keV Images Research Articles

Multi-DECT image-based intratumoral and peritumoral radiomics for preoperative prediction of muscle invasion in bladder cancer

ObjectivesTo assess the predictive value of intratumoral and peritumoral radiomics based on Dual-energy CT urography (DECTU) multi-images for preoperatively predicting the muscle invasion status of bladder cancer (BCa). Material and methodsThis retrospective analysis involved 202 BCa patients who underwent DECTU. DECTU-derived quantitative parameters were identified as risk factors through stepwise regression analysis to construct a DECT model. The radiomic features from the intratumoral and 3mm outward peritumoral regions were extracted from the 120 kVp-like, 40 keV, 100 keV, and iodine-based material-decomposition (IMD) images in the venous-phase and were screened using Mann-Whitney U test, Spearman correlation analysis, and LASSO. Radiomics models were developed using the Multilayer Perceptron for the intratumoral, peritumoral and intra- and peritumoral (IntraPeri) regions. Subsequently, a nomogram was created by integrating the multi-image IntraPeri radiomics and DECT model. Model performance was evaluated using area-under-the-curve (AUC), accuracy, sensitivity, and specificity. ResultsNormalized iodine concentration (NIC) was identified as an independent predictor for the DECT model. The IntraPeri model demonstrated superior performance compared to the intratumoral and peritumoral models both in 40 keV (0.830 vs. 0.766 vs. 0.763) and IMD images (0.881 vs. 0.840 vs. 0.821) in the test cohort. In the test cohort, the nomogram exhibited the best predictability (AUC=0.886, accuracy=0.836, sensitivity=0.737, and specificity=0.881), outperformed the DECT model (AUC=0.763, accuracy=0.754, sensitivity=0.632, and specificity=0.810) in predicting muscle invasion status of BCa with a statistically significant difference (p< 0.05). ConclusionThe nomogram, incorporating IntraPeri radiomics and NIC, serves as a valuable and non-invasive tool for preoperatively assessing the muscle invasion status of BCa.

Dual-energy computed tomography with new virtual monoenergetic image reconstruction enhances prostate lesion image quality and improves the diagnostic efficacy for prostate cancer

BackgroundProstate cancer is one of the most common malignant tumors in middle-aged and elderly men and carries significant prognostic implications, and recent studies suggest that dual-energy computed tomography (DECT) utilizing new virtual monoenergetic images can enhance cancer detection rates. This study aimed to assess the impact of virtual monoenergetic images reconstructed from DECT arterial phase scans on the image quality of prostate lesions and their diagnostic performance for prostate cancer.MethodsWe conducted a retrospective analysis of 83 patients with prostate cancer or prostatic hyperplasia who underwent DECT scans at Meizhou People’s Hospital between July 2019 and December 2023. The variables analyzed included age, tumor diameter and serum prostate-specific antigen (PSA) levels, among others. We also compared CT values, signal-to-noise ratio (SNR), subjective image quality ratings, and contrast-to-noise ratio (CNR) between virtual monoenergetic images (40–100 keV) and conventional linear blending images. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic efficacy of virtual monoenergetic images (40 keV and 50 keV) compared to conventional images.ResultsVirtual monoenergetic images at 40 keV showed significantly higher CT values (168.19 ± 57.14) compared to conventional linear blending images (66.66 ± 15.5) for prostate cancer (P < 0.001). The 50 keV images also demonstrated elevated CT values (121.73 ± 39.21) compared to conventional images (P < 0.001). CNR values for the 40 keV (3.81 ± 2.13) and 50 keV (2.95 ± 1.50) groups were significantly higher than the conventional blending group (P < 0.001). Subjective evaluations indicated markedly better image quality scores for 40 keV (median score of 5) and 50 keV (median score of 5) images compared to conventional images (P < 0.05). ROC curve analysis revealed superior diagnostic accuracy for 40 keV (AUC: 0.910) and 50 keV (AUC: 0.910) images based on CT values compared to conventional images (AUC: 0.849).ConclusionsVirtual monoenergetic images reconstructed at 40 keV and 50 keV from DECT arterial phase scans substantially enhance the image quality of prostate lesions and improve diagnostic efficacy for prostate cancer.

Dual-source photon-counting computed tomography for coronary in-stent observation: influence of heart rate and virtual monoenergetic image.

