Faculty Profiles - NAGANAWA, Shinji

Papers - NAGANAWA, Shinji

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Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI? Reviewed

Taiki Nozaki, Masahiro Hashimoto, Daiju Ueda, Shohei Fujita, Yasutaka Fushimi, Koji Kamagata, Yusuke Matsui, Rintaro Ito, Takahiro Tsuboyama, Fuminari Tatsugami, Noriyuki Fujima, Kenji Hirata, Masahiro Yanagawa, Akira Yamada, Tomoyuki Fujioka, Mariko Kawamura, Takeshi Nakaura, Shinji Naganawa

La radiologia medica Vol. 130 ( 5 ) page： 587 - 597 2025.5

Correction: Generative AI and large language models in nuclear medicine: current status and future prospects. Reviewed Open Access

Kenji Hirata, Yusuke Matsui, Akira Yamada, Tomoyuki Fujioka, Masahiro Yanagawa, Takeshi Nakaura, Rintaro Ito, Daiju Ueda, Shohei Fujita, Fuminari Tatsugami, Yasutaka Fushimi, Takahiro Tsuboyama, Koji Kamagata, Taiki Nozaki, Noriyuki Fujima, Mariko Kawamura, Shinji Naganawa

Annals of nuclear medicine Vol. 39 ( 4 ) page： 404 - 405 2025.4

Assessing large language models for Lugano classification of malignant lymphoma in Japanese FDG-PET reports. Reviewed International journal Open Access

Rintaro Ito, Keita Kato, Kosuke Nanataki, Yumi Abe, Hiroshi Ogawa, Ryogo Minamimoto, Katsuhiko Kato, Toshiaki Taoka, Shinji Naganawa

EJNMMI reports Vol. 9 ( 1 ) page： 8 - 8 2025.3

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

PURPOSE: This study evaluates the performance of four large language models (LLMs) in classifying malignant lymphoma stages using the Lugano classification from free-text FDG-PET reports in Japanese Specifically, we assess GPT-4o, Claude 3.5 Sonnet, Llama 3 70B, and Gemma 2 27B in their ability interpret unstructured radiology texts. MATERIALS AND METHODS: In a retrospective single-center study, 80 patients who underwent staging FDG-PET/CT for malignant lymphoma were included. The "Findings" sections of their reports were analyzed without pre-processing. Each LLM assigned Lugano stages based on these reports. Performance was compared to reference standard stages determined by expert radiologists. Statistical analyses involved overall accuracy, weighted kappa for agreement. RESULTS: GPT-4o achieved the highest accuracy at 75% (60/80 cases) with substantial agreement (weighted kappa κ = 0.801). Claude 3.5 Sonnet had 61.3% accuracy (49/80, κ = 0.763). Gemma 2 27B and Llama 3 70B showed accuracies of 58.8% and 57.5%, respectively, all indicating substantial agreement. CONCLUSION: GPT-4o outperformed other LLMs in assigning Lugano classification from Japanese FDG-PET free-text reports. This demonstrated the potential of advanced LLMs to interpret clinical texts. While the immediate clinical utility of automatically predicting a Lugano stage from an existing report may be limited, these results highlight the value of LLMs for understanding and standardizing free-text radiology data.

DOI： 10.1186/s41824-025-00246-8

Open Access

Web of Science

PubMed

Advancing clinical MRI exams with artificial intelligence: Japan’s contributions and future prospects Reviewed

Shohei Fujita, Yasutaka Fushimi, Rintaro Ito, Yusuke Matsui, Fuminari Tatsugami, Tomoyuki Fujioka, Daiju Ueda, Noriyuki Fujima, Kenji Hirata, Takahiro Tsuboyama, Taiki Nozaki, Masahiro Yanagawa, Koji Kamagata, Mariko Kawamura, Akira Yamada, Takeshi Nakaura, Shinji Naganawa

Japanese Journal of Radiology Vol. 43 ( 3 ) page： 355 - 364 2025.3

Language：English Publishing type：Research paper (scientific journal) Publisher：Springer Science and Business Media LLC

