Lithuanian Prostate Diagnostics Implementation Guide, published by Lithuanian Medical Library. This guide is not an authorized publication; it is the continuous build for version 0.0.1 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7LT/ig-lt-prostate/ and changes regularly. See the Directory of published versions

Home

Oficialus URL: https://hl7.lt/fhir/prostate/ImplementationGuide/lt.hl7.fhir.prostate				Versija: 0.0.1	Paryškinti teksto pakeitimus?
					Mašiniškai apdorojamas pavadinimas: LTProstate

Dabartiniam puslapiui nėra vertimo puslapio, todėl jis pateiktas numatytąja kalba

Lithuanian Prostate Cancer Prevention and Diagnostic Implementation Guide

Introduction and Purpose

This Implementation Guide (IG) specifies how to consistently represent and exchange structured clinical data related to the Prostate Cancer Prevention and Early Diagnostic Programme using the Fast Healthcare Interoperability Resources (FHIR) standard.

The guide supports the national programme for the early detection, diagnosis, monitoring, and follow-up of prostate cancer by defining interoperable data structures for laboratory testing, imaging, clinical interpretation, referrals, invasive diagnostics, and pathology reporting. Its purpose is to enable:

• consistent and high-quality data capture across healthcare providers,
• semantic interoperability between laboratory, radiology, urology, pathology, and clinical systems,
• structured reporting for programme monitoring, quality assurance, and secondary use,
• and reliable longitudinal follow-up of patients across diagnostic and surveillance episodes.

The guide is developed as part of the national ADP project to support coordinated, data-driven management of preventive and early diagnostic programmes in Lithuania.

Audience

This guide is intended for implementation guide authors, system vendors, integrators, healthcare solution developers, and clinical stakeholders involved in exchanging prostate cancer screening and diagnostic data using FHIR. Readers are expected to have at least a basic familiarity with FHIR and to refer to the core FHIR specification where additional background is needed.

Scope and Key Content

This guide focuses on the prostate cancer prevention and diagnostic workflow, which combines population-level screening, diagnostic imaging, risk stratification, and longitudinal monitoring.

It covers the following clinical domains:

• Laboratory testing — primarily Prostate-Specific Antigen (PSA) measurement,
• Imaging acquisition — multiparametric or biparametric prostate MRI,
• Radiological interpretation and reporting using:
  • PI-RADS for lesion-level risk stratification,
  • PRECISE for exam-level longitudinal assessment of disease change over time,
• Detailed anatomical localisation using the PI-RADS 39-sector model, represented with SNOMED CT body structure codes,
• Support for clinical workflow coordination, including referrals across specialties,
• Invasive diagnostic procedures such as prostate biopsy (referenced and integrated via related IGs),
• Pathological examination and reporting (integrated via related laboratory IGs),
• Active surveillance and longitudinal monitoring for low-risk disease.

The guide models prostate cancer prevention and diagnostics as a longitudinal, decision-driven, multidisciplinary process integrating laboratory, radiology, urology, and pathology into a coherent information model.

Key Modelling Principles

The modelling approach is based on the following core principles:

1. Separation of data acquisition and interpretation
   Laboratory tests and imaging procedures generate structured datasets, while interpretation, assessment, and diagnosis are represented separately.

2. Explicit separation of clinical observation and workflow logic
   PI-RADS and PRECISE assessments represent observations, while clinical actions (e.g. referrals, biopsies, treatment decisions) represent workflow processes.

3. Domain-specific modelling
   PSA testing, prostate MRI, radiological scoring, biopsy, and pathology require specialized profiles and modelling approaches.

4. Longitudinal coherence
   All data elements are designed to support linkage across time, enabling continuous clinical history tracking across screening and follow-up.

5. Structured but flexible documentation
   The guide supports fully structured, partially structured, and narrative data, allowing both interoperability and clinical nuance.

6. High-resolution anatomical localisation
   Prostate lesions are localized using the PI-RADS 39-sector model, enabling precise and standardized anatomical referencing.

7. Lesion-centric scoring with exam-level interpretation

   • PI-RADS assessments and MRI sequence scores are lesion-based
   • PRECISE assessments are exam-level and longitudinal

Radiology Assessment Architecture

The guide follows a layered radiology modelling approach:

• LTProstateMpMRIReport — clinical and temporal anchor for each MRI examination
• LTProstateLesion (BodyStructure) — anatomically localized lesions using the PI-RADS model
• PI-RADS assessments — assigned per lesion
• Sequence scores (T2, DWI, ADC, DCE) — recorded per lesion and per sequence
• PI-QUAL — represents exam-level image quality
• PRECISE — represents exam-level longitudinal change, linked to prior MRI examinations

This structure ensures clear separation between data acquisition, lesion characterization, and longitudinal disease assessment.

Content of the Guide

This guide provides:

• FHIR profiles and extensions for prostate cancer screening, imaging, assessment, and reporting,
• terminology bindings using SNOMED CT, LOINC, and ICD-10-AM,
• structured example instances illustrating clinical scenarios,
• mappings from clinical programme datasets to interoperable FHIR artefacts,
• a detailed real-life prostate mpMRI example showing how narrative radiology content is represented using the profiles defined in this guide,
• and supporting documentation for workflow, report structure, and questionnaire-based data capture.

The guide includes both the full set of published artifacts and a detailed MRI Example page that demonstrates the representation of a real-world prostate mpMRI workflow in structured FHIR form.

Why Use This Guide?

By adopting these profiles and guidance, implementers can support a standardized approach to:

• Interoperability: Enable consistent, semantic exchange of prostate cancer screening and diagnostic data across laboratory, radiology, urology, and pathology systems.
• Data Quality: Improve the consistency, completeness, and comparability of structured diagnostic and imaging data.
• Clinical Utility: Support structured reporting, programme monitoring, quality assurance, and clinical decision support.
• Longitudinal Care: Enable linkage of screening, diagnostics, and follow-up data across time and providers.

How to Navigate This Guide

This guide is organized into several sections that support implementation from overview to detailed conformance artifacts. All conformance and example resources are listed on the Artifacts page. Key sections include:

• Artifacts — Complete list of profiles, extensions, terminology resources, and example instances defined by this guide.
• Workflow — Overview of the clinical pathway and diagnostic process.
• Prostate Report — Structure of the ImagingReport and Composition bundle.
• Questionnaires — Structured ESPBI-style forms and data capture models.
• MRI Example — Detailed real-life prostate mpMRI example showing how findings, assessments, imaging context, and report structure are represented in FHIR.

IP Statements

Contributors

Name	Role	Organization
Igor Bossenko	Primary Author	HELEX Solutions
Kati Laidus	Co-Author	HELEX Solutions
Martynas Bieliauskas	Reviewer	LMB