• Gisele Brasil Caseiras, Olga Ciccarelli, Daniel R Altmann, Christopher E Benton, Daniel J Tozer, Paul S Tofts, Tarek A Yousry, Jeremy Rees, Adam D Waldman, and Hans Rolf Jäger.
• University College London, Institute of Neurology, London, England.
• Radiology. 2009 Nov 1; 253 (2): 505-12.

PurposeTo prospectively compare tumor volume, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) and short-term changes of these parameters as predictors of time to malignant transformation and time to death in patients with low-grade gliomas (LGGs).Materials And MethodsPatients gave written informed consent for this institutional ethics committee-approved study. Patients with histologically proved LGGs underwent conventional, perfusion-weighted, and diffusion-weighted magnetic resonance (MR) imaging at study entry and at 6 months. At both time points, tumor volume, maximum rCBV, and ADC histogram measures were calculated. Patient follow-up consisted of MR imaging every 6 months and clinical examinations. To investigate the association between MR imaging variables and time to progression and time to death, a Cox regression curve was applied at study entry and at 6 months. The models were corrected for age, sex, and histologic findings.ResultsThirty-four patients (22 men, 12 women; mean age, 42 years) with histologically proved LGGs (eight oligodendrogliomas, 20 astrocytomas, and six oligoastrocytomas) were followed up clinically and radiologically for a median of 2.6 years (range, 0.4-5.5 years). Tumor growth over the course of 6 months was the best predictor of time to transformation, independent of rCBV, diffusion histogram parameters, age, sex, and histologic findings. When only single-time-point measurements were compared, tumor volume helped predict outcome best and was the only independent predictor of time to death (P < .02).ConclusionSix-month tumor growth helps predict outcome in patients with LGG better than parameters derived from perfusion- or diffusion-weighed MR imaging. Tumor growth can readily be calculated from volume measurements on images acquired with standard MR imaging protocols and may well prove most useful among various MR imaging findings in clinical practice.(c) RSNA, 2009.

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