Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art.

Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major treatment modality for primary and, increasingly, secondary curative therapy. However, with more patients being diagnosed with early stage and premalignant disease manifesting as large polyps, greater accuracy in diagnostic and therapeutic precision is needed right from the time of first endoscopic encounter. Rapid advancements in the field of artificial intelligence (AI), coupled with widespread availability of near infrared imaging (currently based around indocyanine green (ICG)) can enable colonoscopic tissue classification and prognostic stratification for significant polyps, in a similar manner to contemporary dynamic radiological perfusion imaging but with the advantage of being able to do so directly within interventional procedural time frames. It can provide an explainable method for immediate digital biopsies that could guide or even replace traditional forceps biopsies and provide guidance re margins (both areas where current practice is only approximately 80% accurate prior to definitive excision). Here, we discuss the concept and practice of AI enhanced ICG perfusion analysis for rectal cancer surgery while highlighting recent and essential near-future advancements. These include breakthrough developments in computer vision and time series analysis that allow for real-time quantification and classification of fluorescent perfusion signals of rectal cancer tissue intraoperatively that accurately distinguish between normal, benign, and malignant tissues in situ endoscopically, which are now undergoing international prospective validation (the Horizon Europe CLASSICA study). Next stage advancements may include detailed digital characterisation of small rectal malignancy based on intraoperative assessment of specific intratumoral fluorescent signal pattern. This could include T staging and intratumoral molecular process profiling (e.g. regarding angiogenesis, differentiation, inflammatory component, and tumour to stroma ratio) with the potential to accurately predict the microscopic local response to nonsurgical treatment enabling personalised therapy via decision support tools. Such advancements are also applicable to the next generation fluorophores and imaging agents currently emerging from clinical trials. In addition, by providing an understandable, applicable method for detailed tissue characterisation visually, such technology paves the way for acceptance of other AI methodology during surgery including, potentially, deep learning methods based on whole screen/video detailing.

Efferent limb stimulation prior to loop ileostomy closure: a systematic review and meta-analysis.

BACKGROUND: Postoperative ileus (POI) remains a common phenomenon following loop ileostomy closure. Our aim was to determine whether preoperative physiological stimulation (PPS) of the efferent limb reduced POI incidence. METHODS: A PRISMA-compliant meta-analysis searching PubMed, EMBASE and CENTRAL databases was performed. The last search was carried out on 30 January 2023. All randomized studies comparing PPS versus no stimulation were included. The primary endpoint was POI incidence. Secondary endpoints included the time to first passage of flatus/stool, time to resume oral diet, need for nasogastric tube (NGT) placement postoperatively, length of stay (LOS) and other complications. Random effects models were used to calculate pooled effect size estimates. Trial sequential analyses (TSA) were also performed. RESULTS: Three randomized studies capturing 235 patients (116 PPS, 119 no stimulation) were included. On random effects analysis, PPS was associated with a quicker time to resume oral diet (MD - 1.47 days, 95% CI - 2.75 to - 0.19, p = 0.02), shorter LOS (MD - 1.47 days, 95% CI - 2.47 to - 0.46, p = 0.004) (MD - 1.41 days, 95% CI - 2.32 to - 0.50, p = 0.002, I2 = 56%) and fewer other complications (OR 0.42, 95% CI 0.18 to 1.01, p = 0.05). However, there was no difference in POI incidence (OR 0.35, 95% CI 0.10 to 1.21, p = 0.10), the requirement for NGT placement (OR 0.50, 95% CI 0.21 to 1.20, p = 0.12) or time to first passage of flatus/stool (MD - 0.60 days, 95% CI - 1.95 to 0.76, p = 0.39). TSA revealed imprecise estimates for all outcomes (except LOS) and further studies are warranted to meet the required information threshold. CONCLUSIONS: PPS prior to stoma closure may reduce LOS and postoperative complications albeit without a demonstrable beneficial effect on POI. Further high-powered studies are required to confirm or refute these findings.

A feasibility study assessing quantitative indocyanine green angiographic predictors of reconstructive complications following nipple-sparing mastectomy.

Introduction: Immediate post-mastectomy breast reconstruction offers benefits; however, complications can compromise outcomes. Intraoperative indocyanine green fluorescence angiography (ICGFA) may mitigate perfusion-related complications (PRC); however, its interpretation remains subjective. Here, we examine and develop methods for ICGFA quantification, including machine learning (ML) algorithms for predicting complications. Methods: ICGFA video recordings of flap perfusion from a previous study of patients undergoing nipple-sparing mastectomy (NSM) with either immediate or staged immediate (delayed by a week due to perfusion insufficiency) reconstructions were analysed. Fluorescence intensity time series data were extracted, and perfusion parameters were interrogated for overall/regional associations with postoperative PRC. A naïve Bayes ML model was subsequently trained on a balanced data subset to predict PRC from the extracted meta-data. Results: The analysable video dataset of 157 ICGFA featured females (average age 48 years) having oncological/risk-reducing NSM with either immediate (n=90) or staged immediate (n=26) reconstruction. For those delayed, peak brightness at initial ICGFA was lower (p<0.001) and significantly improved (both quicker-onset and brighter p=0.001) one week later. The overall PRC rate in reconstructed patients (n=116) was 11.2%, with such patients demonstrating significantly dimmer (overall, p=0.018, centrally, p=0.03, and medially, p=0.04) and slower-onset (p=0.039) fluorescent peaks with shallower slopes (p=0.012) than uncomplicated patients with ICGFA. Importantly, such relevant parameters were converted into a whole field of view heatmap potentially suitable for intraoperative display. ML predicted PRC with 84.6% sensitivity and 76.9% specificity. Conclusion: Whole breast quantitative ICGFA assessment reveals statistical associations with PRC that are potentially exploitable via ML.