Optimization of anastomotic technique and gastric conduit perfusion with hyperspectral imaging and machine learning in an experimental model for minimally invasive esophagectomy

Indocyanine green quantification in full robotic esophagectomy using an unsupervised learning approach

BACKGROUND

Intraoperative indocyanine green imaging has emerged as a powerful tool for assessing gastric conduit perfusion during open and minimally invasive esophagectomy. Although delayed perfusion correlates with the development of anastomotic leakage, indocyanine green assessments have high surgeon-dependent interuser variability. Therefore, quantitative indocyanine green analysis is recommended. We present a quantitative indocyanine green analysis using an unsupervised, self-organizing map cluster network during robotic-assisted minimally invasive esophagectomy.

METHODS

In total, 70 patients treated with robotic-assisted minimally invasive esophagectomy, intraoperative indocyanine green imaging, and prophylactic endoluminal vacuum therapy were included in the study. The occurrence of anastomotic leakage, cycles of endoluminal vacuum therapy, patient comorbidities, and arteriosclerosis shown on preoperative computed tomography scans was recorded. The recorded videos of intraoperative indocyanine green imaging were clustered using an unsupervised, self-organizing map network, and an indocyanine green perfusion score was determined.

RESULTS

The indocyanine green perfusion score, as well as patient age and body mass index, correlated with an increased risk of anastomotic leakage in the univariate analysis. Other comorbidities and the extent of arteriosclerosis in preoperative computed tomography scans did not differ in patients with and without anastomotic leakage.

CONCLUSION

An unsupervised learning approach to quantify intraoperative indocyanine green imaging could aid the prediction of anastomotic leakage after robotic-assisted minimally invasive esophagectomy in future treatments. However, the value of this approach needs to be clarified in a randomized, controlled prospective study.

Spectral characterization of intraoperative renal perfusion using hyperspectral imaging and artificial intelligence

Accurate intraoperative assessment of organ perfusion is a pivotal determinant in preserving organ function e.g. during kidney surgery including partial nephrectomy or kidney transplantation. Hyperspectral imaging (HSI) has great potential to objectively describe and quantify this perfusion as opposed to conventional surrogate techniques such as ultrasound flowmeter, indocyanine green or the subjective eye of the surgeon. An established live porcine model under general anesthesia received median laparotomy and renal mobilization. Different scenarios that were measured using HSI were (1) complete, (2) gradual and (3) partial malperfusion. The differences in spectral reflectance as well as HSI oxygenation (StO2) between different perfusion states were compelling and as high as 56.9% with 70.3% (± 11.0%) for "physiological" vs. 13.4% (± 3.1%) for "venous congestion". A machine learning (ML) algorithm was able to distinguish between these perfusion states with a balanced prediction accuracy of 97.8%. Data from this porcine study including 1300 recordings across 57 individuals was compared to a human dataset of 104 recordings across 17 individuals suggesting clinical transferability. Therefore, HSI is a highly promising tool for intraoperative microvascular evaluation of perfusion states with great advantages over existing surrogate techniques. Clinical trials are required to prove patient benefit.

Short-term Outcomes of Different Techniques for Gastric Ischemic Preconditioning Before Esophagectomy: A Network Meta-analysis

BACKGROUND

Ischemia at the anastomotic site plays a critical role determinant in the development of anastomosis-related complications after esophagectomy. Gastric ischemic conditioning (GIC) before esophagectomy has been described to improve the vascular perfusion at the tip of the gastric conduit with a potential effect on anastomotic leak (AL) and stenosis (AS) risk minimization. Laparoscopic (LapGIC) and angioembolization (AngioGIC) techniques have been reported.

PURPOSE

Compare short-term outcomes among different GIC techniques.

MATERIALS AND METHODS

Systematic review and network meta-analysis. One-step esophagectomy (noGIC), LapGIC, and AngioGIC were compared. Primary outcomes were AL, AS, and gastric conduit necrosis (GCN). Risk ratio (RR) and weighted mean difference (WMD) were used as pooled effect size measures, whereas 95% credible intervals (CrIs) were used to assess relative inference.

RESULTS

Overall, 1760 patients (14 studies) were included. Of those, 1028 patients (58.4%) underwent noGIC, 593 (33.6%) LapGIC, and 139 (8%) AngioGIC. AL was reduced for LapGIC versus noGIC (RR=0.68; 95% CrI 0.47-0.98) and AngioGIC versus noGIC (RR=0.52; 95% CrI 0.31-0.93). Similarly, AS was reduced for LapGIC versus noGIC (RR=0.32; 95% CrI 0.12-0.68) and AngioGIC versus noGIC (RR=1.30; 95% CrI 0.65-2.46). The indirect comparison, assessed with the network methodology, did not show any differences for LapGIC versus AngioGIC in terms of postoperative AL and AS risk. No differences were found for GCN, pulmonary complications, overall complications, hospital length of stay, and 30-day mortality among different treatments.

