Automatic estimation of extent of resection and residual tumor volume of patients with glioblastoma.

Meier, Raphael; Porz, Nicole; Knecht, Urspeter; Schucht, Philippe; Beck, Jürgen; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio (2017). Automatic estimation of extent of resection and residual tumor volume of patients with glioblastoma. Journal of neurosurgery, 127(4), pp. 798-806. American Association of Neurological Surgeons 10.3171/2016.9.JNS16146

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OBJECTIVE In the treatment of glioblastoma, residual tumor burden is the only prognostic factor that can be actively influenced by therapy. Therefore, an accurate, reproducible, and objective measurement of residual tumor burden is necessary. This study aimed to evaluate the use of a fully automatic segmentation method-brain tumor image analysis (BraTumIA)-for estimating the extent of resection (EOR) and residual tumor volume (RTV) of contrast-enhancing tumor after surgery. METHODS The imaging data of 19 patients who underwent primary resection of histologically confirmed supratentorial glioblastoma were retrospectively reviewed. Contrast-enhancing tumors apparent on structural preoperative and immediate postoperative MR imaging in this patient cohort were segmented by 4 different raters and the automatic segmentation BraTumIA software. The manual and automatic results were quantitatively compared. RESULTS First, the interrater variabilities in the estimates of EOR and RTV were assessed for all human raters. Interrater agreement in terms of the coefficient of concordance (W) was higher for RTV (W = 0.812; p < 0.001) than for EOR (W = 0.775; p < 0.001). Second, the volumetric estimates of BraTumIA for all 19 patients were compared with the estimates of the human raters, which showed that for both EOR (W = 0.713; p < 0.001) and RTV (W = 0.693; p < 0.001) the estimates of BraTumIA were generally located close to or between the estimates of the human raters. No statistically significant differences were detected between the manual and automatic estimates. BraTumIA showed a tendency to overestimate contrast-enhancing tumors, leading to moderate agreement with expert raters with respect to the literature-based, survival-relevant threshold values for EOR. CONCLUSIONS BraTumIA can generate volumetric estimates of EOR and RTV, in a fully automatic fashion, which are comparable to the estimates of human experts. However, automated analysis showed a tendency to overestimate the volume of a contrast-enhancing tumor, whereas manual analysis is prone to subjectivity, thereby causing considerable interrater variability.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurosurgery
04 Faculty of Medicine > Service Sector > Institute of Legal Medicine > Forensic Medicine

UniBE Contributor:

Meier, Raphael; Knecht, Urspeter; Schucht, Philippe; Beck, Jürgen; Slotboom, Johannes; Wiest, Roland and Reyes, Mauricio

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

0022-3085

Publisher:

American Association of Neurological Surgeons

Language:

English

Submitter:

Nicole Söll

Date Deposited:

07 Jun 2017 16:34

Last Modified:

20 Mar 2018 09:09

Publisher DOI:

10.3171/2016.9.JNS16146

PubMed ID:

28059651

BORIS DOI:

10.7892/boris.92799

URI:

https://boris.unibe.ch/id/eprint/92799

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