{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T06:15:57Z","timestamp":1787984157107,"version":"build-2784847793"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T00:00:00Z","timestamp":1779667200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T00:00:00Z","timestamp":1779667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Jpn J Radiol"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to investigate the difference in T1, T2, and proton density (PD) values derived from synthetic magnetic resonance imaging (MRI) across various meningioma subtypes and their potential as imaging biomarkers for the World Health Organization (WHO) grade classification of meningioma.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>This study retrospectively analyzed the data of 100 consecutive meningioma cases. Across subtypes and WHO grades, intratumoral T1, T2, PD, and apparent diffusion coefficient (ADC) values, along with tumor volume, were measured and compared, and the discriminative performance of each parameter was evaluated using the area under the receiver operating characteristic curve (AUC). Simple and multiple regression analyses were conducted to assess the associations between quantitative imaging parameters and atypical pathological features (4\u2009\u2265\u2009mitotic findings\/high power field; brain invasion; increased cellularity; small cells with high nuclear-to-cytoplasmic ratio; prominent nucleoli; sheeting; necrosis).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among all subtypes, angiomatous, microcystic, and metaplastic meningioma demonstrated remarkable high T1 and T2 values. The AUCs for differentiating these subtypes from other subtypes were 0.97 for T1 value and 0.99 for T2 value. Volume (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), T1 value (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), T2 value (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.002), and ADC value (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.035) were significantly higher in high grade meningioma than low grade meningioma, with an AUC of 0.83 achieved by combining volume, T1, and ADC value. Multiple regression analysis revealed that volume was significantly associated with necrosis (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.018), whereas T1 and T2 values were significantly associated with sheeting (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.047 and 0.025 for T1 and T2).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>T1 and T2 mappings may serve as useful quantitative imaging biomarkers for meningioma grading.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11604-026-02014-5","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T06:05:04Z","timestamp":1779689104000},"page":"1607-1615","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Preoperative prediction of meningioma grade based on synthetic MRI quantitative T1 and T2 mapping"],"prefix":"10.1007","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7071-9081","authenticated-orcid":false,"given":"Tsubasa","family":"Nakano","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junki","family":"Kamizono","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomohito","family":"Hasegawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masanori","family":"Nakajo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kiyohisa","family":"Kamimura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryota","family":"Nakanosono","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroaki","family":"Nagano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koji","family":"Takumi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryoji","family":"Yamagishi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fumitaka","family":"Ejima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fumiko","family":"Kanzaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nayuta","family":"Higa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hajime","family":"Yonezawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mari","family":"Kirishima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ikumi","family":"Kitazono","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takashi","family":"Yoshiura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,25]]},"reference":[{"key":"2014_CR1","doi-asserted-by":"publisher","first-page":"1535","DOI":"10.1016\/S0140-6736(04)16153-9","volume":"363","author":"IR Whittle","year":"2004","unstructured":"Whittle IR, Smith C, Navoo P, Collie D, Meningiomas. Lancet. 2004;363:1535\u201343.","journal-title":"Lancet"},{"key":"2014_CR2","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","volume":"23","author":"DN Louis","year":"2021","unstructured":"Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Branger-Figarella D, et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. 