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<p>This work presents a proof-of-concept solution designed to facilitate more accurate radiographic feature characterisation in pre-surgical CT/MR volumes. The solution involves 3D co-location of 2D digital histology slides within <i>ex-vivo</i>, tumour tissue CT volumes. Initially, laboratory dissection measurements seed the placement of histology slices in corresponding CT volumes, followed by in-plane point-based registration of bone in histology images to the bone in CT. Validation using six bisected canine humerus <i>ex-vivo</i> CT datasets indicated a plane misalignment of 0.19 ± 1.8&#xa0;mm. User input sensitivity was assessed at 0.08 ± 0.2&#xa0;mm for plane translation and 0–1.6°&#xa0;deviation. These results show a similar magnitude of error to related prostate histology co-location work. Although demonstrated with a femoral canine sarcoma tumour, this solution can be generalised to various orthopaedic geometries and sites. It supports high-fidelity histology image co-location to improve understanding of tissue characterisation accuracy in clinical radiology. This solution requires only minimal adjustment to routine workflows. By integrating histology insights earlier in the presentation-diagnosis-planning-surgery-recovery loop, this solution guides data co-location to support the continued evaluation of safe pre-surgical margins.</p>

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A Proof-of-Concept Solution for Co-locating 2D Histology Images in 3D for Histology-to-CT and MR Image Registration: Closing the Loop for Bone Sarcoma Treatment Planning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月26日

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  • Robert Phillips,
  • Constantine Zakkaroff,
  • Keren Dittmer,
  • Nicholas Robilliard,
  • Kenzie Baer,
  • Anthony Butler

摘要

This work presents a proof-of-concept solution designed to facilitate more accurate radiographic feature characterisation in pre-surgical CT/MR volumes. The solution involves 3D co-location of 2D digital histology slides within ex-vivo, tumour tissue CT volumes. Initially, laboratory dissection measurements seed the placement of histology slices in corresponding CT volumes, followed by in-plane point-based registration of bone in histology images to the bone in CT. Validation using six bisected canine humerus ex-vivo CT datasets indicated a plane misalignment of 0.19 ± 1.8 mm. User input sensitivity was assessed at 0.08 ± 0.2 mm for plane translation and 0–1.6° deviation. These results show a similar magnitude of error to related prostate histology co-location work. Although demonstrated with a femoral canine sarcoma tumour, this solution can be generalised to various orthopaedic geometries and sites. It supports high-fidelity histology image co-location to improve understanding of tissue characterisation accuracy in clinical radiology. This solution requires only minimal adjustment to routine workflows. By integrating histology insights earlier in the presentation-diagnosis-planning-surgery-recovery loop, this solution guides data co-location to support the continued evaluation of safe pre-surgical margins.