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Precision of manual two-dimensional segmentations of lung and liver metastases and its impact on tumour response assessment using RECIST 1.1

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorCORNELIS, François
hal.structure.identifierDépartement de pharmacochimie moléculaire [DPM ]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorMARTIN, Marie
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorSAUT, Olivier
hal.structure.identifierInstitut Bergonié [Bordeaux]
dc.contributor.authorBUY, Xavier
hal.structure.identifierInstitut Bergonié [Bordeaux]
dc.contributor.authorKIND, Michèle
hal.structure.identifierInstitut Bergonié [Bordeaux]
dc.contributor.authorPALUSSIERE, Jean
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorCOLIN, Thierry
dc.date.accessioned2024-04-04T03:08:00Z
dc.date.available2024-04-04T03:08:00Z
dc.date.issued2017-12
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193494
dc.description.abstractEnBackground: Response evaluation criteria in solid tumours (RECIST) has significant limitations in terms of variability and reproducibility, which may not be independent. The aim of the study was to evaluate the precision of manual bi-dimensional segmentation of lung, liver metastases, and to quantify the uncertainty in tumour response assessment. Methods: A total of 520 segmentations of metastases from six livers and seven lungs were independently performed by ten physicians and ten scientists on CT images, reflecting the variability encountered in clinical practice. Operators manually contoured the tumours, firstly independently according to the RECIST and secondly on a preselected slice. Diameters and areas were extracted from the segmentations. Mean standard deviations were used to build regression models and 95% confidence intervals (95% CI) were calculated for each tumour size and for limits of progressive disease (PD) and partial response (PR) derived from RECIST 1.1. Results: Thirteen aberrant segmentations (2.5%) were observed without significant differences between the physicians and scientists; only the mean area of liver tumours (p = 0.034) and mean diameter of lung tumours (p = 0.021) differed significantly. No difference was observed between the methods. Inter-observer agreement was excellent (intra-class correlation >0.90) for all variables. In liver, overlaps of the 95% CI with the 95% CI of limits of PD or PR were observed for diameters above 22.7 and 37.9 mm, respectively. An overlap of 95% CIs was systematically observed for area. No overlaps were observed in lung. Conclusions: Although the experience of readers might not affect the precision of segmentation in lung and liver, the results of manual segmentation performed for tumour response assessment remain uncertain for large liver metastases.
dc.description.sponsorshipTranslational Research and Advanced Imaging Laboratory - ANR-10-LABX-0057
dc.language.isoen
dc.publisherSpringer
dc.subject.enLung
dc.subject.enComputed tomography
dc.subject.enLiver
dc.subject.enMetasatses
dc.subject.enResponse evaluation criteria in solid tumours (RECIST)
dc.subject.enSegmentation
dc.title.enPrecision of manual two-dimensional segmentations of lung and liver metastases and its impact on tumour response assessment using RECIST 1.1
dc.typeArticle de revue
dc.identifier.doi10.1186/s41747-017-0015-4
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halSciences du Vivant [q-bio]/Cancer
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
bordeaux.journalEuropean Radiology Experimental
bordeaux.volume1
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue1
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01634849
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01634849v1
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