Workflow-centred evaluation of an automatic lesion tracking software for chemotherapy monitoring by CT.

Abstract

In chemotherapy monitoring, an estimation of the change in tumour size is an important criterion for the assessment of treatment success. This requires a comparison between corresponding lesions in the baseline and follow-up computed tomography (CT) examinations. We evaluate the clinical benefits of an automatic lesion tracking tool that identifies the target lesions in the follow-up CT study and pre-computes the lesion volumes. Four radiologists performed volumetric follow-up examinations for 52 patients with and without lesion tracking. In total, 139 lung nodules, liver metastases and lymph nodes were given as target lesions. We measured reading time, inter-reader variability in lesion identification and volume measurements, and the amount of manual adjustments of the segmentation results. With lesion tracking, target lesion assessment time decreased by 38 % or 22 s per lesion. Relative volume difference between readers was reduced from 0.171 to 0.1. Segmentation quality was comparable with and without lesion tracking. Our automatic lesion tracking tool can make interpretation of follow-up CT examinations quicker and provide results that are less reader-dependent. Computed tomography is widely used to follow-up lesions in oncological patients. Novel software automatically identifies and measures target lesions in oncological follow-up examinations. This enables a reduction of target lesion assessment. The automated measurements are less reader-dependent.