Main Page/SlicerCommunity/2019

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The community that relies on 3D Slicer is large and active: (numbers below updated on December 1st, 2023)

  • 2,147+ papers on PubMed citing the Slicer platform paper
    • Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F.M., Sonka M., Buatti J., Aylward S.R., Miller J.V., Pieper S., Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. PMCID: PMC3466397.


The following is a sample of the research performed using 3D Slicer outside of the group that develops it. in 2019

We monitor PubMed and related databases to update these lists, but if you know of other research related to the Slicer community that should be included here please email: marianna (at) bwh.harvard.edu.

2019

A Complete Workflow for Utilizing Monte Carlo Toolkits in Clinical Cases for a Double-Scattering Proton Therapy System

Publication: J Appl Clin Med Phys. 2019 Jan;20(1):23-30. PMID: 30426669 | PDF

Authors: Muller L, Prusator M, Ahmad S, Chen Y.

Institution: Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK.

Abstract: The methods described in this paper allow end users to utilize Monte Carlo (MC) toolkits for patient-specific dose simulation and perform analysis and plan comparisons for double-scattering proton therapy systems. The authors aim to fill two aspects of this process previously not explicitly published. The first one addresses the modeling of field-specific components in simulation space. Patient-specific compensator and aperture models are exported from treatment planning system and converted to STL format using a combination of software tools including Matlab and Autodesk's Netfabb. They are then loaded into the MC geometry for simulation purpose. The second details a method for easily visualizing and comparing simulated doses with the dose calculated from the treatment planning system. This system is established by utilizing the open source software 3D Slicer. The methodology was demonstrated with a two-field proton treatment plan on the IROC lung phantom. Profiles and two-dimensional (2D) dose planes through the target isocenter were analyzed using our in-house software tools. This present workflow and set of codes can be easily adapted by other groups for their clinical practice.

Morphological Analysis of Sigmoid Sinus Anatomy: Clinical Applications to Neurotological Surgery

Publication: J Otolaryngol Head Neck Surg. 2019 Jan 11;48(1):2. PMID: 30635049 | PDF

Authors: Van Osch K, Allen D, Gare B, Hudson TJ, Ladak H, Agrawal SK.

Institution: Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.

Abstract: OBJECTIVES: The primary objective of this study was to use high-resolution micro-CT images to create accurate three-dimensional (3D) models of several intratemporal structures, and to compare several surgically important dimensions within the temporal bone. The secondary objective was to create a statistical shape model (SSM) of a dominant and non-dominant sigmoid sinus (SS) to provide a template for automated segmentation algorithms.

METHODS: A free image processing software, 3D Slicer, was utilized to create three-dimensional reconstructions of the SS, jugular bulb (JB), facial nerve (FN), and external auditory canal (EAC) from micro-CT scans. The models were used to compare several clinically important dimensions between the dominant and non-dominant SS. Anatomic variability of the SS was also analyzed using SSMs generated using the Statismo software framework.

RESULTS: Three-dimensional models from 38 temporal bones were generated and analyzed. Right dominance was observed in 74% of the paired SSs. All distances were significantly shorter on the dominant side (p < 0.05), including: EAC - SS (dominant: 13.7 ± 3.4 mm; non-dominant: 15.3 ± 2.7 mm), FN - SS (dominant: 7.2 ± 1.8 mm; non-dominant: 8.1 ± 2.3 mm), 2nd genu FN - superior tip of JB (dominant: 8.7 ± 2.2 mm; non-dominant: 11.2 ± 2.6 mm), horizontal distance between the superior tip of JB - descending FN (dominant: 9.5 ± 2.3 mm; non-dominant: 13.2 ± 3.5 mm), and horizontal distance between the FN at the stylomastoid foramen - JB (dominant: 5.4 ± 2.2 mm; non-dominant: 7.7 ± 2.1). Analysis of the SSMs indicated that SS morphology is most variable at its junction with the transverse sinus, and least variable at the JB.

CONCLUSIONS: This is the first known study to investigate the anatomical variation and relationships of the SS using high resolution scans, 3D models and statistical shape analysis. This analysis seeks to guide neurotological surgical approaches and provide a template for automated segmentation and surgical simulation.

"In 3D Slicer, nine fiducials (F1 – F9) were placed on the 3D reconstructions of the SS, JB, EAC, and FN to analyze several surgically relevant relationships between these structures."

Funding:

  • 381117/Collaborative Health Research Projects
Fiducials and distances calculated from coordinates (BLUE - SS, YELLOW - FN, PURPLE - EAC). a. EAC – SS (F1 – F2); Descending FN – SS (F3 – F4). b. 2nd genu FN – Superior tip JB. (F5 – F6); Descending FN - Superior tip JB (F6 – F7); FN at the SMF - JB (F8 – F9).
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