Материал: part17

WWW Tractography Results (Informative)​

WWW.1 Introduction​

MRI diffusion imaging is able to quantify diffusion of water along certain directions. The diffusion tensor model is a simple model that​ is able to describe the statistical diffusion process accurately at most white matter positions. To calculate diffusion tensors, a base-​ lineMRIwithoutdiffusion-weightingandatleastsixdifferentlyweighteddiffusionMRIshavetobeacquired.Aftersomepreprocessing​ of the data, at each grid point, a diffusion tensor can be calculated. This gives rise to a tensor volume that is the basis for tracking.​ Refinements to the diffusion model and acquisition method such as HARDI, Q-Ball, diffusion spectrum imaging (DSI) and diffusion​ kurtosis imaging (DKI) are expanding the directionality information available beyond the simple tensor model, enhancing tracking​ through crossings, adjacent fibers, sharp turns, and other difficult scenarios.​

A tracking algorithm produces tracks (i.e., fibers), which are collected into track sets. A track contains the set of x, y and z coordinates​ ofeachpointmakingupthetrack.Dependinguponthealgorithmandsoftwareused,additionalquantitiessuchasFractionalAnisotropy​ (FA) values or color etc. may be associated with the data, by track set, track or point, either to facilitate further filtering or for clinical​ use. Descriptive statistics of quantities such as FA may be associated with the data by track set or track.​

Examples of tractography applications include:​

•​Visualization of white matter tracks to aid in resection planning or to support image guided (neuro) surgery;​

•​Determination of proximity and/or displacement versus infiltration of white matter by tumor processes;​

•​Assessment of white matter health in neurodegenerative disorders, both axonal and myelin integrity, through sampling of derived​ diffusion parameters along the white matter tracks.​

WWW.2 Encoding Example​

This section illustrates the usage of the Section C.8.33.2 “Tractography Results Module” in PS3.3 in the context of the Tractography​ Results IOD.​

Track Set Left Track Set Right

Figure WWW-1. Two Example Track Sets. "Track Set Left" with two tracks, "Track Set Right" with one​ track.​

Figure WWW-1 shows two example track sets. The example consists of:​ •​Two track sets "Track Set Left" and "Track Set Right"​

•​Track Set Sequence (0066,0101) => each item describes one track set.​ •​Track Set "Track Set Left" contains two tracks "A" and "B"​

•​Track Sequence (0066,0102) => each item describes one track.​

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•​Track "A" consists of:​

•​4 points​

•​Point Coordinates Data (0066,0016) => describes the coordinates for all points in the track.​

•​Different color for each point​

•​Recommended Display CIELab Value List (0066,0103) => describes the colors for all points in the track.​

•​Fractional Anisotropy for each point​

•​On how the values are stored, see description in "Encoding of Measurement Values" below.​

•​Apparent Diffusion Coefficient for point 1 and 3​

•​On how the values are stored, see description in "Encoding of Measurement Values" below.​

•​Track "B" consists of:​

•​3 points​

•​Point Coordinates Data (0066,0016) => describes the coordinates for all points in the track.​

•​Same color for each point​

•​Recommended Display CIELab Value (0062,000D) => describes the color for all points in the track.​

•​Fractional Anisotropy for each point​

•​On how the values are stored, see description in "Encoding of Measurement Values" below.​

•​Apparent Diffusion Coefficient for point 2​

•​On how the values are stored, see description in "Encoding of Measurement Values" below.​

•​Encoding of Measurement Values for Tracks "A" and "B"​

•​For storing measurement values like Fractional Anisotropy or Apparent Diffusion Coefficient values on specific points on a track​ the overall view over all tracks of a given track set is needed. Only tracks shall be grouped in track sets that share a specific type​ of measurement value.​

•​Measurements Sequence (0066,0121) => each item describes one value type of all tracks in the track set (here: "Track Set Left"​ contains two value types: Fractional Anisotropy and Apparent Diffusion Coefficient).​

•​Measurement Values Sequence (0066,0132) => one item for each track of a track set.​

•​When used to store Fractional Anisotropy values:Since a Fractional Anisotropy value is stored for each point in both tracks of​ "Track Set Left", Floating Point Values (0066,0125) contains an array of Fractional Anisotropy values for tracks "A" and "B"​ respectively. Track Point Index List (0066,0129) is absent since there is a Fractional Anisotropy value associated with every​ point in Point Coordinates Data (0066,0016).​

•​When used to store Apparent Diffusion Coefficient values:Since an Apparent Diffusion Coefficient value is stored only for a​ subset of points in both tracks of "Track Set Left", Track Point Index List (0066,0129) contains indices to the track points in​ Point Coordinates Data (0066,0016) and Floating Point Values (0066,0125) contains a measurement value for every track​ point referenced in Track Point Index List (0066,0129).​

•​Track Set "Track Set Right" contains one track "C"​

•​Track "C" consists of:​

•​3 points​

•​Point Coordinates Data (0066,0016) => describes the coordinates for all points in the track.​

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•​Same color for all points​

•​Recommended Display CIELab Value (0062,000D) => describes the color for all points in the track set (Note: In this example​ this Attribute is stored on Track Set level).​

•​No measurement values​

The table WWW-1 shows the encoding of the Tractography Results module for the example above. In addition to the two example​ track sets the table WWW-1 also encodes the following information:​

•​Within "Track Set Left" the mean Fractional Anisotropy values for track "A" (0.475) and "B" (0.667).​

•​For "Track Set Left" the maximum Fractional Anisotropy value (0.9).​

•​Diffusion acquisition, model and tracking algorithm information.​

•​Image instance references used to define the Tractography Results instance.​

Table WWW-1. Example of the Tractography Results Module​

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