Impact of Pre- and Post-Processing Steps for Supervised Classification of Colorectal Cancer in Hyperspectral Images.

BACKGROUND: Recent studies have shown that hyperspectral imaging (HSI) combined with neural networks can detect colorectal cancer. Usually, different pre-processing techniques (e.g., wavelength selection and scaling, smoothing, denoising) are analyzed in detail to achieve a well-trained network. The impact of post-processing was studied less. METHODS: We tested the following methods: (1) Two pre-processing techniques (Standardization and Normalization), with (2) Two 3D-CNN models: Inception-based and RemoteSensing (RS)-based, with (3) Two post-processing algorithms based on median filter: one applies a median filter to a raw predictions map, the other applies the filter to the predictions map after adopting a discrimination threshold. These approaches were evaluated on a dataset that contains ex vivo hyperspectral (HS) colorectal cancer records of 56 patients. RESULTS: (1) Inception-based models perform better than RS-based, with the best results being 92% sensitivity and 94% specificity; (2) Inception-based models perform better with Normalization, RS-based with Standardization; (3) Our outcomes show that the post-processing step improves sensitivity and specificity by 6.6% in total. It was also found that both post-processing algorithms have the same effect, and this behavior was explained. CONCLUSION: HSI combined with tissue classification algorithms is a promising diagnostic approach whose performance can be additionally improved by the application of the right combination of pre- and post-processing.

Alternative intraoperative optical imaging modalities for fluorescence angiography in gastrointestinal surgery: spectral imaging and imaging photoplethysmography.

INTRODUCTION: Intraoperative near-infrared fluorescence angiography with indocyanine green (ICG-FA) is a well-established modality in gastrointestinal surgery. Its main drawback is the application of a fluorescent agent with possible side effects for patients. The goal of this review paper is the presentation of alternative, non-invasive optical imaging methods and their comparison with ICG-FA. MATERIAL AND METHODS: The principles of ICG-FA, spectral imaging, imaging photoplethysmography (iPPG), and their applications in gastrointestinal surgery are described based on selected published works. RESULTS: The main applications of the three modalities are the evaluation of tissue perfusion, the identification of risk structures, and tissue segmentation or classification. While the ICG-FA images are mainly evaluated visually, leading to subjective interpretations, quantitative physiological parameters and tissue segmentation are provided in spectral imaging and iPPG. The combination of ICG-FA and spectral imaging is a promising method. CONCLUSIONS: Non-invasive spectral imaging and iPPG have shown promising results in gastrointestinal surgery. They can overcome the main drawbacks of ICG-FA, i.e. the use of contrast agents, the lack of quantitative analysis, repeatability, and a difficult standardization of the acquisition. Further technical improvements and clinical evaluations are necessary to establish them in daily clinical routine.

Spectral Similarity Measures for In Vivo Human Tissue Discrimination Based on Hyperspectral Imaging.

PROBLEM: Similarity measures are widely used as an approved method for spectral discrimination or identification with their applications in different areas of scientific research. Even though a range of works have been presented, only a few showed slightly promising results for human tissue, and these were mostly focused on pathological and non-pathological tissue classification. METHODS: In this work, several spectral similarity measures on hyperspectral (HS) images of in vivo human tissue were evaluated for tissue discrimination purposes. Moreover, we introduced two new hybrid spectral measures, called SID-JM-TAN(SAM) and SID-JM-TAN(SCA). We analyzed spectral signatures obtained from 13 different human tissue types and two different materials (gauze, instruments), collected from HS images of 100 patients during surgeries. RESULTS: The quantitative results showed the reliable performance of the different similarity measures and the proposed hybrid measures for tissue discrimination purposes. The latter produced higher discrimination values, up to 6.7 times more than the classical spectral similarity measures. Moreover, an application of the similarity measures was presented to support the annotations of the HS images. We showed that the automatic checking of tissue-annotated thyroid and colon tissues was successful in 73% and 60% of the total spectra, respectively. The hybrid measures showed the highest performance. Furthermore, the automatic labeling of wrongly annotated tissues was similar for all measures, with an accuracy of up to 90%. CONCLUSION: In future work, the proposed spectral similarity measures will be integrated with tools to support physicians in annotations and tissue labeling of HS images.

