Objectives: The purpose of the study is to identify and validate ultrasound criteria for parotid tumors evaluation, as well as to elaborate a multimodal, multi-criteria and integrative ultrasound approach for allowing tumor discrimination in a noninvasive manner. Material and method: Twenty patients with solid parotid tumors (12 benign, 8 malignant) were examined by ultrasound: real-time "grey scale" ultrasound, Doppler ultrasound, elastography, harmonic ultrasound imaging with i.v. contrast (CEUS). The study focused on tumor morphology and circulation. The analysis of the results was observational, enhanced by statistical methods and artificial intelligence (decision trees). Results: All malignant tumors showed increased hypoechogenicity, tumoral cervical adenopathies, increased stiffness and "in block" mobility with the parotid gland upon palpation with the transducer, uneven distribution of the contrast material during the arterial phase (8/8). To varying degrees, they showed imprecise delineation (7/8), structural heterogeneity (6/8) and disorganized flow pattern (6/8). All cases of benign tumors showed heterogeneous echostructure, clear delineation and no capsule (12). They also showed moderate hypoechogenicity (9/12), no cervical lymph nodes (11/12) and variable rigidity (increased 6/12; low 3/12). A selection and ranking of relevant ultrasound parameters was also made. Some of them were included in a transparent and easy-to-use decision tree model with 100% data accuracy. Conclusions: The characterization and discrimination of solid parotid tumors require a multimodal and multicriteria approach. Ultrasound criteria can be divided into criteria of certainty and criteria of diagnosis probability. CEUS examination of parotid tumors did not reveal significant differences between benign and malignant circulatory bed. Decision trees discovered by artificial intelligence from the data may represent intelligent diagnosis support systems with very high accuracy, up to 100%.
Land grabbing has become a priority topic in academic research and a political concern, due to interests in the dynamics of the phenomenon and its negative impact on the sustainable development of agriculture in rural areas. This phenomenon generates changes in production systems of agriculture with adverse environmental consequences, adversely affects socio-economic and cultural conditions and leads to lower overall efficiency in agriculture. This article analyses the links between land concentration, land grabbing and sustainable development of agriculture in Romania compared to other old and new EU-28 countries. The results of the research show that the land grabbing in Romania has a significant dimension compared to the other countries analyzed, which has led to an inadequate agrarian structure and adverse effects on the sustainable performance of agricultural holdings and the sustainable development of rural areas.
CEUS was easily implemented on the studied tumor model and is adequate for the evaluation of tumor vascularity. US guided intracardiac administration of the CA is an easy and reproducible procedure. If the examination is performed at defined time intervals it detects the alterations within the tumor circulatory bed.
Nuclear grade is important for treatment selection and prognosis in patients with clear cell renal cell carcinoma (ccRCC). This study aimed to determine the ability of preoperative four-phase multiphasic multidetector computed tomography (MDCT)-based radiomics features to predict the WHO/ISUP nuclear grade. In all 102 patients with histologically confirmed ccRCC, the training set (n = 62) and validation set (n = 40) were randomly assigned. In both datasets, patients were categorized according to the WHO/ISUP grading system into low-grade ccRCC (grades 1 and 2) and high-grade ccRCC (grades 3 and 4). The feature selection process consisted of three steps, including least absolute shrinkage and selection operator (LASSO) regression analysis, and the radiomics scores were developed using 48 radiomics features (10 in the unenhanced phase, 17 in the corticomedullary (CM) phase, 14 in the nephrographic (NP) phase, and 7 in the excretory phase). The radiomics score (Rad-Score) derived from the CM phase achieved the best predictive ability, with a sensitivity, specificity, and an area under the curve (AUC) of 90.91%, 95.00%, and 0.97 in the training set. In the validation set, the Rad-Score derived from the NP phase achieved the best predictive ability, with a sensitivity, specificity, and an AUC of 72.73%, 85.30%, and 0.84. We constructed a complex model, adding the radiomics score for each of the phases to the clinicoradiological characteristics, and found significantly better performance in the discrimination of the nuclear grades of ccRCCs in all MDCT phases. The highest AUC of 0.99 (95% CI, 0.92–1.00, p < 0.0001) was demonstrated for the CM phase. Our results showed that the MDCT radiomics features may play a role as potential imaging biomarkers to preoperatively predict the WHO/ISUP grade of ccRCCs.
Aims: The study proposes Acoustic Radiation Force Impulse (ARFI) assessment of the masseter muscle elasticity in the healthy population and in patients who have undergone head and neck radiation therapy. Patients and methods: Twenty-five healthy controls constituted group A, and 13 patients who had underwent radiotherapy (35Gy minimum) formed group B. ARFI was performed bilaterally in the periphery (P) and the muscle center (C), in relaxation and contraction. Means and standard deviations were obtained for the recorded shear waves velocities (SWV).
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