MRIVoxelSignalUniformityAnalyzer

MRI Voxel Signal Uniformity Analyzer

instrumental Hyperpolarized Xenon RPH Xe-129 medical gases CSV→JSON URS & FS rule-based

Utility description: MRI Voxel Signal Uniformity Analyzer

MRI Voxel Signal Uniformity Analyzer — MRI Voxel Signal Uniformity Analyzer

ℹ️  Utility evaluates HP-gas MRI image quality:
    • Signal Coefficient of Variation (CV)
    • Signal-to-Noise Ratio (SNR)
    • Intensity dynamic range

⚠️  CRITICAL: Non-uniformity may be an artifact, not pathology!
    Low SNR makes quantitative ventilation assessment impossible.

Usage:
  MRIVoxelSignalUniformityAnalyzer.exe                            → demo mode (console output)
  MRIVoxelSignalUniformityAnalyzer.exe input.csv output.json      → evaluate your data

Input format:
BatchNumber,ProductName,Mean_Signal,Std_Dev,Max_Signal,Min_Signal,SNR,Max_CV_Percent,Min_SNR

Example:
  IMG-UNI-2026-001,HP-Xe-129 Scan,1000,50,1100,900,25,15,10

— WHY IS THIS NEEDED?
Uniformity control is critical for HP-MRI diagnostic value:
• Hyperpolarized xenon distributes unevenly in lungs due to pathology (COPD, asthma)
• However, sharp signal drops may be caused by magnetic field artifacts (B0/B1 inhomogeneity)
• Low Signal-to-Noise Ratio (SNR) prevents reliable ventilation assessment
• Utility helps distinguish real ventilation defect from technical equipment failure
• ACR/NEMA standards require strict uniformity control for quantitative studies

⚠️  CRITICAL:
• Coefficient of Variation (CV) ≤15% for phantoms/healthy zones
• SNR ≥10 for basic diagnostics, ≥20 for quantitative analysis
• No "dead zones" with zero signal (except anatomical)
• Signal intensity stability over time

Key features:
• Statistical analysis of voxel intensity in ROI
• Coefficient of variation calculation as non-uniformity measure
• Signal-to-noise ratio assessment
• Imaging artifact detection

Critical parameters:
• CV: ≤15%
• SNR: ≥10
• Signal Range: Stable

💡 Usage tips:
1. Use standardized ROIs for comparison between patients
2. Perform phantom scan before each study series to calibrate uniformity
3. Account for receive coil influence on intensity profile
4. Compare ventilation maps with CT structure to exclude atelectasis
5. Maintain SNR log to monitor polarizer degradation

⚠️ Note: Unlike standard MRI where signal is stable, in HP-MRI signal is single-use and decaying. The utility helps ensure that obtained picture reflects physiology, not just noise or technical gas administration error.

input.csv

BatchNumber,ProductName,Mean_Signal,Std_Dev,Max_Signal,Min_Signal,SNR,Max_CV_Percent,Min_SNR
IMG-UNI-2026-001,HP-Xe-129 Phantom Scan,1000,50,1100,900,25,15,10
IMG-UNI-2026-002,HP-Xe-129 Patient Scan (Good),850,60,950,750,18,15,10
IMG-UNI-2026-003,HP-Xe-129 Patient Scan (Bad),400,120,600,200,5,15,10

URS & FS — user requirements and functional specification

URS & FS — User Requirements and Functional Specification

This document defines the controlled interface and behaviour of MRIVoxelSignalUniformityAnalyzer for “MRI Voxel Signal Uniformity Analyzer”. Limits from the source description are an initial configuration and shall be reconciled with the approved specification, study protocol, equipment instructions and local SOPs before production use.

Domain constraints and critical parameters

CV: ≤15%
SNR: ≥10
Signal Range: Stable

URS — User Requirements Specification

ID	Requirement	Criticality	Acceptance criterion
URS-001	The utility shall accept `input.csv` with the exact headers defined by the data contract.	High	The file is processed without manual header renaming.
URS-002	The utility shall perform a deterministic assessment for “MRI Voxel Signal Uniformity Analyzer”.	High	PASS / WARNING / FAIL is produced for each row.
URS-003	Required fields, types, ranges, units and data consistency shall be validated before domain rules.	High	Schema errors are separated from nonconformities.
URS-004	Critical limits from the description and approved local configuration shall create a critical finding.	High	A critical rule violation results in FAIL.
URS-005	The result shall be written to machine-readable `output.json`.	High	JSON contains source values, checks, warnings and failures.
URS-006	The conformity decision shall not use machine learning.	Medium	The result is reproducible from explicit rules and inputs.
URS-007	Traceability of batch, source file, rule version and final status shall be retained.	High	QA/QC can reproduce the decision.
URS-008	The utility shall have exactly one primary portal tag: `instrumental`.	Medium	The other api / instrumental / medical_devices tags are absent.
URS-009	Documentation shall support IQ/OQ/PQ or equivalent CSA/CSV verification.	Medium	The contract, test scenarios and change-control rules are supplied with the utility.

