Obesity-Related Pitfalls of Virtual versus True Non-Contrast Imaging-An Intraindividual Comparison in 253 Oncologic Patients

OBJECTIVES

Dual-source dual-energy CT (DECT) facilitates reconstruction of virtual non-contrast images from contrast-enhanced scans within a limited field of view. This study evaluates the replacement of true non-contrast acquisition with virtual non-contrast reconstructions and investigates the limitations of dual-source DECT in obese patients.

MATERIALS AND METHODS

A total of 253 oncologic patients (153 women; age 64.5 ± 16.2 years; BMI 26.6 ± 5.1 kg/m²) received both multi-phase single-energy CT (SECT) and DECT in sequential staging examinations with a third-generation dual-source scanner. Patients were allocated to one of three BMI clusters: non-obese: <25 kg/m² (n = 110), pre-obese: 25-29.9 kg/m² (n = 73), and obese: >30 kg/m² (n = 70). Radiation dose and image quality were compared for each scan. DECT examinations were evaluated regarding liver coverage within the dual-energy field of view.

RESULTS

While arterial contrast phases in DECT were associated with a higher CTDI_vol than in SECT (11.1 vs. 8.1 mGy; p < 0.001), replacement of true with virtual non-contrast imaging resulted in a considerably lower overall dose-length product (312.6 vs. 475.3 mGy·cm; p < 0.001). The proportion of DLP variance predictable from patient BMI was substantial in DECT (R² = 0.738) and SECT (R² = 0.620); however, DLP of SECT showed a stronger increase in obese patients (p < 0.001). Incomplete coverage of the liver within the dual-energy field of view was most common in the obese subgroup (17.1%) compared with non-obese (0%) and pre-obese patients (4.1%).

CONCLUSION

DECT facilitates a 30.8% dose reduction over SECT in abdominal oncologic staging examinations. Employing dual-source scanner architecture, the risk for incomplete liver coverage increases in obese patients.

Virtual Non-Contrast versus True Non-Contrast Computed Tomography: Initial Experiences with a Photon Counting Scanner Approved for Clinical Use

The present study evaluates the diagnostic reliability of virtual non-contrast (VNC) images acquired with the first photon counting CT scanner that is approved for clinical use by comparing quantitative image properties of VNC and true non-contrast (TNC) images. Seventy-two patients were retrospectively enrolled in this study. VNC images reconstructed from the arterial (VNCa) and the portalvenous (VNCv) phase were compared to TNC images. In addition, consistency between VNCa and VNCv images was evaluated. Regions of interest (ROI) were drawn in the following areas: liver, spleen, kidney, aorta, muscle, fat and bone. Comparison of VNCa and VNCv images revealed a mean offset of less than 4 HU in all tissues. The greatest difference between TNC and VNC images was found in spongious bone (VNCv 86.13 HU ± 28.44, p < 0.001). Excluding measurements in spongious bone, differences between TNC and VNCv of 10 HU or less were found in 40% (VNCa 36%) and differences of 15 HU or less were found in 72% (VNCa 68%) of all measurements. The underlying algorithm for the subtraction of iodine works in principle but requires adjustments. Until then, special caution should be exercised when using VNC images in routine clinical practice.

Prediction of anemia on enhanced computed tomography of the thorax using virtual non-contrast reconstructions

To determine if anemia can be predicted on enhanced computed tomography (CT) examinations of the thorax using virtual non-contrast (VNC) images, in order to support clinicians especially in diagnosing primary asymptomatic patients in daily routine.In this monocentric study, 100 consecutive patients (50 with proven anemia), who underwent a contrast-enhanced CT examination of the thorax due to various indications were included. Attenuation was measured in the descending thoracic aorta, the intraventricular septum, and the left ventricle cavity both in the conventional contrast-enhanced and in the VNC images.Two experienced radiologists annotated the delineation of a dense interventricular septum or a hyperattenuating aortic wall sign for all patients.Hemoglobin levels were then correlated with the measured attenuation values, as well as the visualization of the aortic wall or interventricular septum.Good correlation was shown between hemoglobin levels and CT attenuation values of the left ventricular cavity (r = .59), aorta (r = .56), and ratio between left ventricular cavity and the intraventricular septum (r = .57). Receiver operating characteristic curve revealed ≤ 36.5 hounsfield units (left ventricular cavity) as the threshold for diagnosing anemia. Predicting anemia by visualization of a hyperattenuating aortic wall or a dense interventricular septum yielded a specificity of 98% and 92%, respectively.Predicting anemia on enhanced CT examinations using VNC is feasible. A threshold value of ≤ 36.5 hounsfield units (left ventricular cavity) best defines anemia. Aortic wall or interventricular septum visualization on VNC is a specific anemia indicator.

