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Background Hyperspectral Imaging (HSI) is a reliable and safe imaging method for taking intraoperative perfusion measurements. This is the first study translating intraoperative HSI to an in vivo laparoscopic setting using a CE-certified HSI-system for minimally invasive surgery (HSI-MIS). We aim to compare it to an established HSI-system for open surgery (HSI-Open). Methods Intraoperative HSI was done using the HSI-MIS and HSI-Open at the Region of Interest (ROI). 19 patients undergoing gastrointestinal resections were analyzed in this study. The HSI-MIS-acquired images were aligned with those from the HSI-Open, and spectra and parameter images were compared pixel-wise. We calculated the Mean Absolute Error (MAE) for Tissue Oxygen Saturation (StO2), Near-Infrared Perfusion Index (NIR-PI), Tissue Water Index (TWI), and Organ Hemoglobin Index (OHI), as well as the Root Mean Squared Error (RMSE) over the whole spectrum. Our analysis of parameters was optimized using partial least squares (PLS) regression. Two experienced surgeons carried out an additional color-change analysis, comparing the ROI images and deciding whether they provided the same (acceptable) or different visual information (rejected). Results HSI and subsequent image registration was possible in 19 patients. MAE results for the original calculation were StO2 orig. 17.2% (± 7.7%), NIR-PIorig. 16.0 (± 9.5), TWIorig. 18.1 (± 7.9), OHIorig. 14.4 (± 4.5). For the PLS calculation, they were StO2 PLS 12.6% (± 5.2%), NIR-PIPLS 10.3 (± 6.0), TWIPLS 10.6 (± 5.1), and OHIPLS 11.6 (± 3.0). The RMSE between both systems was 0.14 (± 0.06). In the color-change analysis; both surgeons accepted more images generated using the PLS method. Conclusion Intraoperative HSI-MIS is a new technology and holds great potential for future applications in surgery. Parameter deviations are attributable to technical differences and can be reduced by applying improved calculation methods. This study is an important step toward the clinical implementation of HSI for minimally invasive surgery.

Surgical navigation-assisted interventions, providing augmented previously acquired image data to support the physician, are routinely used. Visualization techniques like extended reality (XR) promise improvements because the desired information can be shown where most suitable. The accuracy of such systems is essential for usability in clinical interventions but lacks research. This work shows a system to project thermal data for use in reconstructive surgery and investigates the accuracy of the XR technology. The system consists of a thermal camera (PI450, Optris GmbH, Germany), a depth camera system (D415, Intel Inc., USA), and a HoloLens2 (Microsoft Corp., USA). 5 probands annotated the locations of 9 marker points on a calibration pattern of the real object and the projection in the XR headset. The mean and max residual projection errors were 2.8 and 6.2 mm, respectively. An XR system to superimpose thermal images was shown. The mean projection error of 2.8 mm is sufficient for further exploration of medical applications.

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.

Objectives Hand-sewn and stapled intestinal anastomoses are both daily performed routine procedures by surgeons. Yet, differences in micro perfusion of these two surgical techniques and their impact on surgical outcomes are still insufficiently understood. Only recently, hyperspectral imaging (HSI) has been established as a non-invasive, contact-free, real-time assessment tool for tissue oxygenation and micro-perfusion. Hence, objective of this study was HSI assessment of different intestinal anastomotic techniques and analysis of patients’ clinical outcome. Methods Forty-six consecutive patients with an ileal–ileal anastomoses were included in our study; 21 side-to-side stapled and 25 end-to-end hand-sewn. Based on adsorption and reflectance of the analyzed tissue, chemical color imaging indicates oxygen saturation (StO2), tissue perfusion (near-infrared perfusion index [NIR]), organ hemoglobin index (OHI), and tissue water index (TWI). Results StO2 as well as NIR of the region of interest (ROI) was significantly higher in stapled anastomoses as compared to hand-sewn ileal–ileal anastomoses (StO2 0.79 (0.74–0.81) vs. 0.66 (0.62–0.70); p Conclusions Intraoperative HSI assessment is able to detect significant differences in tissue oxygenation and NIR of hand-sewn and stapled intestinal anastomoses. Long-term clinical consequences resulting from the reduced tissue oxygenation and tissue perfusion in hand-sewn anastomoses need to be evaluated in larger clinical trials, as patients may benefit from further refined surgical techniques.

