3D Slicer as an Image Computing Platform for the Quantitative Imaging Network methods
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Modules
Image Guided Therapy (IGT): modules that support applications in image-guided therapy. The key functionality provided by the tools in this category is the OpenIGTLink interface that enables exchange of data between Slicer and external systems, such as robotic devices, MR scanners, and commercial image-guided surgery platforms.
Data Formats and Organization
Support of the widely accepted data exchange standards and interfaces are critical for any image computing tool to be useful in a clinical research environment. 3D Slicer supports import, query, retrieve, and storage of clinical images using DICOM protocols and data structures. These features allow data exchange with clinical systems such as scanners, workstations, and PACS servers. Example use cases for DICOM networking include: (1) setting up a scanner to route newly acquired images directly to a DICOM listener in Slicer to support image guided therapy; (2) using Slicer to query and retrieve DICOM studies in a departmental PACS to perform retrospective image analysis; and (3) sending derived (post-processed) images to a PACS system to become part of the patient record. In all cases, coordination with responsible clinical support staff is required to ensure that research use of Slice...
Data Formats and Organization
As images are imported into Slicer, they are added to the Slicer scene that is used to organize the individual data elements. While the user performs operations on the data or reconfigures the visualization elements of the interface, the scene is used to keep track of the application configuration. Scene views cache the complete state of the Slicer application, including the configuration and content of the viewers, together with a screen capture of the visualization elements and a textual description. Slicer scenes can contain multiple scene views that emphasize or communicate different aspects of data or different stages of its processing. Scenes can be stored on disk using the MRML format for sharing of the analysis results and to facilitate reproducibility of the observation. As an example, a scene view can correspond to a visualization that was used to prepare a certain figure in...
Modules
Compared to SEM plugins, Slicer loadable modules have complete access to the Slicer core logic, GUI and MRML elements. Loadable modules are typically developed for interactive tools, or for those applications that require new MRML data types, event handling or customization of the main Slicer GUI. Loadable modules follow the same MVC design pattern as the application core by introducing module-specific Logic, as well as GUI and MRML classes. Logic classes are typically the most important component for the developers of the new image analysis tools, as they include the core computation and the implementation of the analysis algorithms. Such an implementation would usually (although this is not a requirement) rely on the Insight Toolkit and VTK for constructing pipelines and implementing lower level processing steps. The View elements allow the module to interact with the operator to in...
Iowa
Response assessment to cancer therapy based on molecular imaging with PET/CT lacks an accepted robust and accurate quantitative metric. The literature is rife with new and different ways to analyze PET/CT image data, including variants of standardized uptake values (SUV), various lesion-to-background approaches, volume measurement, and metabolic tumor volume, but it is still unclear which of these approaches is best suited for response assessment.
MGH
3D Slicer provides a number of state-of-the-art algorithms for rigid, affine and deformable registration (in addition to manual registration). These algorithms can be selected and optimized depending on the anatomical site (e.g., brain vs prostate), purpose (multimodal vs longitudinal vs registering to an atlas), performance (speed vs accuracy vs robustness), and level of interaction (e.g., use of fiducials or markers). The registration tools within Slicer are utilized in a number of ways. Regions of interest delineated on T1w, T2w or FLAIR MRI are registered to the other imaging modalities and associated parametric maps (e.g., K trans maps from DCE, rCBV maps from DSC and ADC maps from DTI) as seen in. This capability helps better understand the distribution of these parameters in the different regions of the tumor and in different patients. These tools can also be used to register...
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inferred from protocolPreprocessing / cleaning
Review raw outputs for quality, remove unusable captures, and organize the data into a comparison-ready table or image set.
inferred from protocolScoring or quantification
Quantify the primary endpoint described in the methods before moving into any statistical comparison.
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inferred from protocolSource and audit
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Evidence quotes (6)
Image Guided Therapy (IGT): modules that support applications in image-guided therapy. The key functionality provided by the tools in this category is the OpenIGTLink interface that enables exchange of data between Slicer and external systems, such as robotic devices, MR scanners, and commercial image-guided surgery platforms.
