SSTR2-Targeted Theranostics in Hepatocellular Carcinoma

Background: While the clinical use of radiolabeled somatostatin analogs is well established in neuroendocrine tumors, there is growing interest in expanding their application to other somatostatin receptor 2 (SSTR2)-expressing cancers. This study investigates the potential utility of SSTR2-targeted theranostics in hepatocellular carcinoma (HCC). Methods: SSTR2 expression in HCC cell lines and clinical samples was evaluated using qRT-PCR, Western blot analysis, and a public dataset. 67Ga-DOTATATE uptake was measured, 177Lu-DOTATATE cytotoxicity was assessed, and 68Ga-DOTATATE tumor targeting was evaluated in HCC animal models and a patient via PET/CT imaging. Results: SSTR2 expression was confirmed in HCC cell lines and clinical samples. Radioligand uptake studies demonstrated SSTR2-mediated 67Ga-DOTATATE uptake. 177Lu-DOTATATE treatment reduced cell proliferation and enhanced the anti-tumor efficacy of the multikinase inhibitor sorafenib. 68Ga-DOTATATE PET/CT scans successfully identified tumors in HCC animal models and spinal metastases in a patient with HCC. Conclusion: These findings provide evidence that SSTR2-based theranostics could have significant implications for the detection and treatment of HCC

Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity > 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI

Optimization in latent space for real-time intraoperative characterization of digital twins

Physics-based Digital Twins, particularly those using the finite element method to solve the underlying partial differential equation, accurately simulate organ behaviors but are computationally intensive, especially for hyper-elastic tissues. Recently, approaches have leveraged neural-network-based surrogate models to accelerate computation time. However, these models are limited by the accurate knowledge of patient-specific characteristics, such as material properties and boundary conditions, at training time. This paper introduces a novel methodology for patient-specific characteristics estimation from live observations during medical interventions. To retain the benefits of neural network-based surrogate models, we propose a hypernetwork architecture that conditions the surrogate models on patient-specific characteristics, thus maintaining accuracy over a predefined distribution of these characteristics. Using the trained network, we perform a gradient-based optimization process to determine the patient characteristics given an intraoperative observation. We demonstrate the flexibility and efficiency of our approach through experiments with varying geometries, complex physics laws, and various patient characteristics.</div

Enhancing Surgical Guidance: Deep Learning-Based Liver Vessel Segmentation in Real-Time Ultrasound Video Frames

Background/Objectives: In the field of surgical medicine, the planning and execution of liver resection procedures present formidable challenges, primarily attributable to the intricate and highly individualized nature of liver vascular anatomy. In the current surgical milieu, intraoperative ultrasonography (IOUS) has become indispensable; however, traditional 2D ultrasound imaging&rsquo;s interpretability is hindered by noise and speckle artifacts. Accurate identification of critical structures for preservation during hepatectomy requires advanced surgical skills. Methods: An AI-based model that can help detect and recognize vessels including the inferior vena cava (IVC); the right (RHV), middle (MHV), and left (LVH) hepatic veins; the portal vein (PV) and its major first and second order branches the left portal vein (LPV), right portal vein (RPV), and right anterior (RAPV) and posterior (RPPV) portal veins, for real-time IOUS navigation can be of immense value in liver surgery. This research aims to advance the capabilities of IOUS-guided interventions by applying an innovative AI-based approach named the &ldquo;2D-weigthed U-Net model&rdquo; for the segmentation of multiple blood vessels in real-time IOUS video frames. Results: Our proposed deep learning (DL) model achieved a mean Dice score of 0.92 for IVC, 0.90 for RHV, 0.89 for MHV, 0.86 for LHV, 0.95 for PV, 0.93 for LPV, 0.84 for RPV, 0.85 for RAPV, and 0.96 for RPPV. Conclusion: In the future, this research will be extended for real-time multi-label segmentation of extended vasculature in the liver, followed by the translation of our model into the surgical suite

Defining the Role of Adjuvant Radiotherapy for Biliary Tract Cancers: A Site-Specific Propensity-Matched Analysis

Background: Biliary tract cancers (BTCs) have distinct tumor biology but share a poor prognosis, with a 5-year-survival-rate of 5&ndash;19%. Surgical resection is the only potential cure, but recurrences are common. The role of adjuvant radiotherapy (XRT) remains unclear. Methods: Using the National Cancer Database (2006&ndash;2018), we analyzed resected non-metastatic BTCs. Patients who survived beyond 90 days post-surgery were included, while those with R2 resections or neoadjuvant therapy were excluded. Propensity matching was performed based on predictors of adjuvant radiation, age, and sex. Survival outcomes were compared between no adjuvant therapy, chemotherapy alone, and XRT &plusmn; chemotherapy. Results: Among 21,275 patients, including 5308 intrahepatic cholangiocarcinoma (IHC), 2689 perihilar cholangiocarcinoma (PHC), 3092 distal cholangiocarcinoma (DCC), and 10,186 gallbladder cancer (GBC) cases, adjuvant XRT did not improve survival for IHC. For PHC and DCC, XRT improved survival over no adjuvant therapy (PHC: 31.2 vs. 26.3 months, p = 0.004; DCC: 33.7 vs. 27.0 months, p = 0.015) but not over chemotherapy alone. For GBC, XRT significantly improved survival compared to both no adjuvant therapy and chemotherapy (30.2 vs. 26.6 and 24.6 months; p = 0.05 and p = 0.001). Conclusions: XRT provides a survival benefit for GBC, especially in node-positive and R1-resected patients. For PHC and DCC, XRT improves outcomes compared to no therapy, but its benefit over chemotherapy is uncertain. No benefit was observed for IHC

Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS (R) v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 +/- 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 +/- 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 +/- 4.9 and 7.8 +/- 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 +/- 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity &gt; 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI