Ayman Alhasan1,2, Milena Cerny3, Damien Olivié1, Jean-Sébastien Billiard1, Catherine Bergeron1, Kip Brown3, Paule Bodson-Clermont3, Hélène Castel4, Simon Turcotte3,5, Pierre Perreault1, An Tang6,7,8. 1. Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, H2X 0C2, Canada. 2. Faculty of Medicine, Taibah University, Medina, Saudi Arabia. 3. Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), 900, rue Saint-Denis (Tour Viger), Montreal, QC, H2X 0A9, Canada. 4. Department of Hepatology and Liver Transplantation, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. 5. Department of Surgery, Hepatopancreatobiliary and Liver Transplantation Service, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. 6. Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, H2X 0C2, Canada. an.tang@umontreal.ca. 7. Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), 900, rue Saint-Denis (Tour Viger), Montreal, QC, H2X 0A9, Canada. an.tang@umontreal.ca. 8. Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montreal, QC, Canada. an.tang@umontreal.ca.
Abstract
PURPOSE: To evaluate the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS) v2017 major features, the impact of ancillary features, and categories on contrast-enhanced computed tomography (CECT) for the diagnosis of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This retrospective study included 59 patients (104 observations including 72 HCCs) with clinical suspicion of HCC undergoing CECT between 2013 and 2016. Two radiologists independently assessed major and ancillary imaging features for each liver observation and assigned a LI-RADS category based on major features only and in combination with ancillary features. The composite reference standard included pathology or imaging. Per-lesion estimates of diagnostic performance of major features, ancillary features, and LI-RADS categories were assessed by generalized estimating equation models. RESULTS: Major features (arterial phase hyperenhancement, washout, capsule, and threshold growth) respectively had a sensitivity of 86.1%, 81.6%, 20.7%, and 26.1% and specificity of 39.3%, 67.9%, 89.9%, and 85.0% for HCC. Ancillary features (ultrasound visibility as discrete nodule, subthreshold growth, and fat in mass more than adjacent liver) respectively had a sensitivity of 42.6%, 50.8%, and 15.1% and a specificity of 79.2%, 66.9%, and 96.4% for HCC. Ancillary features modified the final category in 4 of 104 observations. For HCC diagnosis, categories LR-3, LR-4, LR-5, and LR-TIV (tumor in vein) had a sensitivity of 5.3%, 29.0%, 53.7%, and 10.7%; and a specificity of 49.1%, 84.4%, 97.3%, and 96.4%, respectively. CONCLUSION: On CT, LR-5 category has near-perfect specificity for the diagnosis of HCC and ancillary features modifies the final category in few observations.
PURPOSE: To evaluate the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS) v2017 major features, the impact of ancillary features, and categories on contrast-enhanced computed tomography (CECT) for the diagnosis of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This retrospective study included 59 patients (104 observations including 72 HCCs) with clinical suspicion of HCC undergoing CECT between 2013 and 2016. Two radiologists independently assessed major and ancillary imaging features for each liver observation and assigned a LI-RADS category based on major features only and in combination with ancillary features. The composite reference standard included pathology or imaging. Per-lesion estimates of diagnostic performance of major features, ancillary features, and LI-RADS categories were assessed by generalized estimating equation models. RESULTS: Major features (arterial phase hyperenhancement, washout, capsule, and threshold growth) respectively had a sensitivity of 86.1%, 81.6%, 20.7%, and 26.1% and specificity of 39.3%, 67.9%, 89.9%, and 85.0% for HCC. Ancillary features (ultrasound visibility as discrete nodule, subthreshold growth, and fat in mass more than adjacent liver) respectively had a sensitivity of 42.6%, 50.8%, and 15.1% and a specificity of 79.2%, 66.9%, and 96.4% for HCC. Ancillary features modified the final category in 4 of 104 observations. For HCC diagnosis, categories LR-3, LR-4, LR-5, and LR-TIV (tumor in vein) had a sensitivity of 5.3%, 29.0%, 53.7%, and 10.7%; and a specificity of 49.1%, 84.4%, 97.3%, and 96.4%, respectively. CONCLUSION: On CT, LR-5 category has near-perfect specificity for the diagnosis of HCC and ancillary features modifies the final category in few observations.
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Keywords:
Ancillary features; CT; Category; Hepatocellular carcinoma; LI-RADS; Major features