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https://www.selleckchem.com/products/oleic-acid.html RESULTS A total of 585 radiomics features were extracted from every phase for each patient. Six of these radiomics features were identified as most discriminant features for G1 and G2 tumors and used to construct the tumor grade prediction model. The prediction model resulted in the area under the curve values of 0.968 (95% CI 0.900-0.991) and 0.876 (95% CI 0.700-0.963) for the training cohort and validation cohort, respectively. Sensitivity and specificity were 96.4% and 83.9%, and 90.9% and 88.9% for the training and validation cohorts, respectively. The decision curves indicated that if the threshold probability is above 0.1, using the rad-score in the current study on G1/2 NF-pNETs is more beneficial than the treat-all-patients scheme or the treat-none scheme. CONCLUSION Radiomics developed with a combination of nonenhanced and portal venous phases can achieve favorable predictive accuracy for histological grade for G1/G2 NF-pNETs. RATIONALE AND OBJECTIVES The aim of this study is to investigate the most appropriate knee MRI report template that not only provides structure and consistency, but also allows enough narrative freedom for the logical organization of findings and improved communication with the orthopedic referral base. MATERIALS AND METHODS Three fictitious knee MRI reports were created using templates with different levels of structuring unstructured free text (FT), structured with headers (SH), and highly structured and itemized (SI). These were then distributed to clinicians in the orthopedics department at all levels of training along with a survey with numerical scoring questions on report readability, usefulness, and quality. Statistical analysis was used to evaluate the data. RESULTS Fifty-three surveys were completed with responses from residents, attendings, and physician assistants. The structured format with headers had statistically significant (p value less then 0.001) higher mean rank

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