Artificial intelligence for ultrasonographic detection and diagnosis of hepatocellular carcinoma and cholangiocarcinoma.

The effectiveness of ultrasonography (USG) in liver cancer screening is partly constrained by the operator's expertise. We aimed to develop and evaluate an AI-assisted system for detecting and classifying focal liver lesions (FLLs) from USG images. This retrospective study incorporated 26,288 USG images from 5444 patients to train YOLOv5 model for FLLs detection and classification of seven different types of FLLs, including hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), focal fatty infiltration, focal fatty sparing (FFS), cyst, hemangioma, and regenerative nodules. AI model performance was assessed for detection and diagnosis of the FLLs on a per-image and per-lesion basis. The AI achieved an overall FLLs detection rate of 84.8% (95%CI:83.3-86.4), with consistent performance for FLLs ≤ 1 cm and > 1 cm. It also exhibited sensitivity and specificity for distinguishing malignant FLLs from other benign FLLs at 97.0% (95%CI:95. 9-98.2) and 97.0% (95%CI:95.9-98.1), respectively. Among specific FLL types, CCA detection rate was at 92.2% (95%CI:88.0-96.4), followed by FFS at 89.7% (95%CI:87.1-92.3), and HCC at 82.3% (95%CI:77.1-87.5). The specificities and NPVs for regenerative nodules were 100% and 99.9% (95%CI:99.8-100.0), respectively. Our AI model can potentially assist physicians in FLLs detection and diagnosis during USG examinations. Further external validation is needed for clinical application.

VOCs from Exhaled Breath for the Diagnosis of Hepatocellular Carcinoma.

BACKGROUND: Volatile organic compound (VOC) profiles as biomarkers for hepatocellular carcinoma (HCC) are understudied. We aimed to identify VOCs from the exhaled breath for HCC diagnosis and compare the performance of VOCs to alpha-fetoprotein (AFP). The performance of VOCs for predicting treatment response and the association between VOCs level and survival of HCC patients were also determined. METHODS: VOCs from 124 HCC patients and 219 controls were identified using the XGBoost algorithm. ROC analysis was used to determine VOCs performance in differentiating HCC patients from controls and in discriminating treatment responders from non-responders. The association between VOCs and the survival of HCC patients was analyzed using Cox proportional hazard analysis. RESULTS: The combination of 9 VOCs yielded 70.0% sensitivity, 88.6% specificity, and 75.0% accuracy for HCC diagnosis. When differentiating early HCC from cirrhotic patients, acetone dimer had a significantly higher AUC than AFP, i.e., 0.775 vs. 0.714, respectively, p = 0.001. Acetone dimer classified HCC patients into treatment responders and non-responders, with 95.7% sensitivity, 73.3% specificity, and 86.8% accuracy. Isopropyl alcohol was independently associated with the survival of HCC patients, with an adjusted hazard ratio of 7.23 (95%CI: 1.36-38.54), p = 0.020. CONCLUSIONS: Analysis of VOCs is a feasible noninvasive test for diagnosing and monitoring HCC treatment response.

Circulating tumor cells as a prognostic biomarker in patients with hepatocellular carcinoma.

Circulating tumor cells (CTCs) have been shown as a surrogate for cancer progression and prognostication. We aimed to determine an association between CTCs and survival of hepatocellular carcinoma (HCC) patients. Peripheral blood was obtained from 73 HCC patients to enumerate for epithelial CTCs/8 mL blood. CTCs were detected by immunoaffinity-based method using epithelial cell adhesion molecule (EpCAM) and mucin1 (MUC1). The CTCs detection rates of BCLC stages A, B, and C patients were 65.4% (17/26), 77.3% (17/22), and 96% (24/25), respectively, p = 0.018. Patients with CTCs < 5 cells/8 mL had significantly longer survival than those with CTCs ≥ 5 cells/8 mL (>36 vs. 4.6 months, p < 0.001). In multivariate analysis, CTP B, BCLC B, BCLC C, AFP ≥ 400 ng/mL, and CTC ≥ 5 cells/8 mL were independently associated with survival, with adjusted HRs (95%CI) of 4.1 (2.0-8.4), 3.5 (1.1-11.4), 4.7 (1.4-15.4), 2.4 (1.1-5.0), and 2.6 (1.2-8.4); p < 0.001, 0.036, 0.011, 0.025 and 0.012, respectively. The combination of CTCs ≥ 5 cells/8 mL and AFP ≥ 400 ng/mL provided additively increased HR to 5.3 (2.5-11.1), compared to HRs of 4.0 (2.0-8.0) and 3.5 (1.8-6.7) for CTCs ≥ 5 cells/8 mL and AFP ≥ 400 ng/mL, p < 0.001, respectively. The larger number of peripheral CTCs is correlated with higher tumor aggressive features and poorer survival of HCC patients. CTCs can potentially become novel prognostic biomarker in HCC.

Physician- and patient-reported barriers to hepatocellular carcinoma surveillance: A nationwide survey.

Hepatocellular carcinoma (HCC) surveillance rates are suboptimal. We aimed to identify HCC surveillance barriers from both physician's and patient's perspectives and assess the effectiveness of physician education using social networks. A nationwide survey with 513 physicians and another single-center survey with 315 HCC-risk patients were conducted. Barriers to suboptimal surveillance were identified using univariate and multivariate logistic regression analysis. We educated 143 physicians by sending brief notes on HCC surveillance guidelines via social networks and re-evaluated their knowledge after 60 days using t test. Surveys showed 458 (86.3%), 254 (47.8%), and 225 (42.4%) physicians recommended surveillance in patients with cirrhosis, at-risk hepatitis B virus, and hepatitis C virus infection, respectively. Only 228 (42.9%) and 241 (38.0%) respondents adhered to recommended surveillance tools and interval, respectively. The main surveillance barriers among physicians were the lack of knowledge and resource limitations. The lack of a doctor's prescription was identified as a major barrier by patient' perspectives (odds ratio 1.4, 95% CI: 1.1-1.8, P = .024). Education via social networks enhanced physicians' knowledge, with pre- and post-education scores for guideline awareness of 63.0% versus 84.3% (P < .001) and for surveillance indication and tools of 40.0% versus 63.0% (P = .001), and 42.0% versus 59.3% (P = .015), respectively. Physicians' knowledge gap is a primary barrier for adherence to HCC surveillance protocols. Brief education via social networks shows effectiveness at increasing physicians' knowledge of HCC surveillance.