Yvonne Purcell1, Riccardo Sartoris1, Valérie Paradis2,3, Valérie Vilgrain1,2,3, Maxime Ronot1,2,4. 1. Department of Radiology, APHP, University Hospitals Paris-Nord-Val-de-Seine, Beaujon, Clichy, France. 2. University Paris Diderot, Sorbonne Paris Cité, Paris, France. 3. Department of Pathology, APHP, University Hospitals Paris-Nord-Val-de-Seine, Beaujon, Clichy, France. 4. INSERM U1149, CRI, Paris, France.
Abstract
BACKGROUND AND AIM: The study aims to assess the influence of pretreatment tumor growth rate (TGR) on modified response evaluation criteria in solid tumors (mRECIST) objective response (OR) after a first session of selective transarterial chemoembolization (TACE) for the treatment of hepatocellular carcinoma (HCC). METHODS: One hundred fifteen patients (101 men [88%], mean 65.1 ± 10.5 years [range 26-87]) with 169 tumors (mean 34.2 ± 29.3 mm [10-160]), undergoing a first session of selective TACE for the treatment of HCC between 2011 and 2016, were included. TGR was calculated as the percentage change in tumor volume per month (%/month) on imaging before treatment. TGR cut-off for prediction of OR was identified by receiver operating characteristic curve analysis. RESULTS: Overall 88/189 (52%) and 46/189 (27%) tumors showed complete response (CR) and partial response (PR) (OR rate 79%), while 32/189 (19%) showed stable disease (SD), and 3/189 (2%) were progressive disease (PD) on computed tomography at 1-month post-TACE. The mean pretreatment TGR was 12.0 ± 15.4 (-3.2-90.4) %/month. TGR of tumors showing CR, PR, SD, and PD was a mean 13.2 ± 16.4%, 12.1 ± 15.1%, 5.3 ± 4.5%, and 44.8 ± 20.4%, respectively (P < 0.001). The three tumors showing PD had TGR values > 20%/month. TGR was significantly higher in tumors with OR (12.8 ± 15.9% vs 5.3 ± 4.5% in SD, P = 0.009). A cut-off value of 6.5%/month had the highest predictive value of OR (AUROC 0.65 ± 0.05, P = 0.009). CONCLUSION: Pretreatment TGR is highly variable in HCC before TACE with a U-shaped distribution for the prediction of tumor response. It provides insight into tumor biology that may be used during pretreatment workup to help stratify patients.
BACKGROUND AND AIM: The study aims to assess the influence of pretreatment tumor growth rate (TGR) on modified response evaluation criteria in solid tumors (mRECIST) objective response (OR) after a first session of selective transarterial chemoembolization (TACE) for the treatment of hepatocellular carcinoma (HCC). METHODS: One hundred fifteen patients (101 men [88%], mean 65.1 ± 10.5 years [range 26-87]) with 169 tumors (mean 34.2 ± 29.3 mm [10-160]), undergoing a first session of selective TACE for the treatment of HCC between 2011 and 2016, were included. TGR was calculated as the percentage change in tumor volume per month (%/month) on imaging before treatment. TGR cut-off for prediction of OR was identified by receiver operating characteristic curve analysis. RESULTS: Overall 88/189 (52%) and 46/189 (27%) tumors showed complete response (CR) and partial response (PR) (OR rate 79%), while 32/189 (19%) showed stable disease (SD), and 3/189 (2%) were progressive disease (PD) on computed tomography at 1-month post-TACE. The mean pretreatment TGR was 12.0 ± 15.4 (-3.2-90.4) %/month. TGR of tumors showing CR, PR, SD, and PD was a mean 13.2 ± 16.4%, 12.1 ± 15.1%, 5.3 ± 4.5%, and 44.8 ± 20.4%, respectively (P < 0.001). The three tumors showing PD had TGR values > 20%/month. TGR was significantly higher in tumors with OR (12.8 ± 15.9% vs 5.3 ± 4.5% in SD, P = 0.009). A cut-off value of 6.5%/month had the highest predictive value of OR (AUROC 0.65 ± 0.05, P = 0.009). CONCLUSION: Pretreatment TGR is highly variable in HCC before TACE with a U-shaped distribution for the prediction of tumor response. It provides insight into tumor biology that may be used during pretreatment workup to help stratify patients.
Authors: Lukas Müller; Felix Hahn; Florian Jungmann; Aline Mähringer-Kunz; Fabian Stoehr; Moritz C Halfmann; Daniel Pinto Dos Santos; Jan Hinrichs; Timo A Auer; Christoph Düber; Roman Kloeckner Journal: Cancer Imaging Date: 2022-01-11 Impact factor: 3.909
Authors: Marco Fronda; Andrea Doriguzzi Breatta; Marco Gatti; Marco Calandri; Claudio Maglia; Laura Bergamasco; Dorico Righi; Riccardo Faletti; Paolo Fonio Journal: Eur Radiol Date: 2021-03-18 Impact factor: 5.315