Support of the widely accepted data exchange standards and interfaces are critical for any image computing tool to be useful in a clinical research environment. 3D Slicer supports import, query, retrieve, and storage of clinical images using DICOM protocols and data structures. These features allow data exchange with clinical systems such as scanners, workstations, and PACS servers. Example use cases for DICOM networking include: (1) setting up a scanner to route newly acquired images directly to a DICOM listener in Slicer to support image guided therapy; (2) using Slicer to query and retrieve DICOM studies in a departmental PACS to perform retrospective image analysis; and (3) sending derived (post-processed) images to a PACS system to become part of the patient record. In all cases, coordination with responsible clinical support staff is required to ensure that research use of Slicer is authorized and has been tested to confirm that it will not interfere with ongoing clinical care. Implementation of the import and export of DICOM RT structures user in radiotherapy is currently under way.
As images are imported into Slicer, they are added to the Slicer scene that is used to organize the individual data elements. While the user performs operations on the data or reconfigures the visualization elements of the interface, the scene is used to keep track of the application configuration. Scene views cache the complete state of the Slicer application, including the configuration and content of the viewers, together with a screen capture of the visualization elements and a textual description. Slicer scenes can contain multiple scene views that emphasize or communicate different aspects of data or different stages of its processing. Scenes can be stored on disk using the MRML format for sharing of the analysis results and to facilitate reproducibility of the observation. As an example, a scene view can correspond to a visualization that was used to prepare a certain figure in a report or manuscript. Accompanied by the Slicer scene, version of the software used and input dataset used to prepare it, such an article would provide a detailed provenance record, together with the methods, parameters and visualization context.
Compared to SEM plugins, Slicer loadable modules have complete access to the Slicer core logic, GUI and MRML elements. Loadable modules are typically developed for interactive tools, or for those applications that require new MRML data types, event handling or customization of the main Slicer GUI. Loadable modules follow the same MVC design pattern as the application core by introducing module-specific Logic, as well as GUI and MRML classes. Logic classes are typically the most important component for the developers of the new image analysis tools, as they include the core computation and the implementation of the analysis algorithms. Such an implementation would usually (although this is not a requirement) rely on the Insight Toolkit and VTK for constructing pipelines and implementing lower level processing steps. The View elements allow the module to interact with the operator to initialize the inputs and processing parameters, and any interactive initialization of the algorithm (e.g., collect the initialization seed points placed in the 2D slice viewer for a lesion segmentation tool). Examples of the interactive loadable modules available in 3D Slicer are "EMSegmenter&#...
Response assessment to cancer therapy based on molecular imaging with PET/CT lacks an accepted robust and accurate quantitative metric. The literature is rife with new and different ways to analyze PET/CT image data, including variants of standardized uptake values (SUV), various lesion-to-background approaches, volume measurement, and metabolic tumor volume, but it is still unclear which of these approaches is best suited for response assessment.
3D Slicer provides a number of state-of-the-art algorithms for rigid, affine and deformable registration (in addition to manual registration). These algorithms can be selected and optimized depending on the anatomical site (e.g., brain vs prostate), purpose (multimodal vs longitudinal vs registering to an atlas), performance (speed vs accuracy vs robustness), and level of interaction (e.g., use of fiducials or markers). The registration tools within Slicer are utilized in a number of ways. Regions of interest delineated on T1w, T2w or FLAIR MRI are registered to the other imaging modalities and associated parametric maps (e.g., K trans maps from DCE, rCBV maps from DSC and ADC maps from DTI) as seen in. This capability helps better understand the distribution of these parameters in the different regions of the tumor and in different patients. These tools can also be used to register the radiation therapy plans (CT-based) to the MR functional imaging, allowing exploration of the site of recurrence with respect to dose field and study the phenomenon of radiation necrosis. Registration algorithms and the change detection tools can be used to identify regions of change in the tumor...
Machine-readable layer
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