Rajiah, Prabhakar

AbstractPurposeA dual‐source CT system can be operated in a high‐pitch helical mode to provide a temporal resolution of 66 ms, which reduces motion artifacts in CT pulmonary angiography (CTPA). It can also be operated in a multi‐energy (ME) mode to provide iodine maps, beneficial in the evaluation of pulmonary embolism (PE). No energy‐integrating detector (EID) CT can perform simultaneous ME and high‐pitch acquisition. This phantom study aimed to evaluate the ability of a photon‐counting‐detector (PCD) CT to perform simultaneous high‐pitch and ME imaging for CTPA.MethodsA motion phantom was used to mimic the respiratory motion. Two tubes filled with iodine with intravascular thrombus mimicked by injecting glue within the tubes were placed along with 5, 10, and 15 mg/mL iodine samples, on a motion phantom at 20 and 30 revolutions per minute. Separate high‐pitch and ME EID‐CT scans and a single high‐pitch ME PCD scan were acquired and virtual monoenergetic images and iodine maps reconstructed. Percent thrombus occlusion was measured and compared between static and moving images.ResultsWhen there was motion, EID‐CT ME suffered from significant motion artifacts. The measured iodine concentrations with PCD‐CT in high‐pitch ME were more stable when there was a motion, with a lower standard deviation than EID‐CT in ME mode. The estimated percent thrombus occlusion dropped significantly with applied motion on EID‐CT, while PCD‐CT high‐pitch ME mode showed good agreement between measurements on static or moving images.ConclusionPCD‐CT with combined ME and high‐pitch mode facilitates simultaneous accurate iodine quantification and assessment of intravascular occlusion.

Abstract Objectives. To improve quality of coronary CT angiography (CCTA) images using a generalizable motion-correction algorithm. Approach . A neural network with attention gate and spatial transformer (ATOM) was developed to correct coronary motion. Phantom and patient CCTA images (39 males, 32 females, age range 19–92, scan date 02/2020 to 10/2021) retrospectively collected from dual-source CT were used to create training, development, and testing sets corresponding to 140- and 75 ms temporal resolution, with 75 ms images as labels. To test generalizability, ATOM was deployed for locally adaptive motion-correction in both 140- and 75 ms patient images. Objective metrics were used to assess motion-corrupted and corrected phantom and patient images, including structural-similarity-index (SSIM), dice-similarity-coefficient (DSC), peak-signal-noise-ratio (PSNR), and normalized root-mean-square-error (NRMSE). In objective quality assessment, ATOM was compared with several baseline networks, including U-net, U-net plus attention gate, U-net plus spatial transformer, VDSR, and ResNet. Two cardiac radiologists independently interpreted motion-corrupted and -corrected images at 75 and 140 ms in a blinded fashion and ranked diagnostic image quality (worst to best: 1–4, no ties). Main results . ATOM improved quality metrics ( p < 0.05) before/after correction: in phantom, SSIM 0.87/0.95, DSC 0.85/0.93, PSNR 19.4/22.5, NRMSE 0.38/0.27; in patient images, SSIM 0.82/0.88, DSC 0.88/0.90, PSNR 30.0/32.0, NRMSE 0.16/0.12. ATOM provided more consistent improvement of objective image quality, compared to the presented baseline networks. The motion-corrected images received better ranks than un-corrected at the same temporal resolution ( p < 0.05): 140 ms images 1.65/2.25, and 75 ms images 3.1/3.2. The motion-corrected 75 ms images received the best rank in 65% of testing cases. A fair-to-good inter-reader agreement was observed (Kappa score 0.58). Significance . ATOM reduces motion artifacts, improving visualization of coronary arteries. This algorithm can be used to virtually improve temporal resolution in both single- and dual-source CT.