Материал: part17

IIII.2 Example of Fused CT/MR Derived Encapsulated STL​

In this example, the patient will shortly be undergoing a complex cardiac surgery. A 3D manufacturing model (encoded in binary STL)​ was created to manufacture a surgical planning aid representing the patient's unique anatomy.​

To begin, a series of CT images (CT-02) and a series of MR images (MR-01) were registered using CT-02's frame of reference as​ the base coordinate system and then fused. An initial version of the model was derived and reviewed by the surgical team who re-​ quested that some of the anatomy surrounding the heart be removed. A second version of the model was created on July 16, 2017​ at 1:04:34 PM then stored in a DICOM instance at 1:33:01 PM. The CT and MR data were acquired at earlier dates.​

The Encapsulated STL file shown in this example is the second version..​

Both versions of the STL were created in the coordinate system of CT-02; so they all share the same Frame of Reference value.​

Note: Mapping to other Frames of Reference of secondary source series would be handled via registration objects.​

A preview image (optional) showing the rendered 3D object was created and included with the encapsulated STL as an icon image.​

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Thecreatorofthemodelinscribedthepatient'smedicalrecordnumberonasideofthemodeltoavoidthepossibilityofawrongpatient​ error.​

Table IIII.2-1. Fused CT/MR Derived Encapsulated STL Example​

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JJJJ Multi-energy CT Imaging (Informative)​

JJJJ.1 Domain of Application​

Multi-energy CT acquires pixel information which correlates to different X-Ray spectra to enable differentiation, quantification and​ classification of different types of tissues.​

To detect the different X-Ray spectra, Multi-energy (ME) CT imaging uses combinations of different Source(s) and Detector(s) tech-​ nologies such as current switching X-Ray tubes, spectral detectors, multi-layer detectors, multi-source and detector pairs.​

JJJJ.2 Use Cases​

Multi-energy CT data can be reconstructed and processed in different ways to serve a variety of purposes.​

•​Differentiate materials that look similar on conventional CT images, e.g., to differentiate Iodine and Calcium in vascular structures​ or to differentiate vascular structures from adjacent bone.​

•​Quantifybasematerialstoaccuratelydefinetissuesandorgans.Theintentistoquantifymaterials,andtoextractregionsandorgans​ based on their composition.​

•​Generate virtual non-contrast images from a contrast-enhanced image rather than having to scan the patient twice.​

•​Reduce beam hardening artifacts.​

•​Enhance the effect of contrast such as highlighting Iodine and soft tissue.​

JJJJ.3 Classification of Multi-energy Images​

The following Multi-energy image types and families are addressed in this supplement:​

Material Removed Image

Examples:

•Virtual unenhanced (VUE)

•Virtual non-contrast (VNC)

Figure JJJJ.3-1. Classification of Multi-energy Images​

Standard CT Image (CT Image​ImagescreatedusingMEtechniques,forexample,incaseofthecreationofconventionalappearing​ IOD, Enhanced CT Image IOD)​CT images out of two energy spectra or images created with only one of the multiple energies​

acquired. No new image type definitions are needed but new optional Attributes are needed.​

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electron density to water (N/NWater). Electron density is used​ commonly in radiotherapy.​

Material Quantification Image​ Theseimagetypescharacterizetheelementalcompositionofmaterialsintheimage.Theyprovide​ Family​ material quantification using a physical scale. Pixel values can be in HU or in equivalent material​

concentration (e.g., mg/ml). The following image types belong to this family:​

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