{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T23:07:16Z","timestamp":1775516836715,"version":"3.50.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Fujian Medical University\u2019s Startup Fund for Scientific Research","award":["2023QH1039; 2024QH1060"],"award-info":[{"award-number":["2023QH1039; 2024QH1060"]}]},{"name":"Guidance Project of Fujian Science and Technology Program","award":["2022Y0024"],"award-info":[{"award-number":["2022Y0024"]}]},{"name":"Hong Kong GRF Project","award":["14112521"],"award-info":[{"award-number":["14112521"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Imaging"],"DOI":"10.1186\/s12880-025-01980-y","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T13:13:15Z","timestamp":1761570795000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A novel MRI diffusion metric \u2018slow diffusion coefficient\u2019 (SDC) for diagnosing isocitrate dehydrogenase (IDH) genotype in diffuse gliomas: initial promising results"],"prefix":"10.1186","volume":"25","author":[{"given":"Wan-Yi","family":"Zheng","sequence":"first","affiliation":[]},{"given":"Yu-Ting","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Ying-Ying","family":"He","sequence":"additional","affiliation":[]},{"given":"Ruo-Lan","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Ben-Heng","family":"Xiao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6959-0027","authenticated-orcid":false,"given":"Ri-Feng","family":"Jiang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5697-0717","authenticated-orcid":false,"given":"Y\u00ec Xi\u00e1ng J.","family":"W\u00e1ng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"1980_CR1","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, Figarella-Branger 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"},{"issue":"1","key":"1980_CR2","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s11060-014-1614-z","volume":"121","author":"S Lee","year":"2015","unstructured":"Lee S, Choi SH, Ryoo I, Yoon TJ, Kim TM, Lee SH, et al. Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1\/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging. J Neurooncol. 2015;121(1):141\u201350.","journal-title":"J Neurooncol"},{"key":"1980_CR3","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1007\/s00062-016-0510-7","volume":"27","author":"C Federau","year":"2017","unstructured":"Federau C, Cerny M, Roux M, Mosimann PJ, Maeder P, Meuli R, et al. IVIM perfusion fraction is prognostic for survival in brain glioma. Clin Neuroradiol. 2017;27:485\u201392.","journal-title":"Clin Neuroradiol"},{"key":"1980_CR4","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1002\/jmri.25191","volume":"44","author":"N Shen","year":"2016","unstructured":"Shen N, Zhao L, Jiang J, Jiang R, Su C, Zhang S, Tang X, Zhu W. Intravoxel incoherent motion diffusion-weighted imaging analysis of diffusion and microperfusion in grading gliomas and comparison with arterial spin labeling for evaluation of tumor perfusion. J Magn Reson Imaging. 2016;44:620\u201332.","journal-title":"J Magn Reson Imaging"},{"key":"1980_CR5","doi-asserted-by":"publisher","first-page":"301","DOI":"10.2478\/raon-2020-0037","volume":"54","author":"X Wang","year":"2020","unstructured":"Wang X, Cao M, Chen H, Ge J, Suo S, Zhou Y. Simplified perfusion fraction from diffusion-weighted imaging in preoperative prediction of IDH1 mutation in WHO grade II-III gliomas: comparison with dynamic contrast-enhanced and intravoxel incoherent motion MRI. Radiol Oncol. 2020;54:301\u201310. d.","journal-title":"Radiol Oncol"},{"key":"1980_CR6","doi-asserted-by":"publisher","first-page":"e6517","DOI":"10.1016\/j.crad.2019.03.020","volume":"74","author":"X Wang","year":"2019","unstructured":"Wang X, Chen XZ, Shi L, Dai JP. Glioma grading and IDH1 mutational status: assessment by intravoxel incoherent motion MRI. Clin Radiol. 