Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death. Recent studies have underlined the importance of non-contrast-enhanced chest CT scans not only for emphysema progression quantification, but for correlation with clinical outcomes as well. As about 40 percent of the 300 million CT scans per year are contrast-enhanced, no proper emphysema quantification is available in a one-stop-shop approach for patients with known or newly diagnosed COPD. Since the introduction of spectral imaging (e.g., dual-energy CT scanners), it has been possible to create virtual non-contrast-enhanced images (VNC) from contrast-enhanced images, making it theoretically possible to offer proper COPD imaging despite contrast enhancing. This study is aimed towards investigating whether these VNC images are comparable to true non-contrast-enhanced images (TNC), thereby reducing the radiation exposure of patients and usage of resources in hospitals. In total, 100 COPD patients with two scans, one with (VNC) and one without contrast media (TNC), within 8 weeks or less obtained by a spectral CT using dual-layer technology, were included in this retrospective study. TNC and VNC were compared according to their voxel-density histograms. While the comparison showed significant differences in the low attenuated volumes (LAVs) of TNC and VNC regarding the emphysema threshold of -950 Houndsfield Units (HU), the 15th and 10th percentiles of the LAVs used as a proxy for pre-emphysema were comparable. Upon further investigation, the threshold-based LAVs (-950 HU) of TNC and VNC were comparable in patients with a water equivalent diameter (DW) below 270 mm. The study concludes that VNC imaging may be a viable option for assessing emphysema progression in COPD patients, particularly those with a normal body mass index (BMI). Further, pre-emphysema was generally comparable between TNC and VNC. This approach could potentially reduce radiation exposure and hospital resources by making additional TNC scans obsolete.

To evaluate the image quality and diagnostic performance for pancreatic lesion between true non-contrast (TNC) and virtual non-contrast (VNC) images obtained from the dual-energy computed tomography (DECT).
One hundred six patients with pancreatic mass underwent contrast-enhanced DECT examinations were retrospectively included in this study. VNC images of the abdomen were generated from late arterial (aVNC) and portal (pVNC) phases. For quantitative analysis, the attenuation differences and reproducibility of abdominal organs were compared between TNC and aVNC/pVNC measurements. Qualitatively image quality was assessed by two radiologists using a five-point scale, and they independently compared the detection accuracy of pancreatic lesions between TNC and aVNC/pVNC images. The volume CT dose index (CTDIvol) and size-specific dose estimates (SSDE) were recorded to evaluate the potential dose reduction when using VNC reconstruction to replace the unenhanced phase.
A total of 78.38% (765/976) of the attenuation measurement pairs were reproducible between TNC and aVNC images, and 71.0% (693/976) between TNC and pVNC images. In triphasic examinations, a total of 108 pancreatic lesions were found in 106 patients, and no significant difference in detection accuracy was found between TNC and VNC images (p = 0.587-0.957). Qualitatively, image quality was rated diagnostic (score ≥ 3) in all the VNC images. Calculated CTDIvol and SSDE reduction of about 34% could be achieved by omitting the non-contrast phase.
VNC images of DECT provide diagnostic image quality and accurate pancreatic lesions detection, which are a promising alternative to unenhanced phase with a substantial reduction of radiation exposure in clinical routine.

BACKGROUND: Prior studies focused on utilization of dual-energy computed tomography (DECT) to better detect intracranial pathology and to reduce artifacts. It is still unclear whether virtual non-contrast (VNC) images of DECT can replace true non-contrast (TNC) images.
OBJECTIVE: To compare attenuation values and image quality of VNC images to TNC images of the brain, obtained using spectral detector CT (SDCT).
METHODS: We retrospectively evaluated patients that underwent head CT with and without contrast material, on a SDCT scanner at our institution (n = 33). The attenuation values of different brain structures were obtained from TNC images, the conventional images of the post-contrast exams (n = 16) or the CT angiography (CTA) (n = 17), and the derived VNC images. In total, 591 regions of interest were obtained, including white and gray matter. Two neuroradiologists independently evaluated the image quality of the VNC and TNC images, using a 5-point Likert scale.
RESULTS: The mean difference between the attenuation values on the VNC versus the TNC images was <4 HU for almost all the structures. The difference reached statistical significance (P < 0.05) for the deep gray structures but not for the white matter. The image quality score of the TNC images was 5 in all the patients (excellent gray-white matter differentiation). The scores of the VNC images differed between post-contrast and CTA examinations, with means of 4.9 ± 0.3 (excellent) and 3.2 ± 0.4 (fair), respectively (P < 0.001).
CONCLUSIONS: Our results show minor differences between attenuation values of different brain structures on VNC versus TNC images of SDCT.

OBJECTIVE: To assess the feasibility of using virtual non-contrast (VNC) images derived from dual-energy computed tomography (DECT) to replace true non-contrast (TNC) images of papillary thyroid carcinoma (PTC) patients.
METHODS: Images of 96 PTC patients were retrospectively analyzed. TNC images were acquired under the single-energy mode of DECT after the plain scanning. The arterial and venous phase VNC (VNC-a and VNC-v) images were generated by the post-processing algorithm from the arterial phase and venous phase of contrast-enhanced CT images, respectively. Mean attenuation values, image noise, number and length of calcification were measured. Radiation dose was also calculated. Last, subjective score of image quality was evaluated by a 5-point scale.
RESULTS: Signal-to-noise ratio (SNR) of each tissue in TNC images is significantly higher than that of VNC images (p<0.050). Contrast-to-noise ratio (CNR) of fat, muscle, thyroid nodules and internal carotid artery in TNC images is significantly higher than that of VNC images, while CNR in TNC images is lower for cervical vertebra (p<0.001). Calcification is detected on TNC images of 44 patients, while it is omitted on VNC images of 14 patients (31.8%). The subjective score of TNC images is higher than VNC images (p<0.001). The effective dose reduction is 47.6% by avoiding plain scanning.
CONCLUSIONS: Considering the different attenuation value, SNR, CNR and especially reduced detection rate of calcification, we deem that VNC images cannot be directly used to replace TNC images in PTC patients, despite the reduced radiation dose.

