Publications by authors named "Masami 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.
Purpose: 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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- The study evaluated a new imaging technique called MIXTURE, used for assessing cartilage and meniscus in knee specimens, compared to traditional turbo spin-echo (TSE) sequences.
- Standardized cartilage defects were created in human cadaver knees, and both MIXTURE and TSE sequences were analyzed for their effectiveness in showing defects and measuring relaxation times.
- The results showed that while both imaging methods had comparable visual results, MIXTURE provided a time-efficient way to obtain useful quantitative data on cartilage conditions.
Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: "MIX1", combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and "MIX2", combining T1-weighted images and T1ρ mapping (6:38 min).
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- The study evaluates a new imaging technique called MIXTURE, developed by Philips, which produces high-resolution T2 maps for diagnosing cervical radiculopathy.
- It compares T2 relaxation times and their variability using MIXTURE with another method, SHINKEI-Quant (S-Q), in both healthy participants and a patient with cervical disc herniation.
- Results show that MIXTURE provides significantly shorter T2 relaxation times and lower variability in measurements, indicating its potential for more accurate preoperative functional diagnosis of cervical nerve issues.
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- The study aims to improve diffusion-weighted imaging (DWI) in diagnostic radiology by tackling issues related to low signal-to-noise ratio (SNR) in high b-value images and biases in apparent diffusion coefficient (ADC) values through deep learning techniques.
- Researchers evaluated various reconstruction methods, including traditional parallel imaging and advanced AI-based techniques, using both commercial diffusion phantoms and numerical simulations, measuring their effectiveness across different acceleration factors and flip angles.
- Results indicated that lower SNR led to increased negative bias and reduced precision in ADC measurements, but the deep learning-based method (C-SENSE AI) showed significant improvements in denoised ADC maps compared to conventional methods, particularly at high acceleration and low flip angles.
Purpose: Prolonged scanning of time-resolved 3D phase-contrast MRI (4D flow MRI) limits its routine use in clinical practice. An echo-planar imaging (EPI)-based sequence and compressed sensing can reduce the scan duration. We aimed to determine the impact of EPI for 4D flow MRI on the scan duration, image quality, and quantitative flow metrics.
View Article and Find Full Text PDFPurpose: Neuromelanin is visualized by optimizing the conditions of longitudinal relaxation (T1)-weighted imaging (T1WI). Although it was originally developed in 2D imaging, 3D imaging has been also reported, and T1WI sequences with magnetization transfer (MT) pulses are now widely used in 3D gradient echo (GRE) sequences. In this study, we assert that the use of spectral presaturation with inversion recovery (SPIR) may also be useful as an alternative to MT pulses, and we optimize SPIR and compare it with MT.
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- This study compared the image quality of two types of diffusion-weighted imaging (DWI) techniques: echo planar imaging with compressed sensing-sensitivity encoding (EPICS-DWI) and conventional parallel imaging (PI-DWI) in healthy volunteers.
- Results showed that EPICS-DWI produced significantly higher signal-to-noise ratios (SNR) and better overall image quality at acceleration factors of 3 and 4 when compared to PI-DWI, although there were no significant differences in apparent diffusion coefficients (ADC) between the two methods.
- Despite EPICS-DWI showing improved quality, it also displayed a higher degree of image distortion at lower acceleration factors, indicating that optimal parameter settings are crucial for achieving the best imaging results.
Article Synopsis
- The study aimed to compare deep learning (DL)-based image reconstruction with traditional compressed sensing (CS) methods for enhancing fat-suppressed contrast-enhanced 3D T1-weighted images (T1WIs) of the head and neck.
- Researchers analyzed images from 39 patients and evaluated them qualitatively (image quality, anatomical structure visibility, etc.) and quantitatively (signal-to-noise ratios and contrast-to-noise ratios).
- Results showed that DL-based reconstruction significantly improved image quality and quantitative metrics, suggesting it is a more effective technique for assessing head and neck conditions than conventional CS methods.
Article Synopsis
- This study evaluated the use of liver MR fingerprinting (MRF) to quantitatively assess and diagnose different focal liver lesions in 89 participants averaging 62 years old.
- The MRF measurements performed comparably to standard MRI assessments, showing strong agreement for T1 values and moderate for T2, while also demonstrating good repeatability across measurements.
- A combination of metrics derived from MRF distinguished between benign and malignant lesions effectively, achieving a high diagnostic accuracy with an area under the curve (AUC) of 0.92.
