Predict Early Recurrence of Resectable Hepatocellular Carcinoma Using Multi-Dimensional Artificial Intelligence Analysis of Liver Fibrosis

Abstract

Background: Liver fibrosis is thought to be associated with early recurrence of hepatocellular carcinoma (HCC) after resection. To recognize HCC patients with higher risk of early recurrence, we used a second harmonic generation and two-photon excitation fluorescence (SHG/TPEF) microscopy to create a fully quantitative fibrosis score which is able to predict early recurrence. Methods: The study included 81 HCC patients receiving curative intent hepatectomy. Detailed fibrotic features of resected hepatic tissues were obtained by SHG/TPEF microscopy, and we used multi-dimensional artificial intelligence analysis to create a recurrence prediction model “combined index” according to the morphological collagen features of each patient’s non-tumor hepatic tissues. Results: Our results showed that the “combined index” can better predict early recurrence (area under the curve = 0.917, sensitivity = 81.8%, specificity = 90.5%), compared to alpha fetoprotein level (area under the curve = 0.595, sensitivity = 68.2%, specificity = 47.6%). Using a Cox proportional hazards analysis, a higher “combined index” is also a poor prognostic factor of disease-free survival and overall survival. Conclusions: By integrating multi-dimensional artificial intelligence and SHG/TPEF microscopy, we may locate patients with a higher risk of recurrence, follow these patients more carefully, and conduct further management if needed.

Predictors of Hepatocellular Carcinoma Early Recurrence in Patients Treated with Surgical Resection or Ablation Treatment: A Single-Center Experience

“…1.12–1.63) for early recurrence after curative treatment. Nevertheless, other studies did not report any significant difference in early, gender-related HCC recurrence [ 50 , 51 , 52 ]. Despite no precise data, it can be assumed that the same hormonal factors promoting tumorigenesis might induce even HCC recurrence.…”

Quantitative collagen analysis using second harmonic generation images for the detection of basal cell carcinoma with ex vivo multiphoton microscopy

“…Although MPM device can improve the diagnosis of BCC in vivo and reduce unnecessary biopsies, reading these images remains challenging for a novice 32 . To expand the widespread adaptation of this technique, artificial intelligence algorithms can be built for automated detection of BCC, similar to the work done for the detection of BCC on RCM 35,36 and on hepatocellular carcinoma detection using MPM 37,38 …”

“…32 To expand the widespread adaptation of this technique, artificial intelligence algorithms can be built for automated detection of BCC, similar to the work done for the detection of BCC on RCM 35,36 and on hepatocellular carcinoma detection using MPM. 37,38 In conclusion, we present the results of an ex vivo collagen…”