Indocyanine green (ICG) fluorescence imaging has revolutionized surgical practice across various medical and surgical specialties. This article reviews the clinical applications of ICG in abdominal, urological, thoracic, and gynecological surgery. ICG fluorescence imaging has been widely adopted in general surgery for various applications, including perfusion assessment, intraoperative visualization of the ureter, and tumor localization. It is particularly valuable in evaluating anastomotic leaks and aiding in precise tumor resection during minimally invasive surgeries. Studies have shown mixed results on its effectiveness in reducing anastomotic leak rates, highlighting the need for further research. In thoracic surgery, ICG facilitates the identification and resection of pulmonary bullae, as well as the precise localization of pulmonary nodules during video-assisted surgery. In urology, ICG aids in localizing renal tumors and guiding selective arterial occlusion during partial nephrectomy. Its role in identifying the lymphatic pathway in prostate cancer and sentinel lymph node biopsy in gynecological cancer is also discussed. Despite its benefits, the use of ICG fluorescence faces challenges such as limited tissue penetration, the potential for false results, a lack of standardized protocols, and high equipment costs. Nonetheless, it remains a powerful tool that could improve surgical outcomes.

Thyroid and parathyroid surgery are considered clean procedures, with an incidence of surgical site infection (SSI) after thyroidectomy ranging from 0.09% to 2.9%. International guidelines do not recommend routine antibiotic prophylaxis (AP), while AP seems to be employed commonly in clinical practice. The purpose of this systematic review is analyzing whether the postoperative SSI rate in thyroid and parathyroid surgery is altered by the practice of AP. We searched Pubmed, Scopus, the Cochrane Library, and Web of Science (WOS) for studies comparing AP to no preoperative antibiotics up to October 2021. Data on the SSI rate was evaluated and summarized as relative risks (RR) with 95% confidence intervals (95% CI). Risk of bias of studies were assessed with standard methods. Nine studies (4 RCTs and 5 nRCTs), including 8710 participants, were eligible for quantitative analysis. A meta-analysis showed that the SSI rate was not significantly different between AP and no preoperative antibiotics (SSI rate: 0.6% in AP vs. 2.4% in control group; RR 0.69, 0.43–1.10 95% CI, p = 0.13, I2 = 0%). A sensitivity analysis and subgroup analysis on RCTs were consistent with the main findings. Evidence of low quality supports that AP in thyroid and parathyroid surgery produce similar SSI rates as to the absence of perioperative antibiotics.

Lateral neck dissection (LND) leads to a significant morbidity involving accessory nerve injury. Modified radical neck dissection (MRND) aims at preservation of the accessory nerve, but patients often present with negative functional outcomes after surgery. The role of neuromonitoring (IONM) in the prevention of shoulder syndrome has not yet been defined in comparison to nerve visualization only. We retrospectively analyzed 56 thyroid cancer patients who underwent MRND over a period of six years (2015–2020) in a high-volume institution. Demographic variables, type of surgical procedure, removed lymph nodes and the metastatic node ratio, pathology, adoption of IONM and shoulder functional outcome were investigated. The mean number of lymph nodes removed was 15.61, with a metastatic node ratio of 0.2745. IONM was used in 41.07% of patients, with a prevalence of 68% in the period 2017–2020. IONM adoption showed an effect on post-operative shoulder function. There were no effects in 89.29% of cases, and temporary and permanent effects in 8.93% and 1.79%, respectively. Confidence intervals and two-sample tests for equality of proportions were used when applicable. Expertise in high-volume centres and IONM during MRND seem to be correlated with a reduced prevalence of accessory nerve lesions and limited functional impairments. These results need to be confirmed by larger prospective randomized controlled trials.

Frailty in the elderly population is associated with increased vulnerability to stressors, including surgical interventions. This study compared machine learning (ML) models with a clinical bedside tool, the Gastrointestinal Surgery Frailty Index (GiS-FI), for predicting mortality and morbidity in elderly patients undergoing gastrointestinal cancer surgery. In a multicenter analysis of 937 patients aged ≥65 years, the performance of various predictive models including Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), Stepwise Regression, K-Nearest Neighbors, Neural Network, and Support Vector Machine algorithms were evaluated. The overall 30-day mortality and morbidity rates were 6.1% and 35.7%, respectively. For mortality prediction, the RF model demonstrated superior performance with an AUC of 0.822 (95% CI 0.714–0.931), outperforming the GiS-FI score (AUC = 0.772, 95% CI 0.675–0.868). For morbidity prediction, all models showed more modest discrimination, with stepwise regression and LASSO regression achieving the highest performance (AUCs of 0.652 and 0.647, respectively). Our findings suggest that ML approaches, particularly RF algorithm, offer enhanced predictive accuracy compared to traditional clinical scores for mortality risk assessment in elderly cancer patients undergoing gastrointestinal surgery. These advanced analytical tools could provide valuable decision support for surgical risk stratification in this vulnerable population.