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- Kawasaki disease is a systemic vasculitis that requires the evaluation of both coronary and systemic arteries, and this study aimed to assess the effectiveness of non-contrast magnetic resonance angiography (NC-MRA) in detecting complications related to the disease.* -
- The study involved 28 patients, with 57 exams focused on coronary arteries and 42 exams that included both coronary and systemic artery assessments, finding high image quality for various systemic arteries.* -
- Results showed no significant differences in examination time or sedation dosages between protocols and identified systemic artery aneurysms in 7.1% of patients, demonstrating the feasibility of a combined examination approach.*
Article Synopsis
- The study aimed to evaluate how effective deep learning (DL) image reconstruction is compared to traditional parallel imaging (PI) in head and neck diffusion-weighted imaging (DWI).
- Researchers analyzed data from 41 patients, focusing on qualitative aspects like image quality and artifacts, as well as quantitative metrics such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).
- Results showed that DL-based reconstructions significantly outperformed PI-based reconstructions in both qualitative and quantitative assessments, indicating DL's potential to improve image quality in head and neck imaging.
Purpose: To assess the reproducibility of ADC, T1, T2, and proton density (PD) measurements on the cortex across the entire brain using high-resolution pseudo-3D diffusion-weighted imaging using echo-planar imaging with compressed SENSE (EPICS-DWI) and 3D quantification with an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) in normal healthy adults.
Methods: Twelve healthy participants (median age, 33 years; range, 28-51 years) were recruited to evaluate the reproducibility of whole-brain EPICS-DWI and synthetic MRI. EPICS-DWI utilizes a compressed SENSE reconstruction framework while maintaining the EPI sampling pattern.
Article Synopsis
- The study aimed to assess the image quality of a faster method for time-of-flight magnetic resonance angiography (TOF-MRA) that combines compressed sensitivity encoding (CS) and spiral imaging.
- Twenty volunteers participated in the analysis, compared four TOF-MRA sequences, and two radiologists evaluated the images based on quality metrics.
- Results showed CS and spiral techniques had lower signal-to-noise ratios for certain branches, but CS-spiral provided better quality overall compared to using either method alone.
We investigated the ability of echo-planar imaging with L1-regularized iterative sensitivity encoding-based diffusion-weighted imaging (DWI) to improve the image quality and reduce the scanning time in prostate magnetic resonance imaging. We retrospectively analyzed 109 cases of prostate magnetic resonance imaging. We compared variables in the quantitative and qualitative assessments among 3 imaging groups: conventional parallel imaging-based DWI (PI-DWI) with an acquisition time of 3 minutes 15 seconds; echo-planar imaging with L1-regularized iterative sensitivity encoding-based DWI (L1-DWI) with a normal acquisition time (L1-DWINEX12) of 3 minutes 15 seconds; and L1-DWI with a half acquisition time (L1-DWINEX6) of 1 minute 45 seconds.
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- Diffusion-weighted imaging (DWI) is a medical imaging technique that visualizes water molecule movement in tissues, providing insights into their health based on how diffusion is affected by tissue structures.
- DWI faces challenges in abdominal imaging due to issues like large volumes, motion during scans, and difficulty with fat suppression, which can degrade image quality.
- Recent advancements, including scan acceleration methods, techniques to handle respiratory motion, and enhanced fat suppression, aim to improve abdominal DWI quality, paving the way for future clinical applications and the integration of artificial intelligence.
Purpose: To evaluate the effect of a cylindrical regional-suppression technique (CREST) on image quality and lesion conspicuity in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast.
Method: This was a comparative study of 67 women with 44 lesions who underwent breast DCE-MRI with CREST (CREST-DCE) and had a previous DCE-MRI without CREST (conv-DCE) available. Two radiologists assessed image quality parameters and lesion conspicuity using five-point Likert scales.
Purpose: We evaluated the usefulness of three-dimensional (3D) chemical exchange saturation transfer (CEST) imaging with compressed sensing and sensitivity encoding (CS-SENSE) for differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs).
Methods: We evaluated 28 patients (mean age 51.0 ± 13.
Purpose: Motion artifacts caused by breathing or involuntary motion of patients, which may lead to reduced image quality and a loss of diagnostic information, are a major problem in shoulder magnetic resonance imaging (MRI). The MultiVane (MV) technique decreases motion artifacts; however, it tends to prolong the acquisition time. As a parallel imaging technique, SENSitivity Encoding (SENSE) can be combined with the compressed sensing method to produce compressed SENSE (C-SENSE), resulting in a markedly reduced acquisition time.
View Article and Find Full Text PDFBackground Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies.
View Article and Find Full Text PDFPurpose: To evaluate diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with compressed SENSE (EPICS) of the head and neck magnetic resonance imaging (MRI).
Method: We retrospectively observed 32 patients who underwent head and neck DWI according to either the conventional method (SENSE, reduction factor = 2), fast scanning method (SENSE, reduction factor = 4), or fast scanning method with EPICS (EPICS, reduction factor = 4). For quantitative analysis, contrast-to-noise-ratio (CNR), apparent diffusion coefficient (ADC) values, geometric distortion, and coefficient of variations (CV) were measured and compared.