Low kV Computed Tomography of Parenchymal Abdominal Organs-A Systematic Animal Study of Different Contrast Media Injection Protocols

Influence of Contrast Media Temperature and Concentration on Patient Comfort and Safety in Computed Tomography: CATCHY II Trial

BACKGROUND

Previous research on the necessity to reduce the viscosity of contrast media (CM) by either prewarming CM before injection during computed tomography (CT) or by using less concentrated CM has yielded conflicting results. In addition, there is limited evidence on patient comfort.

OBJECTIVES

The aim of the study was to examine if prewarming CM, with varying CM concentrations, is superior to CM at room temperature, with respect to patient comfort and safety in CT.

MATERIALS AND METHODS

All elective patients scheduled for contrast-enhanced CT scans at Maastricht University Medical Center+ between October 27, 2021 and October 31, 2022 were eligible for inclusion when a questionnaire evaluating patient comfort was completed. This 1-year period was divided into 4 intervals (4 groups): group 1 (370 mg I/mL, 37°C), group 2 (370 mg I/mL, room temperature), group 3 (300 mg I/mL, 37°C), and group 4 (300 mg I/mL, room temperature). All CT scans were performed using state of the art equipment (Siemens Healthineers; SOMATOM Force and SOMATOM Definition AS, Forchheim, Germany). Contrast media injections were performed using a dual-head power injector (Stellant; Bayer Healthcare, Berlin, Germany) and individualized to body weight and/or tube voltage, depending on the CM protocols. After the CT scan, patients completed a questionnaire covering the primary outcomes comfort, pain, and adverse events such as feelings of heat, nausea, vomiting, itchiness, urticaria, difficulty breathing, dizziness, goosebumps, or an odd taste. Technicians were asked to report any adverse events, including extravasation and allergic-like reactions. The secondary outcome involved attenuation (in Hounsfield unit, HU), which was evaluated by assessing the HU of the coronary arteries for vascular CT, and liver enhancement in portal venous CT. The Kruskal-Wallis test was used for continuous scale outcomes and χ 2 tests for examining adverse events.

RESULTS

Results showed no significant differences examining comfort score ( P = 0.054), pain sensation ( P = 0.469), extravasation ( P = 0.542), or allergic-like reaction ( P = 0.253). Significant differences among the 4 groups were found with respect to heat sensation and dizziness ( P = 0.005 and P = 0.047, respectively), showing small effect sizes. All other adverse effects showed no significant results. No significant differences were observed in coronary attenuation among the 4 groups in coronary CT angiography ( P = 0.113). When analyzing attenuation in portal venous CT scans, significant differences were found among the 4 groups ( P = 0.008).

CONCLUSIONS

Administrating prewarmed CM is nonsuperior compared with CM at room temperature in relation to patient comfort and safety, regardless of CM concentration. These findings suggest that prewarming CM before usage is unnecessary, which will improve the efficiency of daily clinical workflow and brings environmentally friendly benefits.

Impact of CT Photon-Counting Virtual Monoenergetic Imaging on Visualization of Abdominal Arterial Vessels

PURPOSE

The novel photon-counting detector (PCD) technique acquires spectral data for virtual monoenergetic imaging (VMI) in every examination. The aim of this study was the evaluation of the impact of VMI of abdominal arterial vessels on quantitative and qualitative subjective image parameters.

METHODS

A total of 20 patients that underwent an arterial phase computed tomography (CT) scan of the abdomen with a novel PCD CT (Siemens NAEOTOM alpha) were analyzed regarding attenuation at different energy levels in virtual monoenergetic imaging. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated and compared between the different virtual monoenergetic (VME) levels with correlation to vessel diameter. In addition, subjective image parameters (overall subjective image quality, subjective image noise and vessel contrast) were evaluated.

RESULTS

Our research showed decreasing attenuation levels with increasing energy levels in virtual monoenergetic imaging regardless of vessel diameter. CNR showed best overall results at 60 keV, and SNR at 70 keV with no significant difference to 60 keV (p = 0.294). Subjective image quality was rated best at 70 keV for overall image quality, vessel contrast and noise.

CONCLUSIONS

Our data suggest that VMI at 60-70 keV provides the best objective and subjective image quality concerning vessel contrast irrespective of vessel size.

Contrast Media Reduction in Computed Tomography With Deep Learning Using a Generative Adversarial Network in an Experimental Animal Study

OBJECTIVE

This feasibility study aimed to use optimized virtual contrast enhancement through generative adversarial networks (GAN) to reduce the dose of iodine-based contrast medium (CM) during abdominal computed tomography (CT) in a large animal model.

METHODS

Multiphasic abdominal low-kilovolt CTs (90 kV) with low (low CM, 105 mgl/kg) and normal contrast media doses (normal CM, 350 mgl/kg) were performed with 20 healthy Göttingen minipigs on 3 separate occasions for a total of 120 examinations. These included an early arterial, late arterial, portal venous, and venous contrast phase. One animal had to be excluded because of incomplete examinations. Three of the 19 animals were randomly selected and withheld for validation (18 studies). Subsequently, the GAN was trained for image-to-image conversion from low CM to normal CM (virtual CM) with the remaining 16 animals (96 examinations). For validation, region of interest measurements were performed in the abdominal aorta, inferior vena cava, portal vein, liver parenchyma, and autochthonous back muscles, and the contrast-to-noise ratio (CNR) was calculated. In addition, the normal CM and virtual CM data were presented in a visual Turing test to 3 radiology consultants. On the one hand, they had to decide which images were derived from the normal CM examination. On the other hand, they had to evaluate whether both images are pathological consistent.

RESULTS

Average vascular CNR (low CM 6.9 ± 7.0 vs virtual CM 28.7 ± 23.8, P < 0.0001) and parenchymal (low CM 1.5 ± 0.7 vs virtual CM 3.8 ± 2.0, P < 0.0001) CNR increased significantly by GAN-based contrast enhancement in all contrast phases and was not significantly different from normal CM examinations (vascular: virtual CM 28.7 ± 23.8 vs normal CM 34.2 ± 28.8; parenchymal: virtual CM 3.8 ± 2.0 vs normal CM 3.7 ± 2.6). During the visual Turing testing, the radiology consultants reported that images from normal CM and virtual CM were pathologically consistent in median in 96.5% of the examinations. Furthermore, it was possible for the examiners to identify the normal CM data as such in median in 91% of the cases.

CONCLUSIONS

In this feasibility study, it could be demonstrated in an experimental setting with healthy Göttingen minipigs that the amount of CM for abdominal CT can be reduced by approximately 70% by GAN-based contrast enhancement with satisfactory image quality.