MRI based volumetric measurements of vestibular schwannomas in patients with neurofibromatosis type 2: comparison of three different software tools.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
14 07 2020
Historique:
received: 30 07 2019
accepted: 25 06 2020
entrez: 16 7 2020
pubmed: 16 7 2020
medline: 23 1 2021
Statut: epublish

Résumé

Neurofibromatosis type 2 is a neurogenetic disorder with an incidence of about 1:33.000. Hallmarks are bilateral benign vestibular schwannomas, which can lead to deafness or brainstem compression. Volumetric tumor measurements are essential to assess the efficacy of new therapies. We present a statistical and methodical comparison of three volumetric image analysis tools. We performed volumetric measurements on phantoms with predefined volumes (0.1 to 8.0 ml) and tumors seen on 32 head MRI scans from eight NF2 patients with BrainLab, ITK-Snap, or OsiriX. The software was compared with regard to accuracy and reproducibility of the measurements and time required for analysis. The mean volume estimated by all three software programs differed significantly from the true volume of the phantoms, but OsiriX and BrainLab gave estimates that were not significantly different from each other. For the actual tumors, the estimated volumes with all three software tools showed a low coefficient of variability, but the mean volume estimates differed among the tools. OsiriX showed the shortest analysis time. Volumetric assessment of MRI images is associated to an intrinsic risk of miscalculation. For precise volumes it is mandatory to use the same volumetric tools for all measurements.

Identifiants

pubmed: 32665659
doi: 10.1038/s41598-020-68489-y
pii: 10.1038/s41598-020-68489-y
pmc: PMC7360562
doi:

