View clinical trials related to PET Imaging.
Filter by:The main purpose of this study is to develop a computer-aided prediction model for NAC treatment response. Based on the heterogeneity of internal parametric tumor composition commonly observed, this study will utilize the histologic characteristics and treatment response to investigate the image features as input data for predicting treatment response using Deep Learning technology. Using this technique, preoperative treatment evaluation may be facilitated by tumor heterogeneity analysis from developed dynamic radiomics, and the possibility of personal medicine can be realized not far ahead. In the first two years of this study using images from DCE-MRI, PET/CT and QDS-IR, we plan to develop the image processing algorithms, including segmenting breast and tumor region, extracting image feature which reflects angiogenic properties and permeability of tumor, which are highly correlated with NAC treatment response. During the third year of the project, the morphology and texture features from first two years can be combined for PET/MRI and prediction model can be achieved in accordance with the features extracted from dynamic features extraction using longitudinal images of PET/MRI.
A subset of patients diagnosed with severe acute respiratory syndrome (SARS)-CoV2 infection present with lymphopenia. The degree of lymphopenia, and in particular reduced cluster of differentiation (CD)8+ T-cell numbers, is correlated with clinical deterioration and intensive care unit (ICU) admission. The underlying reasons for lymphopenia in coronavirus disease (COVID)-19 is currently unclear, We aim to assess differences in the in vivo distribution of CD8+ T-cells in patients with proven SARS-CoV2 presenting with lymphopenia or with normal lymphocyte counts, using Zirconium-89 ([89Zr])Df-IAB22M2C positron emission tomography (PET) imaging.
Aim: We aim to evaluate αvβ3 integrin expression in proven COVID-19 infected patients with indicative findings on routine contrast-enhanced CT using [68Ga]Ga-DOTA-(RGD)2. If activated vascular endothelium in the lung parenchyma proceeds ARDS, as frequently observed during COVID-19 infection, imaging αvβ3 integrin expression using PET/CT could have potential as a clinical tool to characterize patients at early stages during disease and guide development of novel treatments targeting the vascular endothelium. Study design: This is a prospective, observational non-randomized pilot study. Maximum 10 patients will undergo a [68Ga]Ga-DOTA-(RGD)2 PET/CT scan and CT-subtraction scan in the same procedure. 10-minutes/bed position static [68Ga]Ga-DOTA-(RGD)2 PET/CT scans of the thorax will be acquired starting at 60 minutes post injection. Study population: Maximum 10 patients from the Infectious Diseases ward with proven COVID-19 infection and indicative pulmonary abnormalities on contrast-enhanced CT (CORADS 4-5) undergo PET/CT scans after injection of 70 μg (200 MBq) [68Ga]Ga-DOTA-(RGD)2 and CT-subtraction. Intervention: All patients will undergo a [68Ga]Ga-DOTA-(RGD)2 PET/CT scan, and in the same procedure, a CT-subtraction scan. Primary study objective: The primary objective of this study is to demonstrate and quantitate activation of the endothelium in the lung vasculature using [68Ga]Ga-DOTA-(RGD)2 PET/CT. Secondary study objectives: 1. To assess the spatial correlation between [68Ga]Ga-DOTA-(RGD)2 uptake and abnormal findings on routine contrast-enhanced CT scan of the chest 2. To assess the spatial correlation between [68Ga]Ga-DOTA-(RGD)2 and CTS of the lung parenchyma 3. To assess the correlation between [68Ga]Ga-DOTA-(RGD)2 and laboratory results 4. To explore the correlation between [68Ga]Ga-DOTA-(RGD)2 uptake and clinical course of disease
The goals of this study are to (1) develop and refine PET post-processing acquisition procedures, (2) generate preliminary and comparative imaging data for potential clinical trials, and (3) retrospectively evaluate standard of care PET imaging acquisitions by comparison with investigational PET imaging acquisitions.