ImagingReviewConsistencyChecker

Imaging Review Consistency

Liquid Biopsy жидкостная биопсия cfDNA ctDNA CTC exosomes NGS qPCR

Utility description: Imaging Review Consistency

Imaging Review Consistency Checker — Medical Image Read Consistency Control

ℹ️ Utility performs systematic verification of image expert assessment quality according to FDA Medical Imaging Guidance, EORTC and CDISC ADaM:
• BICR Agreement: Verification of agreement between two independent blinded readers.
• Adjudication Completeness: Guarantee of adjudication for all discordant cases.
• Measurement Completeness: Control of target lesion measurements presence for both readers.
• Lesion Assessment: Verification of non-target and new lesion assessment per applied criteria.
• Measurement Discrepancy: Calculation of percentage difference in sum of diameters between readers.

⚠️ IMPORTANT:
• Discordance without adjudication = visit data NOT USABLE for primary analysis.
• Missing target lesion measurements make response assessment impossible.
• Sum diameter discrepancy >20% requires re-review even with matching categorical response.
• Non-target and new lesions MUST be assessed — they affect overall response.

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

Input format:
StudyID,PatientID,VisitTimepoint,Modality,AssessmentCriteria,Reader1_Response,Reader2_Response,ReadersAgree,AdjudicationPerformed,AdjudicatedResponse,TargetLesions_Count_R1,TargetLesions_Count_R2,ExpectedMinTargetLesions,AllMeasurementsPresent_R1,AllMeasurementsPresent_R2,NonTargetLesions_Assessed_R1,NonTargetLesions_Assessed_R2,NewLesions_Assessed_R1,NewLesions_Assessed_R2,SumDiameters_R1_mm,SumDiameters_R2_mm,MaxAllowableMeasurementDiff_Percent

Example:
ONCO-01,SUBJ-001,Week8,CT,RECIST1.1,PR,PR,true,false,,3,3,1,true,true,true,true,true,true,45.2,47.8,20

📍 Scope of Application (Usage Where):
• Oncology Clinical Trials: BICR data QC before database lock.
• Regulatory Submissions: Confirmation of imaging data quality for FDA/EMA.
• Image Reading Centers: Operational radiologist performance quality control.
• Study Monitoring: Identification of sites with high incomplete read frequency.

— WHY IS THIS NEEDED?
Visual assessment is subjective process with 10-30% inter-reader variability.
Without formalized QC, discordant data enters analysis, distorting therapy efficacy assessment.
Automated verification guarantees that only consistent and complete data is used for regulatory decisions.

⚠️ CRITICAL:
• Agreement OR Adjudication: One of two is MANDATORY. Neither = FAIL.
• All Measurements Present: Absence of any measurement = INCOMPLETE.
• Non-Target + New Lesions: Must be assessed by both readers. Omission = INCOMPLETE.
• Measurement Diff ≤20%: Exceedance requires re-review even if categorical response matches.
• Criteria Compliance: Response must correspond to declared criteria (RECIST/RANO/Lugano).

Key features:
• Six-parameter read consistency check
• Automatic unresolved discordance detection
• Inter-reader measurement discrepancy calculation
• CONSISTENT / DISCORDANT / INCOMPLETE classification
• Compliance with FDA Imaging Guidance and CDISC

Critical parameters:
• Reader Agreement: True OR Adjudication Performed
• Target Lesion Measurements: Complete for both readers
• Non-Target Assessment: Both readers
• New Lesion Assessment: Both readers
• Sum Diameter Difference: ≤ Max Allowable %
• Target Lesion Count: ≥ Protocol Minimum

💡 Usage tips:
1. Charter: Ensure Imaging Charter is approved before reading begins.
2. Training: All readers must pass calibration on training cases.
3. Adjudication: Assign third independent reader for all discordant cases.
4. Query Management: Send queries to sites for missing measurements before database lock.
5. Trends: Monitor discordance rate by reader and site for systemic issue identification.

