https://www.selleckchem.com/products/10-dab-10-deacetylbaccatin.html Four PDD converters (mean age, 74 years ± 10; four men) and 20 nonconverters (mean age, 67 years ± 7; 11 women) were included in the external test set. Models trained with cortical thickness variables (AUC range, 0.75-0.83) showed fair to good performances similar to those trained with clinical variables (AUC range, 0.70-0.81). Model performances improved when models were trained with both variables (AUC range, 0.80-0.88). In pair-wise comparisons, models trained with both variables more frequently showed better performance than others in all model types. The models trained with both variables were successfully validated in the external test set (AUC range, 0.69-0.84). Conclusion Cortical thickness from MRI helped predict conversion from mild cognitive impairment to dementia in Parkinson disease at an individual level, with improved performance when integrated with clinical variables. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Port in this issue.Background There are limited data on outcomes following screening breast MRI in women with a personal history of breast cancer (PHBC). Purpose To investigate outcomes and factors associated with subsequent cancers following a negative screening MRI study in women with a PHBC. Materials and Methods Consecutive women with a PHBC and a negative prevalence screening breast MRI result between August 2014 and December 2016 were retrospectively identified. Inclusion criteria were prevalence screening MRI performed as part of routine surveillance protocol (1-3 years after treatment) and follow-up data for at least 12 months. The incidence and characteristics of subsequent cancers were reviewed. Logistic regression analysis was used to investigate associations between clinical-pathologic characteristics and subsequent cancers. Performance metrics were compared among screening MRI, mammography, and US. Results A