To compare objective and subjective parameters in image quality and radiation dose of two MDCTs (helical 64 detector CT vs. axial 256 detector CT) in paediatric lung CT. Radiation dose and image quality were compared between non-enhanced lung CT from a helical 64-slice multidetector CT (MDCT 1) and a 256-slice scanner (MDCT 2) with axial wide-cone acquisition and using deep learning image reconstruction. In 23 size-matched paediatric studies (age 2-18 years) from each scanner, the radiation exposure, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), image sharpness and delineation of small airways were assessed. Subjective image quality was rated by 6 paediatric radiologists. While MDCT 2 provided higher SNR and CNR, subjective image quality was not significantly different between studies from both scanners. Radiation exposure was lower in studies from MDCT 2 (CTDIvol 0.26 ± 0.14 mGy, effective dose 0.23 ± 0.11 mSv) than from MDCT 1 (CTDIvol 0.96 ± 0.52 mGy, effective dose 1.13 ± 0.58 mSv), p < 0.001. Despite lower radiation dose for the scout images, the relative scout-scan-ratio increased from 2.64 ± 1.42 % in MDCT 1 to 6.60 ± 5.03 % in MDCT 2 (p = 0.001). By using latest scanner technology effective radiation dose can be reduced to 0.1-0.3 mSv for lung CT in children without compromising image quality. Scout image dose increasingly accounts for substantial portions of the total scan dose and needs to be optimized. In children CT should be performed on state-of-the-art MDCT scanners with size-adapted exposure protocols and iterative reconstruction.

Since its delayed re-emergence after non-pharmaceutical interventions (NPIs) against the COVID-19 pandemic, Mycoplasma pneumoniae has caused community-acquired pneumonia outbreaks worldwide. In this study, we aimed to investigate how the clinical characteristics and severity of M. pneumoniae infections have changed after COVID-19 pandemic restriction, in order to enable adequate interpretation of clinical features and response to future M. pneumoniae epidemics. This retrospective, comparative cohort study compared clinical features and severity of children with M. pneumoniae detection by PCR during the periods April 1, 2015, to March 31, 2020 (pre-NPI); April 1, 2020, to March 31, 2022 (NPI); and April 1, 2022, to March 31, 2025 (post-NPI). Clinical features were compared between periods by Kruskal–Wallis rank sum test or Fisher’s exact test, as appropriate. Moreover, we compared hospitalization and intensive care unit (ICU) admission using generalized linear models. In total, 321 patients were included in the study. Since the first detection of M. pneumoniae after the COVID-19 pandemic in summer 2023, the re-emergence has shown a bimodal curve with two distinct peaks (post-NPI first-year and second-year). The median age of patients was higher in the post-NPI than the pre-NPI period (9.05 vs 8.20 years), particularly during the first-year peak (11.00 years). Obstructive diseases were observed more frequently post-NPI compared to pre-NPI (18.6% vs 9.6%). Moreover, more patients presented with chest pain (8.9% vs 2.4%) and pleural effusions (45.7% vs 28.9%) post-NPI than pre-NPI. Conversely, extrapulmonary manifestations were less frequent post-NPI (18.6% vs 30.1%), particularly dermatological (15.7% vs 25.3%) and neurological (1.3% vs 4.8%) manifestations. Hospitalization rate (38.6% post-NPI vs 43.9% pre-NPI) and length of stay (median, 4 [IQR, 2–5] vs 4 [IQR, 3–6] days) were similar, while generalized linear models showed a trend toward fewer hospitalizations post-NPI (odds ratio [OR], 0.72 [95% CI, 0.42–1.23]; P = 0.22). The same applied to ICU admission rate (5.1% post-NPI vs 4.9% pre-NPI), with a trend toward fewer ICU admissions post-NPI (OR, 0.90 [95% CI, 0.29–3.34]; P = 0.86). Conclusion : We observed notable changes in the clinical presentation of re-emerging M. pneumoniae infections compared to the pre-COVID-19 pandemic period, particularly an increase in obstructive phenotypes and pleural effusions. However, overall disease severity appeared to remain largely unchanged. What is Known: • The delayed re-emergence of M. pneumoniae in late 2023 was substantial in terms of case numbers across many geographical locations. • No statistically increased proportion of severe or worse outcomes of re-emerging M. pneumoniae infections could be observed globally compared with pre-COVID-19 pandemic epidemics. What is New: • Clinical features of M. pneumoniae infections in children partly changed following COVID-19 pandemic restrictions, with new signs like obstructive phenotypes and pleural effusions. • The findings suggest that there has been no overall increase in disease severity; in fact, extrapulmonary manifestations were fewer, with trends toward reduced hospitalizations and ICU admissions.

