研究者詳細 - 長縄　慎二

論文 - 長縄　慎二

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Response to letter to the editor from Dr. Muhammed Said Besler: 'the accuracy of large language models in RANZCR's clinical radiology exam sample questions' 査読有り

Nakaura, T; Naganawa, S

JAPANESE JOURNAL OF RADIOLOGY 42 巻 ( 9 ) 頁： 1081 - 1082 2024年9月

Imaging evaluation and volumetric measurement of the space surrounding the diploic veins 査読有り Open Access

Nakamichi, R; Taoka, T; Ito, R; Yoshida, T; Sone, M; Naganawa, S

JAPANESE JOURNAL OF RADIOLOGY 42 巻 ( 9 ) 頁： 953 - 961 2024年9月

Overview of Target-Oriented Project Group United for Nippon (TOP GUN): fostering interdisciplinary collaboration among young researchers in radiology on timely topics 査読有り Open Access

Kamagata, K; Naganawa, S

JAPANESE JOURNAL OF RADIOLOGY 42 巻 ( 9 ) 頁： 935 - 936 2024年9月

Recent trends in AI applications for pelvic MRI: a comprehensive review 査読有り

Tsuboyama, T; Yanagawa, M; Fujioka, T; Fujita, S; Ueda, D; Ito, R; Yamada, A; Fushimi, Y; Tatsugami, F; Nakaura, T; Nozaki, T; Kamagata, K; Matsui, Y; Hirata, K; Fujima, N; Kawamura, M; Naganawa, S

RADIOLOGIA MEDICA 129 巻 ( 9 ) 頁： 1369 - 1381 2024年9月

The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI 査読有り Open Access

Nakaura, T; Ito, R; Ueda, D; Nozaki, T; Fushimi, Y; Matsui, Y; Yanagawa, M; Yamada, A; Tsuboyama, T; Fujima, N; Tatsugami, F; Hirata, K; Fujita, S; Kamagata, K; Fujioka, T; Kawamura, M; Naganawa, S

JAPANESE JOURNAL OF RADIOLOGY 42 巻 ( 7 ) 頁： 685 - 696 2024年7月

Evaluation of alterations in interstitial fluid dynamics in cases of whole-brain radiation using the diffusion-weighted image analysis along the perivascular space method 査読有り国際誌 Open Access

Taoka, T; Ito, R; Nakamichi, R; Nakane, T; Kawamura, M; Ishihara, S; Ichikawa, K; Kawai, H; Naganawa, S

NMR IN BIOMEDICINE 37 巻 ( 7 ) 頁： e5030 2024年7月

Palliative radiotherapy for painful non-bone lesions in patients with advanced cancer: a single center retrospective study 査読有り Open Access

Yurika Shindo, Yutaro Koide, Naoya Nagai, Tomoki Kitagawa, Takahiro Aoyama, Hidetoshi Shimizu, Shingo Hashimoto, Hiroyuki Tachibana, Takeshi Kodaira, Shunichi Ishihara, Shinji Naganawa

JAPANESE JOURNAL OF RADIOLOGY 42 巻 ( 6 ) 頁： 656 - 661 2024年6月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Springer Science and Business Media LLC

Abstract

Purpose

This retrospective study aimed to assess the efficacy and safety of palliative radiotherapy for painful non-bone lesions in patients with advanced cancer.

Materials and methods

We enrolled patients with painful non-bone lesions who underwent conventional palliative radiotherapy between September 2018 and September 2022. The treatment targets included primary tumor lesions, lymph node metastases, non-bone hematogenous metastases, and other lesions. The primary endpoint was the overall pain response rate in evaluable patients, determined based on the International Consensus Pain Response Endpoint criteria. The secondary endpoints included overall survival, pain recurrence, and adverse events.

Results

Of the 420 screened patients, 142 received palliative radiotherapy for painful non-bone lesions, and 112 were evaluable. A pain response was achieved in 67 patients (60%) of the 112 evaluable patients within a median of 1.2 months. Among these patients, 25 exhibited complete response, 42 partial response, 18 indeterminate response, and 27 pain progression. The median survival time was 5.5 months, recorded at a median follow-up of 6.0 months, during which 67 patients died. Multivariate analysis identified poor performance status scores of 2–4, opioid use, and re-irradiation as independent factors associated with a reduced likelihood of achieving a pain response. Pain recurrence occurred in 18 patients over a median of 4.1 months. Seventeen patients had grade 1–2 adverse events, while none experienced grade 3 or higher toxicity.

Conclusion

Palliative radiotherapy can potentially be a safe and well-tolerated modality for managing painful non-bone lesions, with a low rate of adverse events.

