Validation study of a fast, accurate, and precise brain tumor volume measurement

Precision and accuracy are sometimes sacrificed to ensure that medical image processing is rapid. To address this, our lab had developed a novel level set segmentation algorithm that is 16× faster and >96% accurate on realistic brain phantoms.MethodsThis study reports speed, precision and estimated accuracy of our algorithm when measuring MRIs of meningioma brain tumors and compares it to manual tracing and modified MacDonald (MM) ellipsoid criteria. A repeated-measures study allowed us to determine measurement precisions (MPs) – clinically relevant thresholds for statistically significant change.ResultsSpeed: the level set, MM, and trace methods required 1:20, 1:35, and 9:35 (mm:ss) respectively on average to complete a volume measurement (p < 0.05). Accuracy: the level set was not statistically different to the estimated true lesion volumes (p > 0.05). Precision: the MM's within-operator and between-operator MPs were significantly higher (worse) than the other methods (p < 0.05). The observed difference in MP between the level set and trace methods did not reach statistical significance (p > 0.05).ConclusionOur level set is faster on average than MM, yet has accuracy and precision comparable to manual tracing.