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This study aims to investigate the influence of interobserver manual segmentation variability on the reproducibility of 2D and 3D unenhanced computed tomography (CT)- and magnetic resonance imaging (MRI)-based texture analysis. Thirty patients with cartilaginous bone tumors (10 enchondromas, 10 atypical cartilaginous tumors, 10 chondrosarcomas) were retrospectively included. Three radiologists independently performed manual contour-focused segmentation on unenhanced CT and T1-weighted and T2-weighted MRI by drawing both a 2D region of interest (ROI) on the slice showing the largest tumor area and a 3D ROI including the whole tumor volume. Additionally, a marginal erosion was applied to both 2D and 3D segmentations to evaluate the influence of segmentation margins. A total of 783 and 1132 features were extracted from original and filtered 2D and 3D images, respectively. Intraclass correlation coefficient ≥ 0.75 defined feature stability. In 2D vs. 3D contour-focused segmentation, the rates of stable features were 74.71% vs. 86.57% (p < 0.001), 77.14% vs. 80.04% (p = 0.142), and 95.66% vs. 94.97% (p = 0.554) for CT and T1-weighted and T2-weighted images, respectively. Margin shrinkage did not improve 2D (p = 0.343) and performed worse than 3D (p < 0.001) contour-focused segmentation in terms of feature stability. In 2D vs. 3D contour-focused segmentation, matching stable features derived from CT and MRI were 65.8% vs. 68.7% (p = 0.191), and those derived from T1-weighted and T2-weighted images were 76.0% vs. 78.2% (p = 0.285). 2D and 3D radiomic features of cartilaginous bone tumors extracted from unenhanced CT and MRI are reproducible, although some degree of interobserver segmentation variability highlights the need for reliability analysis in future studies., (© 2021. The Author(s).)

Dual-energy X-ray absorptiometry (DXA) in nowadays considered one of the most versatile imaging techniques for the evaluation of metabolic bone disorders such as osteoporosis, sarcopenia and obesity. The advantages of DXA over other imaging techniques are the very low radiation dose, its accuracy and simplicity of use. In addition, fat mass (FM) and lean mass (LM) values by DXA shows very good accuracy compared to that of computed tomography and magnetic resonance imaging. In this review we will explain the technical working principles of body composition with DXA, together with the possible limitations and pitfalls that should be avoided in daily routine to produce high-quality DXA examinations. We will also cover the current clinical practical application of whole body DXA values, with particular emphasis on the use of LM indices in the diagnostic workup of reduced muscle mass, sarcopenia and osteosarcopenic obesity according to the most recent guidelines. The possible use of adipose indices will be considered, such as the fat mass index (FMI) or the android/gynoid ratio, as well as lipodystrophy indices and the evaluation of visceral adipose tissue (VAT). Whenever available, we will provide possible cut-off diagnostic values for each of these LM and FM indices, according to current literature and guidelines., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/qims.2020.03.02). The special issue “Body Composition Imaging” was commissioned by the editorial office without any funding or sponsorship. GG served as the unpaid Guest Editor of the special issue and serves as an unpaid editorial board member of Quantitative Imaging in Medicine and Surgery. AB served as the unpaid Guest Editor of the special issue. The authors have no other conflicts of interest to declare., (2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D* median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.

Postoperative bile leakage is a common complication of abdominal surgical procedures and a precise localization of is important to choose the best management. Many techniques are available to correctly identify bile leaks, including ultrasound (US), computed tomography (CT) or magnetic resonance imaging (MRI), being the latter the best to clearly depict "active" bile leakages. This paper presents the state of the art algorithm in the detection of biliary leakages in order to plan a percutaneous biliary drainage focusing on widely available and safe contrast agent, the Gb-EOB-DPA. We consider its pharmacokinetic properties and impact in biliary imaging explain current debates to optimize image quality. We report common sites of leakage after surgery with special considerations in cirrhotic liver to show what interventional radiologists should look to easily detect bile leaks., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare.