Objectives: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. Methods: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. Results: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. Conclusion: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. Advances in knowledge: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information. The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.

Objectives. The detection of Coronavirus Disease 2019 (COVID-19) by reverse transcription polymerase chain reaction (RT-PCR) has varying sensitivity. Computed tomography (CT) of the chest can verify infection in patients with clinical symptoms and a negative test result, accelerating treatment and actions to prevent further contagion. However, CT employs ionising radiation. The purpose of this study was to evaluate protocol settings, associated radiation exposure, image quality and diagnostic performance of a low-dose CT protocol in a university hospital setting. Materials and Methods. Chest CT examinations were performed on a single scanner (Somatom Definition Edge, Siemens Healthineers, Germany) in 105 symptomatic patients (60 male, 45 female). Images were evaluated with regard to protocol parameters, image quality, radiation exposure and diagnostic accuracy. Serial RT-PCR served as the standard of reference. Based on this reference standard sensitivity, specificity, positive and negative predictive values of CT with 95% confidence interval were calculated. Results. The mean effective dose was 1.3 ± 0.4 mSv (0.7–2.9 mSv) for the patient cohort (mean age 66.6 ± 16.7 years (19–94 years), mean body mass index (BMI) 26.6 ± 5.3 kg m⁻² (16–46 kg/m²)). A sensitivity of 100 [95% CI: 82–100]%, a specificity of 78 [95% CI: 68–86]%, a positive predictive value of 50 [95% CI: 33–67]% and a negative predictive value of 100 [95% CI: 95–100]% were obtained. No COVID-19 diagnoses were missed by CT. Image noise did not strongly correlate with BMI or patient diameter and was rated as average. Conclusions. We presented a robust imaging procedure with a chest CT protocol for confident diagnosis of COVID-19. Even for an overweight patient cohort, an associated radiation exposure of only 1.3 ± 0.4 mSv was achieved with sufficient diagnostic quality to exclude COVID-19.

The purpose of this study was to prospectively analyse image quality and radiation dose of body mass index (BMI)-adapted low-radiation and low-iodine dose CTA of the thoracoabdominal aorta in obese and non-obese patients. This prospective, single-centre study included patients scheduled for aortic CTA between November 2017 and August 2020 without symptoms of high-grade heart failure. A BMI-adapted protocol was used: Group A/Group B, BMI < 30/≥ 30 kg/m², tube potential 80/100 kVp, total iodine dose 14.5/17.4 g. Intraindividual comparison with the institutional clinical routine aortic CTA protocol was performed. The final study cohort comprised 161 patients (mean 71.1 ± 9.4 years, 32 women), thereof 126 patients in Group A (mean BMI 25.4 ± 2.8 kg/m²) and 35 patients in Group B (34.0 ± 3.4 kg/m²). Mean attenuation over five aortoiliac measurement positions for Group A/B was 354.9 ± 78.2/262.1 ± 73.0 HU. Mean effective dose for Group A/B was 3.05 ± 0.46/6.02 ± 1.14 mSv. Intraindividual comparison in 50 patients demonstrated effective dose savings for Group A/B of 34.4 ± 14.5/25.4 ± 14.1% (both p < 0.001), and iodine dose savings for Group A/B of 54/44.8%. Regression analysis showed that female sex and increasing age were independently associated with higher vascular attenuation. In conclusion, BMI-adapted, low-radiation and low-iodine dose CTA of the thoracoabdominal aorta delivers diagnostic image quality in non-obese and obese patients without symptoms of high-grade heart failure, with superior image quality in females and the elderly.

