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Item does not contain fulltext, BACKGROUND: A new tube voltage-switching dual-energy (DE) CT system using a novel deep-learning based reconstruction process has been introduced. Characterizing the performance of this DE approach can help demonstrate its benefits and potential drawbacks. PURPOSE: To evaluate the technical performance of a novel DECT system and compare it to that of standard single-kV CT and a rotate/rotate DECT, for abdominal imaging. METHODS: DE and single-kV images of four different phantoms were acquired on a kV-switching DECT system, and on a rotate/rotate DECT. The dose for the acquisitions of each phantom was set to that selected for the kV-switching DE mode by the automatic tube current modulation (ATCM) at manufacturer-recommended settings. The dose that the ATCM would have selected in single-kV mode was also recorded. Virtual monochromatic images (VMIs) from 40 to 130 keV, as well as iodine maps, were reconstructed from the DE data. Single-kV images, acquired at 120 kV, were reconstructed using body hybrid iterative reconstruction. All reconstructions were made at 0.5 mm section thickness. Task transfer functions (TTFs) were determined for a Teflon and LDPE rod. Noise magnitude (SD), and noise power spectrum (NPS) were calculated using 240 and 320 mm diameter water phantoms. Iodine quantification accuracy and contrast-to-noise ratios (CNRs) relative to water for 2, 5, 10, and 15 mg I/ml were determined using a multi-energy CT (MECT) phantom. Low-contrast visibility was determined and the presence of beam-hardening artifacts and inhomogeneities were evaluated. RESULTS: The TTFs of the kV-switching DE VMIs were higher than that of the single-kV images for Teflon (20% TTF: 6.8 lp/cm at 40 keV, 6.2 lp/cm for single-kV), while for LDPE the DE TTFs at 70 keV and above were equivalent or higher than the single-kV TTF. All TTFs of the kV-switching DECT were higher than for the rotate/rotate DECT. The SD was lowest in the 70 keV VMI (12.0 HU), which was lower than that of single-kV

Item does not contain fulltext, BACKGROUND. Because thick-section images (typically 3-5 mm) have low image noise, radiologists typically use them to perform clinical interpretation, although they may additionally refer to thin-section images (typically 0.5-0.625 mm) for problem solving. Deep learning reconstruction (DLR) can yield thin-section images with low noise. OBJECTIVE. The purpose of this study is to compare abdominopelvic CT image quality between thin-section DLR images and thin- and thick-section hybrid iterative reconstruction (HIR) images. METHODS. This retrospective study included 50 patients (31 men and 19 women; median age, 64 years) who underwent abdominopelvic CT between June 15, 2020, and July 29, 2020. Images were reconstructed at 0.5-mm section using DLR and at 0.5-mm and 3.0-mm sections using HIR. Five radiologists independently performed pairwise comparisons (0.5-mm DLR and either 0.5-mm or 3.0-mm HIR) and recorded the preferred image for subjective image quality measures (scale, -2 to 2). The pooled scores of readers were compared with a score of 0 (denoting no preference). Image noise was quantified using the SD of ROIs on regions of homogeneous liver. RESULTS. For comparison of 0.5-mm DLR images and 0.5-mm HIR images, the median pooled score was 2 (indicating a definite preference for DLR) for noise and overall image quality and 1 (denoting a slight preference for DLR) for sharpness and natural appearance. For comparison of 0.5-mm DLR and 3.0-mm HIR, the median pooled score was 1 for the four previously mentioned measures. These assessments were all significantly different (p < .001) from 0. For artifacts, the median pooled score for both comparisons was 0, which was not significant for comparison with 3.0-mm HIR (p = .03) but was significant for comparison with 0.5-mm HIR (p < .001) due to imbalance in scores of 1 (n = 28) and -1 (slight preference for HIR, n = 1). Noise for 0.5-mm DLR was lower by mean differences of 12.8 HU compared with 0.5-mm HIR and 4.4 HU compared w

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Contains fulltext : 229492.pdf (publisher's version ) (Open Access), OBJECTIVE: To compare nodule enhancement on subtraction CT iodine maps to that on dual-energy CT iodine maps using CT datasets acquired simultaneously. METHODS: A previously-acquired set of lung subtraction and dual-energy CT maps consisting of thirty patients with 95solid pulmonary nodules (>/=4mm diameter) was used. Nodules were annotated and segmented on CT angiography, and mean nodule enhancement in the iodine maps calculated. Three radiologists scored nodule visibility with both techniques on a 4-point scale. RESULTS: Mean nodule enhancement was higher (p<0.001) at subtraction CT (34.9+/-12.9 HU) than at dual-energy CT (25.4+/-21.0 HU). Nodule enhancement at subtraction CT was judged more often to be "highly visible" for each observers (p<0.001) with an area under the curve of 0.81. CONCLUSIONS: Subtraction CT is able to depict iodine enhancement in pulmonary nodules better than dual-energy CT.

