Publications by authors named "M Yoneyama"
New non-contrast MRI of endolymphatic hydrops in Ménière's disease considering inversion time.
Laryngoscope Investig Otolaryngol
August 2024
Objectives: Three-tesla MRI with gadolinium-based contrast agents is important in diagnosing Ménière's disease. However, contrast agents cannot be used in some patients. By using the compositional difference between the inner ear endolymph and perilymph, we performed basic and clinical research focused on potassium ions and protein to find the optimal parameters for visualizing endolymphatic hydrops on MRI without contrast.
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- The study aimed to evaluate the effectiveness of model-based deep learning reconstruction (DL-DWI) in improving prostate diffusion-weighted imaging (DWI) compared to traditional parallel imaging (PI-DWI).
- Researchers analyzed 32 patients with prostate cancer and found that DL-DWI significantly outperformed PI-DWI in terms of image quality, as shown by both qualitative and quantitative measures.
- The results indicated that DL-DWI provided better signal-to-noise ratio, contrast-to-noise ratio, and diffusion coefficient values for prostate tissues and lesions; however, the study lacked comparisons with other deep learning methods, highlighting a need for future research.
Article Synopsis
- This study aimed to evaluate how well lenticulostriate arteries (LSAs) can be seen using advanced imaging techniques, specifically comparing deep learning-based reconstruction with traditional methods.
- It involved five healthy volunteers and analyzed high-resolution images with varying levels of data reduction to assess the visibility and quality of LSAs as recognized by radiologists.
- Results showed that deep learning reconstruction improved the visibility and quality of LSAs compared to conventional methods, particularly at higher data reduction levels, making it a potentially better option for medical imaging.
Background And Purpose: Symptomatic radiation pneumonitis (SRP) is a complication of thoracic stereotactic body radiotherapy (SBRT). As visual assessments pose limitations, artificial intelligence-based quantitative computed tomography image analysis software (AIQCT) may help predict SRP risk. We aimed to evaluate high-resolution computed tomography (HRCT) images with AIQCT to develop a predictive model for SRP.
View Article and Find Full Text PDFPurpose: Quantitative MRI techniques such as T2 mapping are useful in comprehensive evaluation of various pathologies of the knee joint yet require separate scans to conventional morphological measurements and long acquisition times. The recently introduced 3D MIXTURE (Multi-Interleaved X-prepared Turbo-Spin Echo with Intuitive Relaxometry) technique can obtain simultaneous morphologic and quantitative information of the knee joint. To compare MIXTURE with conventional methods and to identify differences in morphological and quantitative information.
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