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Ikuta, Ichiro

0000-0002-7145-833X

Mayo Clinic

Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA.

Citations 5

Multisystemic Imaging Features of Coccidioidomycosis
Haug, Logan P. , Lang, Harrison, Naeem, Muhammad, Kawashima, Akira , Jokerst, Clinton, Ikuta, Ichiro , Long, Jeremiah R. , Sugi, Mark, Yano, Motoyo , Tan, Nelly , Zulfiqar, Maria, Kawashima, Akira , Sugi, Mark , Jokerst, Clinton E , Sugi, Mark D , Zulfiqar, Maria , Long, Jeremiah , Ikuta, Ichiro , Lang, Harrison

RadioGraphics | January 29, 2026 | Volume: 46 | Issue: 2 | Pages: No page available

10.1148/rg.250064 Get It

An understanding of regions of endemicity and the spectrum of organ system involvement can improve recognition of the imaging features of coccidioidomycosis, which can overlap with those of other diseases.
Artificial Intelligence Image Artifacts: A Call to Label AI Images
Matthees, Nicholas , Zhou, Yuxiang , Ikuta, Ichiro , Matthees, Nicholas , Zhou, Yuxiang , Ikuta, Ichiro

Radiology: Artificial Intelligence | June 4, 2025 | Volume: 7 | Issue: 4 | Pages: No page available

10.1148/ryai.250235 Get It

Intensity-Based Assessment of Hippocampal Segmentation Algorithms Using Paired Precontrast and Postcontrast MRI
Cramer, Justin , Baxter, Leslie C. , Lang, Harrison, Parker, Jonathon J. , Matthees, Nicholas , Ikuta, Ichiro , Wang, Yalin , Parker, Jonathon, Chen, Alicia , Matthees, Nicholas , Ikuta, Ichiro , Wang, Yalin , Baxter, Leslie C. , Lang, Harrison, Chen, Alicia M. , Zhou, Yuxiang

Bioengineering | March 4, 2025 | Volume: 12 | Issue: 3 | Pages: 258

10.3390/bioengineering12030258 Get It

Hippocampal segmentation is essential in neuroimaging for evaluating conditions like Alzheimer’s dementia and mesial temporal sclerosis, where small volume changes can significantly impact normative percentiles. However, inaccurate segmentation is common due to the inclusion of non-hippocampal structures such as choroid plexus and cerebrospinal fluid (CSF), leading to volumetric overestimation and confounding of functional analyses. Current methods of assessment largely rely on virtual or manual ground truth labels, which can fail to capture these inaccuracies. To address this shortcoming, this study introduces a more direct voxel intensity-based method of segmentation assessment. Using paired precontrast and postcontrast T1-weighted MRIs, hippocampal segmentations were refined by adding marginal gray matter and removing marginal CSF and enhancement to determine a total required correction volume. Six segmentation algorithms—e2dhipseg, HippMapp3r, hippodeep, AssemblyNet, FastSurfer, and QuickNat—were implemented and compared. HippMapp3r and e2dhipseg, followed closely by hippodeep, exhibited the least total correction volumes, indicating superior accuracy. Dedicated hippocampal segmentation algorithms outperformed whole-brain methods.
How to Implement Clinical 7T MRI—Practical Considerations and Experience with Ultra-High-Field MRI
Cramer, Justin , Ikuta, Ichiro , Ikuta, Ichiro , Zhou, Yuxiang

Bioengineering | December 5, 2024 | Volume: 11 | Issue: 12 | Pages: 1228

10.3390/bioengineering11121228 Get It

The implementation of clinical 7T MRI presents both opportunities and challenges for advanced medical imaging. This tutorial provides practical considerations and experiences with 7T MRI in clinical settings. We first explore the history and evolution of MRI technology, highlighting the benefits of increased signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and susceptibility at 7T. Technical challenges such as increased susceptibility artifacts and RF inhomogeneity are also discussed, along with innovative adaptations. This review also discusses hardware and software considerations, including new parallel transmission head coils and advanced image processing techniques to optimize image quality. Safety considerations, such as managing tissue heating and susceptibility to artifacts, are also discussed. Additionally, clinical applications of 7T MRI are examined, focusing on neurological conditions such as epilepsy, multiple sclerosis, and vascular imaging. Emerging trends in the use of 7T MRI for spectroscopy, perfusion imaging, and multinuclear imaging are explored, with insights into the future of ultra-high-field MRI in clinical practice. This review aims to provide clinicians, technologists, and researchers with a roadmap for successfully implementing 7T MRI in both research and clinical environments.
Evolution and implementation of radiographic response criteria in neuro-oncology
Ramakrishnan, Divya , Reppert, Marc von , Krycia, Mark, Sala, Matthew, Mueller, Sabine , Nabavizadeh, Ali , Lohmann, Philipp , Raji, Cyrus A. , Ikuta, Ichiro , Memon, Fatima, Aboian, Mariam , Nabavizadeh, Ali , Galldiks, Norbert , Lohmann, Philipp , Aboian, Mariam S , Ikuta, Ichiro , Aneja, Sanjay , Weinberg, Brent D.

Neuro-Oncology Advances | September 13, 2023 | Volume: 5 | Issue: 1 | Pages: No page available

10.1093/noajnl/vdad118 Get It

Abstract Radiographic response assessment in neuro-oncology is critical in clinical practice and trials. Conventional criteria, such as the MacDonald and response assessment in neuro-oncology (RANO) criteria, rely on bidimensional (2D) measurements of a single tumor cross-section. Although RANO criteria are established for response assessment in clinical trials, there is a critical need to address the complexity of brain tumor treatment response with multiple new approaches being proposed. These include volumetric analysis of tumor compartments, structured MRI reporting systems like the Brain Tumor Reporting and Data System, and standardized approaches to advanced imaging techniques to distinguish tumor response from treatment effects. In this review, we discuss the strengths and limitations of different neuro-oncology response criteria and summarize current research findings on the role of novel response methods in neuro-oncology clinical trials and practice.