses, and site-transfer testing.
  4. TPLC plan: Require drift monitoring, retraining triggers, versioning, and how updates are communicated.
  5. Human factors & transparency: Ensure limitations, failure modes, and interpretable outputs are presented in-viewer without slowing reads.
  6. Security & support: Patch cadence, vulnerability disclosure, SOC2/ISO posture, uptime SLAs, and rollback paths for version issues.
  7. Governance: Define metrics owners, review cadence, and thresholds to pause or roll back a model.

Implementation playbook: pilot → scale without disruption

Start with a 60–90 day pilot in one high-impact line (e.g., ED stroke CT or mammography triage) and lock in baselines: median TAT, positive/negative agreement, recall rate, PPV/NPV, and discrepancy rate. Set guardrails—when to auto-triage vs. force human review—and document escalation paths for model failures. Require case-level confidence and structured outputs your radiologists can verify quickly. Stand up a model governance huddle (modality lead, QA, IT security, and your teleradiology partner) that meets biweekly to review drift signals, subgroup performance, and near-misses. Bake in a rollback plan (version pinning) and a quiet-hours change window so updates don’t collide with peak volumes. As results stabilize, scale by cohort (e.g., expand to non-contrast head CT, then CTA) and keep training “micro-bursts” for techs/readers—short videos or checklists in-workflow. Tie vendor SLAs to uptime, support response, and clinical KPIs so the AI program stays accountable to operational value.

Where teleradiology fits

AI only delivers when it’s welded to coverage, quality, and speed. A teleradiology partner should provide:

  • 24/7 subspecialty + surge capacity: Vesta absorbs volume peaks so AI never becomes a bottleneck.
  • QA you can see: We benchmark pre/post-AI performance, add targeted second looks for edge cases, and feed variance data back to your team.
  • Standardized outputs: Structured reports that integrate model outputs with radiologist findings—no black-box surprises.
  • Smooth rollout: Pilot by service line (stroke CT, mammo triage, PE workups), then scale with tracked KPIs (TAT, PPV, recalls).
  • Interoperability & security: Seamless PACS/RIS/EMR integration with strict access controls, audit trails, and support for change-controlled updates.

Bottom line: Pairing AI with Vesta Teleradiology gives you round-the-clock subspecialty reads, measurable QA, and operational breathing room while you pilot and scale responsibly. If you’re mapping your AI roadmap under the FDA’s 2025 draft guidance, we’ll be your coverage and quality backbone—so your clinicians see faster answers and your patients see safer care. Visit vestarad.com to get started.