(1) Background: To evaluate the effects of an AI-based denoising post-processing software solution in low-dose whole-body computer tomography (WBCT) stagings; (2) Methods: From 1 January 2019 to 1 January 2021, we retrospectively included biometrically matching melanoma patients with clinically indicated WBCT staging from two scanners. The scans were reconstructed using weighted filtered back-projection (wFBP) and Advanced Modeled Iterative Reconstruction strength 2 (ADMIRE 2) at 100% and simulated 50%, 40%, and 30% radiation doses. Each dataset was post-processed using a novel denoising software solution. Five blinded radiologists independently scored subjective image quality twice with 6 weeks between readings. Inter-rater agreement and intra-rater reliability were determined with an intraclass correlation coefficient (ICC). An adequately corrected mixed-effects analysis was used to compare objective and subjective image quality. Multiple linear regression measured the contribution of “Radiation Dose”, “Scanner”, “Mode”, “Rater”, and “Timepoint” to image quality. Consistent regions of interest (ROI) measured noise for objective image quality; (3) Results: With good–excellent inter-rater agreement and intra-rater reliability (Timepoint 1: ICC ≥ 0.82, 95% CI 0.74–0.88; Timepoint 2: ICC ≥ 0.86, 95% CI 0.80–0.91; Timepoint 1 vs. 2: ICC ≥ 0.84, 95% CI 0.78–0.90; all p ≤ 0.001), subjective image quality deteriorated significantly below 100% for wFBP and ADMIRE 2 but remained good–excellent for the post-processed images, regardless of input (p ≤ 0.002). In regression analysis, significant increases in subjective image quality were only observed for higher radiation doses (≥0.78, 95%CI 0.63–0.93; p < 0.001), as well as for the post-processed images (≥2.88, 95%CI 2.72–3.03, p < 0.001). All post-processed images had significantly lower image noise than their standard counterparts (p < 0.001), with no differences between the post-processed images themselves. (4) Conclusions: The investigated AI post-processing software solution produces diagnostic images as low as 30% of the initial radiation dose (3.13 ± 0.75 mSv), regardless of scanner type or reconstruction method. Therefore, it might help limit patient radiation exposure, especially in the setting of repeated whole-body staging examinations.

(1) This study evaluates the impact of an AI denoising algorithm on image quality, diagnostic accuracy, and radiological workflows in pediatric chest ultra-low-dose CT (ULDCT). (2) Methods: 100 consecutive pediatric thorax ULDCT were included and reconstructed using weighted filtered back projection (wFBP), iterative reconstruction (ADMIRE 2), and AI denoising (PixelShine). Place-consistent noise measurements were used to compare objective image quality. Eight blinded readers independently rated the subjective image quality on a Likert scale (1 = worst to 5 = best). Each reader wrote a semiquantitative report to evaluate disease severity using a severity score with six common pathologies. The time to diagnosis was measured for each reader to compare the possible workflow benefits. Properly corrected mixed-effects analysis with post-hoc subgroup tests were used. Spearman’s correlation coefficient measured inter-reader agreement for the subjective image quality analysis and the severity score sheets. (3) Results: The highest noise was measured for wFBP, followed by ADMIRE 2, and PixelShine (76.9 ± 9.62 vs. 43.4 ± 4.45 vs. 34.8 ± 3.27 HU; each p < 0.001). The highest subjective image quality was measured for PixelShine, followed by ADMIRE 2, and wFBP (4 (4–5) vs. 3 (4–5) vs. 3 (2–4), each p < 0.001) with good inter-rater agreement (r ≥ 0.790; p ≤ 0.001). In diagnostic accuracy analysis, there was a good inter-rater agreement between the severity scores (r ≥ 0.764; p < 0.001) without significant differences between severity score items per reconstruction mode (F (5.71; 566) = 0.792; p = 0.570). The shortest time to diagnosis was measured for the PixelShine datasets, followed by ADMIRE 2, and wFBP (2.28 ± 1.56 vs. 2.45 ± 1.90 vs. 2.66 ± 2.31 min; F (1.000; 99.00) = 268.1; p < 0.001). (4) Conclusions: AI denoising significantly improves image quality in pediatric thorax ULDCT without compromising the diagnostic confidence and reduces the time to diagnosis substantially.

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Background Patients with hepatic metastatic uveal melanoma still have a poor outcome. Purpose To evaluate overall survival (OS), progression-free survival (PFS), and response predictors in these patients treated with chemosaturation by percutaneous hepatic perfusion with melphalan (CS-PHP). Material and Methods Between June 2015 and March 2020, a total of 29 patients (median age 69.7 years; age range 30–81 years; 60% women; median BMI 25.7 kg/m2; range 18.7–35.3kg/m2; 1–6 procedures per patient) were treated with 53 CS-PHPs. All patients received cross-sectional imaging for initial and follow-up examinations. Baseline tumor load, extrahepatic tumor load, tumor response, PFS, and OS were assessed. Non-parametric statistics were used. Results After the initial CS-PHP, a partial response was observed in 11 patients (41%), stable disease in 12 patients (44%) and progressive disease in 4 patients (15%); two patients died before the response was evaluated. After initial CS-PHP, median OS was 12.9 ± 7.4 months and median PFS was 7.1 ± 7.4 months. OS after one year was 50%. After the second CS-PHP, median PFS was 7.9 ± 5.7 months. Seven patients had a liver tumor burden >25%, associated with a significantly shorter OS (6.0 ± 2.4 vs. 14.1 ± 12.7 months; P = 0.008). At the time of first CS-PHP, 41% (12/29) of the patients had extrahepatic metastases that did not affect OS (11.1 ± 8.4 months vs. 12.9 ± 13.6 months; P = 0.66). Conclusion CS-PHP is a safe and effective treatment for the hepatic metastatic uveal melanoma, especially for patients with a hepatic tumor burden <25%.

Background Comfort and recovery are major concerns of patients seeking aesthetic surgery. This study aimed to assess postoperative pain and recovery after outpatient breast surgery under sedation, intercostal block, and local anaesthesia. Methods This prospective cohort study included all consecutive patients who underwent aesthetic breast surgery between April 2021 and August 2022. Epidemiological data, anaesthesia, pain, and patients’ satisfaction were systematically assessed with standardized self-assessment questionnaires. Results Altogether, 48 patients [median (IQR) age: 30 (36–25)] were included. The most frequent surgery was mastopexy. 69% of surgeries involved additional procedures. The mean intercostal block and local anaesthesia time was 15 min. Patients received a median (IQR) of 19 (34–2) mg/kg lidocaine and 2.3 (2.5–2.0) mg/kg ropivacaine. The median (IQR) consumption of propofol and alfentanil was, respectively, 4.89 (5.48–4.26) mg/kg/h and 0.27 (0.39–0.19) µg/kg/min. No conversion to general anaesthesia or unplanned hospital admission occurred. Patients were discharged after a median (IQR) of 2:40 (3:43–1:58) hours. Within the first 24 postoperative hours, 17% required once an antiemetic medication and 38% an opioid. Patients were very satisfied with the anaesthesia and 90% of the patients had not wished more analgesia in the first 24 h. Conclusions Aesthetic breast surgery under sedation, intercostal block, and tumescent anaesthesia can safely be performed as an ambulatory procedure and is associated with minimal intra- and postoperative opioid consumption and high patient satisfaction. These data may be used to inform patients and clinicians and improve the overall quality of care. Level of Evidence IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 . Supplementary Information The online version contains supplementary material available at 10.1007/s00266-022-03214-w.