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Disordered vascularity is a hallmark of carcinogenesis. Fluorescence microperfusion heterogeneity may discriminate malignant transformation within significant (> 20 mm) rectal polyps enabling in-situ endoscopic classification via machine learning (ML) methods to inform clinical care. Patients referred for transanal management of rectal neoplasia were recruited. Indocyanine green was administered intravenously and near-infrared (NIR) endoscopic video recorded. Videos were processed with bespoke fluorescence quantification software producing intensity-timeseries plots for neoplastic and normal regions of interest in the same patients. Plot features were extracted to train/test ML classification algorithms, including coefficient of variation (CV), reporting cancer characterisation sensitivity, specificity and accuracy. 190 video recordings from 182 patients (57.9% with cancer) from six cancer centres provided usable dataset (91% of 201 consenting patients). Overall, the software accurately tracked and detailed NIR perfusion features from, on average (SD), 74.7% (25.3) of annotated regions of interest over the five-minute recording phase. The sensitivity/specificity/accuracy rates of traditional endoscopic biopsy ( n  = 172), MRI ( n  = 139) and expert surgeon opinion ( n  = 190) at surgery were 70.8%/100%/81.7%, 85.4%/ 44.1%/72.7% and 79.1%/80%/79.5% respectively. In comparison, trained ML sensitivity/specificity/ accuracy was 77.6%/39.8%/61.1% and 73.5%/48.2%/62.6% with base and CV featured algorithms respectively. Combining point of care clinical data (specifically MRI and clinicians’ preoperative predictions) with the ML algorithms improved sensitivity/specificity/accuracy to 86.0%/71.1%/79.5% and 82.2%/74.7%/79.0% respectively. Malignant transformation precipitates discriminant perfusion patterns, in a manner exploitable digitally, that indicate cancer presence in significant rectal polyps. Combining clinical indicators appears to improve classification accuracy further, especially specificity. Trial registration: Future of Colorectal Cancer Surgery (FOOCCuS1). Clinicatrials.gov. NCT04220242. Clinicaltrials.gov/study/NCT04220242. CLASSICA: Validating AI in Classifying Cancer in Real-Time Surgery. Clinicaltrials.gov. NCT05793554. Clinicaltrials.gov/study/NCT05793554.

Aims Communication skills are essential for surgeons; typified regarding consent. We evaluated communication simulation training (CST) for informed consent competency in senior medical students. Methods With institutional ethics approval, CST was implemented during our undergraduate clinical surgery module. Students were divided in two groups by randomized cluster sampling and assessed at baseline on consent competency using a simulated patient (SP) for a colonoscopy scenario. The control group proceeded with standard clinical learning, while the intervention group received CST, which included tutor-led roleplay of good and poor consent for laparoscopic cholecystectomy, followed by peer reenactment and discussion. All students then underwent repeat assessment—an observed SP consent for laparoscopic appendicectomy—by an independent, single-blinded senior clinician within the same week. Communication skills were scored by Objective Structured Clinical Examination (OSCE) using both the University College of Dublin School of Medicine OSCE scoring rubric and the externally validated Global Communication Rating Scale (GCRS). Intervention group students were surveyed including anonymously reporting consent confidence pre- and post-CST. All procedures chosen are the three most commonly witnessed by students within their surgical rotations and all are typically familiar with them at this stage in their training. Results Of the 122 students who participated, 61 received Communication Skills Training (CST). Baseline UCD and GCRS scores were similar across groups, but post-intervention scores were significantly higher in the CST group. Their average grade improved from a C to a B+, with a medium to large effect size (0.79), while the control group remained at a C. CST students also showed significant gains in GCRS domains—initiation, verbal communication, session structuring, and information relay. Self-confidence improved notably: only 11 students initially felt confident obtaining consent, compared to 62 post-training, with over 80% survey response rate. Conclusions Medical student CST improves consent communication skills versus observational learning demonstrating its impactful role within clinical undergraduate training. Clinical trial number ISRCTN10251799. Trial registration date 31.10.24.

Background Indocyanine green fluorescence angiography (ICGFA) during colorectal surgery associates with reduced post-operative anastomotic complication rates. Because its interpretation is subjective, quantification has been proposed to address inter-user variability. This study reviews the published literature regarding ICGFA quantification during colorectal surgery with a focus on impactful clinical deployment. Methods A systematic review was performed of English language publications regarding clinical studies of ICGFA quantification in colorectal surgery in PubMed, Scopus, Web of Science and Cochrane Library on 29th August 2024, updated to 18th November 2024, following PRISMA guidelines. Newcastle Ottawa scale (NOS) was used to assess quality. Results A total of 1428 studies were screened with 22 studies (1469 patients) selected. There was significant heterogeneity of ICGFA methodology, quantification methods and parameter selection and only three studies were NOS “high” quality. Extracorporeal application was most common. Four studies (154 patients) conducted real-time ICGFA analyses (others were post hoc) and four utilised artificial intelligence methods. Eleven studies only included patients undergoing left-sided resection (six focusing specifically on rectal resections). Only one study employed the quantification method to guide intra-operative decision-making regarding colonic transection. Twenty-six different perfusion parameters were assessed, with time from injection to visible fluorescence and maximum intensity the most commonly (but not only) correlated parameters regarding anastomotic complication ( n  = 18). Other grounding correlates were tissue oxygenation ( n  = 3, two with hyperspectral imagery), metabolites ( n  = 2) and surgeon interpretation ( n  = 5). Conclusion Quantification of the ICGFA signal for colorectal surgery is feasible but has so far seen limited academic advancement beyond feasibility.

