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

ABSTRACT

OBJECTIVES: 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. METHODS: 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. 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. CONCLUSIONS: Our automatic lesion tracking tool can make interpretation of follow-up CT examinations quicker and provide results that are less reader-dependent. KEY POINTS 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.