Export to BibTeX Export to EndNoteAutomated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose-volume histograms (327 views) (PDF restricted 168 views)
Conson M, Cella L, Pacelli R, Comerci M, Liuzzi R, Salvatore M, Quarantelli M
Radiotherapy And Oncology (ISSN: 0167-8140, 1879-0887, 1879-0887electronic), 2014 Sep; 112(3): 326-331.
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 DSCABAS = 1 (95% CI, 0.97-1.0) vs. DSCMANUAL = 0.90 (0.73-0.98)], acceptable accuracy [DSCABAS = 0.81 (0.68-0.94) vs. DSCMANUAL = 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. © 2014 Elsevier Ireland Ltd. All rights reserved.
Affiliations ▼
*** IBB - CNR Affiliation
Department of Advanced Biomedical Sciences, Università Federico II, Federico II University School of Medicine, via S. Pansini 5, edificio 10Napoli, Italy
Institute of Biostructure and Bioimaging, National Research Council (CNR)Naples, Italy |
Details ▼
Impact factor: 4.857, 5-year impact factor: 4.67
Paper type: Journal Article,
Keywords: Atlas-Based Segmentation, Brain Tumors, Radiotherapy, Algorithm, Article, Automation, Cerebellum, Cingulate Gyrus, Clinical Article, Computer Assisted Radiotherapy, Diagnostic Accuracy, Dosimetry, Frontal Lobe, Glioma, Gray Matter, Histogram, Human, Insula, Magnetic Resonance Imaging Atlas Based Automated Segmentation, Nuclear Magnetic Resonance Imaging, Nuclear Magnetic Resonance Scanner, Occipital Lobe, Parietal Lobe, Radiation Dose Distribution, Temporal Lobe, Brain Mapping, Brain Neoplasms, Female, First Cervical Vertebra, Image Processing, Middle Aged, Observer Variation, Procedures, Radiography, Radiometry, Reproducibility, Three Dimensional Imaging, Cervical Atlas, Computer-Assisted, Three-Dimensional, Radiation Dosage, Radiotherapy Dosage, Radiotherapy Planning, Conformal, Reproducibility Of Results, Brain Radiography, Brain Mapping Methods, Brain Neoplasms Diagnosis Radiotherapy, Cervical Atlas Radiography, Glioma Diagnosis Radiotherapy, Gray Matter Radiography, Computer-Assisted Methods, Three-Dimensional Methods, Magnetic Resonance Imaging Methods, Radiometry Methods, Conformal Methods,
Url: http://www.scopus.com/inward/record.url?eid=2-s2.0-84910142393&partnerID=40&md5=8049742740fbb25f59382481322dffa8 |
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Sort by: date ▼▲ title ▲ ▼ journal ▲ ▼ authors ▲ ▼ impact factor ▲ ▼* An ontology-based technique for validation of MRI brain segmentation methods (96 views) (PDF 69 views)Alfano B, Comerci M, De Pietro G, Esposito A
Lecture Notes In Computer Science (ISSN: 0302-9743, 0302-974335404636319783540463634, 0302-974335402975459783540297543), 2007; 4805LNCS(PART1): 566-575.
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2 Records ( 1 excluding Abstracts and Conferences). Total impact factor: 1.798 ( 1.496 excluding Abstracts and Conferences). Total 5-year impact factor: 1.707 ( 1.707 excluding Abstracts and Conferences).
Your bibliography query: (([btitle, keywords, abstract] ATLAS AND [btitle, keywords, abstract] BASED AND [btitle, keywords, abstract] SEGMENTATION AND [btitle, keywords, abstract] BRAIN)) AND NOT [id] = 52062
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