Enrichment of Cancer-Associated Fibroblasts, Macrophages, and Up-Regulated TNF-α Signaling in the Tumor Microenvironment of CMS4 Colorectal Peritoneal Metastasis.

Background: Metastatic colorectal cancer (mCRC) is the main cause of CRC mortality, with limited treatment options. Although immunotherapy has benefited some cancer patients, mCRC typically lacks the molecular features that respond to this treatment. However, recent studies indicate that the immune microenvironment of mCRC may be modified to enhance the effect of immune checkpoint inhibitors.

Intraoperative patient-specific volumetric reconstruction and 3D visualization for laparoscopic liver surgery.

Despite the benefits of minimally invasive surgery, interventions such as laparoscopic liver surgery present unique challenges, like the significant anatomical differences between preoperative images and intraoperative scenes due to pneumoperitoneum, patient pose, and organ manipulation by surgical instruments. To address these challenges, a method for intraoperative three-dimensional reconstruction of the surgical scene, including vessels and tumors, without altering the surgical workflow, is proposed. The technique combines neural radiance field reconstructions from tracked laparoscopic videos with ultrasound three-dimensional compounding.

Initial experience of parenchyma-sparing liver resection with systematic selective hepatic vein reconstruction for colorectal metastases.

Objectives: This study aims to assess the feasibility and short-term and intermediate-term technical success rate of the concept of systematic selective hepatic vein (HV) reconstruction for parenchyma-sparing hepatectomies (PSHs) in patients with colorectal liver metastases (CRLM) in accordance with stage 2a of the IDEAL framework.

Design: The prospective case series of patients deemed eligible and operated on according to the concept.

Setting: All patients were treated by a single surgical team in three hospitals in Ukraine from June 2022 to November 2023.

Development and external evaluation of a self-learning auto-segmentation model for Colorectal Cancer Liver Metastases Assessment (COALA).

Objectives: Total tumor volume (TTV) is associated with overall and recurrence-free survival in patients with colorectal cancer liver metastases (CRLM). However, the labor-intensive nature of such manual assessments has hampered the clinical adoption of TTV as an imaging biomarker. This study aimed to develop and externally evaluate a CRLM auto-segmentation model on CT scans, to facilitate the clinical adoption of TTV.