input.csv data contract

#	Field	Type	Unit	Sample	Purpose
1	`BatchNumber`	string	as specified	`IMG-UNI-2026-001`	Batch/lot identifier for traceability.
2	`ProductName`	string	as specified	`HP-Xe-129 Phantom Scan`	Name of the controlled product, gas, procedure or equipment.
3	`Mean_Signal`	decimal	as specified	`1000`	Measured signal used for SNR, uniformity or polarization-efficiency assessment.
4	`Std_Dev`	decimal	as specified	`50`	Controlled input.csv field: Std Dev.
5	`Max_Signal`	decimal	as specified	`1100`	Measured signal used for SNR, uniformity or polarization-efficiency assessment.
6	`Min_Signal`	decimal	as specified	`900`	Measured signal used for SNR, uniformity or polarization-efficiency assessment.
7	`SNR`	decimal	as specified	`25`	Signal-to-noise ratio used to assess diagnostic data usability.
8	`Max_CV_Percent`	decimal	%	`15`	Controlled input.csv field: Max CV Percent.
9	`Min_SNR`	decimal	as specified	`10`	Signal-to-noise ratio used to assess diagnostic data usability.

BatchNumber,ProductName,Mean_Signal,Std_Dev,Max_Signal,Min_Signal,SNR,Max_CV_Percent,Min_SNR
IMG-UNI-2026-001,HP-Xe-129 Phantom Scan,1000,50,1100,900,25,15,10
IMG-UNI-2026-002,HP-Xe-129 Patient Scan (Good),850,60,950,750,18,15,10
IMG-UNI-2026-003,HP-Xe-129 Patient Scan (Bad),400,120,600,200,5,15,10

FS — Functional Specification

ID	Function	Implementation
FS-001	CLI execution	`MRIVoxelSignalUniformityAnalyzer.exe` supports demo mode and `input.csv output.json` mode.
FS-002	CSV import	Read UTF-8 CSV and validate header, column count and order.
FS-003	Schema validation	Validate required values, empties, types and basic plausibility.
FS-004	Domain rule engine	Apply explicit rules for “MRI Voxel Signal Uniformity Analyzer” and locally approved limits.
FS-005	Status aggregation	FAIL for a critical finding; WARNING for a non-critical deviation; PASS for conformity.
FS-006	JSON export	Write source values, applied rules, statuses, warnings, failures and configuration version.
FS-007	Audit support	Retain a result structure suitable for review, investigation, IQ/OQ and change control.
FS-008	Integration contract	LIMS/ELN/MES or an instrument wrapper creates CSV; the utility returns JSON.

output.json example

{
  "utilityId": "mri-voxel-signal-uniformity-analyzer",
  "primaryTag": "instrumental",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "checks": [
    {
      "parameter": "BatchNumber",
      "value": "IMG-UNI-2026-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "ProductName",
      "value": "HP-Xe-129 Phantom Scan",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Mean_Signal",
      "value": "1000",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Std_Dev",
      "value": "50",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Max_Signal",
      "value": "1100",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Min_Signal",
      "value": "900",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "SNR",
      "value": "25",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Max_CV_Percent",
      "value": "15",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    }
  ],
  "warnings": [],
  "criticalFindings": []
}

OQ/PQ test scenarios

ID	Scenario	Expected result
OQ-001	Valid example row	PASS or an allowed WARNING under local rules.
OQ-002	Required column missing	Schema error; domain checks do not mask it.
OQ-003	Non-numeric value in numeric field	Type-conversion error.
OQ-004	Critical parameter outside its limit	FAIL and a critical finding.
OQ-005	Boundary value	The result follows the configured ≤ / ≥ / < / > operator.
PQ-001	Real site data	Agreed QA/QC review retaining CSV, JSON, version and checksum.

QA/QC and change control

Do not change column names without updating the validator, documentation and test set.
Retain input.csv, output.json, executable version, rule version and checksums.
Before production use, verify local limits and execute IQ/OQ/PQ or equivalent CSA.
Changes affecting patient safety, dosimetry, gas composition, polarization or equipment require documented impact assessment.

Included in packages

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RPH workflow: dosimetry and therapy planning

Activity planning, absorbed dose, organ dose, lung shunt, preplanning and therapy verification.

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Acquisition, uptake, clearance, perfusion, transit, ejection fraction, segmentation and quantitative imaging.

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PET/gamma-camera state, calibration, detector QC, energy window, TOF, shielding and radiation safety.

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RPH workflow: stability, storage, decay and waste

Kinetic stability, shelf life, decay correction, expiry, storage, trend and radioactive waste.

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