Impact of Non-Linear CT Resampling on Enhancing Synthetic-CT Generation in Total Marrow and Lymphoid Irradiation

Computed tomography (CT) images are stored at a 12-bit depth. However, many deep learning libraries and pre-trained models are designed for 8-bit images, requiring an intermediate compression step before restoring the original 12-bit physical range. This process causes information loss and can compromise image reliability. This study investigated the impact of two CT resampling methods (8-bit compression; 12-bit decompression) on dose calculation and image quality. Ten total marrow and lymphoid irradiation patients were selected. CT scans were resampled using linear and non-linear look-up tables (l_LUT/nl_LUT). Original and resampled CTs were evaluated considering: (i) Hounsfield unit (HU) root mean squared error (RMSE); (ii) dose-volume histogram (DVH) statistics for target volume and several organs; (iii) 3D gamma passing rate (GPR) with a 1%/1.25 mm criterion; (iv) lymph nodes contouring and diagnostic quality (scale 1–5). The RMSE for l_LUT vs. nl_LUT was 7 ± 1 vs. 10 ± 1 HU. Maximum differences in DVH statistics were 0.4%, with a 3D-GPR = 100% for all cases. CTs resampled with l_LUT exhibited evident brain pixelation (score = 1), whereas nl_LUT matched the original CT quality (score = 4). Both LUTs were acceptable for lymph nodes delineation. The nl_LUT optimized the CT resampling process, providing a more efficient method for possible deep learning applications in synthetic CT generation.