2019;74:e6517\u201365114.","journal-title":"Clin Radiol"},{"key":"1980_CR7","doi-asserted-by":"publisher","first-page":"127","DOI":"10.21037\/qims.2019.01.07","volume":"9","author":"YXJ W\u00e1ng","year":"2019","unstructured":"W\u00e1ng YXJ. Living tissue intravoxel incoherent motion (IVIM) diffusion MR analysis without b\u2009=\u20090 image: an example for liver fibrosis evaluation. Quant Imaging Med Surg. 2019;9:127\u201333.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR8","doi-asserted-by":"publisher","first-page":"1710","DOI":"10.21037\/qims-2024-2693","volume":"15","author":"FZ Ma","year":"2025","unstructured":"Ma FZ, Xiao BH, W\u00e1ng YXJ. MRI signal simulation of liver DDVD (diffusion derived \u2018vessel density\u2019) with multiple compartments diffusion model. Quant Imaging Med Surg. 2025;15:1710\u20138.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR9","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1177\/2472630320915838","volume":"25","author":"BH Xiao","year":"2020","unstructured":"Xiao BH, Huang H, Wang LF, Qiu SW, Guo SW, W\u00e1ng YXJ. Diffusion MRI derived per area vessel density as a surrogate biomarker for detecting viral hepatitis B-Induced liver fibrosis: A Proof-of-Concept study. SLAS Technol. 2020;25:474\u201383.","journal-title":"SLAS Technol"},{"key":"1980_CR10","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1186\/s12880-025-01605-4","volume":"25","author":"CX Ni","year":"2025","unstructured":"Ni CX, Lin RL, Yao DQ, Ma FZ, Shi YT, He YY, Song Y, Yang G, Jiang RF, W\u00e1ng YXJ. Magnetic resonance diffusion-derived vessel density (DDVD) as a valuable tissue perfusion biomarker for isocitrate dehydrogenase genotyping in diffuse gliomas. BMC Med Imaging. 2025;25:79.","journal-title":"BMC Med Imaging"},{"key":"1980_CR11","doi-asserted-by":"publisher","first-page":"8873","DOI":"10.21037\/qims-23-1342","volume":"13","author":"YXJ W\u00e1ng","year":"2023","unstructured":"W\u00e1ng YXJ, Ma FZ. A tri-phasic relationship between T2 relaxation time and magnetic resonance imaging (MRI)- derived apparent diffusion coefficient (ADC). Quant Imaging Med Surg. 2023;13:8873\u201380.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR12","doi-asserted-by":"publisher","first-page":"3779","DOI":"10.21037\/qims-2025-195","volume":"15","author":"YXJ W\u00e1ng","year":"2025","unstructured":"W\u00e1ng YXJ. An explanation for the triphasic dependency of apparent diffusion coefficient (ADC) on T2 relaxation time: the multiple T2 compartments model. Quant Imaging Med Surg. 2025;15:3779\u201391.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR13","doi-asserted-by":"publisher","first-page":"e4654","DOI":"10.1002\/nbm.4654","volume":"35","author":"L Egnell","year":"2022","unstructured":"Egnell L, Jerome NP, Andreassen MMS, Bathen TF, Goa PE. Effects of echo time on IVIM quantifications of locally advanced breast cancer in clinical diffusion-weighted MRI at 3 T. NMR Biomed. 2022;35:e4654.","journal-title":"NMR Biomed"},{"key":"1980_CR14","doi-asserted-by":"publisher","first-page":"7657","DOI":"10.21037\/qims-23-1392","volume":"13","author":"YXJ W\u00e1ng","year":"2023","unstructured":"W\u00e1ng YXJ, Aparisi G\u00f3mez MP, Ruiz Santiago F, Bazzocchi A. The relevance of T2 relaxation time in interpreting MRI apparent diffusion coefficient (ADC) map for musculoskeletal structures. Quant Imaging Med Surg. 2023;13:7657\u201366.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR15","doi-asserted-by":"publisher","DOI":"10.21037\/qims-2025-537","author":"FY Xu","year":"2025","unstructured":"Xu FY, Xiao BH, W\u00e1ng YXJ. The rationale for proposing a magnetic resonance slow diffusion metric and its proof-of-concept testing showing spleen parenchyma and hepatocellular carcinoma have faster diffusion than liver parenchyma. Quant Imaging Med Surg. 2025. https:\/\/doi.org\/10.21037\/qims-2025-537.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR16","doi-asserted-by":"publisher","first-page":"74","DOI":"10.21037\/qims-24-2411","volume":"15","author":"ZG Ju","year":"2025","unstructured":"Ju ZG, Leng XM, Xiao BH, Sun MH, Huang H, Hu GW, Zhang G, Sun JH, Zhu MSY, Guglielmi G, W\u00e1ng YXJ. Influences of the second motion probing gradient b-value and T2 relaxation time on magnetic resonance diffusion-derived \u2018vessel density\u2019 (DDVD) calculation: the examples of liver, spleen, and liver simple cyst. Quant Imaging Med Surg. 2025;15:74\u201387.