Abstract

In this narrative review, we review the applications of artificial intelligence (AI) into clinical magnetic resonance imaging (MRI) exams, with a particular focus on Japan’s contributions to this field. In the first part of the review, we introduce the various applications of AI in optimizing different aspects of the MRI process, including scan protocols, patient preparation, image acquisition, image reconstruction, and postprocessing techniques. Additionally, we examine AI’s growing influence in clinical decision-making, particularly in areas such as segmentation, radiation therapy planning, and reporting assistance. By emphasizing studies conducted in Japan, we highlight the nation’s contributions to the advancement of AI in MRI. In the latter part of the review, we highlight the characteristics that make Japan a unique environment for the development and implementation of AI in MRI examinations. Japan’s healthcare landscape is distinguished by several key factors that collectively create a fertile ground for AI research and development. Notably, Japan boasts one of the highest densities of MRI scanners per capita globally, ensuring widespread access to the exam. Japan’s national health insurance system plays a pivotal role by providing MRI scans to all citizens irrespective of socioeconomic status, which facilitates the collection of inclusive and unbiased imaging data across a diverse population. Japan’s extensive health screening programs, coupled with collaborative research initiatives like the Japan Medical Imaging Database (J-MID), enable the aggregation and sharing of large, high-quality datasets. With its technological expertise and healthcare infrastructure, Japan is well-positioned to make meaningful contributions to the MRI–AI domain. The collaborative efforts of researchers, clinicians, and technology experts, including those in Japan, will continue to advance the future of AI in clinical MRI, potentially leading to improvements in patient care and healthcare efficiency.

DOI： 10.1007/s11604-024-01689-y

Web of Science

PubMed

Other Link： https://link.springer.com/article/10.1007/s11604-024-01689-y/fulltext.html

Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature Reviewed

Yusuke Matsui, Daiju Ueda, Shohei Fujita, Yasutaka Fushimi, Takahiro Tsuboyama, Koji Kamagata, Rintaro Ito, Masahiro Yanagawa, Akira Yamada, Mariko Kawamura, Takeshi Nakaura, Noriyuki Fujima, Taiki Nozaki, Fuminari Tatsugami, Tomoyuki Fujioka, Kenji Hirata, Shinji Naganawa

Japanese Journal of Radiology Vol. 43 ( 2 ) page： 164 - 176 2025.2

Language：English Publishing type：Research paper (scientific journal) Publisher：Springer Science and Business Media LLC

Abstract

Interventional oncology provides image-guided therapies, including transarterial tumor embolization and percutaneous tumor ablation, for malignant tumors in a minimally invasive manner. As in other medical fields, the application of artificial intelligence (AI) in interventional oncology has garnered significant attention. This narrative review describes the current state of AI applications in interventional oncology based on recent literature. A literature search revealed a rapid increase in the number of studies relevant to this topic recently. Investigators have attempted to use AI for various tasks, including automatic segmentation of organs, tumors, and treatment areas; treatment simulation; improvement of intraprocedural image quality; prediction of treatment outcomes; and detection of post-treatment recurrence. Among these, the AI-based prediction of treatment outcomes has been the most studied. Various deep and conventional machine learning algorithms have been proposed for these tasks. Radiomics has often been incorporated into prediction and detection models. Current literature suggests that AI is potentially useful in various aspects of interventional oncology, from treatment planning to post-treatment follow-up. However, most AI-based methods discussed in this review are still at the research stage, and few have been implemented in clinical practice. To achieve widespread adoption of AI technologies in interventional oncology procedures, further research on their reliability and clinical utility is necessary. Nevertheless, considering the rapid research progress in this field, various AI technologies will be integrated into interventional oncology practices in the near future.

DOI： 10.1007/s11604-024-01668-3

Web of Science

PubMed

Other Link： https://link.springer.com/article/10.1007/s11604-024-01668-3/fulltext.html

A case of an ectopic Pacinian corpuscle in the pancreas mimicking pancreatic metastasis of renal cell carcinoma. Reviewed Open Access

Hiroshi Ogawa, Yasuo Takehara, Marina Higashi, Hidenori Mizumoto, Daichi Ito, Shinji Naganawa, Hideki Takami, Masato Nakaguro

Nagoya journal of medical science Vol. 87 ( 1 ) page： 178 - 181 2025.2

Predictive Performance of Radiomic Features Extracted from Breast MR Imaging in Postoperative Upgrading of Ductal Carcinoma in Situ to Invasive Carcinoma. Reviewed Open Access

Hiroko Satake, Fumie Kinoshita, Satoko Ishigaki, Keita Kato, Yusuke Jo, Satoko Shimada, Norikazu Masuda, Shinji Naganawa