Comparison of image registration methods for combining laparoscopic video and spectral image data.

Laparoscopic procedures can be assisted by intraoperative modalities, such as quantitative perfusion imaging based on fluorescence or hyperspectral data. If these modalities are not available at video frame rate, fast image registration is needed for the visualization in augmented reality. Three feature-based algorithms and one pre-trained deep homography neural network (DH-NN) were tested for single and multi-homography estimation. Fine-tuning was used to bridge the domain gap of the DH-NN for non-rigid registration of laparoscopic images. The methods were validated on two datasets: an open-source record of 750 manually annotated laparoscopic images, presented in this work, and in-vivo data from a novel laparoscopic hyperspectral imaging system. All feature-based single homography methods outperformed the fine-tuned DH-NN in terms of reprojection error, Structural Similarity Index Measure, and processing time. The feature detector and descriptor ORB1000 enabled video-rate registration of laparoscopic images on standard hardware with submillimeter accuracy.

[Artificial intelligence and hyperspectral imaging for image-guided assistance in minimally invasive surgery]. / Künstliche Intelligenz und hyperspektrale Bildgebung zur bildgestützten Assistenz in der minimal-invasiven Chirurgie.

BACKGROUND: Intraoperative imaging assists surgeons during minimally invasive procedures. Hyperspectral imaging (HSI) is a noninvasive and noncontact optical technique with great diagnostic potential in medicine. The combination with artificial intelligence (AI) approaches to analyze HSI data is called intelligent HSI in this article. OBJECTIVE: What are the medical applications and advantages of intelligent HSI for minimally invasive visceral surgery? MATERIAL AND METHODS: Within various clinical studies HSI data from multiple in vivo tissue types and oncological resections were acquired using an HSI camera system. Different AI algorithms were evaluated for detection and discrimination of organs, risk structures and tumors. RESULTS: In an experimental animal study 20 different organs could be differentiated with high precision (> 95%) using AI. In vivo, the parathyroid glands could be discriminated from surrounding tissue with an F1 score of 47% and sensitivity of 75%, and the bile duct with an F1 score of 79% and sensitivity of 90%. Furthermore, ex vivo tumor tissue could be successfully detected with an area under the receiver operating characteristic (ROC) curve (AUC) larger than 0.91. DISCUSSION: This study demonstrates that intelligent HSI can automatically and accurately detect different tissue types. Despite great progress in the last decade intelligent HSI still has limitations. Thus, accurate AI algorithms that are easier to understand for the user and an extensive standardized and continuously growing database are needed. Further clinical studies should support the various medical applications and lead to the adoption of intelligent HSI in the clinical routine practice.

Video: Clinical evaluation of a laparoscopic hyperspectral imaging system.

BACKGROUND: Hyperspectral imaging (HSI) during surgical procedures is a new method for perfusion quantification and tissue discrimination. Its use has been limited to open surgery due to large camera sizes, missing color video, or long acquisition times. A hand-held, laparoscopic hyperspectral camera has been developed now to overcome those disadvantages and evaluated clinically for the first time. METHODS: In a clinical evaluation study, gastrointestinal resectates of ten cancer patients were investigated using the laparoscopic hyperspectral camera. Reference data from corresponding anatomical regions were acquired with a clinically approved HSI system. An image registration process was executed that allowed for pixel-wise comparisons of spectral data and parameter images (StO2: oxygen saturation of tissue, NIR PI: near-infrared perfusion index, OHI: organ hemoglobin index, TWI: tissue water index) provided by both camera systems. The mean absolute error (MAE) and root mean square error (RMSE) served for the quantitative evaluations. Spearman's rank correlation between factors related to the study design like the time of spectral white balancing and MAE, respectively RMSE, was calculated. RESULTS: The obtained mean MAEs between the TIVITA® Tissue and the laparoscopic hyperspectral system resulted in StO2: 11% ± 7%, NIR PI: 14±3, OHI: 14± 5, and TWI: 10 ± 2. The mean RMSE between both systems was 0.1±0.03 from 500 to 750 nm and 0.15 ±0.06 from 750 to 1000 nm. Spearman's rank correlation coefficients showed no significant correlation between MAE or RMSE and influencing factors related to the study design. CONCLUSION: Qualitatively, parameter images of the laparoscopic system corresponded to those of the system for open surgery. Quantitative deviations were attributed to technical differences rather than the study design. Limitations of the presented study are addressed in current large-scale in vivo trials.