⚠️ Note: This utility verifies read CONSISTENCY and COMPLETENESS, not clinical correctness of assessment. Clinical validity is determined by reader qualification and Imaging Charter compliance.

input.csv

StudyID,PatientID,VisitTimepoint,Modality,AssessmentCriteria,Reader1_Response,Reader2_Response,ReadersAgree,AdjudicationPerformed,AdjudicatedResponse,TargetLesions_Count_R1,TargetLesions_Count_R2,ExpectedMinTargetLesions,AllMeasurementsPresent_R1,AllMeasurementsPresent_R2,NonTargetLesions_Assessed_R1,NonTargetLesions_Assessed_R2,NewLesions_Assessed_R1,NewLesions_Assessed_R2,SumDiameters_R1_mm,SumDiameters_R2_mm,MaxAllowableMeasurementDiff_Percent
ONCO-2026-01,SUBJ-001,Week 8,CT,RECIST 1.1,PR,PR,true,false,,3,3,1,true,true,true,true,true,true,45.2,47.8,20.0
ONCO-2026-01,SUBJ-002,Week 16,CT,RECIST 1.1,SD,PD,false,false,,2,3,1,true,false,true,true,true,true,62.0,78.5,20.0
ONCO-2026-01,SUBJ-003,Week 24,MRI,RANO,PR,SD,false,true,PR,2,2,1,true,true,true,true,true,true,28.0,31.5,20.0

URS & FS — User Requirements and Functional Specification

This document describes the controlled interface and behaviour of ImagingReviewConsistencyChecker for Imaging Review Consistency Checker.

Domain limits URS input.csv FS IQ/OQ/PQ

Domain limits and critical parameters

Key fragments from the source description are shown below. Before production use, limits must be verified against the approved specification, registration dossier and local SOPs.

• Sum diameter discrepancy >20% requires re-review even with matching categorical response.
• Non-target and new lesions MUST be assessed — they affect overall response.
⚠️ CRITICAL:
• Non-Target + New Lesions: Must be assessed by both readers. Omission = INCOMPLETE.
• Measurement Diff ≤20%: Exceedance requires re-review even if categorical response matches.
• Criteria Compliance: Response must correspond to declared criteria (RECIST/RANO/Lugano).
Critical parameters:
• Sum Diameter Difference: ≤ Max Allowable %
• Target Lesion Count: ≥ Protocol Minimum
2. Training: All readers must pass calibration on training cases.

URS — User Requirements Specification

ID	Requirement	Criticality	Acceptance criterion
URS-001	The utility shall accept an input.csv file for Imaging Review Consistency Checker with headers defined in the data contract.	High	The file is processed without manual header editing.
URS-002	The utility shall perform deterministic QC evaluation without machine learning and without probabilistic conformance decisions.	High	Identical input data, rule version and configuration produce reproducible results.
URS-003	The utility shall validate mandatory fields, data types, ranges, units and domain plausibility.	High	Schema, conversion and range errors are explicitly reported.
URS-004	The utility shall apply domain limits and rules from the description, approved specification, registration dossier and local SOPs.	High	Each check has PASS/WARNING/FAIL and a clear message.
URS-005	The utility shall generate output.json with machine-readable results, source values, warnings, failures and critical findings.	High	JSON is suitable for LIMS/ELN/MES integration and QA/QC review.
URS-006	The utility shall preserve traceability between batch/sample, input file, applied rules and final status.	High	Output contains identifiers, checked parameters and audit metadata.
URS-007	The documentation shall support IQ/OQ/PQ, CSV/CSA and review by internal QA or inspectors.	Medium	URS, FS, input/output contract and test scenarios are supplied with the utility.
URS-008	The utility shall be used as a QC decision-support tool and not as a substitute for approved specifications and QA/QP release decision.	Medium	Documentation states change control and limit-verification expectations.

input.csv contract

#	Field	Type	Sample	Purpose
1	`StudyID`	string / controlled vocabulary	`ONCO-2026-01`	Controlled input parameter for deterministic QC rules.
2	`PatientID`	string / controlled vocabulary	`SUBJ-001`	Controlled input parameter for deterministic QC rules.
3	`VisitTimepoint`	string / controlled vocabulary	`Week 8`	Time parameter for process, incubation, storage or analytical workflow.
4	`Modality`	string / controlled vocabulary	`CT`	Controlled input parameter for deterministic QC rules.
5	`AssessmentCriteria`	string / controlled vocabulary	`RECIST 1.1`	Controlled input parameter for deterministic QC rules.
6	`Reader1_Response`	string / controlled vocabulary	`PR`	Controlled input parameter for deterministic QC rules.
7	`Reader2_Response`	string / controlled vocabulary	`PR`	Controlled input parameter for deterministic QC rules.
8	`ReadersAgree`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
9	`AdjudicationPerformed`	string / controlled vocabulary	`false`	Controlled input parameter for deterministic QC rules.
10	`AdjudicatedResponse`	string / controlled vocabulary		Controlled input parameter for deterministic QC rules.
11	`TargetLesions_Count_R1`	integer / decimal	`3`	Count parameter used for microbiological, particulate or cellular control.
12	`TargetLesions_Count_R2`	integer / decimal	`3`	Count parameter used for microbiological, particulate or cellular control.
13	`ExpectedMinTargetLesions`	decimal	`1`	Controlled input parameter for deterministic QC rules.
14	`AllMeasurementsPresent_R1`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
15	`AllMeasurementsPresent_R2`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
16	`NonTargetLesions_Assessed_R1`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
17	`NonTargetLesions_Assessed_R2`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
18	`NewLesions_Assessed_R1`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
19	`NewLesions_Assessed_R2`	string / controlled vocabulary	`true`	Controlled input parameter for deterministic QC rules.
20	`SumDiameters_R1_mm`	decimal	`45.2`	Controlled input parameter for deterministic QC rules.
21	`SumDiameters_R2_mm`	decimal	`47.8`	Controlled input parameter for deterministic QC rules.
22	`MaxAllowableMeasurementDiff_Percent`	decimal	`20.0`	Controlled input parameter for deterministic QC rules.