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 4 ) 2025

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

PURPOSE: To investigate the predictive performance of radiomic features extracted from breast MRI for upgrade of ductal carcinoma in situ (DCIS) to invasive carcinoma. METHODS: This retrospective study included 71 women with DCIS lesions diagnosed preoperatively by biopsy. All women underwent breast dynamic contrast-enhanced (DCE) MRI of the breast, which included pre-contrast and five post-contrast phases continuously with a time resolution of 60s. Lesion segmentation was performed manually, and 144 radiomic features of the lesions were extracted from T2-weighted images (T2WI), pre-contrast T1-weighted images (T1WI), and post-contrast 1st, 2nd, and 5th phase subtraction images on DCE-MRI. Qualitative features of mammography, ultrasound, and MRI were also assessed. Clinicopathological features were evaluated using medical records. The least absolute shrinkage and selection operator (LASSO) algorithm was applied for features selection and model building. The predictive performance of postoperative upgrade to invasive carcinoma was assessed using the area under the receiver operating characteristic curve. RESULTS: Surgical specimens revealed 13 lesions (18.3%) that were upgraded to invasive carcinoma. Among clinicopathological and qualitative features, age was the only significant predictive variable. No significant radiomic features were observed on T2WI and post-contrast 2nd phase subtraction images on DCE-MRI. The area under the curves (AUCs) of the LASSO radiomics model integrated with age were 0.915 for pre-contrast T1WI, 0.862 for post-contrast 1st phase subtraction images, and 0.833 for post-contrast 5th phase subtraction images. The AUCs of the 200-times bootstrap internal validations were 0.885, 0.832, and 0.775. CONCLUSION: A radiomics approach using breast MRI may be a promising method for predicting the postoperative upgrade of DCIS. The present study showed that the radiomic features extracted from pre-contrast T1WI and post-contrast subtraction images in the very early phase of DCE-MRI were more predictable.

DOI： 10.2463/mrms.mp.2023-0168

Open Access

Web of Science

PubMed

Direct Visualization of Tracer Permeation into the Endolymph in Human Patients Using MR Imaging. Reviewed

Shinji Naganawa, Rintaro Ito, Mariko Kawamura, Toshiaki Taoka, Tadao Yoshida, Michihiko Sone

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 2 ) page： 253 - 261 2025

Authorship：Lead author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

PURPOSE: The endolymph of the inner ear, vital for balance and hearing, has long been considered impermeable to intravenously administered gadolinium-based contrast agents (GBCAs) due to the tight blood-endolymph barrier. However, anecdotal observations suggested potential GBCA entry in delayed heavily T2-weighted 3D-real inversion recovery (IR) MRI scans. This study systematically investigated GBCA distribution in the endolymph using this 3D-real IR sequence. METHODS: Forty-one patients suspected of endolymphatic hydrops (EHs) underwent pre-contrast, 4-h, and 24-h post-contrast 3D-real IR imaging. Signal intensity in cerebrospinal fluid (CSF), perilymph, and endolymph was measured and analyzed for temporal dynamics of GBCA uptake, correlations between compartments, and the influence of age and presence of EH. RESULTS: Endolymph showed a delayed peak GBCA uptake at 24h, contrasting with peaks in perilymph and CSF at 4h. Weak to moderate positive correlations between endolymph and CSF contrast effect were observed at both 4 (r = 0.483) and 24h (r = 0.585), suggesting possible inter-compartmental interactions. Neither the presence of EH nor age significantly influenced endolymph enhancement. However, both perilymph and CSF contrast effects significantly correlated with age at both time points. CONCLUSION: This study provides the first in vivo systematic confirmation of GBCA entering the endolymph following intravenous administration. Notably, endolymph uptake peaked at 24h, significantly later than perilymph and CSF. The lack of a link between endolymph contrast and both perilymph and age suggests distinct uptake mechanisms. These findings shed light on inner ear fluid dynamics and their potential implications in Ménière's disease and other inner ear disorders.

DOI： 10.2463/mrms.mp.2024-0011

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PubMed

Intracranial Air Absorption through Arachnoid Granulation: New Considerations from Transsphenoidal Surgery and Implications for Neurofluid Dynamics. Reviewed

Shinji Naganawa, Rintaro Ito, Mariko Kawamura, Toshiaki Taoka

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 1 ) page： 144 - 147 2025

Authorship：Lead author,　Corresponding author Language：English Publishing type：Research paper (scientific journal)

Postsurgery intracranial air usually diminishes, presumably merging with cerebrospinal fluid (CSF) and venous circulation. Our study presents two transsphenoidal surgery cases, highlighting potential air absorption by arachnoid granulation (AG)-an underexplored phenomenon. AG has long been deemed pivotal for CSF absorption, but recent perspectives suggest a significant role in waste clearance, neuroinflammation, and neuroimmunity. These cases may stimulate renewed research on the multifaceted role of AG in neurofluid dynamics and potentially elucidate further AG functions.