Border Line Definition Using Hyperspectral Imaging in Colorectal Resections.

BACKGROUND: A perfusion deficit is a well-defined and intraoperatively influenceable cause of anastomotic leak (AL). Current intraoperative perfusion assessment methods do not provide objective and quantitative results. In this study, the ability of hyperspectral imaging (HSI) to quantify tissue oxygenation intraoperatively was assessed. METHODS: 115 patients undergoing colorectal resections were included in the final analysis. Before anastomotic formation, the bowel was extracted and the resection line was outlined and imaged using a compact HSI camera, in order to provide instantaneously quantitative perfusion assessment. RESULTS: In 105 patients, a clear demarcation line was visible with HSI one minute after marginal artery transection, reaching a plateau after 3 min. In 58 (55.2%) patients, the clinically determined transection line matched with HSI. In 23 (21.9%) patients, the clinically established resection margin was entirely within the less perfused area. In 24 patients (22.8%), the HSI transection line had an irregular course and crossed the clinically established resection line. In four cases, HSI disclosed a clinically undetected lesion of the marginal artery. CONCLUSIONS: Intraoperative HSI is safe, well reproducible, and does not disrupt the surgical workflow. It also quantifies bowel surface perfusion. HSI might become an intraoperative guidance tool, potentially preventing postoperative complications.

Tumor cell identification and classification in esophageal adenocarcinoma specimens by hyperspectral imaging.

Esophageal cancer is the sixth leading cause of cancer-related death worldwide. Histopathological confirmation is a key step in tumor diagnosis. Therefore, simplification in decision-making by discrimination between malignant and non-malignant cells of histological specimens can be provided by combination of new imaging technology and artificial intelligence (AI). In this work, hyperspectral imaging (HSI) data from 95 patients were used to classify three different histopathological features (squamous epithelium cells, esophageal adenocarcinoma (EAC) cells, and tumor stroma cells), based on a multi-layer perceptron with two hidden layers. We achieved an accuracy of 78% for EAC and stroma cells, and 80% for squamous epithelium. HSI combined with machine learning algorithms is a promising and innovative technique, which allows image acquisition beyond Red-Green-Blue (RGB) images. Further method validation and standardization will be necessary, before automated tumor cell identification algorithms can be used in daily clinical practice.

New Intraoperative Imaging Tools and Image-Guided Surgery in Gastric Cancer Surgery.

Innovations and new advancements in intraoperative real-time imaging have gained significant importance in the field of gastric cancer surgery in the recent past. Currently, the most promising procedures include indocyanine green fluorescence imaging (ICG-FI) and hyperspectral imaging or multispectral imaging (HSI, MSI). ICG-FI is utilized in a broad range of clinical applications, e.g., assessment of perfusion or lymphatic drainage, and additional implementations are currently investigated. HSI is still in the experimental phase and its value and clinical relevance require further evaluation, but initial studies have shown a successful application in perfusion assessment, and prospects concerning non-invasive tissue and tumor classification are promising. The application of machine learning and artificial intelligence technologies might enable an automatic evaluation of the acquired image data in the future. Both methods facilitate the accurate visualization of tissue characteristics that are initially indistinguishable for the human eye. By aiding surgeons in optimizing the surgical procedure, image-guided surgery can contribute to the oncologic safety and reduction of complications in gastric cancer surgery and recent advances hold promise for the application of HSI in intraoperative tissue diagnostics.

