Therapy response evaluation of malignant lymphoma in a multicenter study: comparison of manual and semiautomatic measurements in CT.

PURPOSE: Comparison of manual one-/bi-dimensional measurements versus semi-automatically derived one-/bi-dimensional and volumetric measurements for therapy response evaluation of malignant lymphoma during CT follow-up examinations in a multicenter setting.

MATERIALS AND

METHODS

MSCT data sets of patients with malignant lymphoma were evaluated before (baseline) and after two cycles of chemotherapy (follow-up) at radiological centers of five university hospitals. The long axis diameter (LAD), the short axis diameter (SAD) and the bi-dimensional WHO of 307 target lymph nodes were measured manually and semi-automatically using dedicated software. Lymph node volumetry was performed semi-automatically only. The therapeutic response was evaluated according to lymphoma-adapted RECIST.

RESULTS

Based on a single lymph node, semi-automatically derived multidimensional parameters allowed for significantly more accurate therapy response classification than the manual or the semi-automatic unidimensional parameters. Incorrect classifications were reduced by up to 9.6%. Compared to the manual approach, the influence of the study center on correct therapy classification is significantly less relevant when using semi-automatic measurements.

CONCLUSION

Semi-automatic volumetry and bi-dimensional WHO significantly reduce the number of incorrectly classified lymphoma patients by approximately 9.6% in the multicenter setting in comparison to linear parameters. Semi-automatic quantitative software tools may help to significantly reduce wrong classifications that are associated with the manual assessment approach.

KEY POINTS: ► Semi-automatic volumetry and bi-dimensional WHO significantly reduce the number of incorrectly classified lymphoma patients ► Manual lymph node evaluation with uni-dimensional parameters is inferior to semi-automatic analysis in a multicenter setting ► Semi-automatic quantitative software tools should be introduced in clinical study evaluation.