DOI： 10.1007/s11604-024-01536-0

Open Access

Web of Science

PubMed

その他リンク： https://link.springer.com/article/10.1007/s11604-024-01536-0/fulltext.html

Direct Visualization of Tracer Permeation into the Endolymph in Human Patients Using MR Imaging 査読有り Open Access

Naganawa, S; Ito, R; Kawamura, M; Taoka, T; Yoshida, T; Sone, M

MAGNETIC RESONANCE IN MEDICAL SCIENCES 24 巻 ( 2 ) 頁： 253 - 261 2024年4月

Diffusion Tensor Image Analysis ALong the Perivascular Space (DTI-ALPS): Revisiting the Meaning and Significance of the Method 査読有り Open Access

Taoka, T; Ito, R; Nakamichi, R; Nakane, T; Kawai, H; Naganawa, S

MAGNETIC RESONANCE IN MEDICAL SCIENCES 23 巻 ( 3 ) 頁： 268 - 290 2024年4月

Assessing interstitial fluid dynamics in type 2 diabetes mellitus and prediabetes cases through diffusion tensor imaging analysis along the perivascular space 査読有り Open Access

Tuerxun, R; Kamagata, K; Saito, Y; Andica, C; Takabayashi, K; Uchida, W; Yoshida, S; Kikuta, J; Tabata, H; Naito, H; Someya, Y; Kaga, H; Miyata, M; Akashi, T; Wada, A; Taoka, T; Naganawa, S; Tamura, Y; Watada, H; Kawamori, R; Aoki, S

FRONTIERS IN AGING NEUROSCIENCE 16 巻頁： 1362457 2024年3月

Current Understanding of the Anatomy, Physiology, and Magnetic Resonance Imaging of Neurofluids: Update From the 2022 "ISMRM Imaging Neurofluids Study group" Workshop in Rome. 査読有り国際誌

Nivedita Agarwal, Laura D Lewis, Lydiane Hirschler, Leonardo Rivera Rivera, Shinji Naganawa, Swati Rane Levendovszky, Geir Ringstad, Marijan Klarica, Joanna Wardlaw, Costantino Iadecola, Cheryl Hawkes, Roxana Octavia Carare, Jack Wells, Erik N T P Bakker, Vartan Kurtcuoglu, Lynne Bilston, Maiken Nedergaard, Yuki Mori, Marcus Stoodley, Noam Alperin, Mony de Leon, Matthias J P van Osch

JOURNAL OF MAGNETIC RESONANCE IMAGING 59 巻 ( 2 ) 頁： 431 - 449 2024年2月

記述言語：英語掲載種別：研究論文（学術雑誌）

Neurofluids is a term introduced to define all fluids in the brain and spine such as blood, cerebrospinal fluid, and interstitial fluid. Neuroscientists in the past millennium have steadily identified the several different fluid environments in the brain and spine that interact in a synchronized harmonious manner to assure a healthy microenvironment required for optimal neuroglial function. Neuroanatomists and biochemists have provided an incredible wealth of evidence revealing the anatomy of perivascular spaces, meninges and glia and their role in drainage of neuronal waste products. Human studies have been limited due to the restricted availability of noninvasive imaging modalities that can provide a high spatiotemporal depiction of the brain neurofluids. Therefore, animal studies have been key in advancing our knowledge of the temporal and spatial dynamics of fluids, for example, by injecting tracers with different molecular weights. Such studies have sparked interest to identify possible disruptions to neurofluids dynamics in human diseases such as small vessel disease, cerebral amyloid angiopathy, and dementia. However, key differences between rodent and human physiology should be considered when extrapolating these findings to understand the human brain. An increasing armamentarium of noninvasive MRI techniques is being built to identify markers of altered drainage pathways. During the three-day workshop organized by the International Society of Magnetic Resonance in Medicine that was held in Rome in September 2022, several of these concepts were discussed by a distinguished international faculty to lay the basis of what is known and where we still lack evidence. We envision that in the next decade, MRI will allow imaging of the physiology of neurofluid dynamics and drainage pathways in the human brain to identify true pathological processes underlying disease and to discover new avenues for early diagnoses and treatments including drug delivery. Evidence level: 1 Technical Efficacy: Stage 3.

