Continuous MRI Quality Intelligence

MRIQA extends traditional phantom QA by combining phantom validation with real patient-series quality analytics — detecting hidden scanner drift, protocol inefficiencies, and image artifacts before they affect clinical quality.

Initial Clinical Pilot Completed · GE Signa HDxt (1.5T)
100 Clinical Series30 Phantom AnalysesInitial GE DeploymentVendor-Neutral Architecture
ACR-ReadyDICOM-NativeVendor-NeutralPACS-CompatiblePhysicist-Supported

Clinical Pilot Findings

A single-scanner pilot on the GE Signa HDxt 1.5T revealed measurable quality gaps invisible to standard phantom testing.

100 Clinical Series30 Phantom Analyses6 Sequence Groups574 Recommendations Generated

Statistically Significant Variation

Kruskal-Wallis: H = 21.60, p = 0.0006, η² = 0.177. Significant image-quality differences across sequence types — invisible to phantom QA.

Ghosting 69× Above Threshold

Clinical series showed ghosting artifacts 69× higher than ACR phantom results on the same scanner.

PIU Drift Below ACR Threshold

PIU dropped below the ACR 87.5% threshold in clinical series while phantom QA continued to pass.

574 Actionable Recommendations

Prioritized HIGH / MEDIUM / LOW across all series. Protocol-specific, not generic.

Pilot Finding: Phantom QA Misses Real-World Patient Artifacts

Ghosting 69× Higher in Clinical Series

  • ACR phantom ghosting: 0.4% — well within threshold
  • Clinical series ghosting: 27.6% — 69× higher on the same scanner
  • Standard phantom QA gave no warning

Pilot Finding: Catching Drift Before It Becomes a Problem

PIU Dropped Below ACR Threshold Undetected

  • Phantom QA: PIU consistently passed at 91–93%
  • Clinical series PIU: dropped to 84.2% — below the ACR 87.5% threshold
  • Longitudinal trending caught the drift; phantom QA did not

Why Phantom QA Alone Is Not Enough

ACR phantom QA validates scanner performance under controlled conditions — not real clinical variability.

Silent Quality Drift

Scanner performance degrades gradually between phantom QA cycles, going undetected until it affects patient images or triggers a failed accreditation.

Protocol Drift

Phantom QA uses fixed protocols that may not reflect the clinical sequences actually used on patients.

Single-Scenario Testing

Phantoms test one controlled scenario and cannot capture the variable anatomy, motion, and positioning of real patients.

Coil & Channel Degradation

Individual coil elements and RF channels can silently underperform on patient scans even when phantom QA passes.

Why MRIQA Is Different

MRIQA adds the continuous, patient-specific layer that phantom testing cannot provide.

Platform Overview

The MRIQA Platform

Three integrated modules deliver continuous MRI quality intelligence from phantom validation to patient-series analytics and prioritized recommendations.

Technical Differentiator

Sequence-Aware Quality Scoring

MRIQA benchmarks image quality by sequence type, enabling protocol-specific optimization instead of generic pass/fail QA. Each sequence is benchmarked against sequence-specific quality baselines.

1

T1-weighted

2

T2-weighted

3

FLAIR

4

DWI (Diffusion-Weighted)

5

SWI (Susceptibility-Weighted)

6

Additional sequences auto-classified

Who MRIQA Is Built For

MRIQA supports the full MRI quality ecosystem — from physicists to radiology leadership.

Medical Physicists

Automate ACR metric extraction, track longitudinal trends, and generate accreditation-ready reports with physicist sign-off built in.

Radiology Directors

Monitor fleet-wide scanner performance from a single dashboard, identify protocol inconsistencies, and reduce repeat scans.

Accreditation Teams

Maintain continuous, audit-ready documentation of scanner performance and corrective actions between ACR accreditation cycles.

Service Engineers & Biomedical Staff

Detect early hardware degradation signals — coil performance, channel dropout, SNR trends — before they escalate to service events.

Built to Scale

From a single-scanner pilot to enterprise-wide deployment — with full physicist support.

Single Scanner Pilot

Start with one MRI system. Validate phantom QA automation, patient series analysis, and recommendations before broader rollout.

Department-Wide QA

Unified fleet dashboard across all MRI systems. Cross-scanner trending and department-level accreditation documentation.

Multi-Site Health System

Centralized quality oversight across imaging sites. Standardized protocols and system-level reporting across vendors and field strengths.

Physicist Support Included

All deployments supported by qualified medical physicists. Implementation support, protocol review, and ongoing QA consultation.

1.5T Validated · 3T Expansion UnderwayMulti-Vendor Expansion RoadmapPACS-CompatibleMinimal Workflow Disruption

Clinical & Economic Value

MRIQA delivers measurable impact across quality, operations, and cost — without disrupting existing workflows.