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.The principles of ICG-FA, spectral imaging, imaging photoplethysmography (iPPG), and their applications in gastrointestinal surgery are described based on selected published works.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.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.

Hyperspectral Imaging (HSI) provides surgeons intraoperative colored images of abdominal organgs detecting the perfusion and oxygenation. Limiting factors such as missing colour video, camera size, and long acquisition times have been overcome in the first CE-certified HSI-System for Minimally-Invasive Surgery (HSI-MIS; TIVITA® Mini Endoscopy Edition, Diaspective Vision GmbH, Am Salzhaff, Germany). This system was evaluated in-vivo during surgery and compared with an HSI-System for Open Surgery (TIVITA® Tissue, Diaspective Vision GmbH, Am Salzhaff, Germany). Hyperspectral imaging was performed with both the HSI-MIS and the HSI-System for Open Surgery at the Region of Interest. 19 patients undergoing gastroenterologic resections were included in the study. The images acquired with the HSI-MIS were registered onto the images from the open HSI system, and spectra, as well as parameter images, were pixel-wise compared. Violin plots were created for Tissue Oxygen Saturation (StO2), Near-Infrared Perfusion Index (NIR PI), Tissue Water Index (TWI) and Organ Hemoglobin Index (OHI). The raw data was analyzed using a partial least squares (PLS) and compared with the parameters as calculated by the original software The MAE results for the in-vivo evaluation were: StO2: 17.4% ± 7.6%, NIR PI: 16.3 ± 9.4, OHI: 14.3 ± 4.5, and TWI: 18.3 ± 7.8. The results obtained by PLS were StO2: 11.1% ± 3.9% (improved by 36%), NIR PI: 9.5 ± 5.8 (improved by 42%), OHI: 10.7 ± 2.7 (improved by 25%) and TWI: 9.6 ± 4.3 (improved by 48%) Laparoscopic hyperspectral imaging during minimally invasive procedures shows promising results. Parameter deviations might be attributable to technical differences and on how the parameters are calculated. The PLS method has shown significant improvement compared to the original calculation.

Hyperspectral imaging (HSI), as recently applied in medicine, is a novel technology combining imaging with spectroscopy. It might be used to identify, classify and discriminate malignant and non-malignant cells of histopathologic specimens. HSI allows the determination of a spectrum between the visual and near-infrared light (500-1000 nm). After surgical resection, specimens (n = 96) of Barrett’s cancer were fixed in 4% formaldehyde and slices were conducted (3 μm), which were stained with hematoxylin and eosin (HE). Differences in the absorbance of squamous epithelium and esophageal adenocarcinoma (EAC) cells were determined at eosin’s and hematoxylin’s maximal absorption of 530 nm and 590 nm. A classification algorithm, which combines a multilayer perceptron (MLP) with a Gaussian filter and data reduction based on principal component analysis (PCA) was used for discrimination. For the first time in literature, we were able to analyze esophageal adenocarcinoma, tumor stroma and squamous epithelium cells by HSI. For both, the squamous epithelium and the esophageal adenocarcinoma cells, the intragroup variances were quite low. A set of 20 specimens was used in a testing phase, which showed MLP by using reflectance data to provide the best results. Leave-one-patient-out-cross validation for all 96 specimens showed an accuracy of 77% with a sensitivity of 87% and a specificity of 72% for EAC determination and visualization. Squamous epithelium and EAC cells show specific spectral alterations due to their HE-staining, when measured by HSI. However, the training algorithms need further validation to foster a semi-automatic decision-making process in histopathological tumor cell identification.