Using physiological parameters measured by hyperspectral imaging to detect colorectal cancer.

The accurate detection of malignant tissue during colorectal surgery impacts operation outcome. The non-invasive spectral imaging combined with machine learning (ML) methods showed to be promising for tumor identification. However, large spectral range implies large computing time. To reduce the number of features, ML methods (e.g. logistic regression and convolutional neuronal network CNN) were evaluated based on four physiological tissue parameters to automatically classify cancer and healthy mucosa in resected colon tissue. A ROC AUC of 0.81 was achieved with the CNN. This study shows that the use of only specific wavelengths bands can detect cancer.Clinical Relevance- These outcomes support the possibility to automatically classify colon tumor based on physiological parameters calculated using only specific wavelength bands. Hence, future image-guided colorectal surgeries can be performed with real-time multispectral imaging.

Hyperspectral Imaging: A New Intraoperative Tool for Pouch Assessment in Patients Undergoing Restorative Proctocolectomy.

INTRODUCTION: Restorative proctocolectomy with ileal pouch-anal anastomosis (IPAA) is a challenging operation. Especially the mobilization of the pouch into the pelvis can be complex. Adequate perfusion of the pouch is required for optimal healing and functioning. METHODS: With hyperspectral imaging (HSI) wavelengths between 500 and 1,000 nm can be analyzed in addition to visible light and by reflecting patterns. This intraoperative procedure is non-invasive, contact-free, and no contrast medium is needed. Fifteen patients undergoing IPAA were examined prospectively, and the pouch was evaluated by HSI intraoperatively. HSI was measured in standardized fashion at 4 defined locations of the J-pouch. Each measurement took about 10 s. The clinical postoperative course was assessed in all patients and correlated to the intraoperative HSI findings. RESULTS: Mean near-infrared perfusion and oxygenation of patients showed values ≥74% for all defined pouch areas, revealing good blood supply. Three minor anastomotic leaks were detected by standard pouchoscopy in the postoperative course, which could be treated conservatively with endosponge therapy. CONCLUSION: HSI values of perfusion and oxygenation of the IPAA were high. The leak rate is associated with redo procedures. This is reflected by the current literature and most likely related to the higher complexity of the revisional pouch operation. HSI has proved itself as a quick and effective new intraoperative tool to evaluate pouch perfusion objectively and quantitatively.

Automatic Recognition of Colon and Esophagogastric Cancer with Machine Learning and Hyperspectral Imaging.

There are approximately 1.8 million diagnoses of colorectal cancer, 1 million diagnoses of stomach cancer, and 0.6 million diagnoses of esophageal cancer each year globally. An automatic computer-assisted diagnostic (CAD) tool to rapidly detect colorectal and esophagogastric cancer tissue in optical images would be hugely valuable to a surgeon during an intervention. Based on a colon dataset with 12 patients and an esophagogastric dataset of 10 patients, several state-of-the-art machine learning methods have been trained to detect cancer tissue using hyperspectral imaging (HSI), including Support Vector Machines (SVM) with radial basis function kernels, Multi-Layer Perceptrons (MLP) and 3D Convolutional Neural Networks (3DCNN). A leave-one-patient-out cross-validation (LOPOCV) with and without combining these sets was performed. The ROC-AUC score of the 3DCNN was slightly higher than the MLP and SVM with a difference of 0.04 AUC. The best performance was achieved with the 3DCNN for colon cancer and esophagogastric cancer detection with a high ROC-AUC of 0.93. The 3DCNN also achieved the best DICE scores of 0.49 and 0.41 on the colon and esophagogastric datasets, respectively. These scores were significantly improved using a patient-specific decision threshold to 0.58 and 0.51, respectively. This indicates that, in practical use, an HSI-based CAD system using an interactive decision threshold is likely to be valuable. Experiments were also performed to measure the benefits of combining the colorectal and esophagogastric datasets (22 patients), and this yielded significantly better results with the MLP and SVM models.

