Publications by authors named "Keita Nagawa"
Purpose: In this study, we evaluated serial changes in shoulder muscle volume and computed tomography (CT) density of the transverse force couple (i.e., subscapularis (Ssc) vs.
View Article and Find Full Text PDFIn patients with anterior shoulder instability (ASI), a chronic imbalance might exist between the anterior and posterior shoulder muscles (i.e., subscapular [Ssc] vs.
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- * It involved 321 patients divided into three groups based on their kidney function, utilizing data from both kidneys and different MRI methods.
- * The model achieved its highest accuracy of 86.2% when analyzing images from both kidneys using the in-phase technique, indicating its effectiveness in assessing CKD severity.
Purpose: This study assessed the serial volume changes in multiple shoulder muscles simultaneously following arthroscopic rotator cuff repair (ARCR) by a three-dimensional (3D) modeling-based sectional measurement. These volume changes were correlated with background preoperative factors.
Methods: Four consecutive magnetic resonance imaging scans (preoperatively and postoperatively at 3, 6, and 12 months) of 33 shoulders from 31 patients who underwent arthroscopic rotator cuff repair were examined.
This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. Twenty (19 patients) and 31 MRI scans (30 patients) of femurs with PFI and normal femurs, respectively, were used. Bone and cartilage segmentation of the distal femurs was performed and subsequently converted into 3D reconstructed models.
View Article and Find Full Text PDFPurpose: We compared cerebrospinal fluid (CSF) leak conspicuity and image quality as visualized using 3D versus 2D magnetic resonance (MR) myelography in patients with spinal CSF leaks.
Methods: Eighteen patients underwent spinal MR imaging at 3 Tesla. Three board-certified radiologists independently evaluated CSF leak conspicuity and image quality on a 4-point scale; the latter assessed by scoring fat suppression, venous visualization, and severity of CSF flow artifacts.
Article Synopsis
- The study aimed to assess the effectiveness of MRI findings and texture features (TFs) in distinguishing between uterine endometrial carcinoma and uterine carcinosarcoma.
- It included 102 patients and utilized various MRI assessments, including conventional MRI findings and specific imaging techniques, to identify key features for diagnosis.
- The results indicated that a combined model of conventional MRI findings and TFs outperforming individual models, demonstrating a high diagnostic performance with an AUC of 0.915.
Article Synopsis
- Developed a 3D CNN method for automatic kidney segmentation in chronic kidney disease patients using MRI images, focusing on different types of Dixon-based MRI.
- The study involved 100 participants with renal dysfunction and 70 without, with evaluations conducted separately for both groups for accuracy checks.
- The model achieved high performance on non-RD group data, notably the IP image yielding a Dice score of 0.902, and offers potential for future research in assessing kidney volume and related analyses in CKD patients.
Case Reports of TFE3-Rearranged Renal Cell Carcinoma: FDG-PET Uptake Might Help Diagnosis.
J Kidney Cancer VHL
September 2023
Translocation and transcription factor E3 (TFE3)-rearranged renal cell carcinoma (RCC) is a rare subtype of RCCs characterised by the fusion of the TFE3 transcription factor genes on chromosome Xp11.2 with one of the multiple genes. TFE3-rearranged RCC occurs mainly in children and adolescents, although middle-aged cases are also observed.
View Article and Find Full Text PDFPurpose: To assess the usefulness of contrast-enhanced 3D STIR FLAIR imaging for evaluation of pituitary adenomas.
Methods: Patients with pituitary adenomas underwent MR examinations including contrast-enhanced 3D STIR FLAIR and 2D T1-weighted (T1W) imaging. We subjectively compared the two techniques in terms of 10 categories.
Article Synopsis
- A multiclass classification model was developed to predict eGFR groups in CKD patients using MRI texture analysis, focusing on different types of MRI images.
- 166 CKD patients were analyzed, leading to the extraction of 93 texture features and the creation of classification models using various algorithms like SVM and random forest.
- Results showed that T1-weighted MRI images provided the best classification performance, particularly with the random forest classifier, although overall model performances were modest.
Article Synopsis
- The study aimed to assess how effective conventional MRI features and texture analysis are in distinguishing between ovarian thecoma-fibroma groups (OTFGs) and ovarian granulosa cell tumors (OGCTs).
- A total of 52 patients were surveyed, and various MRI-based and texture features were analyzed to create a model capable of differentiating between the two types of ovarian tumors.
- The findings showed that the MRI-based model and a combination model performed nearly equally well in terms of diagnostic accuracy, while texture analysis alone did not significantly improve diagnosis, suggesting MRI analysis is a reliable method for distinguishing these tumors.
To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics features. Twenty-two patients with dermatomyositis (DM), 14 with amyopathic dermatomyositis (ADM), 19 with polymyositis (PM) and 19 with non-IIM were enrolled. Using 2D manual segmentation, 93 original features as well as 93 local binary pattern (LBP) features were extracted from MRI (short-tau inversion recovery [STIR] imaging) of proximal limb muscles.
View Article and Find Full Text PDFStereodivergent construction of three contiguous stereocenters in catalytic doubly diastereoselective nitroaldol reactions of alpha-chiral aldehydes with nitroacetaldehyde dimethyl acetal using two types of heterobimetallic catalysts is described. A La-Li-BINOL (LLB) catalyst afforded anti,syn-nitroaldol products in >20:1-14:1 selectivity, and a Pd/La/Schiff base catalyst afforded complimentary syn,syn-nitroaldol products in 10:1-5:1 selectivity.
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