SIST-TP CEN ISO/ASTM/TR 52916:2022 PDF

Overview

CEN ISO/ASTM/TR 52916:2022 - Additive manufacturing for medical: Data - Optimized medical image data provides guidance for creating optimized image data sets used in medical additive manufacturing (MAM). It focuses on converting static medical imaging modalities (CT, MRI) into high-fidelity 3D digital models suitable for 3D printing and downstream analysis. The report addresses acquisition, processing, segmentation, reconstruction and validation methods to improve the accuracy of solid medical models derived from stacked 2D images (DICOM).

Key topics and technical requirements

The Technical Report covers practical steps and technical considerations to produce optimized medical image data for AM, including:

• Image acquisition and error sources

  • Influence of slice thickness, spatial resolution, image noise, tissue contrast and imaging artefacts on final model accuracy.
  • Use of uncompressed tomography metadata and recommendations to maximize resolution and minimize slice spacing where clinically feasible.

• Preprocessing methods

  • Isotropic conversion to reconfigure slice intervals for consistent voxel dimensions.
  • Image enhancement techniques to reduce noise and improve contrast.

• Segmentation techniques

  • Common algorithms such as thresholding, region growing, morphological operations, level-set and other partial segmentation methods; guidance on algorithm selection for anatomical fidelity.

• Reconstruction and mesh processing

  • Surface extraction (e.g., marching cubes), mesh smoothing, and mesh quality control to prepare watertight models for printing.
  • 3D visualization approaches: surface shaded rendering and volume rendering (ray-casting, 3D texture mapping).

• Additional AM processing

  • Post-segmentation editing, medical CAD tolerancing (see informative annex), and preparing files in AM-compatible formats.

• Validation and error minimization

  • Methods to assess and reduce software and equipment errors, recommended verification strategies, and tolerance/error situation considerations.

Practical applications

This TR is intended to improve the fidelity of patient-specific and anatomical models produced by additive manufacturing for:

• Preoperative surgical planning and simulation
• Patient-specific implant and device design
• Anatomical teaching models and training
• Finite element analysis and biomechanical studies
• Medical device development and quality assurance

Who should use this standard

• Biomedical and clinical engineers
• Radiologists and imaging technicians preparing AM data
• Medical device manufacturers and AM service providers
• Software developers of medical image processing and AM workflows
• Regulatory and quality assurance teams involved in medical 3D printing

Related standards and context

• Produced jointly by ISO/TC 261 and ASTM F42 and endorsed by CEN, this report complements DICOM imaging workflows and existing ISO/ASTM standards on additive manufacturing. It provides practical, interoperable guidance for converting medical imaging (DICOM) into AM-ready 3D models.

Keywords: additive manufacturing for medical, optimized medical image data, medical imaging, CT, MRI, DICOM, segmentation, reconstruction, mesh smoothing, isotropic conversion, patient-specific implants, 3D printing.