Monoenergetic CT Images Research Articles

Effects of different virtual monoenergetic CT image data on chest wall post-processing "unfolded ribs" and proposal of an algorithm improvement.

To find out if the use of different virtual monoenergetic data sets enabled by DECT technology might have a negative impact on post-processing applications, specifically in case of the "unfolded ribs" algorithm. Metal or beam hardening artifacts are suspected to generate image artifacts and thus reduce diagnostic accuracy. This paper tries to find out how the generation of "unfolded rib" CT image reformates is influenced by different virtual monoenergetic CT images and looks for possible improvement of the post-processing tool. Between March 2021 and April 2021, thin-slice dual-energy CT image data of the chest were used creating "unfolded rib" reformates. The same data sets were analyzed in three steps: first the gold standard with the original algorithm on mixed image data sets followed by the original algorithm on different keV levels (40-120keV) and finally using a modified algorithm which in the first step used segmentation based on mixed image data sets, followed by segmentation based on different keV levels. Image quality (presence of artifacts), lesion and fracture detectability were assessed for all series. Both, the original and the modified algorithm resulted in more artifact-free image data sets compared to the gold standard. The modified algorithm resulted in significantly more artifact-free image data sets at the keV-edges (40-120keV) compared the original algorithm. Especially "black artifacts" and pseudo-lesions, potentially inducing false positive findings, could be reduced in all keV level with the modified algorithm. Detection of focal sclerotic, lytic or mixed (k = 0.990-1.000) lesions was very good for all keV levels. The Fleiss-kappa test for detection of fresh and old rib fractures was ≥ 0.997. The use of different virtual monoenergetic keVs for the "unfolded rib" algorithm is generating different artifacts. Segmentation-based artifacts could be eliminated by the proposed new algorithm, showing the best results at 70-80keV.

Conditional generative adversarial networks to generate pseudo low monoenergetic CT image from a single-tube voltage CT scanner.

To generate pseudo low monoenergetic CT images of the abdomen from 120-kVp CT images with cGAN. We retrospectively included 48 patients who underwent contrast-enhanced abdominal CT using dual-energy CT. We reconstructed paired data sets of 120 kVp CT images and virtual low monoenergetic (55-keV) CT images. cGAN was prepared to generate pseudo 55-keV CT images from 120-kVp CT images. The pseudo 55keV CT images in epoch 10, 50, 100, and 500 were compared to the 55keV images generated using peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The PSNRs were 28.0, 28.5, 28.6, and 28.8 at epochs 10, 50, 100, and 500, respectively. The SSIM was approximately constant from epochs 50 to 500. Pseudo low monoenergetic abdominal CT images were generated from 120-kVp CT images using cGAN, and the images had good quality similar to that of monochromatic images obtained with DECT software.

Low kV versus dual-energy virtual monoenergetic CT imaging for proven liver lesions: what are the advantages and trade-offs in conspicuity and image quality? A pilot study.

Single-energy low tube potential (SE-LTP) and dual-energy virtual monoenergetic (DE-VM) CT images both increase the conspicuity of hepatic lesions by increasing iodine signal. Our purpose was to compare the conspicuity of proven liver lesions, artifacts, and radiologist preferences in dose-matched SE-LTP and DE-VM images. Thirty-one patients with 72 proven liver lesions (21 benign, 51 malignant) underwent full-dose contrast-enhanced dual-energy CT (DECT). Half-dose images were obtained using single tube reconstruction of the dual-source SE-LTP projection data (80 or 100kV), and by inserting noise into dual-energy projection data, with DE-VM images reconstructed from 40 to 70keV. Three blinded gastrointestinal radiologists evaluated half-dose SE-LTP and DE-VM images, ranking and grading liver lesion conspicuity and diagnostic confidence (4-point scale) on a per-lesion basis. Image quality (noise, artifacts, sharpness) was evaluated, and overall image preference was ranked on per-patient basis. Lesion-to-liver contrast-to-noise ratio (CNR) was compared between techniques. Mean lesion size was 1.5±1.2cm. Across the readers, the mean conspicuity ratings for 40, 45, and 50keV half-dose DE-VM images were superior compared to other half-dose image sets (p<0.0001). Per-lesion diagnostic confidence was similar between half-dose SE-LTP compared to half-dose DE-VM images (p≥0.05; 1.19 vs. 1.24-1.32). However, SE-LTP images had less noise and artifacts and were sharper compared to DE-VM images less than 70keV (p<0.05). On a per-patient basis, radiologists preferred SE-LTP images the most and preferred 40-50keV the least (p<0.0001). Lesion CNR was also higher in SE-LTP images than DE-VM images (p<0.01). For the same applied dose level, liver lesions were more conspicuous using DE-VM compared to SE-LTP; however, SE-LTP images were preferred more than any single DE-VM energy level, likely due to lower noise and artifacts.

TU-E-201B-05: Photon Counting Radiography and CT: Upper Limits of SNR with Polyenergetic X-Rays

Purpose: To determine upper limits of signal to noise ratio (SNR) in radiography and computed tomography(CT) with polyenergetic x‐rays sources. Methods:Photon energy weighting increases SNR in polyenergetic x‐ray and CTimaging.SNR can be further increased if tube voltage is optimized in combination with x‐ray energy weighting. The SNR achieved with energy weighing at optimized tube voltage is the highest SNR possible in radiography and CT with polyenergetic x‐ray sources. The optimal tube voltages were determined for energy weighting and highest SNR were calculated for contrast elements of CaCO3, iodine, adipose, and tumor with thicknesses of 280 mg/cm2, 15 mg/cm2, 1 g/cm2, and 1 g/cm2, respectively, inserted in soft tissue with 10 cm and 20 cm thicknesses. The tube voltages were in 30 kVp – 140 kVp range and skin exposure was 20 mR. Energy weighting improves contrast to noise ratio (CNR) in CT when monoenergetic projections are optimally weighted. Alternatively, monoenergetic CTimages are reconstructed, optimally weighted, and combined providing final CTimage. It was determined analytically which method provides upper limit of CNR in CT.Results: A generalized weighting theorem was formulated and proven, which expands weighting method into the imaging areas other than x‐ray and CT. An optimal x‐ray tube voltage in energy weighting x‐ray imaging was determined for each contrast/background combination. Depending on imaging task, the highest SNR achieved in energy weighted polyenergetic x‐ray imaging were close to the SNR provided by monoenergetic x‐rays. It was proven that in CT the projection based weighting provides higher CNR than image based weighting thus determining upper limit of CNR.Conclusion: A unique tube voltage exists in energy weighting x‐ray and CT that provides highest SNR with polyenergetic x‐rays which can approach the SNR of monoenergetic x‐ray and CT. Projection based weighting provides highest CNR in CT.