Contains fulltext : 238627.pdf (Publisher’s version ) (Open Access), OBJECTIVES: To evaluate image quality and reconstruction times of a commercial deep learning reconstruction algorithm (DLR) compared to hybrid-iterative reconstruction (Hybrid-IR) and model-based iterative reconstruction (MBIR) algorithms for cerebral non-contrast CT (NCCT). METHODS: Cerebral NCCT acquisitions of 50 consecutive patients were reconstructed using DLR, Hybrid-IR and MBIR with a clinical CT system. Image quality, in terms of six subjective characteristics (noise, sharpness, grey-white matter differentiation, artefacts, natural appearance and overall image quality), was scored by five observers. As objective metrics of image quality, the noise magnitude and signal-difference-to-noise ratio (SDNR) of the grey and white matter were calculated. Mean values for the image quality characteristics scored by the observers were estimated using a general linear model to account for multiple readers. The estimated means for the reconstruction methods were pairwise compared. Calculated measures were compared using paired t tests. RESULTS: For all image quality characteristics, DLR images were scored significantly higher than MBIR images. Compared to Hybrid-IR, perceived noise and grey-white matter differentiation were better with DLR, while no difference was detected for other image quality characteristics. Noise magnitude was lower for DLR compared to Hybrid-IR and MBIR (5.6, 6.4 and 6.2, respectively) and SDNR higher (2.4, 1.9 and 2.0, respectively). Reconstruction times were 27 s, 44 s and 176 s for Hybrid-IR, DLR and MBIR respectively. CONCLUSIONS: With a slight increase in reconstruction time, DLR results in lower noise and improved tissue differentiation compared to Hybrid-IR. Image quality of MBIR is significantly lower compared to DLR with much longer reconstruction times. KEY POINTS: * Deep learning reconstruction of cerebral non-contrast CT results in lower noise and improved tissue differentiation compared to hybrid-iterative reconstruction. * Deep learni

Contains fulltext : 225891.pdf (publisher's version ) (Open Access), Objectives: In this phantom- and cadaver study we investigated the differences of coronary artery calcium (CAC) volume on ultra-high-resolution computed tomography (U-HRCT) scans and conventional CT. Methods: We scanned a coronary calcium phantom and the coronary arteries of five cadavers using U-HRCT in normal- and super-high resolution (NR, SHR) mode. The NR mode was similar to conventional CT; 896 detector channels, a matrix size of 512, and a slice thickness of 0.5 mm were applied. In SHR mode, we used 1792 detector channels, a matrix size of 1024, and a slice thickness of 0.25 mm. The CAC volume on NR- and SHR images were recorded. Differences in the physical- and the calculated CAC volume were defined as the error value and compared between NR- and SHR images of the phantom. Differences between the CAC volume on NR- and SHR scans of the cadavers were also recorded. Results: The mean error value was lower on SHR- than NR images of the phantom (14.0 %, SD 11.1 vs 20.1 %, SD 15.2, p = 0.01). The mean CAC volume was significantly higher on SHR- than NR images of the cadavers (153.4 mm(3), SD 161.0 vs 144.7 mm(3), SD 164.8, p < 0.01). Conclusions: As small calcifications were more clearly visualized on U-HRCT images in SHR mode than on conventional (NR) CT scans, SHR imaging may facilitate the accurate quantification of the CAC.

