Affiliation:
1. Institute for Applied Medical Informatics University Medical Center Hamburg‐Eppendorf Hamburg Germany
2. Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg Germany
3. Center for Biomedical Artificial Intelligence University Medical Center Hamburg‐Eppendorf Hamburg Germany
4. Siemens Healthineers AG Forchheim Germany
5. Pattern Recognition Lab Friedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
6. Department of Radiotherapy and Radiation Oncology University Medical Center Hamburg‐Eppendorf Hamburg Germany
Abstract
AbstractBackgroundBreathing signal‐guided 4D CT sequence scanning such as the intelligent 4D CT (i4DCT) approach reduces imaging artifacts compared to conventional 4D CT. By design, i4DCT captures entire breathing cycles during beam‐on periods, leading to redundant projection data and increased radiation exposure to patients exhibiting prolonged exhalation phases. A recently proposed breathing‐guided dose modulation (DM) algorithm promises to lower the imaging dose by temporarily reducing the CT tube current, but the impact on image reconstruction and the resulting images have not been investigated.PurposeWe evaluate the impact of breathing signal‐guided DM on 4D CT image reconstruction and corresponding images.MethodsThis study is designed as a comparative and retrospective analysis based on 104 4D CT datasets. Each dataset underwent retrospective reconstruction twice: (a) utilizing the acquired clinical projection data for reconstruction, which yields reference image data, and (b) excluding projections acquired during potential DM phases from image reconstruction, resulting in DM‐affected image data. Resulting images underwent automatic organ segmentation (lung/liver). (Dis)Similarity of reference and DM‐affected images were quantified by the Dice coefficient of the entire organ masks and the organ overlaps within the DM‐affected slices. Further, for lung cases, (a) and (b) were deformably registered and median magnitudes of the obtained displacement field were computed. Eventually, for 17 lung cases, gross tumor volumes (GTV) were recontoured on both (a) and (b). Target volume similarity was quantified by the Hausdorff distance.ResultsDM resulted in a median imaging dose reduction of 15.4% (interquartile range [IQR]: 11.3%–19.9%) for the present patient cohort. Dice coefficients for lung () and liver () patients were consistently high for both the entire organs and the DM‐affected slices (IQR lung: [entire lung/DM‐affected slices only] to ; IQR liver: to ), demonstrating that DM did not cause organ distortions or alterations. Median displacements for DM‐affected to reference image registration varied; however, only two out of 73 cases exhibited a median displacement larger than one isotropic 1 voxel size. The impact on GTV definition for the end‐exhalation phase was also minor (median Hausdorff distance: 0.38 mm, IQR: 0.15–0.46 mm).ConclusionThis study demonstrates that breathing signal‐guided DM has a minimal impact on image reconstruction and image appearance while improving patient safety by reducing dose exposure.
Funder
Deutsche Forschungsgemeinschaft
Siemens Healthineers