Adaptive and 4D radiotherapy manipulates information from multiple fractions/phases. Such information includes 4DCT and daily CT, daily doses and deformation maps. Typically, Adaptive/4D radiotherapy involved hundreds time of data than conventional radiotherapy. Such huge data pose significant disk/database storage and network burden. An efficient and effective data compression method is essential to make the adaptive/4D radiotherapy clinically applicable.
Materials/Methods
We developed a wavelet-based compression technique to handle the huge data from adaptive/4D radiotherapy. We use this technique to compress various dose images and deformation maps. The dose images are tomotherapy daily doses of the prostate, head & neck and lung patients. The deformation maps are calculated between the different phase of 4DCT image or between the daily image and the planning CT image using an intensity based deformable registration technique. For a dimension of 256 × 256 × 100, the dose image is about 30MB, while deformation maps are three times larger (90 MB). To evaluate the information lost through the lossy compression, we compare the compressed image with original image. The difference is the compression error. Two metrics are used, standard error and maximum error.
Results
Figure 1 plots the errors vs. the compression ratio for a typical dose image and a deformation map. For dose image, the errors are represented as the percentage of the maximum dose (Dmax). At 100:1 compression, the standard error is ∼0.05% Dmax, the maximum error is ∼0.5% Dmax. For deformation map, the errors are represented in the unit of voxels. At 100:1 compression, the standard error is ∼0.01 voxels, and the maximum error is ∼0.18 voxels.
Conclusions
Both dose and deformation map can be easily compressed with 100:1 ratio without any clinically significant effect. Under this compression level, as for the dose image, the maximum error at ∼1% Dmax and the standard deviation of errors at ∼0.1% Dmax is well within the uncertainty of dose calculation and dose measurement. As for the deformation map, the maximum error at ∼0.2 voxel and standard deviation of errors at ∼0.01 voxel is well-acceptable since the deformation maps are calculated from voxel-based CT image and only have voxel precision. With 100:1 compression ratio, for an adaptive therapy of 40 fractions, all 40 deformation maps and daily doses would only take extra storage that is less than 3–4 times of the planning CT image, instead of 300–400 times if not compressed. In conclusion, the wavelet compression can achieve great compression ratio while maintain the image quality relevant to clinical applications. It will make those advanced treatment techniques like adaptive or 4D to be practical.
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