View clinical trials related to Diffusion-weighted MRI.
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.
The purpose of this study is to determine the clinical and radiologic implications of the intraoperative microemboli during carotid revascularization.
Uterine cervical cancer is the second most common female malignancy. Therapy monitoring is essential to detect early recurrence. Diffusion-weighted magnetic resonance imaging is an emerging MRI imaging technique which has a potential value for the detection of primary and recurrent disease and for the assessment of response to therapy. The purpose of this project is to evaluate the predictive value of DWI during and after therapy in the prediction of recurrence of cervical uterine cancer. It will be considered whether DWI is able to provide early information about the response to therapy. This could enable the identification of less- or non-responsive tumors and in this way therapy can be adapted as soon as possible. Hence the investigators could offer the patient a more efficient treatment scheme and a reduction in toxicity related to the treatment could be established.