Background: Radial k-space sampling is widely employed in paediatric magnetic resonance imaging (MRI) to mitigate motion and aliasing artefacts. Artificial intelligence (AI)-based image reconstruction has been developed to enhance image quality and accelerate acquisition time. Objective: To assess image quality of deep learning (DL)-based denoising image reconstruction of body MRI in children. Materials and methods: Children who underwent thoraco-abdominal MRI employing radial k-space filling technique (PROPELLER) with conventional and DL-based image reconstruction between April 2022 and January 2023 were eligible for this retrospective study. Only cases with previous MRI including comparable PROPELLER sequences with conventional image reconstruction were selected. Image quality was compared between DL-reconstructed axial T1-weighted and T2-weighted images and conventionally reconstructed images from the same PROPELLER acquisition. Quantitative image quality was assessed by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the liver and spleen. Qualitative image quality was evaluated by three observers using a 4-point Likert scale and included presence of noise, motion artefact, depiction of peripheral lung vessels and subsegmental bronchi at the lung bases, sharpness of abdominal organ borders, and visibility of liver and spleen vessels. Image quality was compared with the Wilcoxon signed-rank test. Scan time length was compared to prior MRI obtained with conventional image reconstruction. Results: In 21 children (median age 7 years, range 1.5 years to 15.8 years) included, the SNR and CNR of the liver and spleen on T1-weighted and T2-weighted images were significantly higher with DL-reconstruction (P<0.001) than with conventional reconstruction. The DL-reconstructed images showed higher overall image quality, with improved delineation of the peripheral vessels and the subsegmental bronchi in the lung bases, sharper abdominal organ margins and increased visibility of the peripheral vessels in the liver and spleen. Not respiratory-gated DL-reconstructed T1-weighted images demonstrated more pronounced respiratory motion artefacts in comparison to conventional reconstruction (P=0.015), while there was no difference for the respiratory-gated T2-weighted images. The median scan time per slice was reduced from 6.3 s (interquartile range, 4.2 – 7.0 s) to 4.8 s (interquartile range, 4.4 – 4.9 s) for the T1-weighted images and from 5.6 s (interquartile range, 5.4 – 5.9 s) to 4.2 s (interquartile range, 3.9 – 4.8 s) for the T2-weighted images. Conclusion: DL-based denoising image reconstruction of paediatric body MRI sequences employing radial k-space sampling allowed for improved overall image quality at shorter scan times. Respiratory motion artefacts were more pronounced on ungated T1-weighted images. Graphical

To investigate a quantitative method for assessing image quality of low dose lung computed tomography (CT) and find the lowest exposure dose providing diagnostic images. Axial volumetric lung CT acquisitions (256 slice scanner) were performed on three different sized anthropomorphic phantoms at different dose levels. The maximum steepness of sigmoid curves fitted to line density profiles was measured at lung-to-pleura interfaces. For each phantom, image sharpness was calculated as the median of 468 measurements from 39 different locations. Diagnostic image quality for the adult and paediatric phantom was rated by three radiologists using 4-point Likert scales. The image sharpness cut-off for obtaining adequate image quality was determined from qualitative ratings. Adequate diagnostic image quality was reached at a median steepness of 713 HU/mm in the adult phantom with a corresponding CTDIvol of 0.14 mGy and an effective dose of 0.13 mSv at a dose level of 100 kVp and 10 mA. In the paediatric phantom diagnostic image quality was reached at a median steepness of 1139 HU/mm with a corresponding CTDIvol of 0.13 mGy and an effective dose of 0.08 mSv at a dose level of 100 kVp and 10 mA. Determination of image sharpness on line density profiles can be used as quantitative measure for image quality of lung CT. Sufficient-quality lung CT can be achieved at effective radiation doses of 0.13 mSv (adult phantom) and 0.08 mSv (paediatric phantom). These findings suggest that substantial dose reduction is feasible without compromising diagnostic accuracy.

Background: Photon-counting detector computed tomography (PCD-CT) can reduce radiation dose in paediatric lung imaging. Objective: The aim of this study was to determine the lowest radiation dose maintaining adequate image quality for high-pitch lung imaging using a PCD-CT in a chest phantom replicating the characteristics of a 5-year-old child. Materials and methods: The phantom was imaged on a dual-source PCD-CT with five different volume CT dose indices (CTDI_vol): 0.45 mGy, 0.30 mGy, 0.15 mGy, 0.07 mGy, and 0.01 mGy. Scans were acquired with Sn100 kV in standard and ultra-high resolution modes. Polychromatic images were reconstructed with a 1-mm slice thickness, lung kernel Bl60, without quantum iterative reconstruction and with quantum iterative reconstruction at strengths 2 and 4. Two paediatric radiologists rated reconstructions subjectively, defining adequate image quality as the visibility of small peripheral structures. Objective evaluation included global noise index and global signal-to-noise ratio index. Results: Exposure times were 0.42 s and 0.84 s for standard and ultra-high resolution modes, respectively. Subjective assessments showed no significant differences across scan modes or quantum iterative reconstruction strengths for both readers at all doses (all, P > 0.05). Scans at 0.07 mGy with quantum iterative reconstruction 4 were deemed to maintain adequate image quality at the lowest dose. Global noise index was always lower and global signal-to-noise ratio index always higher in ultra-high resolution compared with standard mode, underscoring noise reduction achieved via ultra-high resolution mode’s small pixel effect. Conclusions: PCD-CT enables high-pitch lung imaging while maintaining adequate image quality at a radiation dose as low as 0.07 mGy, with quantum iterative reconstruction 4, in a paediatric phantom representing a 5-year-old child. Graphical