To investigate the effect of heart rate and virtual monoenergetic image (VMI) on coronary stent imaging in dual-source photon-counting detector computed tomography (PCD-CT). A dynamic cardiac phantom was used to vary the heart rate at 50 beats per minute (bpm), 70bpm, and 90bpm. Five types of stents (4.0mm, 3.5mm, 3.0mm, 2.75mm, and 2.5mm diameter) were scanned at three different locations and reconstructed VMI at 70keV. In addition, 50% stenosis was assessed for 3.0mm and 4.0mm stents. To assess in-stent stenosis, 40keV, 70keV, and 100keV images were compared. Measurable lumen and contrast to noise ratio (CNR) from lumen to stenosis were evaluated quantitatively. A-4-point scale was used for the qualitative image quality of in-stent stenosis. The measurable lumen had no significant differences among heart rates in patent stents (p = 0.55). In-stent stenosis, the residual lumen was significantly larger in 40keV [27.5% (20.8-32.3%)] than in 70keV [11.5% (10.0-23.0%), p < 0.05] and 100keV [0% (0-5.2%), p < 0.05]. The CNR was higher in 40keV [12.5 (7.5-18.2)] than in 70keV [5.3 (2.9-7.7), p < 0.05] and 100keV [1.3 (0.5-2.7), p < 0.05]. The image quality was better in 40keV (3.4 ± 0.7) than in 70keV [(2.6 ± 0.8), p < 0.05] and 100keV [(1.3 ± 0.4), p < 0.05]. Dual-source PCD-CT maintains a measurable lumen even at high heart rates. Adjusting the VMI can be helpful in visualizing the in-stent stenosis.

Improving diagnostic confidence in low-dose dual-energy CTE with low energy level and deep learning reconstruction

ObjectiveTo demonstrate the value of using 50 keV virtual monochromatic images with deep learning image reconstruction (DLIR) in low-dose dual-energy CT enterography (CTE). MethodsIn this prospective study, 114 participants (62 % M; 41.9 ± 16 years) underwent dual-energy CTE. The early-enteric phase was performed using standard-dose (noise index (NI): 8) and images were reconstructed at 70 keV and 50 keV with 40 % strength ASIR-V (ASIR-V40%). The late-enteric phase used low-dose (NI: 12) and images were reconstructed at 50 keV with ASIR-V40%, and DLIR at medium (DLIR-M) and high strength (DLIR-H). Image standard deviation (SD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), edge-rise-slope (ERS) were computed. The quantitative comb sign score was calculated for the 27 patients with Crohn’s disease. The subjective noise, image contrast, display of rectus artery were scored using a 5-point scale by two radiologists blindly. ResultsEffective dose was reduced by 50 % (P < 0.001) in the late-enteric phase to 3.26 mSv. The lower-dose 50 keV-DLIR-H images (SD:17.7 ± 0.5HU) had similar image noise (P = 0.97) as the standard-dose 70 keV-ASIR-V40% images (SD:17.7 ± 0.73HU), but with higher (P < 0.001) SNR, CNR, ERS and quantitative comb sign score (5.7 ± 0.17, 1.8 ± 0.12, 156.04 ± 5.21 and 5.05 ± 0.73, respectively). Furthermore, the lower-dose 50 keV-DLIR-H images obtained the highest score in the rectus artery visibility (4.27 ± 0.6). ConclusionsThe 50 keV images in dual-energy CTE with DLIR provides high-quality images, with a 50 % reduction in radiation dose. Images with high contrast and density resolutions significantly enhance the diagnostic confidence of Crohn’s disease and are essential for the clinical development of individualized treatment plans.

Low energy virtual monochromatic CT with deep learning image reconstruction to improve delineation of endoleaks

