A 10-Year Single Centre Experience of Erosive Pustular Dermatosis of the Leg: A Possible Correlation with Atopic Dermatitis?

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Reduction of Metal Artifacts Caused by Titanium Peduncular Screws in the Spine by Means of Monoenergetic Images and the Metal Artifact Reduction Software in Dual-Energy Computed Tomography

Objectives: To evaluate the reduction of metal artifacts in patients with titanium peduncular screws in the spine using (1) conventional images (CI), (2) virtual monoenergetic reconstructions (VMRs), and (3) VMR + Metal Artifact Reduction Software (VMR + MARS), with dual-energy computed tomography (DECT). Materials and Methods: Twenty-four patients with titanium peduncular screws in the spine were studied using a 64-channel DECT. During the postprocessing phase, the CI, the VMRs from 100 to 140 keV, and the VMR at 140 keV + MARS were synthesized. All the images were considered, and a quantitative evaluation was performed measuring the attenuation values (in terms of Hounsfield Units) with region of interest, in correspondence with the most hyperdense and hypodense artifacts. All the values were then compared. A qualitative evaluation, in terms of image quality and extent of artifacts, was also performed by two radiologists. Results: In quantitative terms, the 140 keV + MARS reconstruction was able to significantly reduce both bright and dark metal artifacts, compared to CI and to VMRs. The VMR was capable of significantly reducing both dark and bright artifacts, compared to CI. In qualitative terms, the VMR at 140 keV proved to be the best, compared to CI and VMR + MARS images. Conclusions: The VMR + MARS image reduces metal artifacts from titanium peduncular screws more than VMRs alone and CI. Furthermore, the VMR can decrease metal artifacts from a quantitative and a qualitative point of view. Combining information from VMRs and VMR + MARS images could be the best way to solve the issue of metal artifacts on computed tomography images

Clinical Application of Diffusion Tensor Imaging for a Brachial Plexus Injury

Brachial plexus injuries are commonly diagnosed clinically, as conventional imaging has a low sensitivity. In recent years, diffusion tensor imaging has established a clinical role in the study of the central nervous system and, while still presenting some limitations due to the technical complexity of the acquisition method, is showing promising results when applied to peripheral nerves. Moreover, deterministic fiber tracking with the Euler's method and multishell acquisition are two novel advances in the field which contribute to enhancing the reliability of the technique reducing the respiratory and inhomogeneity artifacts in this "magnetically complex" region, and better isolating the fibers in a heterogeneous territory. Here, we report a case of brachial plexus traumatic injury, a healthy reference subject, and details on the acquisition protocol of the reconstruction algorithm

Prospective double-blind randomised controlled trial protocol comparing bone marrow aspirate concentrate intra-articular injection combined with subchondral injection versus intra-articular injection alone for the treatment of symptomatic knee osteoarthritis

Introduction: Subchondral and intra-articular injections of bone marrow aspirate concentrate (BMAC) showed promising results for knee osteoarthritis (OA) patients. To date, there is no evidence to demonstrate whether the combination of these treatments provides higher benefits than the intra-articular injection alone. Methods and analysis: Eighty-six patients with symptomatic knee OA (aged between 40 and 70 years) are randomised to BMAC intra-articular injection combined with subchondral BMAC injection or BMAC intra-articular injection alone in a ratio of 1:1. The primary outcome is the total Western Ontario and McMaster Universities Osteoarthritis Index, the secondary outcomes are the International Knee Documentation Committee Subjective and Objective Knee Evaluation Form, the Tegner activity scale, the EuroQol-Visual Analogue Scale, and the health questionnaire European Quality of Life Five Dimension score. Additional CT and MRI evaluations are performed at the baseline assessment and at the final 12-month follow-up. The hypothesis is that the combined injections provide higher knee pain and function improvement compared with BMAC intra-articular injection alone. The primary analysis follows an intention to treat principle. Ethics and dissemination: The study protocol has been approved by the Emilia Wide Area Ethical Committee of the Emilia-Romagna Region (CE-AVEC), Bologna, Italy. Written informed consent is obtained from all the participants. Findings of this study will be disseminated through peer-reviewed publications and conference presentations. Protocol version: Version 1 (14 May 2018). Trial registration number: NCT03876795

Automatically extracted machine learning features from preoperative CT to early predict microvascular invasion in HCC: the role of the Zone of Transition (ZOT)

open12noMicrovascular invasion (MVI) is a consolidated predictor of hepatocellular carcinoma (HCC) recurrence after treatments. No reliable radiological imaging findings are available for preoperatively diagnosing MVI, despite some progresses of radiomic analysis. Furthermore, current MVI radiomic studies have not been designed for small HCC nodules, for which a plethora of treatments exists. This study aimed to identify radiomic MVI predictors in nodules ≤3.0 cm by analysing the zone of transition (ZOT), crossing tumour and peritumour, automatically detected to face the uncertainties of radiologist’s tumour segmentation. Methods: The study considered 117 patients imaged by contrast-enhanced computed tomography; 78 patients were finally enrolled in the radiomic analysis. Radiomic features were extracted from the tumour and the ZOT, detected using an adaptive procedure based on local image contrast variations. After data oversampling, a support vector machine classifier was developed and validated. Classifier performance was assessed using receiver operating characteristic (ROC) curve analysis and related metrics. Results: The original 89 HCC nodules (32 MVI+ and 57 MVI−) became 169 (62 MVI+ and 107 MVI−) after oversampling. Of the four features within the signature, three are ZOT heterogeneity measures regarding both arterial and venous phases. On the test set (19MVI+ and 33MVI−), the classifier predicts MVI+ with area under the curve of 0.86 (95%CI (0.70–0.93), p∼10^−5), sensitivity = 79% and specificity = 82%. The classifier showed negative and positive predictive values of 87% and 71%, respectively. Conclusions: The classifier showed the highest diagnostic performance in the literature, disclosing the role of ZOT heterogeneity in predicting the MVI+ status.noneMatteo Renzulli, Margherita Mottola, Francesca Coppola, Maria Adriana Cocozza, Silvia Malavasi, Arrigo Cattabriga, Giulio Vara, Matteo Ravaioli, Matteo Cescon, Francesco Vasuri, Rita Golfieri, Alessandro BevilacquaMatteo Renzulli, Margherita Mottola, Francesca Coppola, Maria Adriana Cocozza, Silvia Malavasi, Arrigo Cattabriga, Giulio Vara, Matteo Ravaioli, Matteo Cescon, Francesco Vasuri, Rita Golfieri, Alessandro Bevilacqu