DOI： 10.2463/mrms.bc.2023-0122

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PubMed

Association between the Presence of the Parasagittal Cyst-like Structures and Cognitive Function. Reviewed Open Access

Toshio Ohashi, Rintaro Ito, Ryo Yamamoto, Katsuyuki Ukai, Shinji Naganawa

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 4 ) 2025

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

PURPOSE: A cyst-like structure near superior sagittal sinus (Arachnoid Cuff Exit Site cysts: ACES cysts) has been reported in MRI. The purpose of this study was to investigate the association between presence of ACES cysts and cognitive function, as assessed using mini-mental state examination (MMSE) scores. METHODS: We retrospectively analyzed patients who underwent head MRI for dementia screening. Differences in patient ages and MMSE scores between patients with and without ACES cysts were examined using the Mann-Whitney U test. Correlations between patient ages and MMSE scores were examined for patients with and without ACES cysts using Spearman's rank correlation coefficient. Multivariate logistic regression analysis was performed to examine the influence of presence or absence of ACES cysts on MMSE score. RESULTS: A total of 112 patients (male: 28, female: 84) were included for the analysis. The patient ages ranged from 66 to 94 years (median: 83 years). MMSE scores ranged from 6 to 30 (median: 24). ACES cysts were detected in 57 patients (50.9%). There was no significant difference in patient ages between the patients with and without ACES cysts (P = 0.058). The patients with ACES cysts showed significantly lower MMSE scores compared to the patients without ACES cysts (P < 0.001). In the patients with ACES cysts, there was no significant correlation between patient ages and MMSE scores (ρ = -0.178, P = 0.185), whereas a significant negative correlation was observed in the patients without ACES cysts (ρ = -0.347, P = 0.001). The presence of ACES cysts was determined as an independent predictor for the lower MMSE score (odds ratio = 15.2, 95% confidence interval = 5.59-41.4, P < 0.001). CONCLUSION: The presence of the ACES cysts showed significant association with lower MMSE score. ACES cysts might be involved in the pathological processes affecting cognitive function.

DOI： 10.2463/mrms.mp.2024-0138

Open Access

Web of Science

PubMed

MR Imaging Indices for Brain Interstitial Fluid Dynamics and the Effects of Orexin Antagonists on Sleep. Reviewed

Toshiaki Taoka, Kunihiro Iwamoto, Seiko Miyata, Rintaro Ito, Rei Nakamichi, Toshiki Nakane, Ippei Okada, Kazushige Ichikawa, Hirohito Kan, Koji Kamagata, Junko Kikuta, Shigeki Aoki, Akihiro Fujimoto, Yuki Kogo, Nobuyasu Ichinose, Shinji Naganawa, Norio Ozaki

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 4 ) 2025

Language：English Publishing type：Research paper (scientific journal)

PURPOSE: The purpose of this study was to assess the extent to which improvement in sleep with lemborexant contributed to changes in interstitial fluid dynamics. METHODS: The 3 methods including diffusion tensor image analysis along the perivascular space (DTI-ALPS), dynamic contrast-enhanced method to assess tissue vascular permeability (Ktrans), and choroid plexus volume (CPV) were used. Correlations between these imaging indices and sleep parameters (latency to persistent sleep [LPS], wake after sleep onset [WASO], total sleep time [TST], and sleep efficiency [SE]) were evaluated using Pearson correlation analysis. Additionally, multiple regression analysis and linear mixed model analysis were employed to assess the relationship between baseline sleep status and imaging parameter changes. MRI and sleep assessments were performed before treatment initiation (week 0, w0) and at 12 weeks after lemborexant administration (week 12, w12). RESULTS: The ALPS-index was inversely correlated with LPS and positively correlated with TST and SE at w0. In multiple regression analysis, ALPS-index was lower when sleep parameters other than LPS were poor at w0. A linear mixed model analysis suggested that poor sleep status in LPS and SE at w0 may have an effect on greater ALPS-index. In the evaluation of Ktrans measurement, the single regression analysis showed a statistically significant correlation between the reduction in Ktrans and the shortening in LPS. Examination of CPV and sleep parameters showed a significant negative correlation between TST and CPV at w0 and w12. Multiple regression analysis also showed that TST of w12 had a significant effect on CPV at w12. CONCLUSION: Our results suggested that poor sleep status is related to the greater change of ALPS-index and CPV improvement after lemborexant administration may be related to in part to sleep parameter improvement.