This study aimed to investigate the utility of low-energy virtual monochromatic imaging (VMI) combined with deep-learning image reconstruction (DLIR) in improving the delineation of endoleaks (ELs) after endovascular aortic repair (EVAR) in contrast-enhanced dual-energy CT (DECT). A total of 61 consecutive patients (mean age, 77 years; 46 men) after EVAR who underwent contrast-enhanced DECT were enrolled. Virtual monochromatic 40- and 70-keV images were reconstructed using DLIR (TrueFidelity-H) and conventional hybrid iterative reconstruction (IR). Contrast-to-noise ratio (CNR) of the EL on the venous-phase CT was calculated. Four different reconstructed image series (hybrid IR and DLIR at two energy levels, 40- and 70-keV) were displayed side-by-side and visually assessed for EL conspicuity on a 5-point comparative scale from 0 (best) to -4 (significantly inferior). Two experienced radiologists independently conducted a qualitative evaluation of the CT images. A total of 30 out of 61 patients presented with an EL. On both 40- and 70-keV images, the CNR of the EL was significantly higher in DLIR than in hybrid IR (40-keV, 14.5±7.3 vs 8.6±4.2, P<0.001; 70-keV, 8.7±4.5 vs 5.5±2.6, P<0.001). The comparative scale of EL conspicuity in the 40-keV DLIR images (Observer1, -0.2±0.4; Observer2, 0.0±0.0) was significantly higher than 40-keV hybrid IR (Observer1, -0.5±0.5; Observer2, -1.0±0.0; P<0.05), 70-keV DLIR (Observer1, -1.8±0.4; Observer2, -2.0±0.0; P<0.001) and 70-keV hybrid IR images (Observer1, -1.8±0.4; Observer2, -2.4±0.5; P<0.001), respectively. Using 40-keV VMI in combination with DLIR improves EL delineation after EVAR compared with the 70-keV VMI with hybrid IR or DLIR.

Comparison of dual-energy computed tomography (DECT) polychromatic and monochromatic images with and without iterative metal artifact reduction algorithm in patients with dental implants.

Dual-energy computed tomography (DECT) and iterative metal artifact reduction (iMAR) algorithms are valuable tools for reducing metal artifacts. Different parameters of these technologies and their combination can achieve different performance. This study compared various polychromatic and monochromatic images obtained via DECT with and without using iMAR algorithm to reduce artifacts in patients with dental implants. This study included 30 patients with dental implants who underwent DECT for head and neck imaging. The computed tomography (CT) image sets comprised DECT polychromatic image sets [dual-energy (DE) polychromatic] that linearly blended 100 kV and tin-filtered 140 kV images using composition ratios of -1, -0.6, -0.3, 0, and 0.6, and virtual monochromatic images (DE monochromatic) at 90, 110, 130, 150, and 170 keV. These image sets were obtained with and without using iMAR, resulting in a total of 20 image sets. For subjective analysis, metal artifacts and image quality were assessed using a 5-point Likert scale. For objective analysis, CT attenuation, standard deviation (SD), contrast-to-noise ratio (CNR) and artifact index (AI) were evaluated. In addition, subgroup analysis was performed based on implant size. In the subjective evaluation, iMAR + DE polychromatic (-0.3) images exhibited the lowest metal artifact scores [median (interquartile range): 2 (2-3)]. iMAR + DE monochromatic (110 keV) images demonstrated optimal image quality scores [median (interquartile range): 2 (2-3)]. In the objective evaluation, none of the images demonstrated a significant difference in the CNR, except polychromatic images with a composition of -1 and 0.6. iMAR + DE polychromatic (0) exhibited the lowest AI [median (interquartile range): 8.7 (5.9-14.5)]. There was no significant difference between the two groups with different implant sizes for the techniques combined with iMAR (all P>0.05). iMAR + DE polychromatic (-0.3 and 0) and iMAR + DE monochromatic (110 keV) images exhibited better image quality and substantial metal artifact reduction (MAR) compared with the other image sets. The performance of the techniques combined with iMAR was not affected by the size of the implant.

Optimizing twin-beam dual-energy CT reconstruction: Quantitative consistency and stability assessment in reference to 120 kV: An observational study.

The split filter CT can filter X-ray beam. Theoretically, the split filter CT not only provides a good low-energy beam, but also provides a more robust CT value. The aim of this study was to compare conventional single-energy computed tomography (SECT) and twin-beam dual-energy (TBDE) CT regarding the quantitative consistency and stabilities of HU measurements at different abdominal organs. Forty-four patients were prospectively enrolled to randomly receive SECT and TBDE protocols at either body part of a thorax-abdominal examination. Their overlapping scan coverage was subjected to further image analysis. For TBDE scans, composed images(c-images) and virtual monoenergetic images (VMIs) at 60, 70, 80, and 90 kiloelectron volt (keV) were reconstructed. The attenuations were measured at 5 abdominal organs and compared between SECT and TBDE to characterize quantitative consistency by intraclass correlation coefficients (ICCs), whereas their standard deviations were used to assess the Hounsfield Unit (HU) stability. The c-images, 70 keV and 80 keV VMIs from TBDE provided consistent HU values (all ICCs > 0.8) with the SECT measurements; moreover, these TBDE images had superior HU stability over SECT images in all abdominal measurements except for fat tissue. The best HU stability can be achieved in 80 keV VMIs with the lowest noise level. The c-images and VMIs derived from TBDE can produce consistent values as SECT. The 80 keV images displayed better HU stability and a lower noise level across various abdominal organs.

