Quantitation of T2 lesion load in multiple sclerosis with magnetic resonance imaging: a pilot study of a probabilistic neural network approach.

RATIONALE AND OBJECTIVES: To quantitate multiple sclerosis (MS) lesions in the brain by using computerized techniques. METHODS: MS lesions from five patients were quantitated with magnetic resonance (MR) imaging by using three approaches: a probabilistic neural network (PNN) approach, a semiautomated method that uses a bifeature space approach with operator intervention at each section, and the "gold standard" of manual outlining of lesions. Each patient underwent two MR studies in 1 day. RESULTS: The PNN approach allows reasonable quantitation of large data sets with minimal operator input. The mean intraobserver error for the PNN approach was competitive with the more time-consuming bifeature space approach (5.2% vs 4.4%, respectively). On average, both computer assisted methods performed better than the manual method (mean intraobserver error, 10.1%). CONCLUSION: The agreement between the two computerized quantitation approaches was good. The number of interactive steps was substantially reduced with the PNN technique, leading to minimal operator intervention time.