DOI： 10.2463/mrms.mp.2024-0176

Web of Science

PubMed

The Evolution and Clinical Impact of Deep Learning Technologies in Breast MRI. Reviewed

Tomoyuki Fujioka, Shohei Fujita, Daiju Ueda, Rintaro Ito, Mariko Kawamura, Yasutaka Fushimi, Takahiro Tsuboyama, Masahiro Yanagawa, Akira Yamada, Fuminari Tatsugami, Koji Kamagata, Taiki Nozaki, Yusuke Matsui, Noriyuki Fujima, Kenji Hirata, Takeshi Nakaura, Ukihide Tateishi, Shinji Naganawa

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 4 ) 2025

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

The integration of deep learning (DL) in breast MRI has revolutionized the field of medical imaging, notably enhancing diagnostic accuracy and efficiency. This review discusses the substantial influence of DL technologies across various facets of breast MRI, including image reconstruction, classification, object detection, segmentation, and prediction of clinical outcomes such as response to neoadjuvant chemotherapy and recurrence of breast cancer. Utilizing sophisticated models such as convolutional neural networks, recurrent neural networks, and generative adversarial networks, DL has improved image quality and precision, enabling more accurate differentiation between benign and malignant lesions and providing deeper insights into disease behavior and treatment responses. DL's predictive capabilities for patient-specific outcomes also suggest potential for more personalized treatment strategies. The advancements in DL are pioneering a new era in breast cancer diagnostics, promising more personalized and effective healthcare solutions. Nonetheless, the integration of this technology into clinical practice faces challenges, necessitating further research, validation, and development of legal and ethical frameworks to fully leverage its potential.

DOI： 10.2463/mrms.rev.2024-0056

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PubMed

Comparing Lesion Conspicuity and ADC Reliability in High-resolution Diffusion-weighted Imaging of the Breast. Reviewed

Mami Iima, Rena Nakayama, Masako Kataoka, Martins Otikovs, Noam Nissan, Lucio Frydman, Yuta Urushibata, Maya Honda, Aika Okazawa, Hiroko Satake, Shinji Naganawa, Yuji Nakamoto

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Vol. 24 ( 4 ) 2025

Language：English Publishing type：Research paper (scientific journal)

PURPOSE: This study investigated the breast lesion conspicuity and apparent diffusion coefficient (ADC) reliability for three different diffusion-weighted imaging (DWI) protocols: spatiotemporal encoding (SPEN), single-shot echo-planar imaging (SS-EPI), and readout segmentation of long variable echo-trains (RESOLVE). METHODS: Sixty-five women suspected of having breast tumors were included in this study, with 44 lesions (36 malignant, 8 benign) analyzed further. Breast MRI was performed on a 3 Tesla (3T) system (MAGNETOM Prisma, Siemens) equipped with a dedicated 18-channel breast array coil for a phantom and patients. Three DWI protocols-SPEN, SS-EPI, and RESOLVE-were used. SS-EPI was acquired with an in-plane resolution of 2 × 2 mm2, a slice thickness of 3 mm, and b-values of 0 and 1000 s/mm2. SPEN had a higher in-plane resolution of 1 × 1 mm2, a slice thickness of 1.5 mm, and b-values of 0, 850, and 1500 s/mm2. RESOLVE was acquired with an in-plane resolution of 1 × 1 mm2, a slice thickness of 1.5 mm, and b-values of 0 and 850 s/mm2. Lesion conspicuity and ADC values were evaluated. RESULTS: The average lesion conspicuity scores were significantly higher for RESOLVE (3.54 ± 0.65) than for SPEN (3.07 ± 0.91) or SS-EPI (2.48 ± 0.78) (P < 0.01). The SPEN score was significantly higher than the SS-EPI score (P < 0.01). Phantom measurements indicated marginally lower ADC values for SPEN compared to SS-EPI and RESOLVE across all concentrations. The results revealed that SPEN (b = 0, 850, 1500 sec/mm2) yielded significantly lower ADC values compared to SPEN (b = 0, 850 sec/mm2) in malignant lesions (P < 0.01), with no significant difference observed between SPEN (b = 0, 850 sec/mm2), SS-EPI, and RESOLVE. For benign lesions, no significant difference in ADC values was found between SPEN (b = 0, 850 sec/mm2), SPEN (b = 0, 850, 1500 sec/mm2), SS-EPI, and RESOLVE. CONCLUSION: RESOLVE provided the highest lesion conspicuity, and ADC values in breast lesions were not significantly different among sequences ranging b values 850-1000 sec/mm2. SPEN with higher b-values (0, 850, 1500 vs. 0, 850 sec/mm2) yielded significantly lower ADC values in malignant lesions, highlighting the importance of b-value selection in ADC quantification.

