ArticleBMC medical imaging2025
CycleGan-based kV-to-MV image translation for potential in vivo dosimetry application: concept proposal and cross-institutional validation.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThis work aims to develop and validate a novel CycleGan-based methodology to transfer the kV planning CT (pCT) to the reference MV portal images, potentially applicable to in vivo treatment dose monitoring.
methodsThe kV projections of pCT were prepared based on the various gantry angles of MV projections using treatment beams on Varian Halcyon system. A CycleGAN-based network incorporating attention module (ECA-CycleGAN) was trained to learn the relationship between kV and MV images, which performance was compared with the conventional Pix2pix and CycleGAN methods quantitatively. The beam angles and multi-leaf collimator parameters retrieved from the clinical plans were used to segment the treatment apertures on the model-generated reference MV images, within which the sensitivity to the artificial errors were tested using gamma analysis. Cross-institutional validations were performed on multiple machines and scanning protocols.
resultsComparing the 2574 model-generated MV images with the measured ground truth of 13 validation cases, the mean ± standard deviation of the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR) and root mean square error (RMSE) were 0.969 ± 0.007, 41.3 ± 3.2 and 1.6·10
conclusionWithout complex and time-consuming Monte Carlo simulations, the proposed ECA-CycleGAN network facilitates the efficient establishment of the reference MV portal images applicable to in vivo transmitted dosimetry. It may potentially improve the accuracy of dose delivery especially for the advanced treatment techniques when pretreatment measurement verification or inter-fractional dose remediation are impossible.
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