Endoscopic Preoperative Tattooing and Marking in the Gastrointestinal Tract: A Systematic Review of Alternative Methods

A novel polymer platform for endoscopic tattooing with high efficacy and safety

Endoscopic tattooing plays a pivotal role in modern endoscopic localization of gastrointestinal lesions, facilitating further surgical intervention and aiding in the postoperative identification and repositioning of lesions. However, traditional endoscopic tattoo dyes often suffer from drawbacks such as side effects, short tattoo duration, and high overall costs. In this study, we developed polyvinylpyrrolidone (PVP)-modified polypyrrole (PPy) nanoparticles by oxidizing pyrrole in a PVP aqueous solution to create a PPy/PVP nanoparticle solution. This innovation aims to enhance endoscopic tattooing efficiency and mitigate the limitations associated with current tattooing methods. Both in vitro and in vivo evaluations confirmed the biosafety of PPy/PVP nanoparticles. Endoscopic tattooing experiments conducted in a pig model demonstrated the dye's stability within the digestive tract. Similarly, subcutaneous tissue tattooing experiments performed in a mouse model revealed the sustained stability of the PPy/PVP tattoo dye for at least 180 days. With its robust stability, safety, and longevity, PPy/PVP nanoparticles hold promise as novel tattoo dyes for marking intestinal lesion sites. This advancement has the potential to enhance the accuracy of lesion localization and long-term tracking.

Near-infrared fluorescence tattooing: a new approach for endoscopic marking of tumors in minimally invasive colorectal surgery using a persistent near-infrared marker

INTRODUCTION

Intraoperative accurate localization of tumors in the lower gastrointestinal tract is essential to ensure oncologic radicality. In minimally invasive colon surgery, tactile identification of tumors is challenging due to diminished or absent haptics. In clinical practice, preoperative endoscopic application of a blue dye (ink) to the tumor site has become the standard for marking and identification of tumors in the colon. However, this method has the major limitation that accidental intraperitoneal spillage of the dye can significantly complicate the identification of anatomical structures and surgical planes. In this work, we describe a new approach of NIR fluorescent tattooing using a near-infrared (NIR) fluorescent marker instead of a blue dye (ink) for endoscopic tattooing.

METHODS

AFS81x is a newly developed NIR fluorescent marker. In an experimental study with four domestic pigs, the newly developed NIR fluorescent marker (AFS81x) was used for endoscopic tattooing of the colon. 7-12 endoscopic submucosal injections of AFS81x were placed per animal in the colon. On day 0, day 1, and day 10 after endoscopic tattooing with AFS81x, the visualization of the fluorescent markings in the colon was evaluated during laparoscopic surgery by two surgeons and photographically documented.

RESULTS

The detection rate of the NIR fluorescent tattoos at day 0, day 1, and day 10 after endoscopic tattooing was 100%. Recognizability of anatomical structures during laparoscopy was not affected in any of the markings, as the markings were not visible in the white light channel of the laparoscope, but only in the NIR channel or in the overlay of the white light and the NIR channel of the laparoscope. The brightness, the sharpness, and size of the endoscopic tattoos did not change significantly on day 1 and day 10, but remained almost identical compared to day 0.

CONCLUSION

The new approach of endoscopic NIR fluorescence tattooing using the newly developed NIR fluorescence marker AFS81x enables stable marking of colonic sites over a long period of at least 10 days without compromising the recognizability of anatomical structures and surgical planes in any way.

Feedforward Artificial Neural Network-Based Colorectal Cancer Detection Using Hyperspectral Imaging: A Step towards Automatic Optical Biopsy

Simple Summary

Detection of colorectal carcinoma is performed visually by investigators and is confirmed pathologically. With hyperspectral imaging, an expanded spectral range of optical information is now available for analysis. The acquired recordings were analyzed with a neural network, and it was possible to differentiate tumor from healthy mucosa in colorectal carcinoma by automatic classification with high reliability. Classification and visualization were performed based on a four-layer perceptron neural network. Based on a neural network, the classification of CA or AD resulted in a sensitivity of 86% and a specificity of 95%, by means of leave-one-patient-out cross-validation. Additionally, significant differences in terms of perfusion parameters (e.g., oxygen saturation) related to tumor staging and neoadjuvant therapy were observed. This is a step towards optical biopsy.

Abstract

Currently, colorectal cancer (CRC) is mainly identified via a visual assessment during colonoscopy, increasingly used artificial intelligence algorithms, or surgery. Subsequently, CRC is confirmed through a histopathological examination by a pathologist. Hyperspectral imaging (HSI), a non-invasive optical imaging technology, has shown promising results in the medical field. In the current study, we combined HSI with several artificial intelligence algorithms to discriminate CRC. Between July 2019 and May 2020, 54 consecutive patients undergoing colorectal resections for CRC were included. The tumor was imaged from the mucosal side with a hyperspectral camera. The image annotations were classified into three groups (cancer, CA; adenomatous margin around the central tumor, AD; and healthy mucosa, HM). Classification and visualization were performed based on a four-layer perceptron neural network. Based on a neural network, the classification of CA or AD resulted in a sensitivity of 86% and a specificity of 95%, by means of leave-one-patient-out cross-validation. Additionally, significant differences in terms of perfusion parameters (e.g., oxygen saturation) related to tumor staging and neoadjuvant therapy were observed. Hyperspectral imaging combined with automatic classification can be used to differentiate between CRC and healthy mucosa. Additionally, the biological changes induced by chemotherapy to the tissue are detectable with HSI.