Structured Radiology Report Generation Using Instruction-Tuned Language Models

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Solution Overview

Problem

Traditional radiology reporting in free text format leads to inconsistencies, information gaps, and difficulty in automatic information extraction, hindering seamless information transfer and standardization across medical records and clinical databases.

Innovation Solution

The development of systems and methods for generating radiology passages using a trained language model, which maps extracted medical concepts from text-based radiological data to common data elements and associated values, enabling the generation of standardized, structured reports.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If free text format is used for radiology reporting, then radiologists can write observations and differential diagnosis flexibly, but inconsistencies, information gaps, and difficulty in automatic information extraction occur

Engineering Contradiction:

ImproveFlexibility in writing observationsVSAvoidConsistency and completeness of information

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The radiology report is segmented into structured components including patient information, examination information, findings, and impressions. Each section is further divided into standardized data elements with specific formats, transforming the monolithic free text into organized, extractable units that maintain clinical flexibility while ensuring consistency.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes the parameter of report format from unstructured free text to structured standardized format. This transformation applies predefined templates and data element schemas that constrain the output to consistent formats while preserving the ability to capture diverse clinical observations through standardized fields.

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If free text reporting is used, then variable reporting styles are allowed, but difficulty in automatically extracting information for continuity of care and integration of medical records arises

Engineering Contradiction:

ImproveVariable reporting stylesVSAvoidAutomatic information extraction capability

Core Design Contradiction:

Adaptability or versatilityVSExtent of automation

Solution Approach 1:

The structured report format serves multiple functions simultaneously: it maintains adaptability for diverse clinical scenarios through flexible data elements, while also enabling automatic information extraction, integration with electronic health records, and support for continuity of care. The universal structure accommodates various report types and clinical contexts.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The structured data elements and standardized format act as an intermediary layer between the radiologist's clinical observations and the automated systems that need to process this information. This intermediary structure enables both clinical versatility and machine-readable consistency, facilitating automatic extraction and integration without losing the nuance of variable reporting needs.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If standardized structured reporting is implemented, then information consistency and automatic extraction are improved, but complexity of report generation structure increases

Engineering Contradiction:

ImproveInformation consistencyVSAvoidReport generation structure complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by pre-defining standardized data elements, templates, and schemas before the actual report generation process. These pre-established structures include common data elements, value sets, and template configurations that guide the report creation, reducing the complexity during the actual generation phase while ensuring consistency.

Inventive Principle:

Principle #10Preliminary action

4Extent of automation

If standardized structured reporting is implemented, then automatic information extraction is facilitated, but lack of universally agreed reporting structure persists

Engineering Contradiction:

ImproveAutomatic information extractionVSAvoidUniversal applicability of reporting structure

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The structured reporting system is designed with universal applicability through standardized data elements and templates that can be adapted across different healthcare settings and purposes. The same structure supports automatic information extraction, integration with various electronic health record systems, and diverse clinical workflows, making it universally applicable while maintaining automation capabilities.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250149187A1Fact-aware synoptic report generation using instruction-tuned language models

Publication Date: 2025.05.08 SIEMENS HEALTHINEERS AG

AI summary

Systems and methods for generating radiology passages are provided. An input common data element and one or more associated input values are received. A radiology passage is generated based on the input common data element and the one or more associated input values using a trained language model. The generated radiology passage is output.