Preoperative prediction of intra-tumoral tertiary lymphoid structures based on CT in hepatocellular cancer. Issue 151 (June 2022)

• Record Type: Journal Article
• Authors: Li, Pinxiong; Liang, Yun; Zeng, Baozhen; Yang, Guangjun; Zhu, Chao; Zhao, Ke; Xu, Zeyan; Wang, Guiqu; Han, Chu; Ye, Huifen; Liu, Zaiyi; Zhu, Yun; Liang, Changhong
• Is Part Of: European journal of radiology. Issue 151(2022)
• Publication Date: 2022-06
• Subjects: Hepatocellular carcinoma -- X-ray computed tomography -- Tertiary lymphoid structures -- Nomogram; HCC Hepatocellular carcinoma -- TLSs Tertiary lymphoid structures -- LI-RADS Liver imaging reporting and data system -- MRI Magnetic resonance imaging -- CT Computed tomography -- BCLC Barcelona clinic liver cancer -- HBsAg Hepatitis B surface antigen -- HCVAB Hepatitis C virus antibody -- ALBI Albumin-bilirubin -- MTM Macrotrabecular-massive -- VETC Vessels encapsulating tumor clusters -- ROC Receiver operating characteristic -- AUC Area under the ROC curve -- HR Hazard ratio -- CI Confidence interval; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2022.110309
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: The intra-tumoral tertiary lymphoid structures of hepatocellular carcinoma are associated with a favorable prognosis. Imaging features of intratumor arteries and intratumor hemorrhage are independent negative predictors of intra-tumoral TLSs in HCC. CT-based nomogram predictive model is expected to provide a noninvasive preoperative prediction of TLSs in HCC. This study is the first to explore the correlation between imaging features and TLSs. Abstract: Purpose: Intra-tumoral tertiary lymphoid structures (TLSs) are associated with a favorable prognosis for patients with hepatocellular carcinoma (HCC). We aimed to identify image features related to TLSs and develop a nomogram for preoperative noninvasive prediction of intra-tumoral TLSs. Methods: This retrospective study enrolled patients with HCC who underwent contrast-enhanced computed tomography before surgery between January 2014 and September 2020. Two radiologists retrospectively and independently reviewed the CT imaging features, and interobserver agreement was assessed. Univariable and multivariable logistic regression analyses were applied to investigate clinical laboratory data and imaging features related to TLSs. A regression-based predictive model and nomogram were constructed using the identified predictors. Nomogram diagnostic performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration curves, and validated using 5-fold cross-validation. Results: Ninety-three of the 142 HCCs were TLS + HCCs. Multivariable analyses identified intratumor arteries (odds ratio [OR]: 0.23; 95% confidence interval [CI]: 0.07–0.63; p = 0.007), intratumor hemorrhage (OR: 0.08; 95% CI: 0.01–0.50; p = 0.012), positive HBsAg or HCVAB status (OR: 4.52; 95% CI: 1.65–13.29; p = 0.004), platelet count (≥186.5 × 10 9 /L, OR: 0.38; 95% CI: 0.16–0.86; p = 0.022), and aspartate transaminase level (≥33.2 IU/l, OR: 0.24; 95% CI: 0.09–0.59; p = 0.003) as independent predictors of intra-tumoral TLSs. AUC of the regression-based model was 0.79 (95% CI:0.72–0.86) and average AUC at 5-fold cross-validation was 0.75 (95% CI: 0.71–0.80). Conclusions: CT-based nomogram is promising for preoperative prediction of intra-tumoral TLS in HCC.