2021;23:1231\u201351.","journal-title":"Neuro Oncol"},{"key":"2014_CR3","doi-asserted-by":"crossref","unstructured":"Hallak H, Mantziaris G, Pikis S, Islim AI, Peker S, Samanci Y et al. A retrospective comparison of active surveillance to stereotactic radiosurgery for the management of elderly patients with an incidental meningioma. Acta Neurochir (Wien). 2025:167:37.","DOI":"10.1007\/s00701-025-06452-4"},{"key":"2014_CR4","doi-asserted-by":"publisher","first-page":"54","DOI":"10.14791\/btrt.2017.5.2.54","volume":"5","author":"HS Ryu","year":"2017","unstructured":"Ryu HS, Moon KS, Lee KH, Jang WY, Jung TY, Kim IY, et al. Recurred intracranial meningioma: a retrospective analysis for treatment outcome and prognostic factor. Brain Tumor Res Treat. 2017;5:54\u201363.","journal-title":"Brain Tumor Res Treat"},{"key":"2014_CR5","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1227\/01.NEU.0000330399.55586.63","volume":"64","author":"MK Aghi","year":"2009","unstructured":"Aghi MK, Carter BS, Cosgrove GR, Ojemann RG, Amin-Hanjani S, Martuza R, et al. Long-term recurrence rates of atypical meningiomas after gross total resection with or without postoperative adjuvant radiation. Neurosurgery. 2009;64:56\u201360.","journal-title":"Neurosurgery"},{"key":"2014_CR6","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1136\/jnnp.2007.121582","volume":"79","author":"S-Y Yang","year":"2008","unstructured":"Yang S-Y, Park C-K, Park S-H, Kim DG, Chung YS, Jung H-W. Atypical and anaplastic meningiomas: prognostic implications of clinicopathological features. J Neurol Neurosurg Psychiatry. 2008;79:574\u201380.","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"2014_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/1533033820983287","volume":"19","author":"J Yu","year":"2020","unstructured":"Yu J, Chen FF, Zhang HW, Zhang H, Luo S, Huang G, et al. Comparative analysis of the MRI characteristics of meningiomas according to the 2016 WHO pathological classification. Technol Cancer Res Treat. 2020;19:1\u20139.","journal-title":"Technol Cancer Res Treat"},{"key":"2014_CR8","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1007\/s00234-024-03404-0","volume":"66","author":"T Upreti","year":"2024","unstructured":"Upreti T, Dube S, Pareek V, Sinha N, Shankar J. Meningioma grading via diagnostic imaging: a systematic review and meta-analysis. Neuroradiology. 2024;66:1301\u201310.","journal-title":"Neuroradiology"},{"key":"2014_CR9","doi-asserted-by":"publisher","first-page":"e89815","DOI":"10.1016\/j.crad.2019.07.020","volume":"74","author":"F Salah","year":"2019","unstructured":"Salah F, Tabbarah A, ALArab y N, Asmar K, Tamin H, Makki M, et al. Can CT and MRI features differentiate benign from malignant meningiomas? Clin Radiol. 2019;74:e89815\u201323.","journal-title":"Clin Radiol"},{"key":"2014_CR10","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1016\/j.acra.2019.04.012","volume":"27","author":"M Bohara","year":"2020","unstructured":"Bohara M, Nakajo M, Kamimura K, Yoneyama T, Fukukura Y, Kiyao Y, et al. Histological grade of meningioma: prediction by intravoxel incoherent motion histogram parameters. Acad Radiol. 2020;27:342\u201353.","journal-title":"Acad Radiol"},{"key":"2014_CR11","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1097\/RLI.0000000000000365","volume":"52","author":"A Hagiwara","year":"2017","unstructured":"Hagiwara A, Warntjes M, Hori M, Andica C, Nakazawa M, Kumamaru-Kunishima K, et al. SyMRI of the brain: rapid quantification of relaxation rates and proton density, with synthetic MRI, automatic brain segmentation, and myelin measurement. Invest Radiol. 2017;52:647\u201357.","journal-title":"Invest Radiol"},{"key":"2014_CR12","doi-asserted-by":"publisher","first-page":"1010643","DOI":"10.3389\/fonc.2022.1010643","volume":"12","author":"M Micek","year":"2022","unstructured":"Micek M, Aebisher D, Sur\u00f3wka J, Aebisheret-Bartusik D, Madera M. Applications of T1 and T2 relaxation time calculation in tissue differentiation and cancer diagnostics\u2014a systematic literature review. Front Oncol. 2022;12:1010643.","journal-title":"Front Oncol"},{"key":"2014_CR13","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11060-019-03104-3","volume":"142","author":"AI Islim","year":"2019","unstructured":"Islim AI, Dona-Kolamunnage R, Mohan M, Moon RDC, Crofton A, Haylock BJ, et al. A prognostic model to personalize monitoring regimes for patients with incidental asymptomatic meningiomas. Neuro Oncol. 2019;142:211\u201321.","journal-title":"Neuro Oncol"},{"key":"2014_CR14","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1148\/radiology.170.3.2916043","volume":"170","author":"AD Elster","year":"1989","unstructured":"Elster AD, Challa VR, Gilbert TH, Richardson DN, Contento JC. Meningiomas: MR and histopathologic features. Radiology. 