Sarcopenia Predicts Major Complications after Resection for Primary Hepatocellular Carcinoma in Compensated Cirrhosis

The burden of post-operative complications of patients undergoing liver resection for hepatocellular carcinoma (HCC) is a cause of morbidity and mortality. Recently, sarcopenia has been reported to influence the outcome of patients with cirrhosis. We aimed to assess factors associated with sarcopenia and its prognostic role in liver surgery candidates. We included all patients with compensated advanced chronic liver disease (cACLD) undergoing liver resection for primary HCC consecutively referred to the University of Bologna from 2014 to 2019 with an available preoperative abdominal CT-scan performed within the previous three months. A total of 159 patients were included. The median age was 68 years, and 80.5% of the patients were male. Sarcopenia was present in 82 patients (51.6%). Age and body mass index (BMI) were associated with the presence of sarcopenia at multivariate analysis. Thirteen (8.2%) patients developed major complications and 14 (8.9%) presented PHLF grade B-C. The model for end-stage liver disease score was associated with the development of major complications, whereas cACLD presence, thrombocytopenia, portal hypertension (PH), Child-Pugh score and Albumin-Bilirubin score were found to be predictors of clinically significative PHLF. The rate of major complications was 11.8% in sarcopenic patients with cACLD compared with no complications (0%) in patients without sarcopenia and cACLD (p = 0.032). The rate of major complications was significantly higher in patients with (16.3%) vs. patients without (0%) sarcopenia (p = 0.012) in patients with PH. In conclusion, sarcopenia, which is associated with age and BMI, may improve the risk stratification of post-hepatectomy major complications in patients with cACLD and PH

Outcome Prediction for SARS-CoV-2 Patients Using Machine Learning Modeling of Clinical, Radiological, and Radiomic Features Derived from Chest CT Images

Featured Application The present study demonstrates that semi-automatic segmentation enables the identification of regions of interest affected by SARS-CoV-2 infection for the extraction of prognostic features from chest CT scans without suffering from the inter-operator variability typical of segmentation, hence offering a valuable and informative second opinion. Machine Learning methods allow identification of the prognostic features potentially reusable for the early detection and management of other similar diseases. (1) Background: Chest Computed Tomography (CT) has been proposed as a non-invasive method for confirming the diagnosis of SARS-CoV-2 patients using radiomic features (RFs) and baseline clinical data. The performance of Machine Learning (ML) methods using RFs derived from semi-automatically segmented lungs in chest CT images was investigated regarding the ability to predict the mortality of SARS-CoV-2 patients. (2) Methods: A total of 179 RFs extracted from 436 chest CT images of SARS-CoV-2 patients, and 8 clinical and 6 radiological variables, were used to train and evaluate three ML methods (Least Absolute Shrinkage and Selection Operator [LASSO] regularized regression, Random Forest Classifier [RFC], and the Fully connected Neural Network [FcNN]) for their ability to predict mortality using the Area Under the Curve (AUC) of Receiver Operator characteristic (ROC) Curves. These three groups of variables were used separately and together as input for constructing and comparing the final performance of ML models. (3) Results: All the ML models using only RFs achieved an informative level regarding predictive ability, outperforming radiological assessment, without however reaching the performance obtained with ML based on clinical variables. The LASSO regularized regression and the FcNN performed equally, both being superior to the RFC. (4) Conclusions: Radiomic features based on semi-automatically segmented CT images and ML approaches can aid in identifying patients with a high risk of mortality, allowing a fast, objective, and generalizable method for improving prognostic assessment by providing a second expert opinion that outperforms human evaluation

Clinical Application of Diffusion Tensor Imaging for a Brachial Plexus Injury

Brachial plexus injuries are commonly diagnosed clinically, as conventional imaging has a low sensitivity. In recent years, diffusion tensor imaging has established a clinical role in the study of the central nervous system and, while still presenting some limitations due to the technical complexity of the acquisition method, is showing promising results when applied to peripheral nerves. Moreover, deterministic fiber tracking with the Euler’s method and multishell acquisition are two novel advances in the field which contribute to enhancing the reliability of the technique reducing the respiratory and inhomogeneity artifacts in this “magnetically complex” region, and better isolating the fibers in a heterogeneous territory. Here, we report a case of brachial plexus traumatic injury, a healthy reference subject, and details on the acquisition protocol of the reconstruction algorithm

Iatrogenic Spinal Intradural Hemorrhage in a Patient with Dural Ectasia in Marfan Syndrome

No abstract availabl

Homogeneous blue lumps of the nipple-areola complex in pubertal girls

Retroareolar cysts are benign breast lesions caused by the obstruction and consequent dilatation of Montgomery tubercles. Herein, we report two cases of premenarchal girls who developed retroareolar cysts. Their course and differential diagnosis are discussed