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR17","doi-asserted-by":"publisher","first-page":"2646","DOI":"10.1007\/s00261-017-1194-4","volume":"42","author":"J Yeung","year":"2017","unstructured":"Yeung J, Sivarajan S, Treibel TA, Rosmini S, Fontana M, Gillmore JD, Hawkins PN, Punwani S, Moon JC, Taylor SA, Bandula S. Measurement of liver and spleen interstitial volume in patients with systemic amyloid light-chain amyloidosis using equilibrium contrast CT. Abdom Radiol (NY). 2017;42:2646\u201351.","journal-title":"Abdom Radiol (NY)"},{"key":"1980_CR18","doi-asserted-by":"publisher","first-page":"8881","DOI":"10.21037\/qims-23-1363","volume":"13","author":"YXJ W\u00e1ng","year":"2023","unstructured":"W\u00e1ng YXJ. The very low magnetic resonance imaging apparent diffusion coefficient (ADC) measure of abscess is likely due to pus\u2019s specific T2 relaxation time. Quant Imaging Med Surg. 2023;13:8881\u20135.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR19","doi-asserted-by":"publisher","first-page":"6547","DOI":"10.21037\/qims-2025-1010","volume":"15","author":"GH Ling","year":"2025","unstructured":"Ling GH, W\u00e1ng YXJ. MRI slow diffusion coefficient (SDC) shows liver pyogenic abscess has faster diffusion than adjacent liver parenchyma. Quant Imaging Med Surg. 2025;15:6547\u201351.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR20","doi-asserted-by":"publisher","first-page":"1111","DOI":"10.1007\/s00234-023-03154-5","volume":"65","author":"L Siakallis","year":"2023","unstructured":"Siakallis L, Topriceanu CC, Panovska-Griffiths J, Bisdas S. The role of DSC MR perfusion in predicting IDH mutation and 1p19q codeletion status in gliomas: meta-analysis and technical considerations. Neuroradiology. 2023;65:1111\u201326.","journal-title":"Neuroradiology"},{"key":"1980_CR21","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.clineuro.2013.11.003","volume":"116","author":"GA Alexiou","year":"2014","unstructured":"Alexiou GA, Zikou A, Tsiouris S, Goussia A, Kosta P, Papadopoulos A, et al. Correlation of diffusion tensor, dynamic susceptibility contrast MRI and (99m)Tc-Tetrofosmin brain SPECT with tumour grade and Ki-67 immunohistochemistry in glioma. Clin Neurol Neurosurg. 2014;116:41\u20135.","journal-title":"Clin Neurol Neurosurg"},{"key":"1980_CR22","doi-asserted-by":"publisher","DOI":"10.21037\/jgo-2025-424","author":"GW Hu","year":"2025","unstructured":"Hu GW, Li CY, Ling GH, Zheng CJ, Zhu MSY, Sabarudin A, Duan XH, Li XM, Shen J, W\u00e1ng YXJ. A combination of MRI diffusion-derived vessel density (DDVD) and slow diffusion coefficient (SDC) can reliably diagnose liver hemangioma: a testing of three centers\u2019 data. J Gastrointest Oncol. 2025. https:\/\/doi.org\/10.21037\/jgo-2025-424.","journal-title":"J Gastrointest Oncol"},{"key":"1980_CR23","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1002\/jmri.20335","volume":"21","author":"J Oh","year":"2005","unstructured":"Oh J, Cha S, Aiken AH, Han ET, Crane JC, Stainsby JA, Wright GA, Dillon WP, Nelson SJ. Quantitative apparent diffusion coefficients and T2 relaxation times in characterizing contrast enhancing brain tumors and regions of peritumoral edema. J Magn Reson Imaging. 2005;21:701\u20138.","journal-title":"J Magn Reson Imaging"},{"key":"1980_CR24","doi-asserted-by":"publisher","first-page":"18801","DOI":"10.1038\/s41598-022-23527-9","volume":"12","author":"T Sanada","year":"2022","unstructured":"Sanada T, Yamamoto S, Sakai M, Umehara T, Sato H, Saito M, Mitsui N, Hiroshima S, Anei R, Kanemura Y, Tanino M, Nakanishi K, Kishima H, Kinoshita M. Correlation of T1- to T2-weighted signal intensity ratio with T1- and T2-relaxation time and IDH mutation status in glioma. Sci Rep. 2022;12:18801.","journal-title":"Sci Rep"},{"key":"1980_CR25","doi-asserted-by":"publisher","first-page":"110324","DOI":"10.1016\/j.mri.2025.110324","volume":"117","author":"F Wang","year":"2025","unstructured":"Wang F, Wang Y, Qi L, Liang J, Xiao BH, Zhang C, W\u00e1ng YXJ, Ye Z. High correlation between Ki-67 expression and a novel perfusion MRI biomarker diffusion-derived vessel density (DDVD) in endometrial carcinoma. Magn Reson Imaging. 