1989;170:857\u201362.","journal-title":"Radiology"},{"key":"2014_CR15","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s11604-016-0550-6","volume":"34","author":"A Kunimatsu","year":"2016","unstructured":"Kunimatsu A, Kunimatsu N, Kamiya K, Kastura M, Mori H, Ohmoto K. Variants of meningiomas: a review of imaging findings and clinical features. Jpn J Radiol. 2016;34:459\u201369.","journal-title":"Jpn J Radiol"},{"key":"2014_CR16","doi-asserted-by":"publisher","first-page":"7874","DOI":"10.21037\/qims-2025-1041","volume":"15","author":"Z Cai","year":"2025","unstructured":"Cai Z, Wong YH, So TY. Multisequence magnetic resonance imaging habitat analysis for pre-operative meningioma grade prediction. Quant Imaging Med Surg. 2025;15:7874\u201384.","journal-title":"Quant Imaging Med Surg"},{"key":"2014_CR17","doi-asserted-by":"publisher","first-page":"971","DOI":"10.3171\/2016.9.JNS161669","volume":"127","author":"EJ Lee","year":"2017","unstructured":"Lee EJ, Kim JH, Park ES, Kim YH, Lee JK, Hong SH, et al. A novel weighted scoring system for estimating the risk of rapid growth in untreated intracranial meningiomas. J Neurosurg. 2017;127:971\u201380.","journal-title":"J Neurosurg"},{"key":"2014_CR18","doi-asserted-by":"publisher","first-page":"206","DOI":"10.3171\/2024.4.JNS2446","volume":"142","author":"L H\u00e4ni","year":"2025","unstructured":"H\u00e4ni L, Thomann P, Maragkou T, Vulcu S, Sch\u00fctz A, Jesse CM, et al. Velocity and pattern of growth of intracranial meningiomas. J Neurosurg. 2025;142:206\u201313.","journal-title":"J Neurosurg"},{"key":"2014_CR19","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1227\/neu.0000000000003536","volume":"98","author":"PR Wagle","year":"2026","unstructured":"Wagle PR, Loeschner D, Todorov B, Awuah MY, Lobsien D, Rosahl SK, et al. Proposal of a multiparametric meningioma (MEN-CCVol) score for preoperative discrimination of World Health Organization grade 2\/3 from grade 1 intracranial meningiomas based on patient and MRI characteristics. Neurosurgery. 2026;98:221\u201330.","journal-title":"Neurosurgery"},{"key":"2014_CR20","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1007\/s11060-019-03293-x","volume":"145","author":"A Ressel","year":"2019","unstructured":"Ressel A, Fichte S, Brodhun M, Rosahl S, Gerlach R. WHO grade of intracranial meningiomas differs with respect to patient\u2019s age, location, tumor size and peritumoral edema. J Neurooncol. 2019;145:277\u201386.","journal-title":"J Neurooncol"},{"key":"2014_CR21","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1007\/s00330-022-09026-5","volume":"33","author":"T Cao","year":"2023","unstructured":"Cao T, Jiang R, Zheng L, Zhang R, Chen X, Wang Z, et al. T1 and ADC histogram parameters may be an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma. Eur Radiol. 2023;33:258\u201369.","journal-title":"Eur Radiol"},{"key":"2014_CR22","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1186\/s40644-022-00461-7","volume":"22","author":"J Li","year":"2022","unstructured":"Li J, Gao X, Nickel MD, Cheng J, Zhu J. Native T1 mapping for differentiating the histopathologic type, grade, and stage of rectal adenocarcinoma: a pilot study. Cancer Imaging. 2022;22:30.","journal-title":"Cancer Imaging"},{"key":"2014_CR23","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1097\/RLI.0000000000000515","volume":"54","author":"LC Adams","year":"2019","unstructured":"Adams LC, Ralla B, Jurmeister P, Bressem KK, Farlenkamp UL, Hamm B, et al. Native T1 mapping as an in vivo biomarker for the identification of higher-grade renal cell carcinoma: correlation with histopathological findings. Invest Radiol. 2019;54:118\u201328.","journal-title":"Invest Radiol"},{"key":"2014_CR24","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1186\/s40644-020-00365-4","volume":"20","author":"T Meng","year":"2020","unstructured":"Meng T, He N, Liu K, Ke L, Liu H, Zhong L, et al. The diagnostic performance of quantitative mapping in breast cancer patients: a preliminary study using synthetic MRI. Cancer Imaging. 2020;20:88.","journal-title":"Cancer Imaging"},{"key":"2014_CR25","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1007\/s11604-024-01578-4","volume":"42","author":"K Takumi","year":"2024","unstructured":"Takumi K, Nakanosono R, Nagano H, Hakamada H, Kanzaki F, Kamimura K, et al. Multiparametric approach with synthetic MR imaging for diagnosing salivary gland lesions. Jpn J Radiol. 2024;42:983\u201392.","journal-title":"Jpn J Radiol"},{"key":"2014_CR26","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s12880-023-00968-w","volume":"23","author":"F Yang","year":"2023","unstructured":"Yang F, Li Y, Li X, Yu X, Zhao Y, Li L, et al. The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study. BMC Med Imaging. 