Automated Volumetric Analysis of Postoperative Magnetic Resonance Imaging Predicts Survival in Patients with Glioblastoma

Alexey L. Krivoshapkin, Gleb S. Sergeev, Alekey S. Gaytan, Leonid E. Kalneus, Vladislav P. Kurbatov, Orkhan A. Abdullaev, Nidal Salim, Dmitry V. Bulanov, Alexander E. Simonovich

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Background: Glioblastomas (GBMs) are primary brain tumors that are very difficult to treat. Magnetic resonance imaging (MRI) is the reference tool for diagnosis, postoperative control, and follow-up of GBM. The MRI tumor contrast enhancement part serves as a target for surgery. However, there are controversial data about the influence of pre- and postoperative tumor volumetric MRI parameters on overall survival (OS). Methods: Data of 57 patients with GBM were analyzed retrospectively. All patients had maximum safe resection and standard adjuvant treatment. All patients underwent 1.5-T MRI with contrast in the first 24 hours postoperatively. The data of pre- and postoperative volumetric parameters were analyzed using the original software. Results: Correlation analysis between the postoperative volume of the tumor contrast enhancement part and the patient's OS revealed a significant level (on the Chaddock scale) of inverse correlation. Residual tumor volume associated with OS of >6 months was determined as <2.5 cm3. The mortality risk in the first 6 months after tumor resection is 3.4 times higher when the tumor remnant is >2.5 cm3 (risk ratio, 3.4; P = 0.0002). Conclusions: The volume of MRI contrast-enhancing GBM remnants after surgery, automatically measured by the software, was a significant predictor for early postoperative progression and death.

Original languageEnglish
Pages (from-to)e1510-e1517
Number of pages8
JournalWorld Neurosurgery
Publication statusPublished - 1 Jun 2019


  • Glioblastoma management
  • Gross total resection
  • MRI evaluation
  • Software for MRI
  • Volumetric tumor estimation


Dive into the research topics of 'Automated Volumetric Analysis of Postoperative Magnetic Resonance Imaging Predicts Survival in Patients with Glioblastoma'. Together they form a unique fingerprint.

Cite this