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.

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.

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.