Contains fulltext : 220826.pdf (Publisher’s version ) (Open Access), OBJECTIVES: To evaluate the technical performance of an ultra-high-resolution CT (UHRCT) system. METHODS: The physico-technical capabilities of a novel commercial UHRCT system were assessed and compared with those of a current-generation multi-detector (MDCT) system. The super-high-resolution (SHR) mode of the system uses 0.25 mm (at isocentre) detector elements (dels) in the in-plane and longitudinal directions, while the high-resolution (HR) mode bins two dels in the longitudinal direction. The normal-resolution (NR) mode bins dels 2 x 2, resulting in a del-size equivalent to that of the MDCT system. In general, standard procedures and phantoms were used to perform these assessments. RESULTS: The UHRCT MTF (10% MTF 4.1 lp/mm) is twice as high as that of the MDCT (10% MTF 1.9 lp/mm), which is comparable to the MTF in the NR mode (10% MTF 1.7 lp/mm). The width of the slice sensitivity profile in the SHR mode (FWHM 0.45 mm) is about 60% of that of the MDCT (FWHM 0.77 mm). Uniformity and CT numbers are within the expected range. Noise in the high-resolution modes has a higher magnitude and higher frequency components compared with MDCT. Low-contrast visibility is lower for the NR, HR and SHR modes compared with MDCT, but about a 14%, for NR, and 23%, for HR and SHR, dose increase gives the same results. CONCLUSIONS: HR and SHR mode scanning results in double the spatial resolution, with about a 23% increase in dose required to achieve the same low-contrast detectability. KEY POINTS: * Resolution on UHRCT is up to twice as high as for the tested MDCT. * With abdominal settings, UHRCT needs higher dose for the same low-contrast detectability as MDCT, but dose is still below achievable levels as defined by current diagnostic reference levels. * The UHRCT system used in normal-resolution mode yields comparable resolution and noise characteristics as the MDCT system.

Contains fulltext : 203880.pdf (publisher's version ) (Open Access)

Contains fulltext : 201145.pdf (publisher's version ) (Open Access)

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Contains fulltext : 199006.pdf (publisher's version ) (Open Access)

Contains fulltext : 173146.pdf (publisher's version ) (Open Access), Modern Computed Tomography (CT) scanners are capable of acquiring contrast dynamics of the whole brain, adding functional to anatomical information. Soft tissue segmentation is important for subsequent applications such as tissue dependent perfusion analysis and automated detection and quantification of cerebral pathology. In this work a method is presented to automatically segment white matter (WM) and gray matter (GM) in contrast- enhanced 4D CT images of the brain. The method starts with intracranial segmentation via atlas registration, followed by a refinement using a geodesic active contour with dominating advection term steered by image gradient information, from a 3D temporal average image optimally weighted according to the exposures of the individual time points of the 4D CT acquisition. Next, three groups of voxel features are extracted: intensity, contextual, and temporal. These are used to segment WM and GM with a support vector machine. Performance was assessed using cross validation in a leave-one-patient-out manner on 22 patients. Dice coefficients were 0.81 +/- 0.04 and 0.79 +/- 0.05, 95% Hausdorff distances were 3.86 +/- 1.43 and 3.07 +/- 1.72 mm, for WM and GM, respectively. Thus, WM and GM segmentation is feasible in 4D CT with good accuracy.

1 januari 2012, Item does not contain fulltext, Endovascular aortic replacement (EVAR) is an established technique, which uses stent grafts to treat aortic aneurysms in patients at risk of aneurysm rupture. Late stent graft failure is a serious complication in endovascular repair of aortic aneurysms. Better understanding of the motion characteristics of stent grafts will be beneficial for designing future devices. In addition, analysis of stent graft movement in individual patients in vivo can be valuable for predicting stent graft failure in these patients. To be able to gather information on stent graft motion in a quick and robust fashion, we propose an automatic method to segment stent grafts from CT data, consisting of three steps: the detection of seed points, finding the connections between these points to produce a graph, and graph processing to obtain the final geometric model in the form of an undirected graph. Using annotated reference data, the method was optimized and its accuracy was evaluated. The experiments were performed using data containing the AneuRx and Zenith stent grafts. The algorithm is robust for noise and small variations in the used parameter values, does not require much memory according to modern standards, and is fast enough to be used in a clinical setting (65 and 30s for the two stent types, respectively). Further, it is shown that the resulting graphs have a 95% (AneuRx) and 92% (Zenith) correspondence with the annotated data. The geometric model produced by the algorithm allows incorporation of high level information and material properties. This enables us to study the in vivo motions and forces that act on the frame of the stent. We believe that such studies will provide new insights into the behavior of the stent graft in vivo, enables the detection and prediction of stent failure in individual patients, and can help in designing better stent grafts in the future.

