{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T22:59:58Z","timestamp":1792364398635,"version":"4.4.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2024,4,20]],"date-time":"2024-04-20T00:00:00Z","timestamp":1713571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,4,20]],"date-time":"2024-04-20T00:00:00Z","timestamp":1713571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004434","name":"Universit\u00e0 degli Studi di Firenze","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004434","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Childs Nerv Syst"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Texture analysis extracts many quantitative image features, offering a valuable, cost-effective, and non-invasive approach for individual medicine. Furthermore, multimodal machine learning could have a large impact for precision medicine, as texture biomarkers can underlie tissue microstructure. This study aims to investigate imaging-based biomarkers of radio-induced neurotoxicity in pediatric patients with metastatic medulloblastoma, using radiomic and dosiomic analysis.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>This single-center study retrospectively enrolled children diagnosed with metastatic medulloblastoma (MB) and treated with hyperfractionated craniospinal irradiation (CSI). Histological confirmation of medulloblastoma and baseline follow-up magnetic resonance imaging (MRI) were mandatory. Treatment involved helical tomotherapy (HT) delivering a dose of 39 Gray (Gy) to brain and spinal axis and a posterior fossa boost up to 60\u00a0Gy. Clinical outcomes, such as local and distant brain control and neurotoxicity, were recorded. Radiomic and dosiomic features were extracted from tumor regions on T1, T2, FLAIR (fluid-attenuated inversion recovery) MRI-maps, and radiotherapy dose distribution. Different machine learning feature selection and reduction approaches were performed for supervised and unsupervised clustering.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Forty-eight metastatic medulloblastoma patients (29 males and 19 females) with a mean age of 12\u2009\u00b1\u20096\u00a0years were enrolled. For each patient, 332 features were extracted. Greater level of abstraction of input data by combining selection of most performing features and dimensionality reduction returns the best performance. The resulting one-component radiomic signature yielded an accuracy of 0.73 with sensitivity, specificity, and precision of 0.83, 0.64, and 0.68, respectively.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Machine learning radiomic-dosiomic approach effectively stratified pediatric medulloblastoma patients who experienced radio-induced neurotoxicity. Strategy needs further validation in external dataset for its potential clinical use in ab initio management paradigms of medulloblastoma.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00381-024-06416-6","type":"journal-article","created":{"date-parts":[[2024,4,21]],"date-time":"2024-04-21T02:38:01Z","timestamp":1713667081000},"page":"2301-2310","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Radiomic-\u00a0and dosiomic-based clustering development for radio-induced neurotoxicity in pediatric medulloblastoma"],"prefix":"10.1007","volume":"40","author":[{"given":"Stefano","family":"Piffer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniela","family":"Greto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonardo","family":"Ubaldi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marzia","family":"Mortilla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonio","family":"Ciccarone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isacco","family":"Desideri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Genitori","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Livi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Livia","family":"Marrazzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefania","family":"Pallotta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandra","family":"Retico","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iacopo","family":"Sardi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cinzia","family":"Talamonti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,20]]},"reference":[{"key":"6416_CR1","doi-asserted-by":"publisher","first-page":"4151","DOI":"10.1200\/JCO.2016.67.2428","volume":"34","author":"AO Von Bueren","year":"2016","unstructured":"Von Bueren AO, Kortmann RD, Von Hoff K et al (2016) Treatment of children and adolescents with metastatic medulloblastoma