2025;117:110324.","journal-title":"Magn Reson Imaging"},{"key":"1980_CR26","doi-asserted-by":"publisher","first-page":"1834","DOI":"10.1002\/jmri.28211","volume":"56","author":"H Guo","year":"2022","unstructured":"Guo H, Liu J, Hu J, Zhang H, Zhao W, Gao M, Zhang Y, Yang G, Cui Y. Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion-weighted MRI models. J Magn Reson Imaging. 2022;56:1834\u201344.","journal-title":"J Magn Reson Imaging"},{"key":"1980_CR27","doi-asserted-by":"publisher","first-page":"3400","DOI":"10.21037\/qims-22-887","volume":"13","author":"Y Cui","year":"2023","unstructured":"Cui Y, Dang Y, Zhang H, Peng H, Zhang J, Li J, Shen P, Mao C, Ma L, Zhang L. Predicting isocitrate dehydrogenase genotype, histological phenotype, and Ki-67 expression level in diffuse gliomas with an advanced contrast analysis of magnetic resonance imaging sequences. Quant Imaging Med Surg. 2023;13:3400\u201315.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR28","doi-asserted-by":"publisher","first-page":"2569","DOI":"10.3390\/diagnostics14222569","volume":"14","author":"X Han","year":"2024","unstructured":"Han X, Xiao K, Bai J, Li F, Cui B, Cheng Y, Liu H, Lu J. Multimodal MRI and 1H-MRS for preoperative stratification of High-Risk molecular subtype in Adult-Type diffuse gliomas. Diagnostics (Basel). 2024;14:2569.","journal-title":"Diagnostics (Basel)"},{"key":"1980_CR29","doi-asserted-by":"publisher","first-page":"2919","DOI":"10.1016\/j.acra.2024.12.054","volume":"32","author":"H Zhu","year":"2025","unstructured":"Zhu H, Liu Y, Li Y, Ding Y, Shen N, Xie Y, Yan S, Fu Y, Zhang J, Liu D, Zhang X, Li L, Zhu W. Amide proton transfer-weighted (APTw) imaging and derived quantitative metrics in evaluating gliomas: improved performance compared to magnetization transfer ratio asymmetry (MTRasym). Acad Radiol. 2025;32:2919\u201330.","journal-title":"Acad Radiol"},{"key":"1980_CR30","doi-asserted-by":"publisher","first-page":"1663","DOI":"10.1177\/0284185119842288","volume":"60","author":"Z Xing","year":"2019","unstructured":"Xing Z, Zhang H, She D, Lin Y, Zhou X, Zeng Z, Cao D. IDH genotypes differentiation in glioblastomas using DWI and DSC-PWI in the enhancing and peri-enhancing region. Acta Radiol. 2019;60:1663\u201372.","journal-title":"Acta Radiol"},{"key":"1980_CR31","doi-asserted-by":"publisher","first-page":"N667","DOI":"10.1088\/1361-6560\/61\/24\/N667","volume":"61","author":"NP Jerome","year":"2016","unstructured":"Jerome NP, d\u2019Arcy JA, Feiweier T, Koh DM, Leach MO, Collins DJ, Orton MR. Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging. Phys Med Biol. 2016;61:N667\u201380.","journal-title":"Phys Med Biol"},{"key":"1980_CR32","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1002\/mrm.28996","volume":"87","author":"T F\u00fchres","year":"2022","unstructured":"F\u00fchres T, Riexinger AJ, Loh M, Martin J, Wetscherek A, Kuder TA, Uder M, Hensel B, Laun FB. Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver. Magn Reson Med. 2022;87:859\u201371.","journal-title":"Magn Reson Med"},{"key":"1980_CR33","doi-asserted-by":"publisher","first-page":"e4987","DOI":"10.1002\/nbm.4987","volume":"36","author":"WL Yu","year":"2023","unstructured":"Yu WL, Xiao BH, Ma FZ, Zheng CJ, Tang SN, W\u00e1ng YXJ. Underestimation of the spleen perfusion fraction by intravoxel incoherent motion MRI. NMR Biomed. 2023;36:e4987.","journal-title":"NMR Biomed"},{"key":"1980_CR34","doi-asserted-by":"publisher","first-page":"e5125","DOI":"10.1002\/nbm.5125","volume":"37","author":"XM Li","year":"2024","unstructured":"Li XM, Yao DQ, Quan XY, Li M, Chen W, W\u00e1ng YXJ. Perfusion of hepatocellular carcinomas measured by diffusion-derived vessel density biomarker: higher hepatocellular carcinoma perfusion than earlier intravoxel incoherent motion reports. NMR Biomed. 