Ultrahigh-Resolution K-Edge Imaging of Coronary Arteries With Prototype Deep-Silicon Photon-Counting CT: Initial Results in Phantoms.

Background Photon-counting CT (PCCT) represents a recent advancement in CT, offering improved spatial resolution and spectral separability. By using multiple adjustable energy bins, PCCT enables K-edge imaging, allowing mixed contrast agent distinction. Deep-silicon is a new type of photon-counting detector with different characteristics compared with cadmium photon-counting detectors. Purpose To evaluate the performance of a prototype deep-Si PCCT scanner and compare it with that of a state-of-the-art dual-energy energy-integrating detector (EID) scanner in imaging coronary artery plaques enhanced with iodine and K-edge contrast agents. Materials and Methods A series of 10 three-dimensional-printed inserts (diameter, 3.5 mm) was prepared, and materials mimicking soft and calcified plaques were added to simulate stenosed coronary arteries. Inserts filled with an iodine- or gadolinium-based contrast agent (GBCA) were scanned. Virtual monoenergetic images (VMIs) and iodine maps were generated using two- and eight-energy bin data from EID CT and PCCT, respectively. Gadolinium maps were calculated for PCCT. The CT numbers of VMIs and iodine maps were compared. Spatial resolution and blooming artifacts were compared on the 70-keV VMIs in plaque-free and calcified coronary arteries. Results No evidence of a significant difference in the CT number of 70-keV images was found except in inserts containing GBCAs. In the absence of a GBCA, excellent (r > 0.99) agreement for iodine was found. PCCT could quantify the GBCA within 0.2 mg Gd/mL ± 0.8 accuracy of the ground truth, whereas EID CT failed to detect the GBCA. Lumen measurements were more accurate for PCCT than for EID CT, with mean errors of 167 versus 442 µm (P < .001) compared with the 3.5-mm ground truth. Conclusion Deep-Si PCCT demonstrated good accuracy in iodine quantification and could accurately decompose mixtures of two contrast agents. Its improved spatial resolution resulted in sharper images with blooming artifacts reduced by 50% compared with a state-of-the-art dual-energy EID CT scanner. © RSNA, 2024.

Clinical application of dual-layer spectral CT multi-parameter feature to predict microvascular invasion in hepatocellular carcinoma.

This study aimed to investigate the feasibility of using dual-layer spectral CT multi-parameter feature to predict microvascular invasion of hepatocellular carcinoma. This retrospective study enrolled 50 HCC patients who underwent multiphase contrast-enhanced spectral CT studies preoperatively. Combined clinical data, radiological features with spectral CT quantitative parameter were constructed to predict MVI. ROC was applied to identify potential predictors of MVI. The CT values obtained by simulating the conventional CT scans with 70 keV images were compared with those obtained with 40 keV images. 50 hepatocellular carcinomas were detected with 30 lesions (Group A) with microvascular invasion and 20 (Group B) without. There were significant differences in AFP,tumer size, IC, NIC,slope and effective atomic number in AP and ICrr in VP between Group A ((1000(10.875,1000),4.360±0.3105, 1.7750 (1.5350,1.8825) mg/ml, 0.1785 (0.1621,0.2124), 2.0362±0.2108,8.0960±0.1043,0.2830±0.0777) and Group B (4.750(3.325,20.425),3.190±0.2979,1.4700 (1.4500,1.5775) mg/ml, 0.1441 (0.1373,0.1490),1.8601±0.1595, 7.8105±0.7830 and 0.2228±0.0612) (all p < 0.05). Using 0.1586 as the threshold for NIC, one could obtain an area-under-curve (AUC) of 0.875 in ROC to differentiate between tumours with and without microvascular invasion. AUC was 0.625 with CT value at 70 keV and improved to 0.843 at 40 keV. Dual-layer spectral CT provides additional quantitative parameters than conventional CT to enhance the differentiation between hepatocellular carcinoma with and without microvascular invasion. Especially, the normalized iodine concentration (NIC) in arterial phase has the greatest potential application value in determining whether microvascular invasion exists, and can offer an important reference for clinical treatment plan and prognosis assessment.

Low-contrast detectability of photon-counting-detector CT at different scan modes and image types in comparison with energy-integrating-detector CT.