Virtual non-contrast for evaluation of liver parenchyma and vessels: results from 25 patients using multi-phase spectral-detector CT

BACKGROUND

In abdominal imaging, contrast-enhanced computed tomography (CT) examinations are most commonly applied; however, unenhanced examinations are still needed for several clinical questions but require additional scanning and radiation exposure.

PURPOSE

To evaluate accuracy of virtual non-contrast (VNC) from arterial and venous phase spectral-detector CT (SDCT) scans compared to true-unenhanced (TNC) images for the evaluation of liver parenchyma and vessels.

MATERIAL AND METHODS

A total of 25 patients undergoing triphasic SDCT examinations were included. VNC was reconstructed from arterial and venous phases and compared to TNC images. Quantitative image analysis was performed by region of interest (ROI)-based assessment of mean and SD of attenuation (HU) in each liver segment, spleen, portal vein, common hepatic artery, and abdominal aorta. Subjectively, iodine subtraction and diagnostic assessment were rated on 5-point Likert scales.

RESULTS

Attenuation and image noise measured in the liver from VNC were not significantly different from TNC (TNC: 54.6 ± 10.8 HU, VNC arterial phase: 55.7 ± 10.8 HU; VNC venous phase: 58.3 ± 10.0 HU; P > 0.05). VNC also showed accurate results regarding attenuation and image noise for spleen, portal vein, and abdominal aorta. Only iodine subtraction in the common hepatic artery in the arterial phase was insufficient which was confirmed by the subjective reading. Apart from that, subjective reading showed accurate iodine subtraction and comparable diagnostic assessment.

CONCLUSION

VNC from the arterial and venous phases were very similar to TNC yielding mostly negligible differences in attenuation, image noise, and diagnostic utility. Inadequate iodine subtraction occurred in hepatic arteries in the arterial phase.

Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning

Computed tomographic (CT) is a fundamental imaging modality to generate cross-sectional views of internal anatomy in a living subject or interrogate material composition of an object, and it has been routinely used in clinical applications and nondestructive testing. In a standard CT image, pixels having the same Hounsfield Units (HU) can correspond to different materials, and it is therefore challenging to differentiate and quantify materials. Dual-energy CT (DECT) is desirable to differentiate multiple materials, but the costly DECT scanners are not widely available as single-energy CT (SECT) scanners. Recent advancement in deep learning provides an enabling tool to map images between different modalities with incorporated prior knowledge. Here we develop a deep learning approach to perform DECT imaging by using the standard SECT data. The end point of the approach is a model capable of providing the high-energy CT image for a given input low-energy CT image. The feasibility of the deep learning-based DECT imaging method using a SECT data is demonstrated using contrast-enhanced DECT images and evaluated using clinical relevant indexes. This work opens new opportunities for numerous DECT clinical applications with a standard SECT data and may enable significantly simplified hardware design, scanning dose and image cost reduction for future DECT systems.

Reliability of virtual non-contrast computed tomography angiography: comparing it with the real deal

Background

Computed tomographic angiography (CTA) may require a non-contrast enhanced dataset for the diagnostic workup. By using dual-energy acquisition, it is possible to obtain a virtual non-contrast-enhanced (VNC) dataset, thereby possibly eliminating the non-contrast acquisition and reducing the radiation dose.

Purpose

To compare image quality of VNC images reconstructed from arterial phase dual-energy CTA to true non-contrast (TNC) images, and to assess whether VNC images were of sufficient quality to replace TNC images.

Material and methods

Thirty consecutive patients with suspected abdominal aortic aneurysm, aortic dissection, or subacute control after EVAR/TEVAR were examined with dual-energy CT (DECT). The examination protocol included a single-energy TNC, DECT arterial phase (80 kV/Sn140 kV), and single-energy in venous phase of the aorta. A VNC dataset was obtained from the DE acquisition from arterial phase scans. Mean attenuation and image noise were measured within regions of interest at three levels in the aorta in TNC and VNC images. Comparison of the TNC and VNC images for artefacts was made side-by-side. Subjective evaluation included overall image quality on a 4-grade scale, and quantitative analysis of algorithm-induced artefacts by two experienced readers.

Results

For all cases, the aortic attenuation was significantly higher at VNC than at TNC. Image noise measured quantitatively was also significantly higher at VNC than at TNC. Subjective image quality was lower for VNC (mean = 3.1 for VNC, 3.7 = for TNC) but there were no cases rated non-diagnostic.

Conclusion

VNC images based on arterial phase CTA have significantly higher mean attenuation and higher noise levels compared to TNC.