Search

Objective . Clinical implementation of synthetic CT (sCT) from cone-beam CT (CBCT) for adaptive radiotherapy necessitates a high degree of anatomical integrity, Hounsfield unit (HU) accuracy, and image quality. To achieve these goals, a vision-transformer and anatomically sensitive loss functions are described. Better quantification of image quality is achieved using the alignment-invariant Fréchet inception distance (FID), and uncertainty estimation for sCT risk prediction is implemented in a scalable plug-and-play manner. Approach . Baseline U-Net, generative adversarial network (GAN), and CycleGAN models were trained to identify shortcomings in each approach. The proposed CycleGAN-Best model was empirically optimized based on a large ablation study and evaluated using classical image quality metrics, FID, gamma index, and a segmentation analysis. Two uncertainty estimation methods, Monte-Carlo Dropout (MCD) and test-time augmentation (TTA), were introduced to model epistemic and aleatoric uncertainty. Main results . FID was correlated to blind observer image quality scores with a Correlation Coefficient of -0.83, validating the metric as an accurate quantifier of perceived image quality. The FID and mean absolute error (MAE) of CycleGAN-Best was 42.11 ± 5.99 and 25.00 ± 1.97 HU, compared to 63.42 ± 15.45 and 31.80 HU for CycleGAN-Baseline, and 144.32 ± 20.91 and 68.00 ± 5.06 HU for the CBCT, respectively. Gamma 1%/1 mm pass rates were 98.66 ± 0.54% for CycleGAN-Best, compared to 86.72 ± 2.55% for the CBCT. TTA and MCD-based uncertainty maps were well spatially correlated with poor synthesis outputs. Significance . Anatomical accuracy was achieved by suppressing CycleGAN-related artefacts. FID better discriminated image quality, where alignment-based metrics such as MAE erroneously suggest poorer outputs perform better. Uncertainty estimation for sCT was shown to correlate with poor outputs and has clinical relevancy toward model risk assessment and quality assurance. The proposed model and accompanying evaluation and risk assessment tools are necessary additions to achieve clinically robust sCT generation models., (Creative Commons Attribution license.)

Objective. Functional lung avoidance (FLA) radiotherapy treatment aims to spare lung regions identified as functional from imaging. Perfusion contributes to lung function and can be measured from the determination of pulmonary blood volume (PBV). An advantageous alternative to the current determination of PBV from positron emission tomography (PET) may be from dual energy CT (DECT), due to shorter examination time and widespread availability. This study aims to determine the correlation between PBV determined from DECT and PET in the context of FLA radiotherapy. Approach. DECT and PET acquisitions at baseline of patients enrolled in the HI-FIVE clinical trial (ID: NCT03569072) were reviewed. Determination of PBV from PET imaging (PBVPET), from DECT imaging generated from a commercial software (Syngo.via, Siemens Healthineers, Forchheim, Germany) with its lowest (PBVsyngoR=1) and highest (PBVsyngoR=10) smoothing level parameter value ( R ), and from a two-material decomposition (TMD) method (PBVTMDL) with variable median filter kernel size ( L ) were compared. Deformable image registration between DECT images and the CT component of the PET/CT was applied to PBV maps before resampling to the PET resolution. The Spearman correlation coefficient ( r s ) between PBV determinations was calculated voxel-wise in lung subvolumes. Main results. Of this cohort of 19 patients, 17 had a DECT acquisition at baseline. PBV maps determined from the commercial software and the TMD method were very strongly correlated [ r s (PBVsyngoR=1,PBVTMDL=1) = 0.94 ± 0.01 and r s (PBVsyngoR=10,PBVTMDL=9) = 0.94 ± 0.02].PBVPETwas strongly correlated withPBVTMDL[ r s (PBVPET,PBVTMDL=28) = 0.67 ± 0.11]. Perfusion patterns differed along the posterior-anterior direction [ r s (PBVPET,PBVTMDL=28) = 0.77 ± 0.13/0.57 ± 0.16 in the anterior/posterior region]. Significance . A strong correlation between DECT and PET determination of PBV was observed. Streak and smoothing effects in DECT and gravitational artefacts and misregistration in PET reduced the correlation posteriorly., (© 2023 Institute of Physics and Engineering in Medicine.)