A Non-Invasive Integrated Model for Accurate Preoperative Identification of the Aggressive Macrotrabecular-Massive Subtype of Hepatocellular Carcinoma: A Single-Center Retrospective Study

<b>Objective:</b> The objective of this study was to develop and validate a predictive model for MTM-HCC by integrating preoperative ultrasound (US) and contrast-enhanced ultrasound (CEUS) features with relevant clinical characteristics. <b>Methods:</b> This retrospective study analyzed data from patients with histopathologically confirmed hepatocellular carcinoma who underwent preoperative CEUS examination at the Ultrasound Department of the Lanzhou University Second Hospital between December 2021 and March 2025. The study cohort comprised 45 patients diagnosed with MTM-HCC and 194 patients with non-MTM-HCC. Ultrasound and CEUS images were independently reviewed by two senior abdominal radiologists with extensive experience in hepatic imaging, ensuring objective feature assessment. Clinical variables and imaging characteristics were systematically compared between the two groups to identify distinguishing patterns. To evaluate the associations among clinical data, ultrasound-derived features, and MTM-HCC, univariate analyses were first performed, followed by multivariate logistic regression to construct and assess predictive models. <b>Results:</b> A total of 239 patients (mean age: 57.28 ± 9.60 years; 187 males and 52 females) were included in the analysis. Among them, 45 HCC patients (18.8%) were classified as MTM-HCC. Multivariate analysis identified four independent predictors: elevated alpha-fetoprotein (AFP ≥ 467 ng/mL) (OR = 8.5, 95% CI: 4.2-17.30; <i>p</i> < 0.001), presence of non-enhancing necrotic areas (OR = 5.92, 95% CI: 1.82-19.30, <i>p</i> = 0.003), intratumoral arteries (OR = 6.61, 95% CI: 2.28-19.22, <i>p</i> < 0.001), and peritumoral feeding arteries (OR = 3.13, 95% CI: 1.15-8.50, <i>p</i> = 0.025). <b>Conclusions:</b> An integrated prediction model that combines ultrasound imaging and clinical parameters offers a feasible, non-invasive approach for accurate preoperative identification of MTM-HCC.