We aim to compare the low-contrast detectability of a clinical whole-body photon-counting-detector (PCD)-CT at different scan modes and image types with an energy-integrating-detector (EID)-CT. We used a channelized Hotelling observer (CHO) previously optimized for quality control purposes. An American College of Radiology CT accreditation phantom was scanned on both PCD-CT and EID-CT with 10 phantom positionings. For PCD-CT, images were generated using two scan modes, standard resolution (SR) and ultra-high-resolution (UHR); two image types, virtual monochromatic images at 70keV and low-energy threshold (T3D); both filtered-back-projection (FBP) and iterative reconstruction (IR) reconstruction methods; and three reconstruction kernels. For each positioning, three repeated scans were acquired for each scan mode, image type, and CTDIvol of 6, 12, and 24mGy. For EID-CT, images acquired from scans (10 positionings × 3 repeats × 3 doses) were reconstructed using the closest counterpart FBP and IR kernels. CHO was applied to calculate the index of detectability () on both scanners. With the smooth Br44 kernel, the of UHR was mostly comparable with that of the SR mode (difference: -11.4% to 8.3%, to 0.956), and the T3D images had a higher (difference: 0.7% to 25.6%) than 70keV images on PCD-CT. Compared with the EID-CT, UHR-T3D of PCD-CT had non-inferior (difference: -2.7% to 12.9%) with IR and non-superior (difference: 0.8% to 11.2%) with FBP using the Br44 kernel. PCD-CT produced higher than EID-CT by 61.8% to 247.1% with the sharper reconstruction kernels. The comparison between PCD-CT and EID-CT was significantly influenced by the reconstruction method and kernel. With a smooth kernel that is typically used in low-contrast detection tasks, the PCD-CT demonstrated low-contrast detectability that was comparable to EID-CT with IR and showed no superiority when using FBP. With the use of sharper kernels, the PCD-CT significantly outperformed EID-CT in low-contrast detectability.

Latest Evolution of the X-Ray Remnant of SN 1987A: Beyond the Inner Ring

Based on our Chandra imaging-spectroscopic observations, we present the latest evolution of the X-ray remnant of SN 1987A. Recent changes in the electron temperatures and volume emission measures suggest that the blast wave in SN 1987A is moving out of the dense inner ring structure, also called the equatorial ring (ER). The 0.5–2.0 keV X-ray light curve shows a linearly declining trend (by ∼4.5% yr−1) between 2016 and 2020 as the blast wave heats the hitherto unknown circumstellar medium (CSM) outside the ER. While the peak X-ray emission in the latest 0.3–8.0 keV image is still within the ER, the radial expansion rate in the 3.0–8.0 keV images suggests an increasing contribution of the X-ray emission from less dense CSM since 2012, at least partly from beyond the ER. It is remarkable that, since 2020, the declining soft X-ray flux has stabilized around ∼7 × 10−12 erg s−1 cm−2, which may signal a contribution from the reverse-shocked outer layers of ejecta as predicted by the three-dimensional magnetohydrodynamic models. In the latest ACIS spectrum of supernova remnant 1987A in 2022 we report a significant detection of the Fe K line at ∼6.7 keV, which may be due to changing thermal conditions of the X-ray emitting CSM and/or the onset of reverse shock interactions with the Fe ejecta.

Reduced Intravenous Contrast Dose Portal Venous Phase Photon-Counting Computed Tomography Compared With Conventional Energy-Integrating Detector Portal Venous Phase Computed Tomography.