StudyID,PatientID,VisitTimepoint,Modality,AssessmentCriteria,Reader1_Response,Reader2_Response,ReadersAgree,AdjudicationPerformed,AdjudicatedResponse,TargetLesions_Count_R1,TargetLesions_Count_R2,ExpectedMinTargetLesions,AllMeasurementsPresent_R1,AllMeasurementsPresent_R2,NonTargetLesions_Assessed_R1,NonTargetLesions_Assessed_R2,NewLesions_Assessed_R1,NewLesions_Assessed_R2,SumDiameters_R1_mm,SumDiameters_R2_mm,MaxAllowableMeasurementDiff_Percent
ONCO-2026-01,SUBJ-001,Week 8,CT,RECIST 1.1,PR,PR,true,false,,3,3,1,true,true,true,true,true,true,45.2,47.8,20.0
ONCO-2026-01,SUBJ-002,Week 16,CT,RECIST 1.1,SD,PD,false,false,,2,3,1,true,false,true,true,true,true,62.0,78.5,20.0
ONCO-2026-01,SUBJ-003,Week 24,MRI,RANO,PR,SD,false,true,PR,2,2,1,true,true,true,true,true,true,28.0,31.5,20.0

Input validation rules

ID	Field	Rule	Criticality
VR-001	`StudyID`	The field shall match an approved dictionary or accepted string representation.	High
VR-002	`PatientID`	The field shall match an approved dictionary or accepted string representation.	High
VR-003	`VisitTimepoint`	The field shall match an approved dictionary or accepted string representation.	High
VR-004	`Modality`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-005	`AssessmentCriteria`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-006	`Reader1_Response`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-007	`Reader2_Response`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-008	`ReadersAgree`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-009	`AdjudicationPerformed`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-010	`AdjudicatedResponse`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-011	`TargetLesions_Count_R1`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-012	`TargetLesions_Count_R2`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-013	`ExpectedMinTargetLesions`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-014	`AllMeasurementsPresent_R1`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-015	`AllMeasurementsPresent_R2`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-016	`NonTargetLesions_Assessed_R1`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-017	`NonTargetLesions_Assessed_R2`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-018	`NewLesions_Assessed_R1`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-019	`NewLesions_Assessed_R2`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-020	`SumDiameters_R1_mm`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-021	`SumDiameters_R2_mm`	The field shall match an approved dictionary or accepted string representation.	Medium
VR-022	`MaxAllowableMeasurementDiff_Percent`	The field shall match an approved dictionary or accepted string representation.	Medium

FS — Functional Specification

ID	Function	Implementation
FS-001	CLI execution	Support execution modes: demo mode without arguments and production mode input.csv output.json.
FS-002	CSV import	Read input.csv in UTF-8/CSV-compatible format and validate header and expected columns.
FS-003	Schema validation	Check mandatory fields, column count, unknown key fields and empty mandatory values.
FS-004	Type conversion	Convert numeric, flag and text values; invalid format is recorded as a row-level error.
FS-005	Domain rule engine	Apply rules for Imaging Review Consistency Checker, including critical limits from the description and approved specification.
FS-006	Status aggregation	Produce final status: FAIL for critical failure, WARNING for non-critical deviation, PASS for conformance.
FS-007	JSON export	Write output.json with detailed checks, source values, warnings, failures and critical findings.
FS-008	Audit support	Keep result structure suitable for review, deviation investigation and calculation reproduction.
FS-009	Integration contract	Support the scenario LIMS/ELN/MES → input.csv → utility → output.json → portal/admin review.
FS-010	Error handling	Return explicit messages for missing file, empty CSV, invalid schema, output write failure and invalid format.

