[Hyperspectral imaging demonstrates microcirculatory effects of postoperative exercise therapy in Dupuytren's disease]

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

INTRODUCTION

Esophagectomy is the mainstay of esophageal cancer treatment, but anastomotic insufficiency related morbidity and mortality remain challenging for patient outcome. Therefore, the objective of this work was to optimize anastomotic technique and gastric conduit perfusion with hyperspectral imaging (HSI) for total minimally invasive esophagectomy (MIE) with linear stapled anastomosis.

MATERIAL AND METHODS

A live porcine model (n = 58) for MIE was used with gastric conduit formation and simulation of linear stapled side-to-side esophagogastrostomy. Four main experimental groups differed in stapling length (3 vs. 6 cm) and simulation of anastomotic position on the conduit (cranial vs. caudal). Tissue oxygenation around the anastomotic simulation site was evaluated using HSI and was validated with histopathology.

RESULTS

The tissue oxygenation (ΔStO₂) after the anastomotic simulation remained constant only for the short stapler in caudal position (-0.4 ± 4.4%, n.s.) while it was impaired markedly in the other groups (short-cranial: -15.6 ± 11.5%, p = 0.0002; long-cranial: -20.4 ± 7.6%, p = 0.0126; long-caudal: -16.1 ± 9.4%, p < 0.0001). Tissue samples from avascular stomach as measured by HSI showed correspondent eosinophilic pre-necrotic changes in 35.7 ± 9.7% of the surface area.

CONCLUSION

Tissue oxygenation at the site of anastomotic simulation of the gastric conduit during MIE is influenced by stapling technique. Optimal oxygenation was achieved with a short stapler (3 cm) and sufficient distance of the simulated anastomosis to the cranial end of the gastric conduit. HSI tissue deoxygenation corresponded to histopathologic necrotic tissue changes. The experimental model with HSI and ML allow for systematic optimization of gastric conduit perfusion and anastomotic technique while clinical translation will have to be proven.

Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model

Visual discrimination of tissue during surgery can be challenging since different tissues appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by associating each pixel with high-dimensional spectral information. While previous work has shown its general potential to discriminate tissue, clinical translation has been limited due to the method’s current lack of robustness and generalizability. Specifically, the scientific community is lacking a comprehensive spectral tissue atlas, and it is unknown whether variability in spectral reflectance is primarily explained by tissue type rather than the recorded individual or specific acquisition conditions. The contribution of this work is threefold: (1) Based on an annotated medical HSI data set (9059 images from 46 pigs), we present a tissue atlas featuring spectral fingerprints of 20 different porcine organs and tissue types. (2) Using the principle of mixed model analysis, we show that the greatest source of variability related to HSI images is the organ under observation. (3) We show that HSI-based fully-automatic tissue differentiation of 20 organ classes with deep neural networks is possible with high accuracy (> 95%). We conclude from our study that automatic tissue discrimination based on HSI data is feasible and could thus aid in intraoperative decisionmaking and pave the way for context-aware computer-assisted surgery systems and autonomous robotics.

Algorithm for Mapping Kidney Tissue Water Content during Normothermic Machine Perfusion Using Hyperspectral Imaging

The preservation of kidneys using normothermic machine perfusion (NMP) prior to transplantation has the potential for predictive evaluation of organ quality. Investigations concerning the quantitative assessment of physiological tissue parameters and their dependence on organ function lack in this context. In this study, hyperspectral imaging (HSI) in the wavelength range of 500–995 nm was conducted for the determination of tissue water content (TWC) in kidneys. The quantitative relationship between spectral data and the reference TWC values was established by partial least squares regression (PLSR). Different preprocessing methods were applied to investigate their influence on predicting the TWC of kidneys. In the full wavelength range, the best models for absorbance and reflectance spectra provided Rp2 values of 0.968 and 0.963, as well as root-mean-square error of prediction (RMSEP) values of 2.016 and 2.155, respectively. Considering an optimal wavelength range (800–980 nm), the best model based on reflectance spectra (Rp2 value of 0.941, RMSEP value of 3.202). Finally, the visualization of TWC distribution in all pixels of kidneys’ HSI image was implemented. The results show the feasibility of HSI for a non-invasively and accurate TWC prediction in kidneys, which could be used in the future to assess the quality of kidneys during the preservation period.

Intraoperative Assessment of Gastric Sleeve Oxygenation Using Hyperspectral Imaging in Esophageal Resection: A Feasibility Study

Introduction

Sufficient tissue oxygenation is essential for anastomotic healing in visceral surgery. Hyperspectral imaging (HSI) is a noncontact, noninvasive technique for clinical assessment of tissue oxygenation in real time.

Methods

In this case series, HSI was used in 4 patients who were admitted for either esophageal cancer or cardiac carcinoma (AEG type I or II). Thoraco-abdominal surgical esophageal resection was performed after staging and neoadjuvant therapy. Intraoperative oxygenation of superficial (StO₂) and underlying tissue (NIR perfusion index) of the gastric sleeve were studied intrathoracic by means of the TIVITA® Tissue HSI camera. This was performed prior to esophagogastric anastomosis. The postoperative course, especially in view of surgical complications, was recorded.

Results

Assessment of StO₂ and NIR perfusion index was performed in 4 regions of interest per gastric sleeve, aboral and oral of the clinically determined resection line. It allowed the fast quantification of gastric oxygenation prior gastroesophageal anastomosis. Median StO₂ aboral of the determined resection line was 69%, while median StO₂ in the oral part of the gastric sleeve was found at 53%. In contrast, the median NIR perfusion index was similar aboral (80) and oral (82) of the resection line. In none of the 4 studied patients, an anastomotic failure appeared.

Discussion/Conclusion

This report suggests that HSI is a feasible technique for intraoperative assessment of tissue oxygenation before gastroesophageal anastomosis and might reduce the incidence of anastomotic failure in the gastrointestinal tract.