The aim of this study was to compare portal venous phase photon-counting CT (PCCT) using 20 cc less than weight-based contrast dosing with energy-integrating detector CT (EID-CT) using weight-based dosing by quantitative and qualitative analysis. Fifty adult patients who underwent a reduced intravenous contrast dose portal venous phase PCCT from May 1, 2023, to August 10, 2023, and a prior portal-venous EID-CT with weight-based contrast dosing were retrospectively identified. Hounsfield units (HU) and noise (SD of HU) were obtained from region-of-interest measurements on 70-keV PCCT and EID-CT in 4 hepatic segments, the main and right portal vein, and both paraspinal muscles. Signal-to-noise and contrast-to-noise ratios were computed. Three abdominal radiologists qualitatively assessed overall image quality, hepatic enhancement, and confidence for metastasis identification on 5-point Likert scales. Readers also recorded the presence/absence of hepatic metastases. Quantitative variables were compared with paired t tests, and multiple comparisons were accounted for with a Bonferroni-adjusted α level of .0016. Ordinal logistic regression was used to evaluate qualitative assessments. Interreader agreement for hepatic metastases was calculated using Fleiss' κ. Fifty patients (32 women; mean [SD] age, 64 [13] years) were included. There was no significant difference in hepatic HU, portal vein HU, noise, and signal-to-noise or contrast-to-noise ratio between reduced contrast dose portal venous phase PCCT versus EID-CT (all P s > 0.0016). Image quality, degree of hepatic enhancement, and confidence for metastasis identification were not different for reduced dose PCCT 70-keV images and EID-CT ( P = 0.06-0.69). κ Value for metastasis identification was 0.86 (95% confidence interval, 0.70-1.00) with PCCT and 0.78 (95% confidence interval, 0.59-0.98) with EID-CT. Reduced intravenous contrast portal venous phase PCCT 70-keV images had similar attenuation and image quality as EID-CT with weight-based dosing. Metastases were identified with near-perfect agreement in reduced dose PCCT 70-keV images.

Combined 100 keV Cryo-Electron Microscopy and Image Analysis Methods to Characterize the Wider Adeno-Associated Viral Products

Adeno-associated viruses (AAVs) are effective vectors for gene therapy. However, AAV drug products are inevitably contaminated with empty particles (EP), which lack a genome, owing to limitations of the purification steps. EP contamination can reduce the transduction efficiency and induce immunogenicity. Therefore, it is important to remove EPs and to determine the ratio of full genome-containing AAV particles to empty particles (F/E ratio). However, most of the existing methods fail to reliably evaluate F/E ratios that are greater than 90 %. In this study, we developed two approaches based on the image analysis of cryo-electron micrographs to determine the F/E ratios of various AAV products. Using our developed convolutional neural network (CNN) and morphological analysis, we successfully calculated the F/E ratios of various AAV products and determined the slight differences in the F/E ratios of highly purified AAV products (purity > 95 %). In addition, the F/E ratios calculated by analyzing more than 1000 AAV particles had good correlations with theoretical F/E ratios. Furthermore, the CNN reliably determined the F/E ratio with a smaller number of AAV particles than morphological analysis. Therefore, combining 100 keV cryo-EM with the developed image analysis methods enables the assessment of a wide range of AAV products.

Photon-Counting Detector CT: Potential for 75% Reduction in Contrast Medium Amount: A Phantom Study.

This study aimed to evaluate the potential reduction in contrast medium utilization using photon-counting detector computed tomography (PCD-CT). One PCD-CT scan (CT1) and three conventional (non-PCD-CT) CT scans (CT2-CT4) were performed using a multi-energy CT phantom that contained eight rods with different iodine concentrations (0.2, 0.5, 1, 2, 5, 10, 15, and 20 mg/ml). The CT values of the seven groups (CT1 for 40, 50, 60, and 70 keV; and CT2-4) were measured. Noise and contrast-to-noise ratio (CNR) were assessed for the eight rods at various iodine concentrations. CT2 and CT1 (40 keV) respectively required 20 mg/ml and 5 mg/ml of iodine, indicating that a comparable contrast effect could be obtained with approximately one-fourth of the contrast medium amount. The standard deviation values increased at lower energy levels irrespective of the iodine concentration. The CNR exhibited a decreasing trend with lower iodine concentrations, while it remained relatively stable across all iodine levels (40-70 keV). This study demonstrated that virtual monochromatic 40 keV images offer a similar contrast effect with a reduced contrast medium amount when compared to conventional CT systems at 120 kV.

Potential of photon counting computed tomography derived spectral reconstructions to reduce beam-hardening artifacts in chest CT

PurposeAim of the recent study is to point out a method to optimize quality of CT scans in oncological patients with port systems. This study investigates the potential of photon counting computed tomography (PCCT) for reduction of beam hardening artifacts caused by port-implants in chest imaging by means of spectral reconstructions. MethodIn this retrospective single-center study, 8 ROIs for 19 spectral reconstructions (polyenergetic imaging, monoenergetic reconstructions from 40 to 190 keV as well as iodine maps and virtual non contrast (VNC)) of 49 patients with pectoral port systems undergoing PCCT of the chest for staging of oncologic disease were measured. Mean values and standard deviation (SD) Hounsfield unit measurements of port-chamber associated hypo- and hyperdense artifacts, bilateral muscles and vessels has been carried out. Also, a structured assessment of artifacts and imaging findings was performed by two radiologists. ResultsA significant association of keV with iodine contrast as well as artifact intensity was noted (all p < 0.001). In qualitative assessment, utilization of 120 keV monoenergetic reconstructions could reduce severe and pronounced artifacts completely, as compared to lower keV reconstructions (p < 0.001). Regarding imaging findings, no significant difference between monoenergetic reconstructions was noted (all p > 0.05). In cases with very high iodine concentrations in the subclavian vein, image distortions were noted at 40 keV images (p < 0.01). ConclusionsThe present study demonstrates that PCCT derived spectral reconstructions can be used in oncological imaging of the thorax to reduce port-derived beam-hardening artefacts. When evaluating image data sets within a staging, it can be particularly helpful to consider the 120 keV VMIs, in which the artefacts are comparatively low.