Example output.json

{
  "utilityId": "imagingreviewconsistencychecker",
  "utilityFolder": "ImagingReviewConsistencyChecker",
  "package": "LiquidBiopsy",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "processedAtUtc": "2026-06-10T00:00:00Z",
  "checks": [
    {
      "parameter": "StudyID",
      "value": "ONCO-2026-01",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-001"
    },
    {
      "parameter": "PatientID",
      "value": "SUBJ-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-002"
    },
    {
      "parameter": "VisitTimepoint",
      "value": "Week 8",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-003"
    },
    {
      "parameter": "Modality",
      "value": "CT",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-004"
    },
    {
      "parameter": "AssessmentCriteria",
      "value": "RECIST 1.1",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-005"
    },
    {
      "parameter": "Reader1_Response",
      "value": "PR",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-006"
    },
    {
      "parameter": "Reader2_Response",
      "value": "PR",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-007"
    },
    {
      "parameter": "ReadersAgree",
      "value": "true",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-008"
    },
    {
      "parameter": "AdjudicationPerformed",
      "value": "false",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-009"
    },
    {
      "parameter": "AdjudicatedResponse",
      "value": "",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-010"
    },
    {
      "parameter": "TargetLesions_Count_R1",
      "value": "3",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-011"
    },
    {
      "parameter": "TargetLesions_Count_R2",
      "value": "3",
      "status": "PASS|WARNING|FAIL",
      "message": "Deterministic rule-based check result",
      "ruleReference": "FS-RULE-012"
    }
  ],
  "criticalFindings": [],
  "warnings": [],
  "audit": {
    "inputHash": "sha256:<calculated at runtime>",
    "rulesVersion": "<utility executable version>",
    "documentation": "ImagingReviewConsistencyChecker.documentation.html"
  }
}

Traceability matrix

URS	FS	Test	Evidence
URS-001	FS-001, FS-002	OQ-001	Verify execution and import of valid input.csv.
URS-002	FS-005, FS-006	OQ-004	Repeat the same dataset and compare output.json.
URS-003	FS-003, FS-004, FS-010	OQ-002, OQ-003	Verify missing columns and invalid types.
URS-004	FS-005, FS-006	OQ-004, PQ-001	Verify critical deviations on real/boundary data.
URS-005	FS-007, FS-009	OQ-005	Verify JSON schema and downstream-system suitability.
URS-006	FS-008	OQ-006	Verify identifiers and audit metadata.
URS-007	FS-008, FS-010	IQ-001, OQ-007	Verify documentation completeness and control evidence.
URS-008	FS-005, FS-008	PQ-002	Verify review workflow and no replacement of QA decision.

IQ/OQ/PQ test scenarios

ID	Scenario	Expected result
IQ-001	Verify executable, input.csv, documentation and checksum availability.	Delivery set is complete; version is recorded.
OQ-001	Valid sample row from input.csv.	PASS or acceptable WARNING according to rules.
OQ-002	Remove a mandatory CSV column.	Schema error or FAIL with missing-column reference.
OQ-003	Place a non-numeric value into a numeric field.	Type-conversion error with row/field reference.
OQ-004	Set a critical parameter outside the limit.	FAIL and critical finding.
OQ-005	Verify output.json structure.	All mandatory sections are present and JSON is valid.
OQ-006	Verify batch/sample traceability.	Input and result identifiers match.
PQ-001	Verify 3–5 real user batches/samples.	Result is confirmed by QC/QA review.
PQ-002	Verify deviation workflow and manual QA decision.	Utility supports review but does not replace approved decision.

QA/QC and change control

Do not rename columns without updating validator, documentation and test set.
Retain input.csv, output.json, executable version and checksum.
Before production use, perform IQ/OQ/PQ or equivalent CSV/CSA verification.
Critical limits shall be verified against the approved specification, registration dossier and local SOPs.
The utility provides structured QC decision support; final release decision remains with QA/QP and approved procedures.

Included in packages

Liquid Biopsy QC Suite

QC and pre-analytical control package for liquid biopsy workflows: cfDNA/ctDNA, CTC, EV/exosomes, methylation, NGS/qPCR/ddPCR, sample quality, contamination, sensitivity and reporting checks.

Open