Purpose Perioperative decision making for large (> 2 cm) rectal polyps with ambiguous features is complex. The most common intraprocedural assessment is clinician judgement alone while radiological and endoscopic biopsy can provide periprocedural detail. Fluorescence-augmented machine learning (FA-ML) methods may optimise local treatment strategy. Methods Surgeons of varying grades, all performing colonoscopies independently, were asked to visually judge endoscopic videos of large benign and early-stage malignant (potentially suitable for local excision) rectal lesions on an interactive video platform (Mindstamp) with results compared with and between final pathology, radiology and a novel FA-ML classifier. Statistical analyses of data used Fleiss Multi-rater Kappa scoring, Spearman Coefficient and Frequency tables. Results Thirty-two surgeons judged 14 ambiguous polyp videos (7 benign, 7 malignant). In all cancers, initial endoscopic biopsy had yielded false-negative results. Five of each lesion type had had a pre-excision MRI with a 60% false-positive malignancy prediction in benign lesions and a 60% over-staging and 40% equivocal rate in cancers. Average clinical visual cancer judgement accuracy was 49% (with only ‘fair’ inter-rater agreement), many reporting uncertainty and higher reported decision confidence did not correspond to higher accuracy. This compared to 86% ML accuracy. Size was misjudged visually by a mean of 20% with polyp size underestimated in 4/6 and overestimated in 2/6. Subjective narratives regarding decision-making requested for 7/14 lesions revealed wide rationale variation between participants. Conclusion Current available clinical means of ambiguous rectal lesion assessment is suboptimal with wide inter-observer variation. Fluorescence based AI augmentation may advance this field via objective, explainable ML methods.

Background Mean corpuscular volume (MCV) has been shown to have some correlation to oncological outcomes in oesophageal cancer, with high pre-operative MCV associated with disease recurrence. A similar association has previously been reported in colorectal cancer. Aims This study is aimed at investigating whether high MCV bears similar relation to post-operative outcome and disease recurrence in colorectal cancer (CRC). Methods Patients undergoing elective CRC resection with curative intent between January 2008 and December 2019 were identified from our prospective database. Review of patient demographic details, American Society of Anaesthesiologists (ASA) grade, smoking and alcohol intake were performed. In addition, tumour location and staging, operation performed, pre-operative laboratory data and oncological management of each patient were noted. Post-operative morbidity (Clavien-Dindo (CD) score > 2), 30-day mortality, in-hospital mortality and cancer recurrence were examined and multivariable regression analysis was performed to predict these outcomes. Results A total of 1,293 CRCs were resected, with 1,159 patients (89.7%) experiencing a hospital course without major morbidity (CD < 3). 30-day mortality rate was less than 1% (12/1293). There were 176 patients (13.6%) with recurrence at follow-up. When multivariable regression analysis was performed, high pre-operative MCV did not predict negative post-operative or oncological outcomes. Conclusion MCV does not appear to be an independent prognostic factor for outcomes following elective CRC resection.

The Line Emission Mapper (LEM) is an X-ray Probe for the 2030s that will answer the outstanding questions of the Universe's structure formation. It will also provide transformative new observing capabilities for every area of astrophysics, and to heliophysics and planetary physics as well. LEM's main goal is a comprehensive look at the physics of galaxy formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. These processes are best studied in X-rays, and emission-line mapping is the pressing need in this area. LEM will use a large microcalorimeter array/IFU, covering a 30x30' field with 10\" angular resolution, to map the soft X-ray line emission from objects that constitute galactic ecosystems. These include supernova remnants, star-forming regions, superbubbles, galactic outflows (such as the Fermi/eROSITA bubbles in the Milky Way and their analogs in other galaxies), the Circumgalactic Medium in the Milky Way and other galaxies, and the Intergalactic Medium at the outskirts and beyond the confines of galaxies and clusters. LEM's 1-2 eV spectral resolution in the 0.2-2 keV band will make it possible to disentangle the faintest emission lines in those objects from the bright Milky Way foreground, providing groundbreaking measurements of the physics of these plasmas, from temperatures, densities, chemical composition to gas dynamics. While LEM's main focus is on galaxy formation, it will provide transformative capability for all classes of astrophysical objects, from the Earth's magnetosphere, planets and comets to the interstellar medium and X-ray binaries in nearby galaxies, AGN, and cooling gas in galaxy clusters. In addition to pointed observations, LEM will perform a shallow all-sky survey that will dramatically expand the discovery space.