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Background: Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction. This study aims to compare the diagnostic performance of DLIR and iterative reconstruction (IR) in the evaluation of focal hepatic lesions., Methods: We conducted a retrospective study of 216 focal hepatic lesions in 109 adult participants who underwent abdominal CT scanning at our institution. We used DLIR (low, medium, and high strength) and IR (0 %, 10 %, 20 %, and 30 %) techniques for image reconstruction. Four experienced abdominal radiologists independently evaluated focal hepatic lesions based on five qualitative aspects (lesion detectability, lesion border, diagnostic confidence level, image artifact, and overall image quality). Quantitatively, we measured and compared the level of image noise for each technique at the liver and aorta., Results: There were significant differences ( p  < 0.001) among the seven reconstruction techniques in terms of lesion borders, image artifacts, and overall image quality. Low-strength DLIR (DLIR-L) exhibited the best overall image quality. Although high-strength DLIR (DLIR-H) had the least image noise and fewest artifacts, it also had the lowest scores for lesion borders and overall image quality. Image noise showed a weak to moderate positive correlation with participants' body mass index and waist circumference., Conclusions: The optimal-strength DLIR significantly improved overall image quality for evaluating focal hepatic lesions compared to the IR technique. DLIR-L achieved the best overall image quality while maintaining acceptable levels of image noise and quality of lesion borders., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

To evaluate and validate the minor lymphatic pathway for distant metastases in cervical cancer. This is a retrospective cohort of cervical cancer patients underwent curative concurrent chemoradiotherapy. We used original dataset from 1 university hospital and validation dataset from 3 university hospitals. Lymphadenopathy status in CT imaging was reviewed by radiologist in either the obturator and external iliac nodes (major pathway) or the internal iliac and presacral nodes (minor pathway). We then used Cox regression to adjust for all potential confounders, including paraaortic nodes, T stage, histology, age, total treatment time, total number of nodes, total short axis of nodes. 397 and 384 patients were in the original and validation datasets (median follow-up period, 59.5 month's). The minor pathway was independent prognostic factor in multivariable analysis [HR=2.64; 95%CI=1.07-6.55; P = 0.036] and [HR=14.84; 95%CI=3.15-70.01; P= 0.001] in original and validation datasets, respectively. Whereas, the major pathway was statistically non-significant. Further validation showed that the minor pathway had the highest HR for distant metastases with both the EMBRACE (HR=6.05; 95% CI=1.30-28.08; P = 0.022) and the FIGO 2018 (HR=7.43; 95% CI=2.94-18.78; P<0.001) in the original dataset. A similar result was found with the validation dataset: EMBRACE, HR=30.91; 95% CI=2.78-343.62; P = 0.005; and FIGO 2018, HR=42.41; 95% CI=8.83-203.60; P<0.001.This is the first clinical study to validate that the minor lymphatic pathway was predominantly associated with distant metastases in cervical cancer. This finding should be validated in larger cohort to further integrate in standard staging for prediction of distant metastases., (Copyright © 2022. Published by Elsevier Inc.)

To develop and validate a prognostic model, including the minor lymphatic pathway (internal iliac and presacral nodes)., Study Design: Retrospective cohort., Participants: Locally advanced cervical cancer underwent concurrent chemoradiotherapy., Sample Size: 397 and 384 patients in the development and validation data set., Predictors: Our new nodal staging system with the minor lymphatic pathway., Outcome: Distant metastases., Statistical Analysis: Cox regression; net reclassification improvement (NRI) and decision curve analysis (DCA). Our new nodal system was the strongest predictor. The predictors in the final model were new nodal system, tumor stage, adenocarcinoma, initial hemoglobin, tumor size and age. The nodal system and the pretreatment model had concordance indices of 0.661 and 0.708, respectively, with good calibration curves. Compared to the OUTBACK eligibility criteria, the nodal system showed NRI for both cases (22%) and controls (16%). The pretreatment model showed NRI for cases (31%) and controls (18%). DCA in both models showed threshold probability of 15% and 12%, respectively, when compared with 24% in OUTBACK eligibility criteria. Our new nodal staging system and the pretreatment model could differentiate between high-risk and low-risk patients, thus facilitating decisions to provide more aggressive treatment to prevent distant metastases., (© 2022. The Author(s).)

Background: Physical inactivity and sarcopenia are two important predictors associated with increased morbidity and mortality in patients with cirrhosis. At present, the benefit of a home-based exercise training program is not well established in cirrhotic patients. The main objective of this study was to evaluate the effect of a 12-week home-based exercise training program on aerobic capacity in cirrhotic patients., Methods: This is a randomized controlled study. Patients with compensated cirrhosis were randomized by a block of 4 with concealed allocation to the home-based exercise training (n = 20) or control (n = 20). Both groups received protein supplementation (9 g/day) for 12 weeks. The home-based exercise training program included several aerobic/isotonic moderate-intensity continuous training exercises for 40 min per session, at least four times a week, with a total duration of 12 weeks. The heart rate was continuously monitored using a Garmin® watch. In the control group, patients received exercise instruction without active encouragement and continuous monitoring. The primary outcome was a change in the 6-min walk test from baseline. Secondary outcomes were the difference in thigh muscle thickness, liver stiffness, spleen stiffness, and quality of life., Results: A total of 40 patients were enrolled prospectively. The mean age was 56.3 ± 7.8 years, with a male predominance of 65%. The mean body mass index was 25.23 ± 3.0 kg/m 2 , and all were Child-Pugh A. Chronic hepatitis B or C was the primary cause of cirrhosis. The baseline values were a 6-min walk test of 475 ± 70 m, liver stiffness of 15.3 ± 9.3 kPa, spleen stiffness of 29.8 ± 21.7 kPa, and thigh muscle thickness (average compression index) of 0.64 ± 0.2 cm/m 2 . All baseline characteristics between the two groups were not different except the mean muscle mass which was significantly higher in the home-based exercise training group (p = 0.03, 95% CI 0.01 to 0.17). At the end of the study, no significant difference in the 6-min walk test was observed (p = 0.36, 95% CI -15.5 to 41.7). Liver stiffness measurement significantly improved in both groups, but no significant difference between groups was demonstrated (p = 0.77, 95% CI -1.3 to 1.8). Thigh muscle thickness was not different between groups. The fatigue domain of the quality of life index was significantly improved in the home-based exercise training group compared with the control group (p = 0.05, 95% CI 0.00 to 0.67). No adverse events occurred in a home-based exercise training program., Conclusions: A 12-week moderate-intensity home-based exercise training program in compensated cirrhotic patients significantly improved the fatigue domain of the quality of life index without an increase in adverse events. However, no benefit in terms of aerobic capacity, thigh muscle mass, liver stiffness, and spleen stiffness was demonstrated., Trial Registration: Thai Clinical Trials Registry number TCTR20190926002, 26/09/2019 (Retrospectively registered)., (© 2022. The Author(s).)