Impact of ultra -low dose CT acquisition on semi -automated RECIST tool in the evaluation of malignant focal liver lesions

Purpose: To compare the evaluation of malignant focal liver lesions (FLLs) using a semi -automated RECIST tool with a standard and an ultra -low dose (ULD) computed tomography (CT) protocol. Materials and methods: Thirty-four patients with malignant FLLs underwent two abdominal -pelvic CT examinations one using a standard protocol and one using an ULD protocol. There were 23 men and 11 women with a mean age 64.3 ? 14.4 (SD) years (range: 22-91 years). Dosimetric indicators were recorded, and effective dose was calculated for both examinations. Mean malignant FLL attenuation, image noise and contrast -to -noise -ratio (CNR) were compared. The largest malignant FLL per patient was evaluated using the semi -automated RECIST tool to determine longest axis length, longest orthogonal axis length, volume and World Health Organisation area. Results: Dosimetric values were significantly reduced by -56% with ULD compared to standard protocol. No differences in mean malignant FLL attenuation values were found between the two protocols. Image noise was significantly increased for all locations ( P < 0.05) with ULD compared to standard protocol, and CNR was significantly reduced ( P < 0.05). On the 34 malignant FLLs analyzed, six semi -automated shapes non -concordant with radiologist?s visual impression were highlighted with the software, including one FLL (1/34; 3%) with standard CT acquisition only, three FLLs (3/34; 9%) with ULD CT acquisition only and two FLLs (2/34; 6%) with both CT acquisitions. After manual editing, the concordance of the values of the studied criteria between both acquisitions was good and no significant difference was reported. Conclusion: Semi -automated RECIST tool demonstrates good performances using ULD CT protocol. It could be used in routine clinical practice with a ULD protocol for follow-up studies in patients with known malignant FLL. (C) 2020 Societe francaise de radiologie. Published by Elsevier Masson SAS. All rights reserved.