Clinical Value

Detect scanner drift early

Reduce repeat scans

Maintain accreditation readiness

Economic Value

Reduce downtime

Improve scanner utilization

Lower repeat imaging costs

Phantom QA Module: Fleet-Wide Dashboard

Monitor ACR accreditation status, QA pass/fail results, next QA due dates, and longitudinal PIU trends across your entire scanner fleet — in a single view. Status indicators (Pass / Action / Overdue) surface issues before they become compliance failures.

What you see at a glance

Fleet-wide scanner status: Pass / Action / Overdue

ACR accreditation countdown and renewal alerts

Next QA due dates per scanner

Longitudinal PIU trend tracking

One-click drill-down to individual scanner reports

Multi-vendor support: GE · Siemens · Philips (roadmap)

Patient QA Module: Batch Analysis & Study Scoring

Every de-identified clinical DICOM series is automatically scored across five image quality dimensions: SNR, CNR, ghosting, sharpness, and motion. The batch overview surfaces studies needing attention — with per-study drill-down for root-cause analysis.

Batch Overview

7 studies shown — dates, sequences, overall scores, grades

Grades: Suboptimal / Acceptable / Good / Excellent

Days-to-ACR-QA countdown per study

Scanner and session filtering

Sortable by score, grade, or date

Per-Study Detail: Score 33/100

Overall score: 33/100 — RED (Suboptimal)

Brain SNR: 4.3 — RED

GM CNR: 1.8 — RED

Ghosting: 8.9% — AMBER (single-study example; pilot mean: 3.82%)

Sharpness: 19.2 — RED

Motion Score: 6.3% — GREEN

Bar chart visualization of all five metrics

Nearest ACR QA date shown for context

Recommendation Engine: Prioritized, Protocol-Specific Guidance

Every analysis generates protocol-specific recommendations — automatically prioritized as HIGH, MEDIUM, or LOW.

HIGH Priority

Immediate action recommended. Issues with direct impact on diagnostic image quality or ACR compliance.

MEDIUM Priority

Action recommended within the next QA cycle. Performance is suboptimal but not immediately critical.

LOW Priority

Monitor and address during routine maintenance. Optimization opportunities with lower urgency.

Privacy & Data Security by Design

MRIQA is built for healthcare environments where patient privacy is non-negotiable.

De-Identification First

All DICOM data is de-identified prior to analysis to minimize PHI handling within institutional workflows.

Quantitative Image Quality Analysis

MRIQA analyzes image quality metrics — SNR, CNR, ghosting, motion — from pixel analysis and DICOM metadata, with no diagnostic interpretation.

Designed for Institutional Deployment

Data governance, access controls, and audit logging are built into the platform architecture for seamless hospital IT and PACS integration.

MRIQA is designed to operate within institutional de-identification and governance workflows. HIPAA compliance depends on site-specific implementation. No protected health information is required for core quality analytics when de-identification workflows are followed. Role-based access controls, audit logs, and site-governed data retention policies are supported at deployment.

Research & Publications

MRIQA is grounded in peer-reviewed methodology and original clinical research. The platform's analytical framework is documented in a technical white paper and supported by statistically validated pilot findings.

Technical White Paper

Peer-reviewed framework + pilot-validated analytics

MRIQA: Integrated Phantom and Patient-Specific MRI Quality Assurance for Diagnostic Imaging Optimization and ACR Accreditation Support.

Ali Fatemi, PhD, MCCPM, DABMP · June 2026

Download White Paper

Patent Pending

MRIQA's integrated phantom + patient-specific longitudinal QA architecture is patent pending.

Patent application filed. Details available under NDA to qualified partners.

Key Statistical Finding

Kruskal-Wallis analysis across six sequence groups: H = 21.60, p = 0.0006, η² = 0.177 — statistically significant image-quality differences across sequence types, invisible to standard phantom QA.

Analysis conducted on de-identified pilot data. Results are for research and quality optimization purposes only.

Talk to the Physicist Behind MRIQA

Ali Fatemi, PhD, MCCPM, DABMP

Board-Certified Medical Physicist

Ali Fatemi is a board-certified medical physicist specializing in MRI quality assurance, ACR accreditation, and clinical imaging optimization. MRIQA was built directly from clinical QA practice and validated on real-world patient data. Currently validating MRIQA across clinical MRI systems for quality optimization and accreditation support.

Get in Touch

Email: contact@spintecx.com

See What Your MRI Is Actually Delivering

Continuous MRI quality intelligence beyond phantom QA.

MRIQA is a scanner quality optimization platform for QA and accreditation support. Not for diagnostic use.

© 2026 MRIQA LLC | MRI Quality Intelligence · contact@spintecx.com