Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials and Methods Patients with pathologically proven HCC from May 2012 to September 2020 were retrospectively included from four medical centers. Radiomics features were extracted from tumors and peritumor regions on preoperative registration or subtraction CT images. In the training set, these features were used to build five radiomics models via logistic regression after feature reduction. The models were tested using internal and external test sets against a pathologic reference standard to calculate area under the receiver operating characteristic curve (AUC). The optimal AUC radiomics model and clinical-radiologic characteristics were combined to build the hybrid model. The log-rank test was used in the outcome cohort (Kunming center) to analyze early recurrence-free survival and overall survival based on high versus low model-derived score. RNA sequencing data from The Cancer Image Archive were used for gene expression analysis. Results A total of 773 patients (median age, 59 years; IQR, 49-64 years; 633 men) were divided into the training set (n = 334), internal test set (n = 142), external test set (n = 141), outcome cohort (n = 121), and RNA sequencing analysis set (n = 35). The AUCs from the radiomics and hybrid models, respectively, were 0.76 and 0.86 for the internal test set and 0.72 and 0.84 for the external test set. Early recurrence-free survival (P < .01) and overall survival (P < .007) can be categorized using the hybrid model. Differentially expressed genes in patients with findings positive for MVI were involved in glucose metabolism. Conclusion The hybrid model showed the best performance in prediction of MVI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Summers in this issue.

The accurate and timely diagnosis of acute aortic syndrome (AAS) in patients presenting with acute chest pain remains a clinical challenge. Aortic computed tomography (CT) angiography is the imaging protocol of choice in patients with suspected AAS. However, due to economic and workflow constraints in China, the majority of suspected patients initially undergo noncontrast CT as the initial imaging testing, and CT angiography is reserved for those at higher risk. Although noncontrast CT can reveal specific signs indicative of AAS, its diagnostic efficacy when used alone has not been well characterized. Here we present an artificial intelligence-based warning system, iAorta, using noncontrast CT for AAS identification in China, which demonstrates remarkably high accuracy and provides clinicians with interpretable warnings. iAorta was evaluated through a comprehensive step-wise study. In the multicenter retrospective study (n = 20,750), iAorta achieved a mean area under the receiver operating curve of 0.958 (95% confidence interval 0.950–0.967). In the large-scale real-world study (n = 137,525), iAorta demonstrated consistently high performance across various noncontrast CT protocols, achieving a sensitivity of 0.913–0.942 and a specificity of 0.991–0.993. In the prospective comparative study (n = 13,846), iAorta demonstrated the capability to significantly shorten the time to correct diagnostic pathway for patients with initial false suspicion from an average of 219.7 (115–325) min to 61.6 (43–89) min. Furthermore, for the prospective pilot deployment that we conducted, iAorta correctly identified 21 out of 22 patients with AAS among 15,584 consecutive patients presenting with acute chest pain and under noncontrast CT protocol in the emergency department. For these 21 AAS-positive patients, the average time to diagnosis was 102.1 (75–133) min. Finally, iAorta may help prevent delayed or missed diagnoses of AAS in settings where noncontrast CT remains the only feasible initial imaging modality—such as in resource-limited regions or in patients who cannot receive, or did not receive, intravenous contrast.

Diabetes mellitus presents a significant threat to human health because it disrupts energy metabolism and gives rise to various complications, including diabetic kidney disease (DKD). Metabolic adaptations occurring in the kidney in response to diabetes contribute to the pathogenesis of DKD. Iron metabolism and ferroptosis, a recently defined form of cell death resulting from iron-dependent excessive accumulation of lipid peroxides, have emerged as crucial players in the progression of DKD. In this comprehensive review, we highlight the profound impact of adaptive and maladaptive responses regulating iron metabolism on the progression of kidney damage in diabetes. We summarize the current understanding of iron homeostasis and ferroptosis in DKD. Finally, we propose that precise manipulation of iron metabolism and ferroptosis may serve as potential strategies for kidney management in diabetes.

Background and aims: Many patients with HCC of Barcelona Clinic Liver Cancer (BCLC) stage A exceeding the Milan criteria, or of BCLC stage B, can undergo resection after successful preoperative therapy, but an optimal approach has not been identified. We investigated preoperative drug-eluting bead transarterial chemoembolization (DEB-TACE) plus sintilimab, in this setting. Approach and Results: In this prospective, phase II study (NCT04174781), adults with HCC of BCLC stage A exceeding the Milan criteria, or BCLC stage B, and ineligible for surgical resection, received sintilimab 200 mg and DEB-TACE. The primary endpoint was progression-free survival by modified RECIST. Secondary endpoints included objective response rate, pathologic response rate, and safety. At the data cutoff (July 2022), among 60 patients, the objective response rate was 62% (37/60) and 51 patients had undergone surgery. After a median follow-up of 26.0 months (range, 3.4–31.8), the median progression-free survival was 30.5 months (95% CI: 16.1–not reached). Among patients undergoing surgery, median progression-free survival was not reached and the 12-month progression-free survival rate was 76% (95% CI: 67–91). A pathologic complete response was achieved in 14% (7/51) of these patients. All patients experienced at least one adverse event, but these were generally manageable. Exploratory analyses showed an association between cytokeratin, V-domain Ig-containing Suppressor of T-cell Activation, CD68, CD169, and cluster 13 fibroblasts and recurrence after surgery. Conclusions.: Sintilimab plus DEB-TACE before surgery showed good efficacy and safety in patients with HCC of BCLC stage A exceeding the Milan criteria or BCLC stage B.