Hyperspectral Imaging during Normothermic Machine Perfusion—A Functional Classification of Ex Vivo Kidneys Based on Convolutional Neural Networks

Classification of Benign-Malignant Thyroid Nodules Based on Hyperspectral Technology

In recent years, the incidence of thyroid cancer has rapidly increased. To address the issue of the inefficient diagnosis of thyroid cancer during surgery, we propose a rapid method for the diagnosis of benign and malignant thyroid nodules based on hyperspectral technology. Firstly, using our self-developed thyroid nodule hyperspectral acquisition system, data for a large number of diverse thyroid nodule samples were obtained, providing a foundation for subsequent diagnosis. Secondly, to better meet clinical practical needs, we address the current situation of medical hyperspectral image classification research being mainly focused on pixel-based region segmentation, by proposing a method for nodule classification as benign or malignant based on thyroid nodule hyperspectral data blocks. Using 3D CNN and VGG16 networks as a basis, we designed a neural network algorithm (V3Dnet) for classification based on three-dimensional hyperspectral data blocks. In the case of a dataset with a block size of 50 × 50 × 196, the classification accuracy for benign and malignant samples reaches 84.63%. We also investigated the impact of data block size on the classification performance and constructed a classification model that includes thyroid nodule sample acquisition, hyperspectral data preprocessing, and an algorithm for thyroid nodule classification as benign and malignant based on hyperspectral data blocks. The proposed model for thyroid nodule classification is expected to be applied in thyroid surgery, thereby improving surgical accuracy and providing strong support for scientific research in related fields.

Normothermic Machine Perfusion Systems: Where Do We Go From Here?

Normothermic machine perfusion (NMP) aims to preserve organs ex vivo by simulating physiological conditions such as body temperature. Recent advancements in NMP system design have prompted the development of clinically effective devices for liver, heart, lung, and kidney transplantation that preserve organs for several hours/up to 1 d. In preclinical studies, adjustments to circuit structure, perfusate composition, and automatic supervision have extended perfusion times up to 1 wk of preservation. Emerging NMP platforms for ex vivo preservation of the pancreas, intestine, uterus, ovary, and vascularized composite allografts represent exciting prospects. Thus, NMP may become a valuable tool in transplantation and provide significant advantages to biomedical research. This review recaps recent NMP research, including discussions of devices in clinical trials, innovative preclinical systems for extended preservation, and platforms developed for other organs. We will also discuss NMP strategies using a global approach while focusing on technical specifications and preservation times.

Deep Learning in Medical Hyperspectral Images: A Review

With the continuous progress of development, deep learning has made good progress in the analysis and recognition of images, which has also triggered some researchers to explore the area of combining deep learning with hyperspectral medical images and achieve some progress. This paper introduces the principles and techniques of hyperspectral imaging systems, summarizes the common medical hyperspectral imaging systems, and summarizes the progress of some emerging spectral imaging systems through analyzing the literature. In particular, this article introduces the more frequently used medical hyperspectral images and the pre-processing techniques of the spectra, and in other sections, it discusses the main developments of medical hyperspectral combined with deep learning for disease diagnosis. On the basis of the previous review, tne limited factors in the study on the application of deep learning to hyperspectral medical images are outlined, promising research directions are summarized, and the future research prospects are provided for subsequent scholars.

Preoperative Function Assessment of Ex Vivo Kidneys with Supervised Machine Learning Based on Blood and Urine Markers Measured during Normothermic Machine Perfusion

Establishing an objective quality assessment of an organ prior to transplantation can help prevent unnecessary discard of the organ and reduce the probability of functional failure. In this regard, normothermic machine perfusion (NMP) offers new possibilities for organ evaluation. However, to date, few studies have addressed the identification of markers and analytical tools to determine graft quality. In this study, function and injury markers were measured in blood and urine during NMP of 26 porcine kidneys and correlated with ex vivo inulin clearance behavior. Significant differentiation of kidneys according to their function could be achieved by oxygen consumption, oxygen delivery, renal blood flow, arterial pressure, intrarenal resistance, kidney temperature, relative urea concentration, and urine production. In addition, classifications were accomplished with supervised learning methods and histological analysis to predict renal function ex vivo. Classificators (support vector machines, k-nearest-neighbor, logistic regression and naive bayes) based on relevant markers in urine and blood achieved 75% and 83% accuracy in the validation and test set, respectively. A correlation between histological damage and function could not be detected. The measurement of blood and urine markers provides information of preoperative renal quality, which can used in future to establish an objective quality assessment.

Hyperspectral Imaging for Viability Assessment of Human Liver Allografts During Normothermic Machine Perfusion

Normothermic machine perfusion (NMP) is nowadays frequently utilized in liver transplantation. Despite commonly accepted viability assessment criteria, such as perfusate lactate and perfusate pH, there is a lack of predictive organ evaluation strategies to ensure graft viability. Hyperspectral imaging (HSI)-as an optical imaging modality increasingly applied in the biomedical field-might provide additional useful data regarding allograft viability and performance of liver grafts during NMP.

METHODS

Twenty-five deceased donor liver allografts were included in the study. During NMP, graft viability was assessed conventionally and by means of HSI. Images of liver parenchyma were acquired at 1, 2, and 4 h of NMP, and subsequently analyzed using a specialized HSI acquisition software to compute oxygen saturation, tissue hemoglobin index, near-infrared perfusion index, and tissue water index. To analyze the association between HSI parameters and perfusate lactate as well as perfusate pH, we performed simple linear regression analysis.

RESULTS

Perfusate lactate at 1, 2, and 4 h NMP was 1.5 [0.3-8.1], 0.9 [0.3-2.8], and 0.9 [0.1-2.2] mmol/L. Perfusate pH at 1, 2, and 4 h NMP was 7.329 [7.013-7.510], 7.318 [7.081-7.472], and 7.265 [6.967-7.462], respectively. Oxygen saturation predicted perfusate lactate at 1 and 2 h NMP (R² = 0.1577, P = 0.0493; R² = 0.1831, P = 0.0329; respectively). Tissue hemoglobin index predicted perfusate lactate at 1, 2, and 4 h NMP (R² = 0.1916, P = 0.0286; R² = 0.2900, P = 0.0055; R² = 0.2453, P = 0.0139; respectively).

CONCLUSIONS

HSI may serve as a noninvasive tool for viability assessment during NMP. Further evaluation and validation of HSI parameters are warranted in larger sample sizes.

Normothermic machine perfusion of kidneys: current strategies and future perspectives

PURPOSE OF REVIEW

This review aims to summarize the latest original preclinical and clinical articles in the setting of normothermic machine perfusion (NMP) of kidney grafts.

RECENT FINDINGS

Kidney NMP can be safely translated into the clinical routine and there is increasing evidence that NMP may be beneficial in graft preservation especially in marginal kidney grafts. Due to the near-physiological state during NMP, this technology may be used as an ex-vivo organ assessment and treatment platform. There are reports on the application of mesenchymal stromal/stem cells, multipotent adult progenitor cells and microRNA during kidney NMP, with first data indicating that these therapies indeed lead to a decrease in inflammatory response and kidney injury. Together with the demonstrated possibility of prolonged ex-vivo perfusion without significant graft damage, NMP could not only be used as a tool to perform preimplant graft assessment. Some evidence exists that it truly has the potential to be a platform to treat and repair injured kidney grafts, thereby significantly reducing the number of declined organs.

SUMMARY

Kidney NMP is feasible and can potentially increase the donor pool not only by preimplant graft assessment, but also by ex-vivo graft treatment.