[New intraoperative fluorescence-based and spectroscopic imaging techniques in visceral medicine - precision surgery in the "high tech"-operating room]. / Neue intraoperative fluoreszenzbasierte und spektroskopische Bildgebungsverfahren in der Viszeralmedizin ­ Präzisionschirurgie im "Hightech"-OP.

INTRODUCTION: Fluorescence angiography (FA) with indocyanine green (ICG) and hyperspectral imaging (HSI) are novel intraoperative visualization techniques in abdominal, vascular and transplant surgery. With the purpose of precision surgery, and in order to increase patient's safety, these new tools aim at reducing postoperative morbidity and mortality. This review discusses and highlights recent developments and the future potential of real-time imaging modalities. METHODS: The underlying mechanisms of the novel imaging methods and their clinical impact are displayed in the context of avoiding anastomotic leaks, the most momentous complications in gastrointestinal surgery after oncologic resections. RESULTS: While FA is associated with the admission of a fluorescence agent, HSI is contact-free and non-invasive. Both methods are able to record physiological tissue properties in real-time. Additionally, FA also measures dynamic phenomena. The techniques take a few seconds only and do not hamper the operative workflow considerably. With regard to a potential change of the surgical strategy, FA and HSI have an equal significance. Our own advancements reflect, in particular, the topics of data visualization and automated data analyses together with the implementation of artificial intelligence (AI) and minimalization of the current devices to install them into endoscopes, minimal-invasive and robot-guided surgery. CONCLUSION: There are a limited number of studies in the field of intraoperative imaging techniques. Whether precision surgery in the "high-tech" OR together with FA, HSI and robotics will result in more secure operative procedures to minimize the postoperative morbidity and mortality will have to be evaluated in future multicenter trials.

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

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.

[Status of minimally invasive gastrectomy : Current advancements: robotic surgery and intraoperative imaging for gastric cancer]. / Stellenwert der minimal-invasiven Gastrektomie : Aktuelle Weiterentwicklungen: Robotik und intraoperatives Imaging beim Magenkarzinom.

The surgical treatment of gastric cancer has arrived at a turning point towards the routine application of minimally invasive techniques. After the first results of prospective randomized trials from Asia confirmed the surgical and oncological safety, the latest results of international trials provided evidence for minimally invasive gastrectomy of advanced gastric cancer in a multimodal setting. A new addition in the field of minimally invasive procedures is robotic-assisted surgical techniques, which have already been implemented for these indications in many centers in Germany. The technical advantages that are applicable in the robotics setting in comparison to laparoscopy lead to a rapid dissemination of the procedure but still need to be evaluated in controlled trials. Further developments for the surgical treatment of gastric cancer are found in the field of intraoperative imaging procedures. In this field various technologies are available, such as fluorescence imaging using a near-infrared camera, which requires the use of a fluorescent agent or the hyperspectral camera system, which does not require the application of a fluorophore and merges pictures from visible and non-visible wavelengths to a functional image. It is to be expected that in the future various technological advancements can make a valuable contribution to the surgical treatment of gastric cancer in the clinical routine, especially if they support and facilitate the use of minimally invasive surgical techniques.

Novel Intraoperative Imaging of Gastric Tube Perfusion during Oncologic Esophagectomy-A Pilot Study Comparing Hyperspectral Imaging (HSI) and Fluorescence Imaging (FI) with Indocyanine Green (ICG).