Contains fulltext : 80349.pdf (publisher's version ) (Open Access), PURPOSE: To quantify dynamic changes in aortoiliac dimensions using dynamic electrocardiographically (ECG)-gated computed tomographic angiography (CTA) and to investigate any potential impact on preoperative endograft sizing in relation to observer variability. METHODS: Dynamic ECG-gated CTA was performed in 18 patients with abdominal aortic aneurysms. Postprocessing resulted in 11 datasets per patient: 1 static CTA and 10 dynamic CTA series. Vessel diameter, length, and angulation were measured for all phases of the cardiac cycle. The differences between diastolic and systolic aneurysm dimensions were analyzed for significance using paired t tests. To assess intraobserver variability, 20 randomly selected datasets were analyzed twice. Intraobserver repeatability coefficients (RC) were calculated using Bland-Altman analysis. RESULTS: Mean aortic diameter at the proximal neck was 21.4+/-3.0 mm at diastole and 23.2+/-2.9 mm at systole, a mean increase of 1.8+/-0.4 mm (8.5%, p<0.01). The RC for the aortic diameter at the level of the proximal aneurysm neck was 1.9 mm (8.9%). At the distal sealing zones, the mean increase in diameter was 1.7+/-0.3 mm (14.1%, p<0.01) for the right and 1.8+/-0.5 mm (14.2%, p<0.01) for the left common iliac artery (CIA). At both distal sealing zones, the mean increase in CIA diameter exceeded the RC (10.0% for the right CIA and 12.6% for the left CIA). CONCLUSION: The observed changes in aneurysm dimension during the cardiac cycle are small and in the range of intraobserver variability, so dynamic changes in proximal aneurysm neck diameter and aneurysm length likely have little impact on preoperative endograft selection. However, changes in diameter at the distal sealing zones may be relevant to sizing, so distal oversizing of up to 20% should be considered to prevent distal type I endoleak.

Contains fulltext : 80262.pdf (publisher's version ) (Open Access), PURPOSE: To evaluate in-vivo thrombus compressibility in abdominal aortic aneurysms (AAAs) to hopefully shed light on the biomechanical importance of intraluminal thrombus. METHODS: Dynamic electrocardiographically-gated computed tomographic angiography was performed in 17 AAA patients (15 men; mean age 73 years, range 69-76): 11 scheduled for surgical repair and 6 under routine surveillance. The volumes of intraluminal thrombus, the lumen, and the total aneurysm were quantified for each phase of the cardiac cycle. Thrombus compressibility was defined as the percent change in thrombus volume between diastole and peak systole. Continuous data are presented as medians and interquartile ranges (IQR). RESULTS: A substantial interpatient variability was observed in thrombus compressibility, ranging from 0.4% to 43.6% (0.2 to 13.5 mL, respectively). Both thrombus and lumen volumes varied substantially during the cardiac cycle. As lumen volume increased (5.2%, IQR 2.8%-8.8%), thrombus volume decreased (3.0%, IQR 1.0%-4.6%). Total aneurysm volume remained relatively constant (1.3%, IQR 0.4-1.9%). Changes in lumen volume were inversely correlated with changes in thrombus volume (r = -0.73; p = 0.001). CONCLUSION: In-vivo thrombus compressibility varied from patient to patient, and this variation was irrespective of aneurysm size, pulse pressure, and thrombus volume. This suggests that thrombus might act as a biomechanical buffer in some, while it has virtually no effect in others. Whether differences in thrombus compressibility alter the risk of rupture will be the focus of future research.

Contains fulltext : 69921.pdf (publisher's version ) (Closed access), PURPOSE: To evaluate the effect of arm position on image quality and effective radiation dose in an automatic exposure-controlled (AEC) multidetector thoracoabdominal computed tomography (CT) protocol in trauma patients. MATERIALS AND METHODS: This retrospective study of the data of 177 trauma patients (117 male; median age, 39 years) was approved by the institutional ethics board, with informed patient consent waived. Patients underwent scanning by using an AEC 16-detector thoracoabdominal CT protocol in which both arms were raised above the shoulder region (standard-position group, 132 patients), one arm was raised and the other was down (one-arm group, 27 patients), or both arms were down (two-arm group, 18 patients). Objective and subjective image quality was assessed. Individual effective radiation dose was calculated from the effective tube current-time product per exposed section. For this purpose, section location-dependent conversion factors were derived by using a CT dosimetry calculator. The effect of arm position on effective dose was quantified by using linear regression analysis with correction for patient volume and attenuation. RESULTS: Compared with the image quality in the standard-position group, the image quality in the one- and two-arm groups was decreased but within acceptable diagnostic limits. The median corrected effective dose in the standard-position group was 18.6 mSv; the dose in the one-arm group was 18% (95% confidence interval: 11%, 25%) higher than this, and that in the two-arm group was 45% (95% confidence interval: 34%, 57%) higher. CONCLUSION: Omitting arm raising results in lower but acceptable image quality and a substantially higher effective radiation dose. Hence, effort should be made to position the arms above the shoulder when scanning trauma patients. Clinical trial registration no. NCT00228111.