To evaluate vessel assessment in virtual monoenergetic images (VMI40keV) and virtual-non-contrast images (VNC) derived from venous phase spectral detector computed tomography (SDCT) acquisitions in comparison to arterial phase and true non-contrast (TNC) images.
Triphasic abdominal SDCT was performed in 25 patients including TNC, arterial and venous phase. VMI40keV and VNC were reconstructed from the venous phase and compared to conventional arterial-phase images (CIart), TNC and conventional venous-phase images (CIven). Vessel contrast and virtual contrast removal were analyzed with region-of-interest-based measurements and in a qualitative assessment.
Quantitative analysis revealed no significant attenuation differences between TNC and VNC in arterial vessels (p-range 0.07-0.47) except for the renal artery (p = 0.011). For venous vessels, significant differences between TNC and VNC were found for all veins (p < 0.001) except the inferior vena cava (p = 0.26), yet these differences remained within a 10 HU range in most patients. No significant attenuation differences were found between CIart/VMI40keV in arterial vessels (p-range 0.06-0.86). Contrast-to-noise ratio provided by VMI40keV and CIart was equivalent for all arterial vessels assessed (p-range 0.14-0.91). Qualitatively, VMI40keV showed similar enhancement of abdominal and pelvic arteries as CIart and VNC were rated comparable to TNC.
Our study suggests that VNC and VMI40keV derived from single venous-phase SDCT offer comparable assessment of major abdominal vessels as provided by routine triphasic examinations, if no dynamic contrast information is required.

OBJECTIVE: To investigate the association of vertebral CT attenuation between virtual non-contrast (VNC) and true non-contrast (TNC) images and to evaluate if VNC vertebral CT attenuation could be used for phantom-less osteoporosis detection in dual-layer spectral-detector CT (SDCT).
METHODS: 200 patients with non-contrast and portal-venous phase SDCT were retrospectively assigned to a test and a validation group of 100 patients each. CT attenuation of L1 vertebrae were measured on VNC and TNC. The test group was used to determine the difference between VNC and TNC CT attenuation and to calculate a statistical model for TNC CT attenuation prediction. The validation group was used to assess the capability of the model to predict TNC from VNC CT attenuation and its accuracy to identify osteoporosis. Osteoporosis was defined as a TNC CT attenuation of ≤110HU.
RESULTS: In both groups, CT attenuation was lower in VNC than in TNC (P < 0.001). VNC and TNC CT attenuation was correlated strongly (r = 0.958). Using the regression equation established in the test group (TNC = 23.677 + 1.540 × VNC), the predicted TNC CT attenuation did not differ from the real TNC CT attenuation in the validation group (P = 0.359). A VNC CT attenuation cut-off of 52HU yielded an AUC of 0.978 for osteoporosis detection.
CONCLUSIONS: L1 CT attenuation is systematically underestimated in VNC compared with TNC images. However, TNC L1 CT attenuation can be predicted reliably from VNC. VNC may perform well in phantom-less osteoporosis detection.

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This article reviews the physical principles of dual-energy material decomposition and its current implementation. Clinical applications of dual-energy material decomposition including differentiation of calcification from hemorrhage and iodinated contrast from hemorrhage are highlighted, and their applications to neuroimaging are reviewed.

OBJECTIVE: To evaluate the potential of gadolinium (Gd) as contrast material (CM) in second generation dual energy computed tomography (DECT).
METHODS: In a phantom model, DECT post-processing was used to increase Gd attenuation using advanced monoenergetic extrapolation (MEI), to create virtual non-contrast images (Gd-VNC) and Gd maps and to quantify Gd content. Dilutions of Gd and iodinated CM (7-296 HU) were filled in syringes, placed in an attenuation phantom and scanned with standard DECT protocols (80 &100/Sn140 kV). MEI (40-190 keV) and VNC images as well as Gd maps were computed. The amount of Gd was quantified and the accuracy was compared to iodine images. Linear regression models were calculated to evaluate Gd attenuation of equivolume CM doses and clinical MRI doses.
RESULTS: Applying monoenergetic reconstructions and using Gd as contrast agent (Gd MEI 40 keV) doubled Hounsfield-Units (HU) and 90% of the SNR (averaged: 225 HU, SNR3.1) are achievable, as compared to iodinated CM at 120 kV (averaged:110 HU, SNR3.5), at Gd doses of 1.0mmol/kg BW. The accuracies of Gd-VNC (deviation, 6±12 HU) images and Gd quantification (measurement error, 17%) were not significantly different to those of iodine enhanced images (VNC:deviation, 2±11 HU; measurement error,14%).
CONCLUSIONS: Using monoenergetic extrapolation at 40keV, it is possible to increase Gd-CM attenuation significantly. Thus, equivalent HU and half the SNR in comparison to a standard dose of ICM at 120kV can be expected at a Gd-CM dose of 0.5mmol/kg BW. Post-processing features of iodine based DECT like monoenergetic or VNC images, iodine maps or quantification of CM are feasible with the use of Gd-CM.