Motivation: The MRI LI-RADS v2018 table is complex and has insufficient sensitivity. Goal(s): To evaluate the diagnostic performance of the simplified LI-RADS table for HCC on ECA-MRI, and to determine the value of AFP level as an additional major feature. Approach: We developed and compared the per-lesion sensitivity for HCC defined by LI-RADS v2018, simplified LI-RADS table, and both of them combined with AFP ≥ 200 ng/mL. Results: Compared with LR-5 v2018, the simplified LI-RADS table provided higher sensitivity and comparable specificity for HCC. AFP ≥ 200 ng/mL may be a suitable additional major feature for further improving LR-5 v2018 and sLR-5 classification. Impact: Our simplified LI-RADS table may be more convenient and clinically helpful, and the AFP ≥ 200 ng/mL may be a suitable additional major feature for accurate LR-5 and sLR-5 classification.
A histologic sign known as “vessels encapsulating tumor clusters” (VETC) has been shown to be a powerful predictor of aggressive hepatocellular carcinoma (HCC) and is associated with unfavorable prognosis. It has been previously demonstrated that MR elastography (MRE)-based stiffness and shear strain mapping are promising in prediction of HCC aggressiveness. We investigated the diagnostic performance of MRE for predicting the VETC finding in HCC. Our results showed that 3D MRE-based peritumor OSS-pLSL and tumor stiffness performed well in predicting VETC status preoperatively, and their combination achieved an AUC of 0.92 in predicting VETC with sensitivity (87.9%) and specificity (83.9%).
High drug resistance remains a challenge for chemotherapy against hepatocellular carcinoma (HCC). Combining chemotherapeutic agents with microRNA (miRNA), which simultaneously regulates multiple pathways, offers a promising approach to improve therapeutic efficacy against HCC. Although cationic amphiphilic copolymers have been used to co-deliver these agents, their effectiveness is often limited by low co-encapsulation efficiency and inherent cationic toxicity. In this study, we developed a facile approach to co-deliver doxorubicin (DOX) and miRNA-26a (miR-26a) using a non-cationic nanogel. The incorporation of an amphiphilic monomer and a lysosomal enzyme-sensitive crosslinker endows the nanomedicine with several advantages, including high co-encapsulation efficiency, lysosomal escape, and minimal toxicity. miR-26a significantly increased the sensitivity of HCC to DOX by 3.35-fold through targeting multiple pathways, and promoted DOX penetration within tumor tissue through reducing type I collagen content, thereby showing significant synergistic anticancer effects. This study provides a facile and biosafe nanoplatform for the efficient co-delivery of DOX and miRNA with synergistic drug effect.
Motivation: Hepatocellular carcinoma (HCC) exhibits significant intertumoral heterogeneity, which contributes significantly to treatment resistance and failure. Noninvasive imaging and radiomics for preoperative decoding of the subtypes and prognosis may be valuable in clinical management. Goal(s): To preoperatively develop and validate clustering analysis of HCC based on MRI radiomics features for identifying subtypes with discrete prognosis. Approach: We performed clustering analysis of HCC based on MRI radiomics features to detect distinct subtypes, and subsequently clinicopathological parameters and prognosis were compared and evaluated between different subtypes. Results: Based on the radiomics features of MRI, clustering analysis identified two distinct subtypes with discrete prognosis in HCC patients. Impact: Clustering analysis based on the radiomics features of multiparametric MRI is a potential noninvasive decision-making method for the management of patients with HCC in clinical practice.
Background Hepatocellular carcinoma (HCC) heterogeneity impacts prognosis, and imaging is a potential indicator. Purpose To characterize HCC image subtypes in MRI and correlate subtypes with recurrence. Study Type Retrospective. Population A total of 440 patients (training cohort = 213, internal test cohort = 140, external test cohort = 87) from three centers. Field Strength/Sequence 1.5‐T /3. 0‐T , fast/turbo spin‐echo T 2 ‐weighted, spin‐echo echo‐planar diffusion‐weighted, contrast‐enhanced three‐dimensional gradient‐recalled‐echo T 1 ‐weighted with extracellular agents ( Gd‐DTPA , Gd‐DTPA‐BMA , and Gd‐BOPTA ). Assessment Three‐dimensional volume‐of‐interest of HCC was contoured on portal venous phase, then coregistered with precontrast and late arterial phases. Subtypes were identified using non‐negative matrix factorization by analyzing radiomics features from volume‐of‐interests, and correlated with recurrence. Clinical (demographic and laboratory data), pathological, and radiologic features were compared across subtypes. Among clinical, radiologic features and subtypes, variables with variance inflation factor above 10 were excluded. Variables ( P < 0.10) in univariate Cox regression were included in stepwise multivariate analysis. Three recurrence estimation models were built: clinical‐radiologic model, subtype model, hybrid model integrating clinical‐radiologic characteristics, and subtypes. Statistical Tests Mann–Whitney U test, Kruskal–Wallis H test, chi‐square test, Fisher's exact test, Kaplan–Meier curves, log‐rank test, concordance index (C‐index). Significance level: P < 0.05. Results Two subtypes were identified across three cohorts (subtype 1:subtype 2 of 86:127, 60:80, and 36:51, respectively). Subtype 1 showed higher microvascular invasion (MVI)‐positive rates (53%–57% vs. 26%–31%), and worse recurrence‐free survival. Hazard ratio (HR) for the subtype is 6.10 in subtype model. Clinical‐radiologic model included alpha‐fetoprotein (HR: 3.01), macrovascular invasion (HR: 2.32), nonsmooth tumor margin (HR: 1.81), rim enhancement (HR: 3.13), and intratumoral artery (HR: 2.21). Hybrid model included alpha‐fetoprotein (HR: 2.70), nonsmooth tumor margin (HR: 1.51), rim enhancement (HR: 3.25), and subtypes (HR: 5.34). Subtype model was comparable to clinical‐radiologic model (C‐index: 0.71–0.73 vs. 0.71–0.73), but hybrid model outperformed both (C‐index: 0.77–0.79). Conclusion MRI radiomics‐based clustering identified two HCC subtypes with distinct MVI status and recurrence‐free survival. Hybrid model showed superior capability to estimate recurrence. Level of Evidence 3 Technical Efficacy Stage 2
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