Structured radiology report
A structured report is not about rigid text: it is about reducing dangerous variation, preserving important findings and leaving data ready for governance. Applied well, the structured report reduces dangerous variation without turning the physician into a form operator. This guide covers when to structure, where to place fields, how to keep the impression consistent with the findings and how to validate the workflow in the real routine. It is worth separating two levels that are usually treated as one: the structure visible to the human reader (sections, subheadings, pertinent negatives, impression) and the machine-readable structure (coded data, standardized classifications, DICOM-SR), which feeds quality, research and clinical BI. A report can be well organized for the eye and still opaque to the data — and the governance gain only appears when the two levels move together.
Framing and responsibility
Informative and assistive content. Laudos.AI speeds up the report's structure; the radiologist reviews, edits and signs. Responsibility for the report remains with the physician.
Assistive use, under the radiologist's responsibility (CFM Resolution 2.454/2026). Data processing in accordance with LGPD/ANPD.
When it makes sense
- Protocols with recurring fields
- Comparison between exams
- Clinical and operational audit
- Quality programs that depend on comparable data across reports
- Screening and follow-up that require consistent measurements and classifications
Structure without rigidity
A structured report reduces dangerous variation without turning the physician into a form operator. Fields should exist where they help decision, comparison or traceability — not to bureaucratize every sentence.
The impression must keep the correspondence between the findings described and the final conclusion. Where applicable, classifications such as BI-RADS, TI-RADS, LI-RADS and Lung-RADS provide standardization; and structured data stays reusable for quality, research, clinical BI and governance.
Where to start
A practical path to introduce structuring without friction:
- Choose the modalities with the most repeated fields
- Create reviewable templates per exam
- Validate pertinent negatives and comparison with prior exams
- Review how the impression is assembled before signing
How to evaluate this workflow in the real routine
A structured radiology report needs to be tested in the clinical routine, not only in a demo.
Before the pilot, define modality, volume, signature flow, who reviews templates and which integration will actually be tested. During the test, measure review time, the radiologist's corrections, structure failures and the friction of going back to the usual flow. After validation, scale only if the team gains speed without losing traceability, medical control or clarity of the final report.
Decision criteria
- Medical control: the radiologist reviews, edits and signs; the AI speeds up the structure, it does not make the clinical decision
- Real integration: the tool fits into the PACS/RIS, the worklist and the exam data without forcing an infrastructure change
- Governance: auditability of templates, history, permissions and critical findings
- Measurable productivity: gains in time, rework, standardization and operational safety
The two levels of structure: for the eye and for the data
The biggest confusion about structured reporting is treating formatting and structuring as synonyms. They are not. A report can have sections, subheadings and pertinent negatives — well organized for the reader — and still deliver zero reusable data, because every measurement and every classification lives as free text.
The structuring that produces governance is the one that codes: measurements with units, standardized classifications as entities, laterality and location as fields. That layer is what allows comparing exams over time, building quality cohorts, doing research and exporting via DICOM-SR. The goal is not to choose between human readability and machine readability — it is to get both in the same document, without doubling the physician's work.
- Human layer: sections, impression, pertinent negatives and clear language for the requesting physician
- Data layer: measurements, units, laterality, classifications and machine-readable codes
- Bridge between the two: the physician dictates once; the tool fills both layers for review
- Result: comparability across exams, structured export and reliable quality indicators
When not to structure: the cost of too many fields
Structuring everything is as harmful as structuring nothing. Too many fields turn the radiologist into a form operator, lengthen the report without clinical gain and create the illusion of completeness — the field gets filled just because it exists. Structure where decision, comparison or traceability is at stake; leave free text where clinical reasoning needs room.
- Structure what repeats across exams and what will be compared or audited later
- Structure measurements, classifications and sentinel findings that trigger management
- Leave free the synthesis, the differential diagnosis and the recommendation, where judgment does not fit in boxes
- Distrust templates that force filling fields irrelevant to the clinical indication
- Reassess fields nobody reads or reuses: unused structure is just bureaucracy
Consistency between findings and impression: a review checklist
The most frequent error in structured reports is one of consistency: the impression states what the findings did not describe, or the findings record something the impression ignores. Before signing, a quick pass through these points is worth it:
- Does every conclusion in the impression have explicit support in the body of findings?
- Does every finding relevant to management appear in the impression, not just in the body?
- Do the measurements in the impression match those described in the findings, with no divergence in number or unit?
- Is the comparison with prior exams reflected (stable, increased, decreased, new)?
- Was the degree of certainty preserved — does probable stay probable, rather than becoming definitive?
- Were critical findings flagged and the communication recorded before release?
How Laudos.AI solves it
Laudos.AI offers fields by modality, an impression assembled consistently with the findings and output that is always reviewable by the physician. A useful 30-day pilot proves reporting speed, clinical review quality, template adherence and integration friction — with curated clinical material.
Fields by modality, created where they help decision, comparison or traceability
Impression consistent with the findings described, assembled for review
Standardized classifications (BI-RADS, TI-RADS, LI-RADS, Lung-RADS) suggested by GUIDE
Structured data reusable for quality, research, clinical BI and governance
Frequently asked questions
When does the structured radiology report make sense?
A structured report is not about rigid text: it is about reducing dangerous variation, preserving important findings and leaving data ready for governance. It makes sense in protocols with recurring fields, comparison between exams and clinical and operational audit.
Is a structured report the same as a well-formatted report?
No. Formatting organizes the text for the human eye — sections, subheadings, pertinent negatives. Structuring codes the data for the machine — measurements with units, classifications as entities, laterality and location as fields. A report can be very well formatted and still be opaque to the data. The governance gain comes when both layers coexist in the same document.
Won't structuring turn me into a form operator?
That is the risk of excess. Useful structuring lands where there is decision, comparison or traceability — measurements, classifications, sentinel findings. The synthesis, the differential diagnosis and the recommendation stay in free text, where clinical judgment needs room. Templates that force filling fields irrelevant to the indication are bureaucracy, not structure.
What is DICOM-SR for in the structured report?
DICOM-SR (Structured Report) is a format that carries the report with its machine-readable structure — measurements, classifications and relationships — instead of text alone. In practice, it is what lets measurements and findings return to the PACS in a form that is comparable across exams and reusable for quality, research and clinical BI, with no retyping.
Does Laudos.AI replace the radiologist?
No. Laudos.AI structures and speeds up the report, but the physician reviews, edits and signs. Use is assistive and responsibility for the report remains with the radiologist (CFM Resolution 2.454/2026).
Do I need to change PACS/RIS?
No. The planned deployment connects to the existing infrastructure and keeps the familiar reporting flow, without forcing a change of PACS/RIS, worklist or exam data.
References
- Insights into Imaging (Bruls & Kwee) · 2020 · DOI: 10.1186/s13244-020-00925-z
- Journal of Digital Imaging (Forsberg et al.) · 2017 · DOI: 10.1007/s10278-016-9911-z
Meet Laudos.AI
Dictation in Portuguese with radiological terminology, automatic structuring, critical-finding flagging (CRIT) and integration with your current PACS/RIS. The physician reviews, edits and signs.
Content updated on .