To implement typical doses (TD) and typical values (TV) for fluoroscopic diagnostic and interventional procedures. A total of 3811 fluoroscopic procedures performed within 34 months on three devices were included in this retrospective study. Dose-, patient- and procedure-related information were extracted using the institutional dose management system (DMS). TD/TV were defined as median dose and calculated for the five most frequent procedures per device for dose area product (DAP), cumulative air kerma (CAK) and fluoroscopy time (FT). National diagnostic reference levels and other single facility studies were compared to our results. Additionally, the five procedures with the highest doses of each device were analysed. To evaluate the data coverage of the DMS compared to the picture archiving and communication system (PACS), procedure lists were extracted from the PACS and compared to the procedure information extracted from the DMS. TD/TV for 15 procedures were implemented. Among all devices, TD for DAP ranged between 0.6 Gycm² for port catheter control (n = 64) and 145.9 Gycm² for transarterial chemoembolisation (n = 84). TD for CAK ranged between 5 mGy for port catheter control and 1397 mGy for aneurysm treatment (n = 129) and TV for FT ranged between 0.3 min for upper cavography (n = 67) and 51.4 min for aneurysm treatment. TD for DAP and CAK were lower or within the range of other single facility studies. The five procedures with the highest median DAP per device were identified, 6 of 15 procedures were also found to be among the most frequent procedures. Data coverage of the DMS compared to the PACS ranged between 71% (device 2, stroke treatment) and 78% (device 1, lower limb angiography) for the most common procedure per device. Thus, in 22%–29% of cases dose data of the performed procedure was not transferred into the DMS. We implemented TD/TV for fluoroscopic diagnostic and interventional procedures which enable a comprehensive dose analysis and comparison with previously published values.

Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenuation, and objective image quality of reno-ureteric stones denoised using DL-software in comparison to traditionally reconstructed low-dose abdominal CT-images and evaluated its clinical impact. In this institutional review-board-approved retrospective study, 45 patients with renal and/or ureteral stones were included. All patients had undergone abdominal CT between August 2019 and October 2019. CT-images were reconstructed using the following three methods: filtered back-projection, iterative reconstruction, and PixelShine (DL-software) with both sharp and soft kernels. Stone size, CT attenuation, and objective image quality (signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) were evaluated and compared using Bonferroni-corrected Friedman tests. Objective image quality was measured in six regions-of-interest. Stone size ranged between 4.4 × 3.1–4.4 × 3.2 mm (sharp kernel) and 5.1 × 3.8–5.6 × 4.2 mm (soft kernel). Mean attenuation ranged between 704–717 Hounsfield Units (HU) (soft kernel) and 915–1047 HU (sharp kernel). Differences in measured stone sizes were ≤1.3 mm. DL-processed images resulted in significantly higher CNR and SNR values (p < 0.001) by decreasing image noise significantly (p < 0.001). DL-software significantly improved objective image quality while maintaining both correct stone size and CT-attenuation values. Therefore, the clinical impact of stone assessment in denoised image data sets remains unchanged. Through the relevant noise suppression, the software additionally offers the potential to further reduce radiation exposure.

Objectives: Evaluation of performance and forensic relevance of a novel, photorealistic, 3D reconstruction method (cinematic rendering, (CR)) in comparison with conventional post-mortem CT (PMCT) and volume rendering (VR) technique for visualization of traumatic injuries. Methods: 112 pathologies (fractures, soft tissue injuries and foreign bodies) from 33 human cadavers undergoing whole body PMCT after traumatic death were retrospectively analyzed. Pathologies were reconstructed with CR and VR techniques. Fractures were classified according to their dislocation. Images were evaluated according to their expressiveness and judicial relevance by two forensic pathologists using a five-level Likert-scale (1: high expressiveness, 5: low expressiveness). They decided whether CR reconstructions were suitable for judicial reviews. The detection rate of pathologies was determined by two radiologists. Results: CR was more expressive than VR for all three trauma categories (p < 0.01) and than conventional CT when used for fractures with dislocation (p < 0.001), injuries of the ventral body surface (p < 0.001), and demonstration of foreign bodies (p = 0.033). CR and VR became more expressive with a higher grade of fracture dislocation (p < 0.001). 20% of all pathologies in the CR and VR reconstructions were not detectable by radiologists. Conclusion: CR reconstructions are superior to VR regarding the expressiveness. For fractures with substantial dislocation, soft tissue injuries, and foreign bodies in situ, CR showed a significantly better expressiveness than conventional PMCT. CR and VR have significant limitations in cases of fractures with minor dislocations and covered soft tissue injuries. Advances in knowledge: CR is a helpful tool to present pathologies found in PMCT for judicial reviews.