The Impact of MRI Features and Observer Confidence on the Treatment Decision-Making for Patients with Untreated Glioma

Paulina Due-Tønnessen, Marco C. Pinho, Kyrre E. Emblem, John K. Hald, Masafumi Kanoto, Andreas Abildgaard, Donatas Sederevicius, Inge R. Groote, Otto Rapalino, Atle Bjørnerud

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In a blind, dual-center, multi-observer setting, we here identify the pre-treatment radiologic features by Magnetic Resonance Imaging (MRI) associated with subsequent treatment options in patients with glioma. Study included 220 previously untreated adult patients from two institutions (94 + 126 patients) with a histopathologically confirmed diagnosis of glioma after surgery. Using a blind, cross-institutional and randomized setup, four expert neuroradiologists recorded radiologic features, suggested glioma grade and corresponding confidence. The radiologic features were scored using the Visually AcceSAble Rembrandt Images (VASARI) standard. Results were retrospectively compared to patient treatment outcomes. Our findings show that patients receiving a biopsy or a subtotal resection were more likely to have a tumor with pathological MRI-signal (by T2-weighted Fluid-Attenuated Inversion Recovery) crossing the midline (Hazard Ratio; HR = 1.30 [1.21–1.87], P < 0.001), and those receiving a biopsy sampling more often had multifocal lesions (HR = 1.30 [1.16–1.64], P < 0.001). For low-grade gliomas (N = 50), low observer confidence in the radiographic readings was associated with less chance of a total resection (P = 0.002) and correlated with the use of a more comprehensive adjuvant treatment protocol (Spearman = 0.48, P < 0.001). This study may serve as a guide to the treating physician by identifying the key radiologic determinants most likely to influence the treatment decision-making process.

Original languageEnglish (US)
Article number19898
JournalScientific reports
Issue number1
StatePublished - Dec 1 2019

ASJC Scopus subject areas

  • General


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