CONCLUSIONS

Compared to noGIC, both LapGIC and AngioGIC before esophagectomy seem equivalent and associated with a reduced risk for postoperative AL and AS.

Effects of endoluminal vacuum sponge therapy on the perfusion of gastric conduit in a porcine model for esophagectomy

BACKGROUND

After esophagectomy, the postoperative rate of anastomotic leakage is up to 30% and is the main driver of postoperative morbidity. Contemporary management includes endoluminal vacuum sponge therapy (EndoVAC) with good success rates. Vacuum therapy improves tissue perfusion in superficial wounds, but this has not been shown for gastric conduits. This study aimed to assess gastric conduit perfusion with EndoVAC in a porcine model for esophagectomy.

MATERIAL AND METHODS

A porcine model (n = 18) was used with gastric conduit formation and induction of ischemia at the cranial end of the gastric conduit with measurement of tissue perfusion over time. In three experimental groups EndoVAC therapy was then used in the gastric conduit (- 40, - 125, and - 200 mmHg). Changes in tissue perfusion and tissue edema were assessed using hyperspectral imaging. The study was approved by local authorities (Project License G-333/19, G-67/22).

RESULTS

Induction of ischemia led to significant reduction of tissue oxygenation from 65.1 ± 2.5% to 44.7 ± 5.5% (p < 0.01). After EndoVAC therapy with - 125 mmHg a significant increase in tissue oxygenation to 61.9 ± 5.5% was seen after 60 min and stayed stable after 120 min (62.9 ± 9.4%, p < 0.01 vs tissue ischemia). A similar improvement was seen with EndoVAC therapy at - 200 mmHg. A nonsignificant increase in oxygenation levels was also seen after therapy with - 40 mmHg, from 46.3 ± 3.4% to 52.5 ± 4.3% and 53.9 ± 8.1% after 60 and 120 min respectively (p > 0.05). An increase in tissue edema was observed after 60 and 120 min of EndoVAC therapy with - 200 mmHg but not with - 40 and - 125 mmHg.

CONCLUSIONS

EndoVAC therapy with a pressure of - 125 mmHg significantly increased tissue perfusion of ischemic gastric conduit. With better understanding of underlying physiology the optimal use of EndoVAC therapy can be determined including a possible preemptive use for gastric conduits with impaired arterial perfusion or venous congestion.

Intraoperative Laparoscopic Hyperspectral Imaging during Esophagectomy-A Pilot Study Evaluating Esophagogastric Perfusion at the Anastomotic Sites

Hyperspectral imaging (HSI) is a non-invasive and contactless technique that enables the real-time acquisition of comprehensive information on tissue within the surgical field. In this pilot study, we investigated whether a new HSI system for minimally-invasive surgery, TIVITA® Mini (HSI-MIS), provides reliable insights into tissue perfusion of the proximal and distal esophagogastric anastomotic sites during 21 laparoscopic/thoracoscopic or robotic Ivor Lewis esophagectomies of patients with cancer to minimize the risk of dreaded anastomotic insufficiency. In this pioneering investigation, physiological tissue parameters were derived from HSI measurements of the proximal site of the anastomosis (esophageal stump) and the distal site of the anastomosis (tip of the gastric conduit) during the thoracic phase of the procedure. Tissue oxygenation (StO2), Near Infrared Perfusion Index (NIR-PI), and Tissue Water Index (TWI) showed similar median values at both anastomotic sites. Significant differences were observed only for NIR-PI (median: 76.5 vs. 63.9; p = 0.012) at the distal site (gastric conduit) compared to our previous study using an HSI system for open surgery. For all 21 patients, reliable and informative measurements were attainable, confirming the feasibility of HSI-MIS to assess anastomotic viability. Further studies on the added benefit of this new technique aiming to reduce anastomotic insufficiency are warranted.

HeiPorSPECTRAL - the Heidelberg Porcine HyperSPECTRAL Imaging Dataset of 20 Physiological Organs

Hyperspectral Imaging (HSI) is a relatively new medical imaging modality that exploits an area of diagnostic potential formerly untouched. Although exploratory translational and clinical studies exist, no surgical HSI datasets are openly accessible to the general scientific community. To address this bottleneck, this publication releases HeiPorSPECTRAL ( https://www.heiporspectral.org ; https://doi.org/10.5281/zenodo.7737674 ), the first annotated high-quality standardized surgical HSI dataset. It comprises 5,758 spectral images acquired with the TIVITA® Tissue and annotated with 20 physiological porcine organs from 8 pigs per organ distributed over a total number of 11 pigs. Each HSI image features a resolution of 480 × 640 pixels acquired over the 500-1000 nm wavelength range. The acquisition protocol has been designed such that the variability of organ spectra as a function of several parameters including the camera angle and the individual can be assessed. A comprehensive technical validation confirmed both the quality of the raw data and the annotations. We envision potential reuse within this dataset, but also its reuse as baseline data for future research questions outside this dataset. Measurement(s) Spectral Reflectance Technology Type(s) Hyperspectral Imaging Sample Characteristic - Organism Sus scrofa.