Right hepatectomy with preservation of the entire caudate lobe in patients with metastatic liver tumors: a case of a new hepatectomy technique and treatment strategy for patients with marginal liver function

Background Performing major hepatectomy for patients with marginal hepatic function is challenging. In some cases, the procedure is contraindicated owing to the threat of postoperative liver failure. In this case report, we present the first case of marginal liver function (indocyanine green clearance retention rate at 15 min [ICGR15]: 28%) successfully treated with right hepatectomy, resulting in total caudate lobe preservation. Case presentation A 71-year-old man was diagnosed with sigmoid colon cancer with three liver metastases (S5, S7, and S8). All of metastatic lesions shrunk after chemotherapy, but his ICGR15 and indocyanine green clearance rate (ICGK) were 21% and 0.12, respectively. Moreover, the remnant liver volume was only 39%. Therefore, portal venous embolism (PVE) of the right portal vein was suggested. Portography showed divergence of the considerably preserved right caudate lobe branch (PV1R) from the root of the right portal vein. The liver function was reevaluated 18 days after PVE was suggested. During this time, the ICGR15 (21–28%) and ICGK rate (0.12–0.10) deteriorated. The right caudate lobe was significantly enlarged; thus, a total caudate lobe-preserving hepatectomy (TCPRx) was performed. Patients eligible for TCPRx included those with (1) hepatocellular carcinoma or metastatic liver cancer, (2) no tumor in the caudate lobe, (3) marginal liver function (ICG Krem greater than 0.05 if TCPRx was adapted; otherwise, less than 0.05) and Child–Pugh classification category A, and (4) preserved PV1R and right caudate bile duct branch. The procedure was performed through (A) precise estimation of the remnant liver volume preoperatively, (B) repeated intraoperative cholangiography to confirm the biliary branch of the right caudate lobe (B1R) conservation, and (C) stapler division of posterior and anterior Glisson’s pedicles laterally to avoid injuries to the PV1R and B1R. Conclusions Right hepatectomy with total caudate lobe preservation, following PVE, was a safe and viable surgical technique for patients with marginal liver function.

Theranostic Platforms Based on Silica and Magnetic Nanoparticles Containing Quinacrine, Chitosan, Fluorophores, and Quantum Dots

In this paper, we describe the synthesis of multilayer nanoparticles as a platform for the diagnosis and treatment of ischemic injuries. The platform is based on magnetite (MNP) and silica (SNP) nanoparticles, while quinacrine is used as an anti-ischemic agent. The synthesis includes the surface modification of nanoparticles with (3-glycidyloxypropyl)trimethoxysilane (GPMS), the immobilization of quinacrine, and the formation of a chitosan coating, which is used to fix the fluorophore indocyanine green (ICG) and colloidal quantum dots AgInS2/ZnS (CQDs), which serve as secondary radiation sources. The potential theranostic platform was studied in laboratory animals.

Multispectral Imaging Using Fluorescent Properties of Indocyanine Green and Methylene Blue in Colorectal Surgery—Initial Experience

Introduction: Image-guided surgery is becoming a new tool in colorectal surgery. Intraoperative visualisation of different structures using fluorophores helps during various steps of operations. In our report, we used two fluorophores—indocyanine green (ICG), and methylene blue (MB)—during different steps of colorectal surgery, using one camera system for two separate near-infrared wavelengths. Material and methods: Twelve patients who underwent complex open or laparoscopic colorectal surgeries were enrolled. Intravenous injections of MB and ICG at different time points were administered. Visualisation of intraoperative ureter position and fluorescent angiography for optimal anastomosis was performed. A retrospective analysis of patients treated in our departments during 2020 was performed, and data about ureter injury and anastomotic site complications were collected. Results: Intraoperative localisation of ureters with MB under fluorescent light was possible in 11 patients. The mean signal-to-background ratio was 1.58 ± 0.71. Fluorescent angiography before performing anastomosis using ICG was successful in all 12 patients, and none required a change in position of the planned colon resection for anastomosis. The median signal-to-background ratios was 1.25 (IQR: 1.22–1.89). Across both centres, iatrogenic injury of the ureter was found in 0.4% of cases, and complications associated with anastomosis was found in 5.5% of cases. Conclusions: Our study showed a substantial opportunity for using two different fluorophores in colorectal surgery, whereby the visualisation of one will not change the possible quantification analysis of the other. Using two separate dyes during one procedure may help in optimisation of the fluorescent properties of both dyes when using them for different applications. Visualisation of different structures by different fluorophores seems to be the future of image-guided surgery, and shows progress in optical technologies used in image-guided surgery.

Deep-Learning-Based Cerebral Artery Semantic Segmentation in Neurosurgical Operating Microscope Vision Using Indocyanine Green Fluorescence Videoangiography

There have been few anatomical structure segmentation studies using deep learning. Numbers of training and ground truth images applied were small and the accuracies of which were low or inconsistent. For a surgical video anatomy analysis, various obstacles, including a variable fast-changing view, large deformations, occlusions, low illumination, and inadequate focus occur. In addition, it is difficult and costly to obtain a large and accurate dataset on operational video anatomical structures, including arteries. In this study, we investigated cerebral artery segmentation using an automatic ground-truth generation method. Indocyanine green (ICG) fluorescence intraoperative cerebral videoangiography was used to create a ground-truth dataset mainly for cerebral arteries and partly for cerebral blood vessels, including veins. Four different neural network models were trained using the dataset and compared. Before augmentation, 35,975 training images and 11,266 validation images were used. After augmentation, 260,499 training and 90,129 validation images were used. A Dice score of 79% for cerebral artery segmentation was achieved using the DeepLabv3+ model trained using an automatically generated dataset. Strict validation in different patient groups was conducted. Arteries were also discerned from the veins using the ICG videoangiography phase. We achieved fair accuracy, which demonstrated the appropriateness of the methodology. This study proved the feasibility of operating field view of the cerebral artery segmentation using deep learning, and the effectiveness of the automatic blood vessel ground truth generation method using ICG fluorescence videoangiography. Using this method, computer vision can discern blood vessels and arteries from veins in a neurosurgical microscope field of view. Thus, this technique is essential for neurosurgical field vessel anatomy-based navigation. In addition, surgical assistance, safety, and autonomous surgery neurorobotics that can detect or manipulate cerebral vessels would require computer vision to identify blood vessels and arteries.