DOI： 10.2463/mrms.tn.2024-0089

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PubMed

The Endolymph Signal in Non-contrast Enhanced 3D-real IR Image Differs between the Ears with and without Significant Endolymphatic Hydrops Reviewed Open Access

Shinji Naganawa, Rintaro Ito, Mariko Kawamura, Toshiaki Taoka, Tadao Yoshida, Michihiko Sone

MAGNETIC RESONANCE IN MEDICAL SCIENCES Vol. 24 ( 4 ) 2025

Preliminary Findings on Non-contrast Enhanced Positive Endolymph Images: Limited Delineation of Endolymphatic Space Reviewed Open Access

Shinji Naganawa, Rintaro Ito, Mariko Kawamura, Toshiaki Taoka, Tadao Yoshida, Michihiko Sone

MAGNETIC RESONANCE IN MEDICAL SCIENCES Vol. 24 ( 4 ) 2025

Stereotactic arrhythmia radioablation for ventricular tachycardia: a review of clinical trials and emerging roles of imaging Reviewed

Mariko Kawamura, Masafumi Shimojo, Fuminari Tatsugami, Kenji Hirata, Shohei Fujita, Daiju Ueda, Yusuke Matsui, Yasutaka Fushimi, Tomoyuki Fujioka, Taiki Nozaki, Akira Yamada, Rintaro Ito, Noriyuki Fujima, Masahiro Yanagawa, Takeshi Nakaura, Takahiro Tsuboyama, Koji Kamagata, Shinji Naganawa

Journal of Radiation Research Vol. 66 ( 1 ) page： 1 - 9 2024.12

Language：English Publishing type：Research paper (scientific journal) Publisher：Oxford University Press (OUP)

ABSTRACT

Ventricular tachycardia (VT) is a severe arrhythmia commonly treated with implantable cardioverter defibrillators, antiarrhythmic drugs and catheter ablation (CA). Although CA is effective in reducing recurrent VT, its impact on survival remains uncertain, especially in patients with extensive scarring. Stereotactic arrhythmia radioablation (STAR) has emerged as a novel treatment for VT in patients unresponsive to CA, leveraging techniques from stereotactic body radiation therapy used in cancer treatments. Recent clinical trials and case series have demonstrated the short-term efficacy and safety of STAR, although long-term outcomes remain unclear. Imaging techniques, such as electroanatomical mapping, contrast-enhanced magnetic resonance imaging and nuclear imaging, play a crucial role in treatment planning by identifying VT substrates and guiding target delineation. However, challenges persist owing to the complex anatomy and variability in target volume definitions. Advances in imaging and artificial intelligence are expected to improve the precision and efficacy of STAR. The exact mechanisms underlying the antiarrhythmic effects of STAR, including potential fibrosis and improvement in cardiac conduction, are still being explored. Despite its potential, STAR should be cautiously applied in prospective clinical trials, with a focus on optimizing dose delivery and understanding long-term outcomes. Collaborative efforts are necessary to standardize treatment strategies and enhance the quality of life for patients with refractory VT.

