Two α-synuclein ligands, 3-methoxy-7-nitro-10H-phenothiazine (2a, Ki = 32.1 ± 1.3 nM) and 3-(2-fluoroethoxy)-7-nitro-10H-phenothiazine (2b, Ki = 49.0 ± 4.9 nM), were radiolabeled as potential PET imaging agents by respectively introducing 11C and 18F. The syntheses of [11C]2a and [18F]2b were accomplished in a good yield with high specific activity. Ex vivo biodistribution studies in rats revealed that both [11C]2a and [18F]2b crossed the blood-brain barrier (BBB) and demonstrated good brain uptake 5 min post-injection. MicroPET imaging of [11C]2a in a non-human primate (NHP) confirmed that the tracer was able to cross the BBB with rapid washout kinetics from brain regions of a healthy macaque. The initial studies suggested that further structural optimization of [11C]2a and [18F]2b is necessary in order to identify a highly specific positron emission tomography (PET) radioligand for in vivo imaging of α-synuclein aggregation in the central nervous system (CNS).

It is highly desirable to develop novel approaches to improve patient survival rate of pancreatic cancer through early detection. Here, we present such an approach based on photoacoustic and fluorescence molecular imaging of pancreatic tumor using a miniature multimodal endoscope in combination with targeted multifunctional iron oxide nanoparticles (IONPs). A novel fan-shaped scanning mechanism was developed to minimize the invasiveness for endoscopic imaging of pancreatic tumors. The results show that the enhancements in photoacoustic and fluorescence signals using amino-terminal fragment (ATF) targeted IONPs were ~four to six times higher compared to that using non-targeted IONPs. Our study indicates the potential of the combination of the multimodal photoacoustic-fluorescence endoscopy and targeted multifunctional nanoparticles as an efficient tool to provide improved specificity and sensitivity for pancreatic cancer detection.

Radiomics, one of the potential methods for developing clinical biomarker, is one of the exponentially growing research fields. In addition to its potential, several limitations have been identified in this field, and most importantly the effects of variations in imaging parameters on radiomic features (RFs). In this study, we investigate the potential of RFs to predict overall survival in patients with clear cell renal cell carcinoma, as well as the impact of ComBat harmonization on the performance of RF models. We assessed the robustness of the results by performing the analyses a thousand times. Publicly available CT scans of 179 patients were retrospectively collected and analyzed. The scans were acquired using different imaging vendors and parameters in different medical centers. The performance was calculated by averaging the metrics over all runs. On average, the clinical model significantly outperformed the radiomic models. The use of ComBat harmonization, on average, did not significantly improve the performance of radiomic models. Hence, the variability in image acquisition and reconstruction parameters significantly affect the performance of radiomic models. The development of radiomic specific harmonization techniques remain a necessity for the advancement of the field.