Choice of intraoperative ultrasound adjuncts for brain tumor surgery.
Background: Gliomas are among the most typical brain tumors tackled by neurosurgeons. During navigation for surgery of glioma brain tumors, preoperatively acquired static images may not be accurate due to shifts. Surgeons use intraoperative imaging technologies (2-Dimensional and navigated 3-Dimensi...
| Publicado en: | BMC Medical Informatics & Decision Making Vol. 22; no. 1; pp. 1 - 12 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
11/28/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160423669&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 160423669 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726947 1CI0 jtl: BMC Medical Informatics & Decision Making issn: 14726947 maglogo: N pubinfo: dt: 11/28/2022 vid: 22 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 160423669 160423669 NLM36437463 10.1186/s12911-022-02046-7 NLM36437463 160423669 ppf: 1 ppct: 11 formats: tig: atl: Choice of intraoperative ultrasound adjuncts for brain tumor surgery. aug: au: Kumar, Manoj Noronha, Santosh Rangaraj, Narayan Moiyadi, Aliasgar Shetty, Prakash Singh, Vikas Kumar affil: Department of Industrial Engineering and Operations Research, Indian Institute of Technology Bombay, Mumbai, India sug: subj: Brain Neoplasms Surgery Glioma Surgery Brain Neoplasms Pathology Brain Neoplasms Glioma Ultrasonography Methods Algorithms Arthritis Impact Measurement Scales ab: Background: Gliomas are among the most typical brain tumors tackled by neurosurgeons. During navigation for surgery of glioma brain tumors, preoperatively acquired static images may not be accurate due to shifts. Surgeons use intraoperative imaging technologies (2-Dimensional and navigated 3-Dimensional ultrasound) to assess and guide resections. This paper aims to precisely capture the importance of preoperative parameters to decide which type of ultrasound to be used for a particular surgery.Methods: This paper proposes two bagging algorithms considering base classifier logistic regression and random forest. These algorithms are trained on different subsets of the original data set. The goodness of fit of Logistic regression-based bagging algorithms is established using hypothesis testing. Furthermore, the performance measures for random-forest-based bagging algorithms used are AUC under ROC and AUC under the precision-recall curve. We also present a composite model without compromising the explainability of the models.Results: These models were trained on the data of 350 patients who have undergone brain surgery from 2015 to 2020. The hypothesis test shows that a single parameter is sufficient instead of all three dimensions related to the tumor ([Formula: see text]). We observed that the choice of intraoperative ultrasound depends on the surgeon making a choice, and years of experience of the surgeon could be a surrogate for this dependence.Conclusion: This study suggests that neurosurgeons may not need to focus on a large set of preoperative parameters in order to decide on ultrasound. Moreover, it personalizes the use of a particular ultrasound option in surgery. This approach could potentially lead to better resource management and help healthcare institutions improve their decisions to make the surgery more effective. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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