DOI： 10.1002/jmri.28759

Web of Science

PubMed

Revolutionizing radiation therapy: the role of AI in clinical practice 査読有り

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

Journal of Radiation Research 65 巻 ( 1 ) 頁： 1 - 9 2024年1月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Oxford University Press (OUP)

Abstract

This review provides an overview of the application of artificial intelligence (AI) in radiation therapy (RT) from a radiation oncologist’s perspective. Over the years, advances in diagnostic imaging have significantly improved the efficiency and effectiveness of radiotherapy. The introduction of AI has further optimized the segmentation of tumors and organs at risk, thereby saving considerable time for radiation oncologists. AI has also been utilized in treatment planning and optimization, reducing the planning time from several days to minutes or even seconds. Knowledge-based treatment planning and deep learning techniques have been employed to produce treatment plans comparable to those generated by humans. Additionally, AI has potential applications in quality control and assurance of treatment plans, optimization of image-guided RT and monitoring of mobile tumors during treatment. Prognostic evaluation and prediction using AI have been increasingly explored, with radiomics being a prominent area of research. The future of AI in radiation oncology offers the potential to establish treatment standardization by minimizing inter-observer differences in segmentation and improving dose adequacy evaluation. RT standardization through AI may have global implications, providing world-standard treatment even in resource-limited settings. However, there are challenges in accumulating big data, including patient background information and correlating treatment plans with disease outcomes. Although challenges remain, ongoing research and the integration of AI technology hold promise for further advancements in radiation oncology.

DOI： 10.1093/jrr/rrad090

Web of Science

PubMed

Fairness of artificial intelligence in healthcare: review and recommendations 査読有り

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

Japanese Journal of Radiology 42 巻 ( 1 ) 頁： 3 - 15 2024年1月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

In this review, we address the issue of fairness in the clinical integration of artificial intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a subfield of AI, progresses, concerns have arisen regarding the impact of AI biases and discrimination on patient health. This review aims to provide a comprehensive overview of concerns associated with AI fairness; discuss strategies to mitigate AI biases; and emphasize the need for cooperation among physicians, AI researchers, AI developers, policymakers, and patients to ensure equitable AI integration. First, we define and introduce the concept of fairness in AI applications in healthcare and radiology, emphasizing the benefits and challenges of incorporating AI into clinical practice. Next, we delve into concerns regarding fairness in healthcare, addressing the various causes of biases in AI and potential concerns such as misdiagnosis, unequal access to treatment, and ethical considerations. We then outline strategies for addressing fairness, such as the importance of diverse and representative data and algorithm audits. Additionally, we discuss ethical and legal considerations such as data privacy, responsibility, accountability, transparency, and explainability in AI. Finally, we present the Fairness of Artificial Intelligence Recommendations in healthcare (FAIR) statement to offer best practices. Through these efforts, we aim to provide a foundation for discussing the responsible and equitable implementation and deployment of AI in healthcare.

DOI： 10.1007/s11604-023-01474-3

Web of Science

Scopus

PubMed

The Glymphatic System in Humans: Investigations With Magnetic Resonance Imaging. 査読有り国際誌

Shinji Naganawa, Toshiaki Taoka, Rintaro Ito, Mariko Kawamura

Investigative radiology 59 巻 ( 1 ) 頁： 1 - 12 2024年1月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（学術雑誌）

The concept of the glymphatic system was proposed more than a decade ago as a mechanism for interstitial fluid flow and waste removal in the central nervous system. The function of the glymphatic system has been shown to be particularly activated during sleep. Dysfunction of the glymphatic system has been implicated in several neurodegenerative diseases. Noninvasive in vivo imaging of the glymphatic system is expected to be useful in elucidating the pathophysiology of these diseases. Currently, magnetic resonance imaging is the most commonly used technique to evaluate the glymphatic system in humans, and a large number of studies have been reported. This review provides a comprehensive overview of investigations of the human glymphatic system function using magnetic resonance imaging. The studies can be divided into 3 categories, including imaging without gadolinium-based contrast agents (GBCAs), imaging with intrathecal administration of GBCAs, and imaging with intravenous administration of GBCAs. The purpose of these studies has been to examine not only the interstitial fluid movement in the brain parenchyma, but also the fluid dynamics in the perivascular and subarachnoid spaces, as well as the parasagittal dura and meningeal lymphatics. Recent research has even extended to include the glymphatic system of the eye and the inner ear. This review serves as an important update and a useful guide for future research directions.

DOI： 10.1097/RLI.0000000000000969

Web of Science

PubMed

Glymphatic System Dysfunction in Myelin Oligodendrocyte Glycoprotein Immunoglobulin G Antibody-Associated Disorders: Association with Clinical Disability. 査読有り国際誌

Akifumi Hagiwara, Yuji Tomizawa, Yasunobu Hoshino, Kazumasa Yokoyama, Koji Kamagata, Towa Sekine, Kaito Takabayashi, Moto Nakaya, Tomoko Maekawa, Toshiaki Akashi, Akihiko Wada, Toshiaki Taoka, Shinji Naganawa, Nobutaka Hattori, Shigeki Aoki