2023;23:15.","journal-title":"BMC Med Imaging"},{"key":"2014_CR27","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1111\/cpf.12803","volume":"43","author":"L Yuan","year":"2023","unstructured":"Yuan L, Zhao P, Lin X, Yu T, Diao R, Ning G. T1 mapping and reduced field-of\u2010view DWI at 3.0 T MRI for differentiation of thyroid papillary carcinoma from nodular goiter. Clin Physiol Funct Imaging. 2023;43:137\u201345.","journal-title":"Clin Physiol Funct Imaging"},{"key":"2014_CR28","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1186\/s12880-022-00873-8","volume":"22","author":"F Wang","year":"2022","unstructured":"Wang F, Yang Q, Zhang Y, Liu J, Liu M, Zhu J. 3D variable flip angle T1 mapping for differentiating benign and malignant liver lesions at 3T: comparison with diffusion weighted imaging. BMC Med Imaging. 2022;22:146.","journal-title":"BMC Med Imaging"},{"key":"2014_CR29","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1002\/jmri.27075","volume":"52","author":"Y Cui","year":"2020","unstructured":"Cui Y, Han S, Liu M, Wu P, Zhang W, Zhang J, et al. Diagnosis and grading of prostate cancer by relaxation maps from synthetic MRI. J Magn Reson Imaging. 2020;52:552\u201364.","journal-title":"J Magn Reson Imaging"},{"key":"2014_CR30","doi-asserted-by":"publisher","first-page":"2514","DOI":"10.1007\/s00330-012-2519-x","volume":"22","author":"A Cieszanowski","year":"2012","unstructured":"Cieszanowski A, Grodzicka-Anysz A, Szeszkowski W, Kaczynski B, Maj E, Gornicka B, et al. Characterization of focal liver lesions using quantitative techniques: comparison of apparent diffusion coefficient values and T2 relaxation times. Eur Radiol. 2012;22:2514\u201324.","journal-title":"Eur Radiol"},{"key":"2014_CR31","doi-asserted-by":"publisher","first-page":"20120469","DOI":"10.1259\/bjr.20120469","volume":"86","author":"CJ Simpkin","year":"2013","unstructured":"Simpkin CJ, Morgan VA, Giles SL, Riches SF, Parker C, deSouza NM. Relationship between T2 relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume. Br J Radiol. 2013;86:20120469.","journal-title":"Br J Radiol"},{"key":"2014_CR32","doi-asserted-by":"publisher","first-page":"538845","DOI":"10.3389\/fonc.2020.538845","volume":"10","author":"Z Shao","year":"2020","unstructured":"Shao Z, Liu L, Zheng Y, Tu S, Pan Y, Yan S, et al. Molecular mechanism and approach in progression of meningioma. Front Oncol. 2020;10:538845.","journal-title":"Front Oncol"},{"key":"2014_CR33","doi-asserted-by":"publisher","first-page":"4558","DOI":"10.1038\/s41598-023-31644-2","volume":"13","author":"G Cao","year":"2023","unstructured":"Cao G, Gao S, Xiong B. Application of quantitative T1, T2 and T2* mapping magnetic resonance imaging in cartilage degeneration of the shoulder joint. Sci Rep. 2023;13:4558.","journal-title":"Sci Rep"},{"key":"2014_CR34","doi-asserted-by":"publisher","first-page":"e549","DOI":"10.5114\/pjr.2019.91375","volume":"84","author":"S Mittal","year":"2019","unstructured":"Mittal S, Pradhan G, Singh S, Batra R. T1 and T2 mapping of articular cartilage and menisci in early osteoarthritis of the knee using 3-Tesla magnetic resonance imaging. Pol J Radiol. 2019;84:e549\u201364.","journal-title":"Pol J Radiol"},{"key":"2014_CR35","doi-asserted-by":"publisher","first-page":"471","DOI":"10.3174\/ajnr.A6930","volume":"42","author":"S Fujita","year":"2021","unstructured":"Fujita S, Yokoyama K, Hagiwara A, Kato S, Andica C, Kamagata K, et al. 3D quantitative synthetic MRI in the evaluation of multiple sclerosis lesions. AJNR Am J Neuroradiol. 2021;42:471\u20138.","journal-title":"AJNR Am J Neuroradiol"}],"container-title":["Japanese Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11604-026-02014-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11604-026-02014-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11604-026-02014-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T05:17:29Z","timestamp":1787980649000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11604-026-02014-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,25]]},"references-count":35,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["2014"],"URL":"https:\/\/doi.org\/10.1007\/s11604-026-02014-5","relation":{},"ISSN":["1867-1071","1867-108X"],"issn-type":[{"value":"1867-1071","type":"print"},{"value":"1867-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,25]]},"assertion":[{"value":"25 March 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 May 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no competing interests.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Kagoshima University Hospital.","order":2,"name":"Ethics","label":"Ethics approval","group":{"name":"EthicsHeading","label":"Declarations"}}]}}