As nanotechnologies move closer to use in humans, quantitative imaging methods will play a vital role in answering questions of biodistribution. Accurate knowledge of the location and quantity of in vivo nanoconstructs and carriers is a challenging task, and new methods of quantitative imaging at appropriate resolutions are being developed and tested. Sustaining simultaneous advancement in both imaging development and nanotechnology research requires multidisciplinary research teams conducting experiments with interconnected goals. On an even greater scale, networks of multidisciplinary teams focused on similar issues of imaging and probe development offer opportunities for leveraging resources, as well as providing a forum for sharing ideas and creating consensus on solutions to common challenges. The Network for Translational Research (NTR): Optical Imaging in Multimodal Platforms from the National Cancer Institute is just such a network. Four multidisciplinary centers are accepting the challenges of developing and optimizing multimodal imaging hardware and software along with imaging probe development. These efforts are similar to the efforts that will be required for future studies of in vivo nanoparticle biodistribution. In addition to technology development and optimization, the network is organized to confront the challenges of validation of the imaging hardware and associated imaging agents, similar to the methods needed for validating nanomedicine.
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http://dx.doi.org/10.1002/wnan.117 | DOI Listing |
Med Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
Med Phys
January 2025
Department of Engineering Physics, Tsinghua University, Beijing, China.
Background: X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.
View Article and Find Full Text PDFAnn Surg Oncol
January 2025
Department of Surgery, National Defense Medical College, Tokorozawa, Saitama, Japan.
Background: Tumor size (TS) in pancreatic ductal adenocarcinoma (PDAC) is one of the most important prognostic factors. However, discrepancies between TS on preoperative images (TSi) and pathological specimens (TSp) have been reported. This study aims to evaluate the factors associated with the differences between TSi and TSp.
View Article and Find Full Text PDFOral Radiol
January 2025
Faculty of Dentistry, Department of Oral and Maxillofacial Radiology, Istanbul University, Istanbul, Turkey.
Objectives: This study evaluates the potential of pulp volume/total tooth-volume measurements of canine teeth in relation to chronologic age in patients with cleft lip and palate (CLP). The significance of this study lies in its exploration of the usability of these measurements for age determination in CLP patients, providing a novel perspective to the existing literature.
Methods: Cone beam computed tomography images of 33 patients (16 females, 17 males) with unilateral CLP aged 14-45 years and 33 age- and sex-matched healthy individuals (16 females, 17 males) were retrospectively evaluated.
Behav Res Methods
January 2025
CAP Team, Centre de Recherche en Neurosciences de Lyon - INSERM U1028 - CNRS UMR 5292 - UCBL - UJM, 95 Boulevard Pinel, 69675, Bron, France.
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