Pancreatic cancer detection with dual-energy CT: diagnostic performance of 40 keV and 70 keV virtual monoenergetic images.

To compare the diagnostic performance of 40 keV and 70keV virtual monoenergetic images (VMIs) generated from dual-energy CT in the detection of pancreatic cancer. This retrospective study included patients who underwent pancreatic protocol dual-energy CT from January 2019 to August 2022. Four radiologists (1-11years of experience), who were blinded to the final diagnosis, independently and randomly interpreted 40 keV and 70keV VMIs and graded the presence or absence of pancreatic cancer. For each image set (40keV and 70keV VMIs), the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The diagnostic performance of each image set was compared using generalized estimating equations. Overall, 137 patients (median age, 71years; interquartile range, 63-78years; 77 men) were included. Among them, 62 patients (45%) had pathologically proven pancreatic cancer. The 40 keV VMIs had higher specificity (75% vs. 67%; P < .001), PPV (76% vs. 71%; P < .001), and accuracy (85% vs. 81%; P = .001) than the 70 keV VMIs. On the contrary, 40keV VMIs had lower sensitivity (96% vs. 98%; P = .02) and NPV (96% vs. 98%; P = .004) than 70keV VMIs. However, the diagnostic confidence in patients with (P < .001) and without (P = .001) pancreatic cancer was improved in 40 keV VMIs than in 70 keV VMIs. The 40 keV VMIs showed better diagnostic performance in diagnosing pancreatic cancer than the 70keV VMIs, along with higher reader confidence.

Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs—A Preliminary Study

Thus, the aim of this study is to evaluate the performance of deep learning imaging reconstruction (DLIR) algorithm in different image sets derived from carotid dual-energy computed tomography angiography (DECTA) for evaluating cervical intervertebral discs (IVDs) and compare them with those reconstructed using adaptive statistical iterative reconstruction-Veo (ASiR-V). Forty-two patients who underwent carotid DECTA were included in this retrospective analysis. Three types of image sets (70 keV, water-iodine, and water-calcium) were reconstructed using 50% ASiR-V and DLIR at medium and high levels (DLIR-M and DLIR-H). The diagnostic acceptability and conspicuity of IVDs were assessed using a 5-point scale. Hounsfield Units (HU) and water concentration (WC) values of the IVDs; standard deviation (SD); and coefficient of variation (CV) were calculated. Measurement parameters of the 50% ASIR-V, DLIR-M, and DLIR-H groups were compared. The DLIR-H group showed higher scores for diagnostic acceptability and conspicuity, as well as lower SD values for HU and WC than the ASiR-V and DLIR-M groups for the 70 keV and water-iodine image sets (all p < .001). However, there was no significant difference in scores and SD among the three groups for the water-calcium image set (all p > .005). The water-calcium image set showed better diagnostic accuracy for evaluating IVDs compared to the other image sets. The inter-rater agreement using ASiR-V, DLIR-M, and DLIR-H was good for the 70 keV image set, excellent for the water-iodine and water-calcium image sets. DLIR improved the visualization of IVDs in the 70 keV and water-iodine image sets. However, its improvement on color-coded water-calcium image set was limited.

Detecting bone marrow infiltration in nonosteolytic multiple myeloma through separation of hydroxyapatite via the two-material decomposition technique in spectral computed tomography.