and prognostic relevance of clinical and biologic parameters. J Clin Oncol 34:4151\u20134160. https:\/\/doi.org\/10.1200\/JCO.2016.67.2428","journal-title":"J Clin Oncol"},{"key":"6416_CR2","doi-asserted-by":"publisher","first-page":"2355","DOI":"10.1200\/JCO.2017.72.7842","volume":"35","author":"V Ramaswamy","year":"2017","unstructured":"Ramaswamy V, Taylor MD (2017) Medulloblastoma: from myth to molecular. J Clin Oncol 35:2355\u20132363. https:\/\/doi.org\/10.1200\/JCO.2017.72.7842","journal-title":"J Clin Oncol"},{"issue":"12","key":"6416_CR3","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1177\/0883073815600866","volume":"31","author":"NE Millard","year":"2016","unstructured":"Millard NE, De Braganca KC (2016) Medulloblastoma. J Child Neurol 31(12):1341\u20131353. https:\/\/doi.org\/10.1177\/0883073815600866","journal-title":"Journal of Child Neurology"},{"key":"6416_CR4","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/S13311-017-0526-Y\/TABLES\/1","volume":"14","author":"TC Archer","year":"2017","unstructured":"Archer TC, Mahoney EL, Pomeroy SL (2017) Medulloblastoma: molecular classification-based personal therapeutics. Neurotherapeutics 14:265\u2013273. https:\/\/doi.org\/10.1007\/S13311-017-0526-Y\/TABLES\/1","journal-title":"Neurotherapeutics"},{"key":"6416_CR5","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/J.NEUCHI.2019.05.007","volume":"67","author":"E Bouffet","year":"2021","unstructured":"Bouffet E (2021) Management of high-risk medulloblastoma. Neurochirurgie 67:61\u201368. https:\/\/doi.org\/10.1016\/J.NEUCHI.2019.05.007","journal-title":"Neurochirurgie"},{"key":"6416_CR6","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1126\/SCIENCE.1198056","volume":"331","author":"DW Parsons","year":"2011","unstructured":"Parsons DW, Li M, Zhang X et al (2011) The genetic landscape of the childhood cancer medulloblastoma. Science 331:435\u2013439. https:\/\/doi.org\/10.1126\/SCIENCE.1198056","journal-title":"Science"},{"key":"6416_CR7","doi-asserted-by":"publisher","first-page":"1415","DOI":"10.1200\/JCO.2010.28.1675","volume":"29","author":"P Tamayo","year":"2011","unstructured":"Tamayo P, Cho YJ, Tsherniak A et al (2011) Predicting relapse in patients with medulloblastoma by integrating evidence from clinical and genomic features. J Clin Oncol 29:1415\u20131423. https:\/\/doi.org\/10.1200\/JCO.2010.28.1675","journal-title":"J Clin Oncol"},{"key":"6416_CR8","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1093\/NEUONC\/NOS267","volume":"15","author":"RJ Packer","year":"2013","unstructured":"Packer RJ, Zhou T, Holmes E et al (2013) Survival and secondary tumors in children with medulloblastoma receiving radiotherapy and adjuvant chemotherapy: results of Children\u2019s Oncology Group trial A9961. Neuro Oncol 15:97\u2013103. https:\/\/doi.org\/10.1093\/NEUONC\/NOS267","journal-title":"Neuro Oncol"},{"key":"6416_CR9","doi-asserted-by":"publisher","first-page":"2234","DOI":"10.1002\/CNCR.24267","volume":"115","author":"M Lorenzi","year":"2009","unstructured":"Lorenzi M, McMillan AJ, Siegel LS et al (2009) Educational outcomes among survivors of childhood cancer in British Columbia, Canada: report of the Childhood\/Adolescent\/Young Adult Cancer Survivors (CAYACS) Program. Cancer 115:2234\u20132245. https:\/\/doi.org\/10.1002\/CNCR.24267","journal-title":"Cancer"},{"key":"6416_CR10","doi-asserted-by":"publisher","first-page":"1760","DOI":"10.1200\/JCO.2013.52.3290","volume":"32","author":"I Moxon-Emre","year":"2014","unstructured":"Moxon-Emre I, Bouffet E, Taylor MD et al (2014) Impact of craniospinal dose, boost volume, and neurologic complications on intellectual outcome in patients with medulloblastoma. J Clin Oncol 32:1760\u20131768. https:\/\/doi.org\/10.1200\/JCO.2013.52.3290","journal-title":"J Clin Oncol"},{"issue":"23","key":"6416_CR11","doi-asserted-by":"publisher","first-page":"5945","DOI":"10.3390\/cancers13235945","volume":"13","author":"C Seidel","year":"2021","unstructured":"Seidel C, Heider S, Hau P et al (2021) Radiotherapy in medulloblastoma-evolution of treatment, current concepts and future perspectives. Cancers 13(23):5945. https:\/\/doi.org\/10.3390\/cancers13235945","journal-title":"Cancers"},{"key":"6416_CR12","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.3174\/ajnr.A3990","volume":"35","author":"S Perreault","year":"2014","unstructured":"Perreault S, Ramaswamy V, Achrol AS et al (2014) MRI surrogates for molecular subgroups of medulloblastoma. Am J Neuroradiol 35:1263\u20131269. https:\/\/doi.org\/10.3174\/ajnr.A3990","journal-title":"Am J