AJNR. American journal of neuroradiology 45 巻 ( 1 ) 頁： 66 - 71 2024年1月

記述言語：英語掲載種別：研究論文（学術雑誌）

BACKGROUND AND PURPOSE: Impaired glymphatic function has been suggested to be implicated in the pathophysiology of MS and aquaporin-4 immunoglobulin G-positive neuromyelitis optica spectrum disorder. This study aimed to investigate the interstitial fluid dynamics in the brain in patients with myelin oligodendrocyte glycoprotein antibody disorders (MOGAD), another demyelinating disorder, using a noninvasive imaging technique called the diffusivity along the perivascular space (ALPS) index. MATERIALS AND METHODS: A prospective study was conducted on 16 patients with MOGAD in remission and 22 age- and sex-matched healthy control subjects. MR imaging was performed using a 3T scanner, and the ALPS index was calculated using diffusion MR imaging data with a b-value of 1000 s/mm2. The ALPS index and gray matter volumes were compared between the 2 groups, and these parameters were correlated with the Expanded Disability Status Scale. RESULTS: The mean ALPS index of patients with MOGAD was significantly lower than that of healthy controls (Cohen d = 0.93, false discovery rate-corrected P = .02). The lower mean ALPS index was significantly associated with a worse Expanded Disability Status Scale score (Spearman ρ = -0.51; 95% CI, -0.85 to -0.02; P = .03). However, cortical volume and deep gray matter volume were not significantly different between the 2 groups, and they were not correlated with the Expanded Disability Status Scale. CONCLUSIONS: This study suggests that patients with MOGAD may have impaired glymphatic function, as measured by the ALPS index, which is associated with patient disability. Further study is warranted with a larger sample size.

DOI： 10.3174/ajnr.A8066

Web of Science

PubMed

Association between the Putative Meningeal Lymphatics at the Posterior Wall of the Sigmoid Sinus and Delayed Contrast-agent Elimination from the Cerebrospinal Fluid 査読有り Open Access

Naganawa, S; Ito, R; Kawamura, M; Taoka, T; Yoshida, T; Sone, M

MAGNETIC RESONANCE IN MEDICAL SCIENCES 23 巻 ( 1 ) 頁： 80 - 91 2024年

Assessing the Real-World, Long-Term Impact of Lemborexant on Sleep Quality in a Home-Based Clinical Study 査読有り国際誌 Open Access

Miyata, S; Iwamoto, K; Okada, I; Fujimoto, A; Kogo, Y; Mori, D; Amano, M; Matsuyama, N; Nishida, K; Ando, M; Taoka, T; Naganawa, S; Ozaki, N

NATURE AND SCIENCE OF SLEEP 16 巻頁： 291 - 303 2024年

Measurement of solid size in early-stage lung adenocarcinoma by virtual 3D thin-section CT applied artificial intelligence. 査読有り国際誌

Shingo Iwano, Shinichiro Kamiya, Rintaro Ito, Akira Kudo, Yoshiro Kitamura, Keigo Nakamura, Shinji Naganawa

Scientific reports 13 巻 ( 1 ) 頁： 21709 - 21709 2023年12月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

An artificial intelligence (AI) system that reconstructs virtual 3D thin-section CT (TSCT) images from conventional CT images by applying deep learning was developed. The aim of this study was to investigate whether virtual and real TSCT could measure the solid size of early-stage lung adenocarcinoma. The pair of original thin-CT and simulated thick-CT from the training data with TSCT images (thickness, 0.5-1.0 mm) of 2700 pulmonary nodules were used to train the thin-CT generator in the generative adversarial network (GAN) framework and develop a virtual TSCT AI system. For validation, CT images of 93 stage 0-I lung adenocarcinomas were collected, and virtual TSCTs were reconstructed from conventional 5-mm thick-CT images using the AI system. Two radiologists measured and compared the solid size of tumors on conventional CT and virtual and real TSCT. The agreement between the two observers showed an almost perfect agreement on the virtual TSCT for solid size measurements (intraclass correlation coefficient = 0.967, P < 0.001, respectively). The virtual TSCT had a significantly stronger correlation than that of conventional CT (P = 0.003 and P = 0.001, respectively). The degree of agreement between the clinical T stage determined by virtual TSCT and the clinical T stage determined by real TSCT was excellent in both observers (k = 0.882 and k = 0.881, respectively). The AI system developed in this study was able to measure the solid size of early-stage lung adenocarcinoma on virtual TSCT as well as on real TSCT.

DOI： 10.1038/s41598-023-48755-5

Web of Science

PubMed

第1章　画像診断機器　【基調論文】最新医療機器の現況と将来的方向性 2024年　最新医療機器の現状と展望 CTやMRIなどの画像診断装置の技術的到達点への評価と課題査読有り

長縄慎二

月間新医療データブック・シリーズ　医療機器システム白書 2024 頁： 8 - 11 2023年12月

公益社団法人愛知県医師会「現代医学」誌70巻号の特集テーマ「がん検診」座談会招待有り査読有り

長縄慎二

現代醫学 70 巻 ( 2 ) 頁： 1 - 13 2023年12月

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