DOI： 10.1093/jrr/rrae090

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PubMed

Evaluation of 4D Flow MRI-Derived Relative Residence Time as a Marker for Cirrhosis Associated Portal Vein Thrombosis. Reviewed International journal

Ryota Hyodo, Yasuo Takehara, Yoji Ishizu, Kazuki Nishida, Takashi Mizuno, Kazushige Ichikawa, Ryota Horiguchi, Nobuhiko Kurata, Yasuhiro Ogura, Shinya Yokoyama, Shinji Naganawa, Ning Jin, Yoshito Ichiba

Journal of magnetic resonance imaging : JMRI Vol. 60 ( 6 ) page： 2592 - 2601 2024.12

Language：English Publishing type：Research paper (scientific journal)

BACKGROUND: Portal vein thrombosis (PVT) is thought to arise from stagnant blood flow, yet conclusive evidence is lacking. Relative residence time (RRT) assessed using 4D Flow MRI may offer insight into portal flow stagnation. PURPOSE: To explore the relationship between RRT values and the presence of PVT in cirrhotic participants. STUDY TYPE: Prospective. POPULATION: Forty-eight participants with liver cirrhosis (27 males, median age 67 years [IQR: 57-73]) and 20 healthy control participants (12 males, median age 45 years [IQR: 40-54]). FIELD STRENGTH/SEQUENCE: 3 T/4D Flow MRI. ASSESSMENT: Laboratory (liver and kidney function test results and platelet count) and clinical data (presence of tumors and other imaging findings), and portal hemodynamics derived from 4D Flow MRI (spatiotemporally averaged RRT [RRT-mean], flow velocity, and flow rate) were analyzed. STATISTICAL TESTS: We used multivariable logistic regression, adjusted by selected covariates through the Lasso method, to explore whether RRT-mean is an independent risk factor for PVT. The area under the ROC curve (AUC) was also calculated to assess the model's discriminative ability. P < 0.05 indicated statistical significance. RESULTS: The liver cirrhosis group consisted of 16 participants with PVT and 32 without PVT. Higher RRT-mean values (odds ratio [OR] 11.4 [95% CI: 2.19, 118]) and lower platelet count (OR 0.98 per 1000 μL [95% CI: 0.96, 0.99]) were independent risk factors for PVT. The incorporation of RRT-mean (AUC, 0.77) alongside platelet count (AUC, 0.75) resulted in an AUC of 0.84. When including healthy control participants, RRT-mean had an adjusted OR of 12.4 and the AUC of the combined model (RRT-mean and platelet count) was 0.90. DATA CONCLUSION: Prolonged RRT values and low platelet count were significantly associated with the presence of PVT in cirrhotic participants. RRT values derived from 4D Flow MRI may have potential clinical relevance in the management of PVT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

DOI： 10.1002/jmri.29357

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PubMed

40 years of diffusion MRI: a journey from basic science to clinical breakthrough. Reviewed Open Access

Mami Iima, Yukio Miki, Shinji Naganawa

Japanese journal of radiology Vol. 42 ( 12 ) page： 1355 - 1356 2024.12

Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future Reviewed

Daiju Ueda, Shannon L Walston, Shohei Fujita, Yasutaka Fushimi, Takahiro Tsuboyama, Koji Kamagata, Akira Yamada, Masahiro Yanagawa, Rintaro Ito, Noriyuki Fujima, Mariko Kawamura, Takeshi Nakaura, Yusuke Matsui, Fuminari Tatsugami, Tomoyuki Fujioka, Taiki Nozaki, Kenji Hirata, Shinji Naganawa

Diagnostic and Interventional Imaging Vol. 105 ( 11 ) page： 453 - 459 2024.11

Generative AI and large language models in nuclear medicine: current status and future prospects. Reviewed

Annals of nuclear medicine Vol. 38 ( 11 ) page： 853 - 864 2024.11

Language：English Publishing type：Research paper (scientific journal)

This review explores the potential applications of Large Language Models (LLMs) in nuclear medicine, especially nuclear medicine examinations such as PET and SPECT, reviewing recent advancements in both fields. Despite the rapid adoption of LLMs in various medical specialties, their integration into nuclear medicine has not yet been sufficiently explored. We first discuss the latest developments in nuclear medicine, including new radiopharmaceuticals, imaging techniques, and clinical applications. We then analyze how LLMs are being utilized in radiology, particularly in report generation, image interpretation, and medical education. We highlight the potential of LLMs to enhance nuclear medicine practices, such as improving report structuring, assisting in diagnosis, and facilitating research. However, challenges remain, including the need for improved reliability, explainability, and bias reduction in LLMs. The review also addresses the ethical considerations and potential limitations of AI in healthcare. In conclusion, LLMs have significant potential to transform existing frameworks in nuclear medicine, making it a critical area for future research and development.

DOI： 10.1007/s12149-024-01981-x

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PubMed

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Papers - NAGANAWA, Shinji