Neuroradiol"},{"key":"6416_CR13","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1097\/CCO.0000000000000793","volume":"33","author":"L Nichelli","year":"2021","unstructured":"Nichelli L, Casagranda S (2021) Current emerging MRI tools for radionecrosis and pseudoprogression diagnosis. Curr Opin Oncol 33:597\u2013607. https:\/\/doi.org\/10.1097\/CCO.0000000000000793","journal-title":"Curr Opin Oncol"},{"key":"6416_CR14","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1038\/NRCLINONC.2017.141","volume":"14","author":"P Lambin","year":"2017","unstructured":"Lambin P, Leijenaar RTH, Deist TM et al (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 14:749\u2013762. https:\/\/doi.org\/10.1038\/NRCLINONC.2017.141","journal-title":"Nat Rev Clin Oncol"},{"key":"6416_CR15","doi-asserted-by":"publisher","first-page":"3692","DOI":"10.1007\/S00330-017-5180-6","volume":"28","author":"S Zhang","year":"2018","unstructured":"Zhang S, Song G, Zang Y et al (2018) Non-invasive radiomics approach potentially predicts non-functioning pituitary adenomas subtypes before surgery. Eur Radiol 28:3692\u20133701. https:\/\/doi.org\/10.1007\/S00330-017-5180-6","journal-title":"Eur Radiol"},{"key":"6416_CR16","doi-asserted-by":"publisher","first-page":"1180","DOI":"10.1016\/S1470-2045(18)30413-3","volume":"19","author":"R Sun","year":"2018","unstructured":"Sun R, Limkin EJ, Vakalopoulou M et al (2018) A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study. Lancet Oncol 19:1180\u20131191. https:\/\/doi.org\/10.1016\/S1470-2045(18)30413-3","journal-title":"Lancet Oncol"},{"key":"6416_CR17","doi-asserted-by":"publisher","first-page":"5765","DOI":"10.1158\/1078-0432.CCR-16-0702","volume":"22","author":"P Kickingereder","year":"2016","unstructured":"Kickingereder P, G\u00f6tz M, Muschelli J et al (2016) Large-scale radiomic profiling of recurrent glioblastoma identifies an imaging predictor for stratifying anti-angiogenic treatment response. Clin Cancer Res 22:5765\u20135771. https:\/\/doi.org\/10.1158\/1078-0432.CCR-16-0702","journal-title":"Clin Cancer Res"},{"key":"6416_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/cancers13020339","volume":"13","author":"G Buizza","year":"2021","unstructured":"Buizza G, Paganelli C, D\u2019Ippolito E et al (2021) Radiomics and dosiomics for predicting local control after carbon-ion radiotherapy in skull-base chordoma. Cancers (Basel) 13:1\u201315. https:\/\/doi.org\/10.3390\/cancers13020339","journal-title":"Cancers (Basel)"},{"key":"6416_CR19","doi-asserted-by":"publisher","first-page":"1709","DOI":"10.1118\/1.596958","volume":"20","author":"T Kinsella","year":"1993","unstructured":"Kinsella T, Deasy JO (1993) Tomotherapy: A new concept for the delivery of dynamic conformal radiotherapy. Med Phys 20:1709\u20131719. https:\/\/doi.org\/10.1118\/1.596958","journal-title":"Med Phys"},{"key":"6416_CR20","doi-asserted-by":"publisher","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","volume":"77","author":"JJM Van Griethuysen","year":"2017","unstructured":"Van Griethuysen JJM, Fedorov A, Parmar C et al (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77:e104\u2013e107. https:\/\/doi.org\/10.1158\/0008-5472.CAN-17-0339","journal-title":"Cancer Res"},{"key":"6416_CR21","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/s0004-3702(97)00043-x","volume":"97","author":"R Kohavi","year":"1997","unstructured":"Kohavi R, John GH (1997) Wrappers for feature subset selection. Artif Intell 97:273\u2013324. https:\/\/doi.org\/10.1016\/s0004-3702(97)00043-x","journal-title":"Artif Intell"},{"key":"6416_CR22","doi-asserted-by":"publisher","unstructured":"Chen T, Guestrin C (2016) XGBoost: a scalable tree boosting system. KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 785\u2013794. https:\/\/doi.org\/10.1145\/2939672.2939785","DOI":"10.1145\/2939672.2939785"},{"key":"6416_CR23","first-page":"27","volume":"5","author":"E Rend\u00f3n","year":"2011","unstructured":"Rend\u00f3n E, Abundez I, Arizmendi A, Quiroz EM (2011) Internal versus external cluster validation indexes. Int J Comput Commun 5:27\u201334","journal-title":"Int J Comput Commun"},{"key":"6416_CR24","doi-asserted-by":"publisher","first-page":"1085","DOI":"10.1007\/S00381-022-05507-6","volume":"38","author":"ZM Liu","year":"2022","unstructured":"Liu ZM, Zhang H, Ge M et al (2022) Radiomics signature for the prediction of progression-free survival and radiotherapeutic benefits in pediatric medulloblastoma. Childs Nerv Syst 38:1085\u20131094. https:\/\/doi.org\/10.1007\/S00381-022-05507-6","journal-title":"Childs Nerv