Conventional computed tomography (CT) has low sensitivity for the diagnosis of bone marrow infiltration in nonosteolytic multiple myeloma (NOL-MM). This study aimed to compare the performance of the two-material decomposition technique of spectral CT with the removal of X-ray absorption components of calcium (Ca) versus that of hydroxyapatite (HAP) for diagnosis of NOL-MM. From October 2022 to March 2023, a total of 41 consecutive patients with MM without focal bone lesions undergoing chest spectral CT and thoracic spine magnetic resonance imaging (MRI) in Fujian Medical University Union Hospital were prospectively enrolled; meanwhile, another set of 41 age- and sex-matched healthy consecutive participants were selected as a comparison group. Based on MRI findings, patients with MM were classified with a diffuse infiltration pattern MM (DP-MM) or a normal pattern MM (NP-MM). Regions of interest (ROIs) were manually drawn on vertebrae. CT values of 70-keV images and basic material density within the ROIs were stored. The basic two-material pairs included a Ca-related pair (Ca-X) and an HAP-related pair (HAP-X), with X referring to fat, water, or muscle. Material density values DCa(X), DX(Ca), DHAP(X), and DX(HAP) were each used to diagnose MM, and the area under the receiver operating characteristic curve (AUC) was used to assess diagnostic performance. The 41 patients with NOL-MM included 30 with DP-MM and 11 with NP-MM. CT value, DCa(X), and DHAP(X) were comparable between the NOL-MM, DP-MM, NP-MM, and comparison groups. DX(HAP) was better than DX(Ca) for distinguishing the NOL-MM group from the comparison group {AUC [95% confidence interval (CI)], 0.874 (0.800, 0.949) vs. 0.737 (0.630, 0.844); P=0.02}, the DP-MM group from the comparison group [AUC (95% CI), 0.933 (0.878, 0.989) vs. 0.785 (0.677, 0.894); P=0.01], the NP-MM group from the comparison group [AUC (95% CI), 0.714 (0.540, 0.888) vs. 0.605 (0.429, 0.782); P=0.03], and the DP-MM group from the NP-MM group [AUC (95% CI), 0.809 (0.654, 0.964) vs. 0.736 (0.566, 0.907); P=0.049]. The diagnostic performance of DX(HAP) and DX(Ca) was influenced only by the removed material, while the X material had no influence. The spectral CT two-material decomposition technique with removal of X-ray absorption components of HAP is useful for diagnosis of NOL-MM, irrespective of the paired material.

Spectral performance evaluation of a second-generation spectral detector CT.

The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities. A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150keV, and root mean square error (RMSE) for adipose and iron content was reported. Measured inserts exhibited quantitative accuracy across a wide range of MonoE levels. MonoE 70keV images demonstrated reduced dependence compared to conventional images for phantom size (1vs. 27 HU) and acquisition parameters, particularly tube voltage (4vs. 37 HU). Iodine density quantification was successful with errors ranging from -0.58 to 0.44mg/mL. Similarly, inserts with different amounts of adipose and iron were differentiated, and the small deviation in values within inserts corresponded to a RMSE of 3.49±1.76% and 1.67±0.84mg/mL for adipose and iron content, respectively. The second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.

Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.

To evaluate the performance of deep learning image reconstruction (DLIR) algorithm in dual-energy spectral CT (DEsCT) as a function of radiation dose and image energy level, in comparison with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction-V (ASIR-V) algorithms. An ACR464 phantom was scanned with DEsCT at four dose levels (3.5 mGy, 5 mGy, 7.5 mGy, and 10 mGy). Virtual monochromatic images were reconstructed at five energy levels (40 keV, 50 keV, 68 keV, 74 keV, and 140 keV) using FBP, 50% and 100% ASIR-V, DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) settings. The noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d') were computed and compared among reconstructions. NPS area and noise increased as keV decreased, with DLIR having slower increase than FBP and ASIR-V, and DLIR-H having the lowest values. DLIR had the best 40 keV/140 keV noise ratio at various energy levels, DLIR showed higher TTF (50%) than ASIR-V for all materials, especially for the soft tissue-like polystyrene insert, and DLIR-M and DLIR-H provided higher d' than DLIR-L, ASIR-V and FBP in all dose and energy levels. As keV increases, d' increased for acrylic insert, and d' of the 50 keV DLIR-M and DLIR-H images at 3.5 mGy (7.39 and 8.79, respectively) were higher than that (7.20) of the 50 keV ASIR-V50% images at 10 mGy. DLIR provides better noise containment for low keV images in DEsCT and higher TTF(50%) for the polystyrene insert over ASIR-V. DLIR-H has the lowest image noise and highest detectability in all dose and energy levels. DEsCT 50 keV images with DLIR-M and DLIR-H show potential for 65% dose reduction over ASIR-V50% withhigher d'.