PETNormalizationTrendChecker
PET Normalization Trend Checker
PET Normalization and Detector-State Trend Check
Compares the current normalization with the previous run and installation baseline to detect gradual drift.
- mean-factor drift;
- CV change;
- new dead detectors and deviation from baseline.
Compared normalization runs shall refer to the same scanner configuration and compatible software versions.
input.csv
ScannerID,CurrentNormID,PreviousNormID,BaselineNormID,CurrentMeanFactor,PreviousMeanFactor,BaselineMeanFactor,CurrentCV,PreviousCV,BaselineCV,CurrentDeadDetectors,PreviousDeadDetectors,BaselineDeadDetectors,TrendPeriodDays PET-SIEMENS-01,NORM-2026-07-22,NORM-2026-06-22,NORM-INSTALL-2024,1.005,1.002,1.000,1.5,1.4,1.2,0,0,0,30 PET-GE-02,NORM-2026-07-20,NORM-2026-06-20,NORM-INSTALL-2023,1.080,1.010,1.000,3.5,2.0,1.5,2,0,0,30 PET-PHILIPS-03,NORM-2026-07-21,NORM-2026-06-21,NORM-INSTALL-2025,1.001,1.000,1.000,1.2,1.2,1.2,0,0,0,30
URS & FS — user requirements and functional specification
URS — User Requirements Specification
- The utility shall accept input.csv with the headers defined by the data contract.
- Before calculation, the utility shall detect missing columns, type errors, empty mandatory values and illogical dates or ranges.
- The utility shall deterministically perform “PET Normalization and Detector-State Trend Check”.
- Limits and rules shall be loaded from an approved profile or explicitly fixed in the validated version.
- Each record shall receive a clear final status: PASS, WARNING or FAIL, with the reason.
- The result shall retain source values, derived values, applied limits and individual check statuses.
- Invalid input shall not return a successful result. The output supports qualified review under an approved procedure.
FS — Functional Specification
- Run PETNormalizationTrendChecker.exe in demonstration mode or with input.csv output.json arguments.
- Read UTF-8 CSV and map columns to the data contract.
- Convert values to the expected types and validate mandatory fields.
- Perform calculations and rule checks for “PET Normalization and Detector-State Trend Check”.
- Create individual checks and derive the overall status from the worst result.
- Write machine-readable output.json; populate errors when a valid calculation cannot be produced.
input.csv example
ScannerID,CurrentNormID,PreviousNormID,BaselineNormID,CurrentMeanFactor,PreviousMeanFactor,BaselineMeanFactor,CurrentCV,PreviousCV,BaselineCV,CurrentDeadDetectors,PreviousDeadDetectors,BaselineDeadDetectors,TrendPeriodDays PET-SIEMENS-01,NORM-2026-07-22,NORM-2026-06-22,NORM-INSTALL-2024,1.005,1.002,1.000,1.5,1.4,1.2,0,0,0,30 PET-GE-02,NORM-2026-07-20,NORM-2026-06-20,NORM-INSTALL-2023,1.080,1.010,1.000,3.5,2.0,1.5,2,0,0,30 PET-PHILIPS-03,NORM-2026-07-21,NORM-2026-06-21,NORM-INSTALL-2025,1.001,1.000,1.000,1.2,1.2,1.2,0,0,0,30
Minimum output.json structure
{
"utility": "PETNormalizationTrendChecker",
"source": "input.csv",
"status": "PASS|WARNING|FAIL",
"derivedValues": {},
"checks": [
{
"parameter": "example",
"value": 0,
"limit": "configured profile",
"status": "PASS",
"message": "criterion satisfied"
}
],
"errors": []
}
Minimum OQ scenarios
- A row within the approved profile shall return PASS.
- A non-critical limit violation shall return WARNING or a review status.
- A critical violation shall return FAIL or the applicable operational decision.
- A missing column, invalid type or impossible date shall populate errors and shall not return PASS.
Before operational use
- Reconcile formulas and limits with manufacturer documentation and the approved SOP.
- Fix the scanner model, software version and profile version.
- After an executable, formula or profile change, repeat affected tests.
- Retain the source CSV and JSON result together.
Included in packages
PET Scanner State QC Suite
14 utilities for PET/PET-CT scanner state control: Ge-68/Ga-68 source activity, blank sinogram, detector efficiency, normalization acquisition and factor distribution, normalization-file assignment, trending, energy window, TOF, attenuation-correction map, PET/CT cross-calibration and the daily operational decision.
OpenRPH use case: PET scanner state, gamma camera and radiation physics
The linked medical-device/radiation-physics layer: PET detector QC, normalization, AC map, cross-calibration, TOF, gamma-camera uniformity, source strength and staff dose.
OpenRPH workflow: instruments, devices and radiation safety
PET/gamma-camera state, calibration, detector QC, energy window, TOF, shielding and radiation safety.
OpenRPH workflow: stability, storage, decay and waste
Kinetic stability, shelf life, decay correction, expiry, storage, trend and radioactive waste.
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