Artificial neural network modelling hydrodenticity for optimal design by microfluidics of polymer nanoparticles to apply in magnetic resonance imaging.

The engineering of nanoparticles impacts the control of their nano-bio interactions at each level of the delivery pathway. Therefore, optimal nanoparticle physicochemical properties should be identified to favour on-target interactions and deliver efficiently active compounds to a specific target. To date, traditional batch processes do not guarantee the reproducibility of results and low polydispersity index of the nanostructures, while microfluidics has emerged as cost effectiveness, short-production time approach to control the nanoparticle size and size distribution. Several thermodynamic processes have been implemented in microfluidics, such as nanoprecipitation, ionotropic gelation, self-assembly, etc., to produce nanoparticles in a continuous mode and high throughput way.   In this work, we show how the Artificial Neural Network (ANN) can be adopted to model the impact of microfluidic parameters (namely, flow rates and polymer concentrations) on the size of the nanoparticles. Promising results have been obtained, with the highest model accuracy reaching 98.9 %, thus confirming the proposed approach's potential applicability for an ANN-guided biopolymer nanoparticle design for biomedical applications. Nanostructures with different degrees of complexity are analysed, and a proof-of-concept machine learning approach is proposed to evaluate Hydrodenticity in biopolymer matrices. STATEMENT OF SIGNIFICANCE: Size, shape and surface charge determine nano-bio interactions of nanoparticles and their ability to target diseases. The ideal nanoparticle design avoids off-target interactions and favours on-target interactions. So, tools enabling the identification of the optimal nanoparticle physicochemical properties for delivery to a specific target are required. In this work, we evaluate the use of Artificial Neural Network (ANN) to analyse the role of microfluidic parameters in predicting the optimal size of the different hydrogel nanoparticles and their ability to trigger Hydrodenticity.

Update on the Use of PET/MRI Contrast Agents and Tracers in Brain Oncology: A Systematic Review.

The recent advancements in hybrid positron emission tomography-magnetic resonance imaging systems (PET/MRI) have brought massive value in the investigation of disease processes, in the development of novel treatments, in the monitoring of both therapy response and disease progression, and, not least, in the introduction of new multidisciplinary molecular imaging approaches. While offering potential advantages over PET/CT, the hybrid PET/MRI proved to improve both the image quality and lesion detectability. In particular, it showed to be an effective tool for the study of metabolic information about lesions and pathological conditions affecting the brain, from a better tumor characterization to the analysis of metabolic brain networks. Based on the PRISMA guidelines, this work presents a systematic review on PET/MRI in basic research and clinical differential diagnosis on brain oncology and neurodegenerative disorders. The analysis includes literature works and clinical case studies, with a specific focus on the use of PET tracers and MRI contrast agents, which are usually employed to perform hybrid PET/MRI studies of brain tumors. A systematic literature search for original diagnostic studies is performed using PubMed/MEDLINE, Scopus and Web of Science. Patients, study, and imaging characteristics were extracted from the selected articles. The analysis included acquired data pooling, heterogeneity testing, sensitivity analyses, used tracers, and reported patient outcomes. Our analysis shows that, while PET/MRI for the brain is a promising diagnostic method for early diagnosis, staging and recurrence in patients with brain diseases, a better definition of the role of tracers and imaging agents in both clinical and preclinical hybrid PET/MRI applications is needed and further efforts should be devoted to the standardization of the contrast imaging protocols, also considering the emerging agents and multimodal probes.

Tuning of Hydrogel Architectures by Ionotropic Gelation in Microfluidics: Beyond Batch Processing to Multimodal Diagnostics.

Microfluidics is emerging as a promising tool to control physicochemical properties of nanoparticles and to accelerate clinical translation. Indeed, microfluidic-based techniques offer more advantages in nanomedicine over batch processes, allowing fine-tuning of process parameters. In particular, the use of microfluidics to produce nanoparticles has paved the way for the development of nano-scaled structures for improved detection and treatment of several diseases. Here, ionotropic gelation is implemented in a custom-designed microfluidic chip to produce different nanoarchitectures based on chitosan-hyaluronic acid polymers. The selected biomaterials provide biocompatibility, biodegradability and non-toxic properties to the formulation, making it promising for nanomedicine applications. Furthermore, results show that morphological structures can be tuned through microfluidics by controlling the flow rates. Aside from the nanostructures, the ability to encapsulate gadolinium contrast agent for magnetic resonance imaging and a dye for optical imaging is demonstrated. In conclusion, the polymer nanoparticles here designed revealed the dual capability of enhancing the relaxometric properties of gadolinium by attaining Hydrodenticity and serving as a promising nanocarrier for multimodal imaging applications.

New Strategies in the Design of Paramagnetic CAs.

Nowadays, magnetic resonance imaging (MRI) is the first diagnostic imaging modality for numerous indications able to provide anatomical information with high spatial resolution through the use of magnetic fields and gradients. Indeed, thanks to the characteristic relaxation time of each tissue, it is possible to distinguish between healthy and pathological ones. However, the need to have brighter images to increase differences and catch important diagnostic details has led to the use of contrast agents (CAs). Among them, Gadolinium-based CAs (Gd-CAs) are routinely used in clinical MRI practice. During these last years, FDA highlighted many risks related to the use of Gd-CAs such as nephrotoxicity, heavy allergic effects, and, recently, about the deposition within the brain. These alerts opened a debate about the opportunity to formulate Gd-CAs in a different way but also to the use of alternative and safer compounds to be administered, such as manganese- (Mn-) based agents. In this review, the physical principle behind the role of relaxivity and the T 1 boosting will be described in terms of characteristic correlation times and inner and outer spheres. Then, the recent advances in the entrapment of Gd-CAs within nanostructures will be analyzed in terms of relaxivity boosting obtained without the chemical modification of CAs as approved in the chemical practice. Finally, a critical evaluation of the use of manganese-based CAs will be illustrated as an alternative ion to Gd due to its excellent properties and endogenous elimination pathway.