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3D-printed moulds for image-guided surgical biopsies: an open source computational platform

View ORCID ProfileMireia Crispin-Ortuzar, View ORCID ProfileMarcel Gehrung, View ORCID ProfileStephan Ursprung, Andrew B Gill, View ORCID ProfileAnne Y Warren, Lucian Beer, Ferdia A Gallagher, View ORCID ProfileThomas J Mitchell, View ORCID ProfileIosif A Mendichovszky, Andrew N Priest, Grant D Stewart, Evis Sala, View ORCID ProfileFlorian Markowetz
doi: https://doi.org/10.1101/658831
Mireia Crispin-Ortuzar
1Cancer Research UK, Cambridge Institute, University of Cambridge, UK
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  • For correspondence: mireia.crispinortuzar@cruk.cam.ac.uk
Marcel Gehrung
1Cancer Research UK, Cambridge Institute, University of Cambridge, UK
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Stephan Ursprung
1Cancer Research UK, Cambridge Institute, University of Cambridge, UK
2Department of Radiology, University of Cambridge, UK
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Andrew B Gill
2Department of Radiology, University of Cambridge, UK
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Anne Y Warren
3Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Lucian Beer
2Department of Radiology, University of Cambridge, UK
4Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, 1090 Vienna, Austria
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Ferdia A Gallagher
2Department of Radiology, University of Cambridge, UK
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Thomas J Mitchell
5Department of Surgery, University of Cambridge, UK
6Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
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Iosif A Mendichovszky
2Department of Radiology, University of Cambridge, UK
7Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Andrew N Priest
2Department of Radiology, University of Cambridge, UK
7Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Grant D Stewart
5Department of Surgery, University of Cambridge, UK
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Evis Sala
1Cancer Research UK, Cambridge Institute, University of Cambridge, UK
2Department of Radiology, University of Cambridge, UK
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Florian Markowetz
1Cancer Research UK, Cambridge Institute, University of Cambridge, UK
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ABSTRACT

PURPOSE Spatial heterogeneity of tumours is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood, as it relies on the accurate co-registration of medical images and tissue biopsies. tumour moulds can guide the localization of biopsies, but their creation is time consuming, technologically challenging, and difficult to interface with routine clinical practice. These hurdles have so far hindered the progress in the area of multiscale integration of tumour heterogeneity data.

METHODS We have developed an open source computational framework to automatically produce patient-specific 3D-printed moulds that can be used in the clinical setting. Our approach achieves accurate co-registration of sampling location between tissue and imaging, and integrates seamlessly with clinical, imaging and pathology workflows.

RESULTS We applied our framework to patients with renal cancer undergoing radical nephrectomy. We created personalised moulds for five patients, obtaining Dice similarity coefficients between imaging and tissue sections ranging from 0.86 to 0.93 for tumour regions, and between 0.70 and 0.76 for healthy kidney. The framework required minimal manual intervention, producing the final mould design in just minutes, while automatically taking into account clinical considerations such as a preference for specific cutting planes.

CONCLUSION Our work provides a robust and automated interface between imaging and tissue samples, enabling the development of clinical studies to probe tumour heterogeneity on multiple spatial scales.

Footnotes

  • ↵‡ Shared senior authorship.

  • ↵* mireia.crispinortuzar{at}cruk.cam.ac.uk, florian.markowetz{at}cruk.cam.ac.uk

  • Additional confirmatory data included; Figures updated and extended; Author added and affiliations updated.

  • https://zenodo.org/record/3066305#.Xl6KJpNKiu4

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted March 04, 2020.
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3D-printed moulds for image-guided surgical biopsies: an open source computational platform
Mireia Crispin-Ortuzar, Marcel Gehrung, Stephan Ursprung, Andrew B Gill, Anne Y Warren, Lucian Beer, Ferdia A Gallagher, Thomas J Mitchell, Iosif A Mendichovszky, Andrew N Priest, Grant D Stewart, Evis Sala, Florian Markowetz
bioRxiv 658831; doi: https://doi.org/10.1101/658831
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3D-printed moulds for image-guided surgical biopsies: an open source computational platform
Mireia Crispin-Ortuzar, Marcel Gehrung, Stephan Ursprung, Andrew B Gill, Anne Y Warren, Lucian Beer, Ferdia A Gallagher, Thomas J Mitchell, Iosif A Mendichovszky, Andrew N Priest, Grant D Stewart, Evis Sala, Florian Markowetz
bioRxiv 658831; doi: https://doi.org/10.1101/658831

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