Syst"},{"key":"6416_CR25","doi-asserted-by":"publisher","first-page":"103093","DOI":"10.1016\/j.ebiom.2020.103093","volume":"61","author":"J Yan","year":"2020","unstructured":"Yan J, Zhang S, Li KKW et al (2020) Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma. EBioMedicine 61:103093. https:\/\/doi.org\/10.1016\/j.ebiom.2020.103093","journal-title":"EBioMedicine"},{"key":"6416_CR26","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1186\/s12957-021-02239-w","volume":"19","author":"H Zheng","year":"2021","unstructured":"Zheng H, Li J, Liu H et al (2021) Clinical-MRI radiomics enables the prediction of preoperative cerebral spinal fluid dissemination in children with medulloblastoma. World J Surg Oncol 19:134. https:\/\/doi.org\/10.1186\/s12957-021-02239-w","journal-title":"World J Surg Oncol"},{"key":"6416_CR27","doi-asserted-by":"publisher","first-page":"1665","DOI":"10.21037\/ATM-21-5348","volume":"9","author":"L Zhou","year":"2021","unstructured":"Zhou L, Peng H, Ji Q et al (2021) Radiomic signatures based on multiparametric MR images for predicting Ki-67 index expression in medulloblastoma. Ann Transl Med 9:1665\u20131665. https:\/\/doi.org\/10.21037\/ATM-21-5348","journal-title":"Ann Transl Med"},{"key":"6416_CR28","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1002\/jmri.28537","volume":"58","author":"H Zheng","year":"2023","unstructured":"Zheng H, Li J, Liu H et al (2023) MRI radiomics signature of pediatric medulloblastoma improves risk stratification beyond clinical and conventional MR imaging features. J Magn Reson Imaging 58:236\u2013246. https:\/\/doi.org\/10.1002\/jmri.28537","journal-title":"J Magn Reson Imaging"},{"issue":"7","key":"6416_CR29","doi-asserted-by":"publisher","first-page":"e0255500","DOI":"10.1371\/journal.pone.0255500","volume":"16","author":"FC Chang","year":"2021","unstructured":"Chang FC, Wong TT, Wu KS et al (2021) Magnetic resonance radiomics features and prognosticators in different molecular subtypes of pediatric medulloblastoma. PLoS One 16(7):e0255500. https:\/\/doi.org\/10.1371\/journal.pone.0255500","journal-title":"PLoS One"},{"key":"6416_CR30","doi-asserted-by":"publisher","first-page":"2314","DOI":"10.1109\/EMBC46164.2021.9629697","volume":"2021","author":"R Larracy","year":"2021","unstructured":"Larracy R, Phinyomark A, Scheme E (2021) Machine learning model validation for early stage studies with small sample sizes. Annu Int Conf IEEE Eng Med Biol Soc IEEE Eng Med Biol Soc Annu Int Conf 2021:2314\u20132319. https:\/\/doi.org\/10.1109\/EMBC46164.2021.9629697","journal-title":"Annu Int Conf IEEE Eng Med Biol Soc IEEE Eng Med Biol Soc Annu Int Conf"},{"key":"6416_CR31","doi-asserted-by":"publisher","DOI":"10.1371\/JOURNAL.PONE.0256152","volume":"16","author":"C An","year":"2021","unstructured":"An C, Park YW, Ahn SS et al (2021) Radiomics machine learning study with a small sample size: single random training-test set split may lead to unreliable results. PLoS ONE 16:e0256152. https:\/\/doi.org\/10.1371\/JOURNAL.PONE.0256152","journal-title":"PLoS ONE"}],"container-title":["Child's Nervous System"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00381-024-06416-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00381-024-06416-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00381-024-06416-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T10:07:53Z","timestamp":1721815673000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00381-024-06416-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,20]]},"references-count":31,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["6416"],"URL":"https:\/\/doi.org\/10.1007\/s00381-024-06416-6","relation":{},"ISSN":["0256-7040","1433-0350"],"issn-type":[{"value":"0256-7040","type":"print"},{"value":"1433-0350","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,20]]},"assertion":[{"value":"10 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 April 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was approved by the Institutional Pediatric Ethics Committee of Anna Meyer Children\u2019s University Hospital, decision n. 486 of 11\u201313-2020. Since this study is a retrospective analysis, all the procedures being performed were part of the routine care, and the patients have been anonymously processed; the need for informed consent was waived. All methods were performed in accordance with the ethical standards as laid down in the Declaration of Helsinki and its later amendments or comparable ethical standards.","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":"The authors declare no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}