Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms.
Saved in:
| Title: | Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms. |
|---|---|
| Authors: | Conson, Manuel1,2, Cella, Laura1,2, Pacelli, Roberto1,2 roberto.pacelli@unina.it, Comerci, Marco2, Liuzzi, Raffaele1,2, Salvatore, Marco1, Quarantelli, Mario1,2 |
| Source: | Radiotherapy & Oncology. Sep2014, Vol. 112 Issue 3, p326-331. 6p. |
| Subjects: | Brain tumors, Cancer radiotherapy, Magnetic resonance imaging of the brain, Gray market, Parameter estimation, Robust control, Patients |
| Abstract: | Purpose To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). Patients and methods 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient – DSC). Dosimetric parameters from dose–volume-histograms were also generated and compared. Results Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSC ABAS = 1 (95% CI, 0.97–1.0) vs. DSC MANUAL = 0.90 (0.73–0.98)], acceptable accuracy [DSC ABAS = 0.81 (0.68–0.94) vs. DSC MANUAL = 0.90 (0.76–0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. Conclusions The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose–volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures. [ABSTRACT FROM AUTHOR] |
| Copyright of Radiotherapy & Oncology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 99508080 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Conson%2C+Manuel%22">Conson, Manuel</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Cella%2C+Laura%22">Cella, Laura</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Pacelli%2C+Roberto%22">Pacelli, Roberto</searchLink><relatesTo>1,2</relatesTo><i> roberto.pacelli@unina.it</i><br /><searchLink fieldCode="AR" term="%22Comerci%2C+Marco%22">Comerci, Marco</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Liuzzi%2C+Raffaele%22">Liuzzi, Raffaele</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Salvatore%2C+Marco%22">Salvatore, Marco</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Quarantelli%2C+Mario%22">Quarantelli, Mario</searchLink><relatesTo>1,2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Radiotherapy+%26+Oncology%22">Radiotherapy & Oncology</searchLink>. Sep2014, Vol. 112 Issue 3, p326-331. 6p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Brain+tumors%22">Brain tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Cancer+radiotherapy%22">Cancer radiotherapy</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging+of+the+brain%22">Magnetic resonance imaging of the brain</searchLink><br /><searchLink fieldCode="DE" term="%22Gray+market%22">Gray market</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+control%22">Robust control</searchLink><br /><searchLink fieldCode="DE" term="%22Patients%22">Patients</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). Patients and methods 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient – DSC). Dosimetric parameters from dose–volume-histograms were also generated and compared. Results Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSC ABAS = 1 (95% CI, 0.97–1.0) vs. DSC MANUAL = 0.90 (0.73–0.98)], acceptable accuracy [DSC ABAS = 0.81 (0.68–0.94) vs. DSC MANUAL = 0.90 (0.76–0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. Conclusions The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose–volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Radiotherapy & Oncology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=99508080 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.radonc.2014.06.006 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 326 Subjects: – SubjectFull: Brain tumors Type: general – SubjectFull: Cancer radiotherapy Type: general – SubjectFull: Magnetic resonance imaging of the brain Type: general – SubjectFull: Gray market Type: general – SubjectFull: Parameter estimation Type: general – SubjectFull: Robust control Type: general – SubjectFull: Patients Type: general Titles: – TitleFull: Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Conson, Manuel – PersonEntity: Name: NameFull: Cella, Laura – PersonEntity: Name: NameFull: Pacelli, Roberto – PersonEntity: Name: NameFull: Comerci, Marco – PersonEntity: Name: NameFull: Liuzzi, Raffaele – PersonEntity: Name: NameFull: Salvatore, Marco – PersonEntity: Name: NameFull: Quarantelli, Mario IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 01678140 Numbering: – Type: volume Value: 112 – Type: issue Value: 3 Titles: – TitleFull: Radiotherapy & Oncology Type: main |
| ResultId | 1 |