A transfer learning nomogram for predicting prostate cancer and benign conditions on MRI.

BACKGROUND: Deep learning has been used to detect or characterize prostate cancer (PCa) on medical images. The present study was designed to develop an integrated transfer learning nomogram (TLN) for the prediction of PCa and benign conditions (BCs) on magnetic resonance imaging (MRI). METHODS: In this retrospective study, a total of 709 patients with pathologically confirmed PCa and BCs from two institutions were included and divided into training (n = 309), internal validation (n = 200), and external validation (n = 200) cohorts. A transfer learning signature (TLS) that was pretrained with the whole slide images of PCa and fine-tuned on prebiopsy MRI images was constructed. A TLN that integrated the TLS, the Prostate Imaging-Reporting and Data System (PI-RADS) score, and the clinical factor was developed by multivariate logistic regression. The performance of the TLS, clinical model (CM), and TLN were evaluated in the validation cohorts using the receiver operating characteristic (ROC) curve, the Delong test, the integrated discrimination improvement (IDI), and decision curve analysis. RESULTS: TLS, PI-RADS score, and age were selected for TLN construction. The TLN yielded areas under the curve of 0.9757 (95% CI, 0.9613-0.9902), 0.9255 (95% CI, 0.8873-0.9638), and 0.8766 (95% CI, 0.8267-0.9264) in the training, internal validation, and external validation cohorts, respectively, for the discrimination of PCa and BCs. The TLN outperformed the TLS and the CM in both the internal and external validation cohorts. The decision curve showed that the TLN added more net benefit than the CM. CONCLUSIONS: The proposed TLN has the potential to be used as a noninvasive tool for PCa and BCs differentiation.

Buchwald-Hartwig Amination of Coordinating Heterocycles Enabled by Large-but-Flexible Pd-BIAN-NHC Catalysts.

A new class of large-but-flexible Pd-BIAN-NHC catalysts (BIAN=acenaphthoimidazolylidene, NHC=N-heterocyclic carbene) has been rationally designed to enable the challenging Buchwald-Hartwig amination of coordinating heterocycles. This robust class of BIAN-NHC catalysts permits cross-coupling under practical aerobic conditions of a variety of heterocycles with aryl, alkyl, and heteroarylamines, including historically challenging oxazoles and thiazoles as well as electron-deficient heterocycles containing multiple heteroatoms with BIAN-INon (N,N'-bis(2,6-di(4-heptyl)phenyl)-7H-acenaphtho[1,2-d]imidazol-8-ylidene) as the most effective ligand. Studies on the ligand structure and electronic properties of the carbene center are reported. The study should facilitate the discovery of even more active catalyst systems based on the unique BIAN-NHC scaffold.

Pd-PEPPSI-IPentAn Promoted Deactivated Amination of Aryl Chlorides with Amines under Aerobic Conditions.

We report herein a highly efficient Pd-catalyzed amination by "bulky-yet-flexible" Pd-PEPPSI-IPentAn complexes. The relationship between the N-heterocyclic carbenes (NHCs) structure and catalytic properties was discussed. Sterically hindered (hetero)aryl chlorides and a variety of aliphatic and aromatic amines can be applied in this cross-coupling, which smoothly proceeded to provide desired products. The operationally simple protocol highlights the rapid access to CAr-N bond formation under mild conditions without the exclusion of air and moisture.