BACKGROUND: Novel intraoperative imaging techniques, namely, hyperspectral (HSI) and fluorescence imaging (FI), are promising with respect to reducing severe postoperative complications, thus increasing patient safety. Both tools have already been used to evaluate perfusion of the gastric conduit after esophagectomy and before anastomosis. To our knowledge, this is the first study evaluating both modalities simultaneously during esophagectomy. METHODS: In our pilot study, 13 patients, who underwent Ivor Lewis esophagectomy and gastric conduit reconstruction, were analyzed prospectively. HSI and FI were recorded before establishing the anastomosis in order to determine its optimum position. RESULTS: No anastomotic leak occurred during this pilot study. In five patients, the imaging methods resulted in a more peripheral adaptation of the anastomosis. There were no significant differences between the two imaging tools, and no adverse events due to the imaging methods or indocyanine green (ICG) injection occurred. CONCLUSIONS: Simultaneous intraoperative application of both modalities was feasible and not time consuming. They are complementary with regard to the ideal anastomotic position and may contribute to better surgical outcomes. The impact of their simultaneous application will be proven in consecutive prospective trials with a large patient cohort.

Situation-Dependent Medical Device Risk Estimation: Design and Evaluation of an Equipment Management Center For Vendor-Independent Integrated Operating Rooms.

OBJECTIVES: The complexity of surgical interventions and the number of technologies involved are constantly rising. Hospital staff has to learn how to handle new medical devices efficiently. However, if medical device-related incidents occur, the patient treatment is delayed. Patient safety could therefore be supported by an optimized assistance system that helps improve the management of technical equipment by nonmedical hospital staff. METHODS: We developed a system for the optimal monitoring of networked medical device activity and maintenance requirements, which works in conjunction with a vendor-independent integrated operating room and an accurate surgical intervention Time And Resource Management System. An integrated situation-dependent risk assessment system gives the medical engineers optimal awareness of the medical devices in the operating room. RESULTS: A qualitative and quantitative survey among ten medical engineers from three different hospitals was performed to evaluate the approach. A series of 25 questions was used to evaluate various aspects of our system as well as the system currently used. Moreover, the respondents were asked to perform five tasks related to system supervision and incident handling. Our system received a very positive feedback. The evaluation studies showed that the integration of information, the structured presentation of information, and the assistance modules provide valuable support to medical engineers. CONCLUSIONS: An automated operating room monitoring system with an integrated risk assessment and Time And Resource Management System module is a new way to assist the staff being outside of a vendor-independent integrated operating room, who are nevertheless involved in processes in the operating room.

Comparison of hyperspectral imaging and fluorescence angiography for the determination of the transection margin in colorectal resections-a comparative study.

PURPOSE: One relevant aspect for anastomotic leakage in colorectal surgery is blood perfusion of both ends of the anastomosis. The clinical evaluation of this issue is limited, but new methods like fluorescence angiography with indocyanine green or non-invasive and contactless hyperspectral imaging have evolved as objective parameters for perfusion evaluation. METHODS: In this prospective, non-randomized, open-label and two-arm study, fluorescence angiography and hyperspectral imaging were compared in 32 consecutive patients with each other and with the clinical assessment by the surgeon. After preparation of the bowel and determination of the surgical resection line, the tissue was evaluated with hyperspectral imaging for 5 min before and after cutting the marginal artery and assessed by 6 hyperspectral pictures followed by fluorescence angiography with indocyanine green. RESULTS: In 30 of 32 patients, the image data could be evaluated and compared. Both methods provided a comparable borderline between well-perfused and poorly perfused tissue (p = 0.704). In 15 cases, the surgical resection line was shifted to the central position due to the imaging. The border zone was sharper in fluorescence angiography and best assessed 31 s after injection. With hyperspectral imaging, the border zone was visualized wider and with more differences between proximal and distal border. CONCLUSION: Hyperspectral imaging and fluorescence angiography provide similar results in determining the perfusion border. Both methods allow a good and safe visualization of the blood perfusion at the central resection margin to create a well-perfused anastomosis. TRIAL REGISTRATION: This study was registered at Clinicaltrials.gov ( NCT04226781 ) on January 13, 2020.