Dataset Information

Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform.

ABSTRACT:

Purpose

Spatial heterogeneity of tumors is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood because it relies on the accurate coregistration of medical images and tissue biopsies. Tumor molds 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 tumor heterogeneity data.

Methods

We have developed an open-source computational framework to automatically produce patient-specific 3-dimensional-printed molds that can be used in the clinical setting. Our approach achieves accurate coregistration 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 personalized molds for 6 patients, obtaining Dice similarity coefficients between imaging and tissue sections ranging from 0.86 to 0.96 for tumor regions and between 0.70 and 0.76 for healthy kidneys. The framework required minimal manual intervention, producing the final mold 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 tumor heterogeneity on multiple spatial scales.

SUBMITTER: Crispin-Ortuzar M

PROVIDER: S-EPMC7469624 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform.

Crispin-Ortuzar Mireia M Gehrung Marcel M Ursprung Stephan S Gill Andrew B AB Warren Anne Y AY Beer Lucian L Gallagher Ferdia A FA Mitchell Thomas J TJ Mendichovszky Iosif A IA Priest Andrew N AN Stewart Grant D GD Sala Evis E Markowetz Florian F

JCO clinical cancer informatics 20200801

<h4>Purpose</h4>Spatial heterogeneity of tumors is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood because it relies on the accurate coregistration of medical images and tissue biopsies. Tumor molds 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 ...[more]

PMID: 32804543

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Project description:Objective. Stereotactic technology enables fine navigation to small structures in the human body. While current stereotactic systems facilitate accurate targeting, they are mechanically cumbersome and limited in scope. Here, we hypothesized that a stereotactic system could be developed with a reduced footprint while maintaining broad targeting capabilities in order to improve versatility in frame placement location and surgical workflow.Approach. We designed a stereotactic system around the center-of-arc principle, with mechanical properties that would enable a compact design and ample targeting and trajectory maneuverability. To examine the opportunity for a low-cost rapidly-deployable system we developed two fabrication variants, one using three dimensional (3D)-printing and the other using conventional machining. Mechanical and image-guided accuracies were tested in phantom studies using magnetic resonance imaging (MRI) and computed tomography. Using human cadaver head specimens, we assessed the system's surgical workflow and its ability to reliably and accurately implant electrodes in deep brain stimulation (DBS) surgery.Main results. We developed a small 7.7 × 5.4 cm2device platform that rigidly mounts to curvilinear bone and supports the attachment of surgical instrumentation. Attachment of two surgical instruments, an imaging localizer and a compact targeting device, demonstrated successful MRI-guided intervention in phantom studies with a vector error of 1.79 ± 0.41 mm. Evaluation of the 3D-printed system for DBS surgery confirmed ease of device platform attachment and instrument functionality, as well as demonstrated a surgical targeting accuracy of 1.83 ± 0.15 mm. In addition, we found the surgical time to be 78.3 ± 5.4 min for bilateral electrode implantation.Significance. We developed a light and compact stereotactic system whose accuracy is on par with those used clinically. This technology is suitable for clinical translation and its flexibility in positioning will seamlessly expand the capabilities for stereotaxy to treat a wide range of conditions, both within neurosurgery and beyond.

Dataset Information

Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform.

Purpose

Methods

Results

Conclusion

Publications

Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform.

Similar Datasets

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