267 research outputs found
Nuove prospettive della conferenze epicopali e delle relazioni fra Chiesa e stati. Il caso italiano
La libertà religiosa nel magistero di Giovanni Paolo II.
Material incluido en el volumen especial de la revista del Instituto MartÃn de Azpilcueta, Universidad de Navarra : Ius Canonicum (1999), en honor de Javier Hervada
Injuries in Medium to Long-Distance Triathlon: A Retrospective Analysis of Medical Conditions Treated in Three Editions of the Ironman Competition
Triathlon's popularity is rapidly increasing, and epidemiological data relating to its related medical conditions is crucial to the development of proper medical plans and safety guidelines for it. This study examined the data from the medical reports collected during three consecutive editions of Ironman Italy, from 2017 to 2019. Out of 10,653 race-starters, 3.3% required medical attention sustaining 472 medical conditions. A significantly higher injury risk was found for females versus males (χ2 = 9.78, p = 0.02) and in long-distance (IR: 4.09/1,000hours) rather than in Olympic/middle distance races (IR: 1.75/1,000hours). Most (68.4%) conditions (including muscular exhaustion, hypothermia, and dehydration) were systemic, whilst only 10.2% were acute traumatic injuries. Of a total of 357 triathletes requiring medical assistance, 8.1% were a candidate for hospitalisation. The equipment and personnel that are required for the medical assistance in future triathlon events were estimated based on Maurer's algorithm, and ten practical recommendations for triathlon medical support were formulated
An annotated T2-weighted magnetic resonance image collection of testicular germ and non-germ cell tumors
open7noTesticular cancer is a rare tumor with a worldwide incidence that has increased over the last few decades. The majority of these tumors are testicular non-germ (TNGCTs) and germ cell tumors (TGCTs); the latter divided into two broad classes - seminomatous (SGCTs) and non-seminomatous germ cell tumors (NSGCTs). Although ultrasonography (US) maintains a primary role in the diagnostic workup of scrotal pathology, magnetic resonance imaging (MRI) has emerged as the imaging modality recommended for challenging cases, providing additional information to clarify inconclusive/equivocal US. In this work we describe and publicly share a collection of 44 images of annotated T2-weighted MRI lesions from 42 patients. Given that testicular cancer is a rare tumor, we are confident that this collection can be used to validate statistical models and to further investigate TNGCT and TGCT peculiarities using medical imaging features.openFeliciani G.; Mellini L.; Loi E.; Piccinini F.; Galeotti R.; Sarnelli A.; Parenti G.C.Feliciani G.; Mellini L.; Loi E.; Piccinini F.; Galeotti R.; Sarnelli A.; Parenti G.C
The potential role of MR based radiomic biomarkers in the characterization of focal testicular lesions
How to differentiate with MRI-based techniques testicular germ (TGCTs) and testicular non-germ cell tumors (TNGCTs) is still under debate and Radiomics may be the turning key. Our purpose is to investigate the performance of MRI-based Radiomics signatures for the preoperative prediction of testicular neoplasm histology. The aim is twofold: (i), differentiating TGCTs and TNGCTs status and (ii) differentiating seminomas (SGCTs) from non-seminomatous (NSGCTs). Forty-two patients with pathology-proven testicular neoplasms and referred for pre-treatment MRI, were retrospectively enrolled. Thirty-two out of 44 lesions were TGCTs. Twelve out of 44 were TNGCTs or other histologies. Two radiologists segmented the volume of interest on T2-weighted images. Approximately 500 imaging features were extracted. Least Absolute Shrinkage and Selection Operator (LASSO) was applied as method for variable selection. A linear model and a linear support vector machine (SVM) were trained with selected features to assess discrimination scores for the two endpoints. LASSO identified 3 features that were employed to build fivefold validated linear discriminant and linear SVM classifiers for the TGCT-TNGCT endpoint giving an overall accuracy of 89%. Four features were employed to build another SVM for the SGCT-SNGCT endpoint with an overall accuracy of 86%. The data obtained proved that T2-weighted-based Radiomics is a promising tool in the diagnostic workup of testicular neoplasms by discriminating germ cell from non-gem cell tumors, and seminomas from non-seminomas
EP-1864: A 18FDG-PET texture analysis study on early stage Hodgkin Lymphoma patient outcome prediction
A New Approach for a Safe and Reproducible Seeds Positioning for Diffusing Alpha-Emitters Radiation Therapy of Squamous Cell Skin Cancer: A Feasibility Study
The purpose of this study is to discuss how to use an external radio-opaque template in the Diffusing Alpha-emitters Radiation Therapy (DaRT) technique’s pre-planning and treatment stages. This device would help to determine the proper number of sources for tumour coverage, accounting for subcutaneous invasion and augmenting DaRT safety. The procedure will be carried out in a first phase on a phantom and then applied to a clinical case. A typical DaRT procedure workflow comprises steps like tumour measurements and delineation, source number assessment, and therapy administration. As a first step, an adhesive fiberglass mesh (spaced by 2 mm) tape was applied on the skin of the patient and employed as frame of reference. A physician contoured the lesion and marked the entrance points for the needles with a radio opaque ink marker. According to the radio opaque marks and metabolic uptake the clinical target volume was defined, and with a commercial brachytherapy treatment planning system (TPS) it was possible to simulate and adjust the spatial seeds distribution. After the implant procedure a CT was again performed to check the agreement between simulations and seeds positions. With the procedure described above it was possible to simulate a DaRT procedure on a phantom in order to train physicians and subsequently apply the novel approach on patients, outlining the major issues involved in the technique. The present work innovates and supports DaRT technique for the treatment of cutaneous cancers, improving its efficacy and safety
Radiomics in the characterization of lipid-poor adrenal adenomas at unenhanced CT: time to look beyond usual density metrics
Objectives: In this study, we developed a radiomic signature for the classification of benign lipid-poor adenomas, which may potentially help clinicians limit the number of unnecessary investigations in clinical practice. Indeterminate adrenal lesions of benign and malignant nature may exhibit different values of key radiomics features. Methods: Patients who had available histopathology reports and a non-contrast-enhanced CT scan were included in the study. Radiomics feature extraction was done after the adrenal lesions were contoured. The primary feature selection and prediction performance scores were calculated using the least absolute shrinkage and selection operator (LASSO). To eliminate redundancy, the best-performing features were further examined using the Pearson correlation coefficient, and new predictive models were created. Results: This investigation covered 50 lesions in 48 patients. After LASSO-based radiomics feature selection, the test dataset’s 30 iterations of logistic regression models produced an average performance of 0.72. The model with the best performance, made up of 13 radiomics features, had an AUC of 0.99 in the training phase and 1.00 in the test phase. The number of features was lowered to 5 after performing Pearson’s correlation to prevent overfitting. The final radiomic signature trained a number of machine learning classifiers, with an average AUC of 0.93. Conclusions: Including more radiomics features in the identification of adenomas may improve the accuracy of NECT and reduce the need for additional imaging procedures and clinical workup, according to this and other recent radiomics studies that have clear points of contact with current clinical practice. Clinical relevance statement: The study developed a radiomic signature using unenhanced CT scans for classifying lipid-poor adenomas, potentially reducing unnecessary investigations that scored a final accuracy of 93%. Key Points: • Radiomics has potential for differentiating lipid-poor adenomas and avoiding unnecessary further investigations. • Quadratic mean, strength, maximum 3D diameter, volume density, and area density are promising predictors for adenomas. • Radiomics models reach high performance with average AUC of 0.95 in the training phase and 0.72 in the test phase
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