2024;37:e5125.","journal-title":"NMR Biomed"},{"key":"1980_CR35","doi-asserted-by":"publisher","first-page":"1316","DOI":"10.21037\/qims-23-1437","volume":"14","author":"FZ Ma","year":"2024","unstructured":"Ma FZ, W\u00e1ng YXJ. T2 relaxation time elongation of hepatocellular carcinoma relative to native liver tissue leads to an underestimation of perfusion fraction measured by standard intravoxel incoherent motion magnetic resonance imaging. Quant Imaging Med Surg. 2024;14:1316\u201322.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR36","doi-asserted-by":"publisher","first-page":"e4488","DOI":"10.1002\/nbm.4488","volume":"34","author":"YXJ W\u00e1ng","year":"2021","unstructured":"W\u00e1ng YXJ. Observed Paradoxical perfusion fraction elevation in steatotic liver: an example of intravoxel incoherent motion modeling of the perfusion component constrained by the diffusion component. NMR Biomed. 2021;34:e4488.","journal-title":"NMR Biomed"},{"key":"1980_CR37","doi-asserted-by":"publisher","first-page":"1840","DOI":"10.21037\/qims.2019.09.18","volume":"9","author":"YXJ W\u00e1ng","year":"2019","unstructured":"W\u00e1ng YXJ, Wang X, Wu P, Wang Y, Chen W, Chen H, Li J. Topics on quantitative liver magnetic resonance imaging. Quant Imaging Med Surg. 2019;9:1840\u201390.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR38","doi-asserted-by":"publisher","first-page":"3264","DOI":"10.21037\/qims-24-406","volume":"14","author":"BL Lu","year":"2024","unstructured":"Lu BL, Yao DQ, W\u00e1ng YXJ, Zhang ZW, Wen ZQ, Xiao BH, Yu SP. Higher perfusion of rectum carcinoma relative to tumor-free rectal wall: quantification by a new imaging biomarker diffusion-derived vessel density (DDVD). Quant Imaging Med Surg. 2024;14:3264\u201374.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR39","doi-asserted-by":"publisher","first-page":"8478","DOI":"10.21037\/qims-23-415","volume":"13","author":"C Weng","year":"2023","unstructured":"Weng C, Yang Y, Yang L, Hu C, Ma X, Li G. Evaluations of the diagnostic performance of ZOOMit diffusion-weighted imaging and conventional diffusion-weighted imaging for breast lesions. Quant Imaging Med Surg. 2023;13:8478\u201388.","journal-title":"Quant Imaging Med Surg"},{"key":"1980_CR40","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.neuroimage.2013.01.038","volume":"72","author":"NK Chen","year":"2013","unstructured":"Chen NK, Guidon A, Chang HC, Song AW. A robust multi-shot scan strategy for high-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE). NeuroImage. 2013;72:41\u20137.","journal-title":"NeuroImage"}],"container-title":["BMC Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-025-01980-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12880-025-01980-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-025-01980-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T11:05:40Z","timestamp":1761908740000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedimaging.biomedcentral.com\/articles\/10.1186\/s12880-025-01980-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":40,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1980"],"URL":"https:\/\/doi.org\/10.1186\/s12880-025-01980-y","relation":{},"ISSN":["1471-2342"],"issn-type":[{"value":"1471-2342","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"11 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethical approval was granted by the Ethics Committee of Fujian Medical University Union Hospital, and all participants provided informed consent. All methods were carried out according to relevant guidelines and regulations.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"Y\u00ec Xi\u00e1ng J. W\u00e1ng is the founder of Yingran Medicals Ltd., which develops medical image-based diagnostics software. Other authors declare no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"427"}}