Types de publication

Comparative Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

11541

Références

Evans, D. G. et al. A genetic study of type 2 neurofibromatosis in the United Kingdom. I. Prevalence, mutation rate, fitness, and confirmation of maternal transmission effect on severity. J. Med. Genet. 29, 841–846 (1992).
doi: 10.1136/jmg.29.12.841
Evans, D. G. R. Neurofibromatosis type 2 (NF2) A clinical and molecular review. Orphanet J. Rare Dis. 4, 16. https://doi.org/10.1186/1750-1172-4-16 (2009).
doi: 10.1186/1750-1172-4-16 pubmed: 19545378 pmcid: 2708144
von Kirschbaum, C. & Gürkov, R. Audiovestibular function deficits in vestibular schwannoma. BioMed Res. Int. 2016, 4980562. https://doi.org/10.1155/2016/4980562 (2016).
doi: 10.1155/2016/4980562
Plotkin, S. R. et al. Hearing improvement after bevacizumab in patients with neurofibromatosis type 2. N. Engl. J. Med. 361, 358–367. https://doi.org/10.1056/NEJMoa0902579 (2009).
doi: 10.1056/NEJMoa0902579 pubmed: 19587327 pmcid: 4816642
Blakeley, J. O. et al. Efficacy and biomarker study of bevacizumab for hearing loss resulting from neurofibromatosis type 2-associated vestibular schwannomas. J. Clin. Oncol. 34, 1669–1675. https://doi.org/10.1200/JCO.2015.64.3817 (2016).
doi: 10.1200/JCO.2015.64.3817 pubmed: 26976425 pmcid: 4872317
Farschtschi, S., Kollmann, P., Dalchow, C., Stein, A. & Mautner, V.-F. Reduced dosage of bevacizumab in treatment of vestibular schwannomas in patients with neurofibromatosis type 2. Eur. Arch. Oto-Rhino-Laryngol. 272, 3857–3860. https://doi.org/10.1007/s00405-015-3604-y (2015).
doi: 10.1007/s00405-015-3604-y
Huang, V. et al. Improvement in patient-reported hearing after treatment with bevacizumab in people with neurofibromatosis type 2. Otol. Neurotol. 39, 632–638. https://doi.org/10.1097/MAO.0000000000001781 (2018).
doi: 10.1097/MAO.0000000000001781 pubmed: 29649040 pmcid: 6642810
Mautner, V.-F. et al. Bevacizumab induces regression of vestibular schwannomas in patients with neurofibromatosis type 2. Neuro-oncology 12, 14–18. https://doi.org/10.1093/neuonc/nop010 (2010).
doi: 10.1093/neuonc/nop010 pubmed: 20150363
Riina, H. A. et al. Short-term clinico-radiographic response to super-selective intra-arterial cerebral infusion of Bevacizumab for the treatment of vestibular schwannomas in Neurofibromatosis type 2. Interv. Neuroradiol. 18, 127–132. https://doi.org/10.1177/159101991201800201 (2012).
doi: 10.1177/159101991201800201 pubmed: 22681725 pmcid: 3380388
Cai, W. et al. Tumor burden in patients with neurofibromatosis types 1 and 2 and schwannomatosis: determination on whole-body MR images. Radiology 250, 665–673. https://doi.org/10.1148/radiol.2503080700 (2009).
doi: 10.1148/radiol.2503080700 pubmed: 19244040
Harris, G. J. et al. Three-dimensional volumetrics for tracking vestibular schwannoma growth in neurofibromatosis type II. Neurosurgery 62, 1314–1319. https://doi.org/10.1227/01.neu.0000333303.79931.83 (2008) (discussion 1319-20).
doi: 10.1227/01.neu.0000333303.79931.83 pubmed: 18824998
Lawson McLean, A. C., McLean, A. L. & Rosahl, S. K. Evaluating vestibular schwannoma size and volume on magnetic resonance imaging: an inter- and intra-rater agreement study. Clin. Neurol. Neurosurg. 145, 68–73. https://doi.org/10.1016/j.clineuro.2016.04.010 (2016).
doi: 10.1016/j.clineuro.2016.04.010 pubmed: 27101086
Cai, W. et al. (2018) Volumetric MRI analysis of plexiform neurofibromas in neurofibromatosis type 1. Comparison of two methods. Acad. Radiol. 25, 144–152. https://doi.org/10.1016/j.acra.2017.09.004 (2018).
doi: 10.1016/j.acra.2017.09.004 pubmed: 29097016
Despotović, I., Goossens, B. & Philips, W. MRI segmentation of the human brain. Challenges, methods, and applications. Comput. Math. Methods Med. 2015, 450341. https://doi.org/10.1155/2015/450341 (2015).
doi: 10.1155/2015/450341 pubmed: 25945121 pmcid: 4402572
Fabri, D. et al. A quantitative comparison of the performance of three deformable registration algorithms in radiotherapy. Z. Med. Phys. 23, 279–290. https://doi.org/10.1016/j.zemedi.2013.07.006 (2013).
doi: 10.1016/j.zemedi.2013.07.006 pubmed: 23969092 pmcid: 3865361
Heckel, F. et al. On the evaluation of segmentation editing tools. J. Med. Imag. 1, 34005. https://doi.org/10.1117/1.JMI.1.3.034005 (2014).
doi: 10.1117/1.JMI.1.3.034005
Yushkevich, P. A., Yang, G. & Gerig, G. ITK-SNAP. An interactive tool for semi-automatic segmentation of multi-modality biomedical images. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2016, 3342–3345. https://doi.org/10.1109/EMBC.2016.7591443 (2016).
doi: 10.1109/EMBC.2016.7591443
Blakeley, J. Development of drug treatments for neurofibromatosis type 2-associated vestibular schwannoma. Curr. Opin. Otolaryngol. Head Neck Surg. 20, 372–379. https://doi.org/10.1097/MOO.0b013e328357d2ee (2012).
doi: 10.1097/MOO.0b013e328357d2ee pubmed: 22931905 pmcid: 4778430

Auteurs

Philipp Kollmann (P)

Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.

Victor-Felix Mautner (VF)

Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.

Johannes Koeppen (J)

Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Ralph Wenzel (R)

Radiological Practice Altona, Hamburg, Germany.

Jan M Friedman (JM)

Department of Medical Genetics, University of British Columbia, Vancouver, Canada.

Johannes Salamon (J)

Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Said Farschtschi (S)

Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany. s.farschtschi@uke.de.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH