External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal CT images.

Objectives: Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.

Exploring the Biology of Cancer-Associated Fibroblasts in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy characterised by a stubbornly low 5-year survival which is essentially unchanged in the past 5 decades. Despite recent advances in chemotherapy and surgical outcomes, progress continues to lag behind that of other cancers. The PDAC microenvironment is characterised by a dense, fibrotic stroma of which cancer-associated fibroblasts (CAFs) are key players.

Unexpected internal hernia in a patient with small bowel obstruction: an old surgical axiom.

An 85-year-old man with no previous laparotomies and no herniae presented with a small bowel obstruction. CT imaging did not suggest any obvious cause; however, a transition point at the terminal ileum was noted. At laparotomy, the small bowel was unexpectedly found to be obstructed through a tight anterior hiatal defect.

Lifestyle interventions are feasible in patients with colorectal cancer with potential short-term health benefits: a systematic review.

Purpose: Lifestyle interventions have been proposed to improve cancer survivorship in patients with colorectal cancer (CRC), but with treatment pathways becoming increasingly multi-modal and prolonged, opportunities for interventions may be limited. This systematic review assessed the evidence for the feasibility of performing lifestyle interventions in CRC patients and evaluated any short- and long-term health benefits.

Methods: Using PRISMA Guidelines, selected keywords identified randomised controlled studies (RCTs) of lifestyle interventions [smoking, alcohol, physical activity (PA) and diet/excess body weight] in CRC patients.

Analysis of lesion localisation at colonoscopy: outcomes from a multi-centre U.K. study.

Background: Colonoscopy is currently the gold standard for detection of colorectal lesions, but may be limited in anatomically localising lesions. This audit aimed to determine the accuracy of colonoscopy lesion localisation, any subsequent changes in surgical management and any potentially influencing factors.

Methods: Patients undergoing colonoscopy prior to elective curative surgery for colorectal lesion/s were included from 8 registered U.

Improving lesion localisation at colonoscopy: an analysis of influencing factors.

Purpose: Colonoscopy detects colorectal cancer and determines lesion localisation that influences surgical planning. However, published work suggests that the accuracy of lesion localisation can be low as 60%, with implications for both the surgeon and the patient. This work aims to identify potential influencing factors at colonoscopy that could lead to improved lesion localisation accuracy.