¹¹C-choline positron emission tomography/computed tomography (PET/CT) has been used for patients with some types of tumors, but few data are available for hepatocellular carcinoma (HCC). We queried our prospective database for patients with HCC staged with ¹¹C-choline PET/CT to assess the clinical impact of this imaging modality. Seven parameters were recorded: maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), liver standardized uptake value (SUVliver), metabolic tumor volume (MTV), photopenic area, metabolic tumor burden (MTB = MTVxSUVmean), and SUVratio (SUVmax/SUVliver). Analysis was performed to identify parameters that could be predictors of overall survival (OS). Sixty patients were analyzed: fourteen (23%) were in stage 0-A, 37 (62%) in stage B, and 9 (15%) in stage C of the Barcelona classification. The Cox regression for OS showed that Barcelona stages (HR = 2.94; 95%CI = 1.41–4.51; p = 0.003) and MTV (HR = 2.11; 95%CI = 1.51–3.45; p = 0.026) were the only factors independently associated with OS. Receiver operating characteristics curve analysis revealed MTV ability in discriminating survival (area under the curve (AUC) = 0.77; 95%CI = 0.57–097; p < 0.001: patients with MTV ≥ 380 had worse OS (p = 0.015)). The use of ¹¹C-choline PET/CT allows for better prognostic refinement in patients undergoing hepatectomy for HCC. Incorporation of such modality into HCC staging system should be considered.

Background: Emergency laparotomy (EL) is related to a high risk of morbidity and mortality. Sarcopenia (low skeletal muscle mass) and myosteatosis (poor muscle quality) have emerged as prognostic indicators in various clinical contexts. This study evaluated the impact of these conditions on postoperative outcomes in patients undergoing EL for abdominal emergencies. Methods: A retrospective analysis was conducted on 242 patients who underwent EL between January 2016 and December 2023. Skeletal muscle index (SMI) and muscle radiation attenuation (MRA) were measured using CT imaging at the L3 level. Sarcopenia was defined as SMI ≤ 41.6 cm²/m² for men and ≤ 32 cm²/m² for women. Myosteatosis was defined as MRA ≤ 29.3 HU for men and ≤ 22 HU for women. Outcomes included 30-day mortality, hospital length of stay (h-LOS), severe complications (Clavien-Dindo ≥ 3), and Intensive Care Unit (ICU) admission. Results: Of the 242 patients (median age: 70; 51.2% men), 42.6% were sarcopenic and 78.1% had myosteatosis. Sarcopenia was not significantly associated with any postoperative outcomes. Conversely, myosteatosis was significantly associated with longer h-LOS (17 vs. 8 days; p < 0.001), higher rates of severe complications (37.1% vs. 22.7%; p = 0.048), and ICU admission (48.2% vs. 28.3%; p = 0.010), but not with 30-day mortality. Multivariate analysis confirmed myosteatosis as an independent predictor of prolonged hospital stay (HR 0.59, 95% CI: 0.42–0.84 p = 0.003). Conclusions: Myosteatosis, rather than sarcopenia, is associated with worse postoperative outcomes following EL for abdominal emergencies. Including myosteatosis in preoperative risk assessments may improve the identification of high-risk patients and guide perioperative management.

Esophageal cancer is a highly lethal malignancy, representing 5% of all cancer-related deaths. The two main subtypes are esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While most research has focused on ESCC, few studies have analyzed EAC for transcriptional signatures linked to diagnosis or prognosis. In this study, we utilized single-cell RNA sequencing and bulk RNA sequencing to identify specific immune cell types that contribute to anti-tumor responses, as well as differentially expressed genes (DEGs). We have characterized transcriptional signatures, validated against a wide cohort of TCGA patients, that are capable of predicting clinical outcomes and the prognosis of EAC post-surgery with efficacy comparable to the currently accepted prognostic factors. In conclusion, our findings provide insights into the immune landscape and therapeutic targets of EAC, proposing novel immunological biomarkers for predicting prognosis, aiding in patient stratification for post-surgical outcomes, follow-up, and personalized adjuvant therapy decisions.

Esophageal cancer is an extremely deadly tumor that accounts for 5% of all cancer deaths. The two main subtypes of the disease are esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). To date, few studies analyse EAC for transcriptional signatures associated with diagnosis and/or prognosis, while most focus on the analysis of transcriptional profiles of ESCC. In this study, we used single-cell RNA sequencing (scRNA-seq) analysis of CD45+ cells enriched from Tumors and matched Non Tumor tissues from therapy naїve patients to identify all types of immune cells present in tumor immune infiltrate and its transcriptional profile. In addi-tion, we analysed the entire transcriptome in a cohort of 23 patients whose tissue biopsies were taken from Tumors and matched with Non Tumor tissue. The transcriptional signatures we obtained were then used to stratify a large cohort of TCGA EAC patients, demonstrating a strong association with their prognosis, as well as the ability to predict a patient's clinical outcome and better define the prognosis of EAC after surgery. In addition, these features may lead patients to effective therapies including immunotherapy approaches.

Introduction: Small Bowel Obstruction (SBO) accounts for 15% of emergency department (ED) admissions. While conservative management is recommended, surgery becomes necessary when strangulation is suspected. Identifying which patients need surgery remains a challenge, as traditional imaging lacks sufficient sensitivity and specificity. This study aimed to explore radiomic features to identify potential predictors of strangulation. Methods: This retrospective study included patients admitted to a tertiary referral hospital ED between 2019 and 2023, diagnosed with Adhesion Small Bowel Obstruction (aSBO) via contrast-enhanced abdominal CT scans. Two patient groups were examined: those who underwent surgery with bowel resection and ischemic changes confirmed histologically (operative management—OM) and those successfully treated with conservative management (CM). All CT scans were reviewed blindly by a general surgeon and an experienced radiologist. Pre-obstructive loop segmentation was performed using 3D Slicer software, with slice-by-slice contouring of intestinal borders on images of suspected strangulated bowel. Radiomic features were extracted, followed by univariate and multivariate regression analysis. Results: A total of 55 patients were included: 27 CM and 28 OM. Significant differences emerged in GLCM (Gray Level Co-occurrence Matrix), GLDM (Gray Level Dependence Matrix), GLRLM (Gray Level Run Length Matrix), and GLSZM (Gray Level Size Zone Matrix), particularly involving entropy and uniformity. These metrics reflect subtle variations in gray levels not visible to the naked eye. Conclusions: Differences in entropy, uniformity, and energy align with imaging and histopathological findings, supporting the development of radiomic models and future AI-based prediction tools.