André Pedersen

today's publication

1. Cancers

   Glioblastoma Surgery Imaging—Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentations

   Ivar Kommers, David Bouget,  André Pedersen, Roelant Eijgelaar, Hilko Ardon, Frederik Barkhof, Lorenzo Bello, Mitchel Berger, Marco Conti Nibali, Julia Furtner, Even Fyllingen, Shawn Hervey-Jumper, Albert Idema, Barbara Kiesel, Alfred Kloet, Emmanuel Mandonnet, Domenique Müller, Pierre Robe, Marco Rossi, and Philip De Witt Hamer

   Cancers Jun 2021

   Abs Bib PDF Code

   Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software.

   @article{kommers2021gsirads,
     abbr = {Cancers},
     bibtex_show = {true},
     author = {Kommers, Ivar and Bouget, David and Pedersen, André and Eijgelaar, Roelant and Ardon, Hilko and Barkhof, Frederik and Bello, Lorenzo and Berger, Mitchel and Conti Nibali, Marco and Furtner, Julia and Fyllingen, Even and Hervey-Jumper, Shawn and Idema, Albert and Kiesel, Barbara and Kloet, Alfred and Mandonnet, Emmanuel and Müller, Domenique and Robe, Pierre and Rossi, Marco and De Witt Hamer, Philip},
     year = {2021},
     month = jun,
     pages = {2854},
     title = {Glioblastoma Surgery Imaging—Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentations},
     volume = {13},
     journal = {Cancers},
     doi = {10.3390/cancers13122854},
     pdf = {https://www.mdpi.com/2072-6694/13/12/2854/htm},
     code = {https://github.com/SINTEFMedtek/GSI-RADS},
     rgvalue = {5}
   }