Publications by authors named "S Yokosawa"
Article Synopsis
- The study investigates the relationship between intestinal metaplasia (IM) in the gastric mucosa and the risk of developing gastric cancer (GC), focusing on risk stratification using endoscopic and histological methods.
- A multicenter analysis involving 380 patients found that specific patterns, like light blue crest (LBC) and white opaque substance (WOS), along with histological IM, significantly correlated with increased GC risk.
- The results indicated that EGGIM and OLGIM scoring systems were effective tools for assessing GC risk, suggesting their potential use in clinical practice for better patient management.*
Purpose: Deep neural networks (DNNs) for MRI reconstruction often require large datasets for training. Still, in clinical settings, the domains of datasets are diverse, and how robust DNNs are to domain differences between training and testing datasets has been an open question. Here, we numerically and clinically evaluate the generalization of the reconstruction networks across various domains under clinically practical conditions and provide practical guidance on what points to consider when selecting models for clinical application.
View Article and Find Full Text PDFPurpose: To increase the number of images that can be acquired in MR examinations using quantitative parameters, we developed a method for obtaining arterial and venous images with mapping of proton density (PD), RF inhomogeneity (B1), longitudinal relaxation time (T1), apparent transverse relaxation time (T2*), and magnetic susceptibility through calculation, all with the same spatial resolution.
Methods: The proposed method uses partially RF-spoiled gradient echo sequences to obtain 3D images of a subject with multiple scan parameters. The PD, B1, T1, T2*, and magnetic susceptibility maps are estimated using the quantification method we previously developed.
Purpose: MR parameter mapping is a technique that obtains distributions of parameters such as relaxation time and proton density (PD) and is starting to be used for disease quantification in clinical diagnoses. Quantitative susceptibility mapping is also promising for the early diagnosis of brain disorders such as degenerative neurological disorders. Therefore, we developed an MR quantitative parameter mapping (QPM) method to map four tissue-related parameters (T, T*, PD, and susceptibility) and B simultaneously by using a 3D partially RF-spoiled gradient echo (pRSGE).
View Article and Find Full Text PDFArticle Synopsis
- The study aims to evaluate the effectiveness of various endoscopic and histological methods in assessing the risk of gastric cancer (GC) in Japanese clinical settings.
- Researchers analyzed both GC and non-GC patients across ten hospitals using several classification systems, finding significant associations between these methods and GC risk.
- Key findings included that the modified Kyoto classification showed improved predictive ability for GC risk, highlighting specific high-risk endoscopic features that may enhance early detection efforts.