Zusammenfassung Hintergrund Die Fluoreszenz-Angiografie (FA) mit Indocyanin-Grün (ICG) und das Hyperspektral-Imaging (HSI) sind neue intraoperative Visualisierungsmöglichkeiten in der Abdominal-, Gefäß- und Transplantationschirurgie. Ziel ist es, damit die postoperative Morbidität und Mortalität im Sinne der Präzisionschirurgie und Patientensicherheit zu reduzieren. In diesem Artikel werden aktuelle Daten und das zukünftige innovative Potenzial der Echtzeit-Bildgebungsmodalitäten hervorgehoben. Methoden Das Prinzip der neuen „Imaging“-Verfahren und deren klinische Anwendungen werden aufgearbeitet mit Blick auf Anastomoseninsuffizienzen, die die folgenschwersten Komplikationen in der gastrointestinalen Chirurgie nach onkologischen Resektionen darstellen. Ergebnisse Während die FA die Gabe eines Fluoreszenzfarbstoffs erfordert, ist HSI völlig kontaktfrei und nichtinvasiv. Beide Methoden können in „Real-Time“-Applikation physiologische Gewebeeigenschaften, zudem die FA auch dynamische Phänomene, erfassen. Die Verfahren dauern nur wenige Sekunden und stören den operativen Ablauf nicht wesentlich. Sie sind hinsichtlich ihrer Aussagekraft für eine mögliche Änderung der operativen Strategie als komplementär zu betrachten. Unsere eigenen Weiterentwicklungen der Modalitäten liegen insbesondere im Bereich der Datenvisualisierung sowie der automatischen Datenanalyse unter Einsatz der künstlichen Intelligenz (KI) und der Miniaturisierung der bisherigen Geräte für einen zukünftigen Einsatz in der Endoskopie, der minimalinvasiven und der roboterassistierten Chirurgie. Schlussfolgerung Insgesamt ist die Zahl der Studien im Forschungsfeld der intraoperativen Bildgebung zurzeit noch sehr limitiert. Ob diese neue Art der Präzisionschirurgie im „Hightech“-OP mit der Kombination aus HSI, FA und Robotik zu einer verbesserten Patientensicherheit durch Minimierung der postoperativen Morbidität und Mortalität führt, muss in weiterführenden multizentrischen Studien evaluiert werden.

Die vollstandige Resektion von Tumorgewebe und erfolgreiche Rekonstruktion der Kontinuitat des Magen-Darm-Trakts sind in der onkologischen Viszeralchirurgie von essenzieller Bedeutung fur das postoperative Outcome. Neuerungen und Weiterentwicklungen in der intraoperativen Bildgebung ermoglichen die Visualisierung zuvor nur schwer beurteilbarer Parameter, wie der Gewebeperfusion und der Lymphdrainagewege. Dies erlaubt eine direkte Optimierung des operativen Verfahrens und kann somit zur Reduktion von Komplikationen und zur Erhohung der Patientensicherheit beitragen. Eine bereits in vielen Fachgebieten etablierte Methode der Echtzeitbildgebung ist das Fluoreszenz-Imaging mittels Indozyaningrun (ICG-FI). In der Viszeralchirurgie wird es aktuell besonders zur Perfusionsbeurteilung gastrointestinaler Anastomosen und zum „Lymphknoten-Mapping“ eingesetzt. Jedoch werden in ersten Untersuchungen auch weitere mogliche Anwendungsgebiete beschrieben, beispielsweise die Detektion von Lebermetastasen und Peritonealkarzinosen im Rahmen von Staging-Untersuchungen oder der zytoreduktiven Chirurgie. Eine weitere vielversprechende Methode ist das Hyperspektral-Imaging (HSI), welches sich aktuell noch in einer experimentellen Phase befindet, zukunftig aber ein wichtiges Instrument zur noninvasiven Perfusionsbeurteilung und Gewebedifferenzierung darstellen konnte. Im vorliegenden Beitrag wird ein Uberblick uber die aktuellen Anwendungsgebiete neuer intraoperativer Imaging-Verfahren gegeben und auf neue Moglichkeiten und Perspektiven der modernen „image-guided surgery“ hingewiesen.

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.What are the medical applications and advantages of intelligent HSI for minimally invasive visceral surgery?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.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.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.HINTERGRUND: Intraoperative Bildgebung unterstützt Chirurgen bei minimal-invasiven Eingriffen. Die hyperspektrale Bildgebung („hyperspectral imaging“, HSI) ist ein nichtinvasives und kontaktloses optisches Verfahren mit großem diagnostischem Potenzial in der Medizin. Die Kombination mit Ansätzen der künstlichen Intelligenz (KI) für die Analyse der HSI-Daten wird in diesem Artikel intelligente HSI genannt.Wie kann intelligente HSI in der minimal-invasiven Viszeralchirurgie eingesetzt werden und wo liegen die Vorteile?Innerhalb verschiedener klinischer Studien wurden HSI-Daten mehrerer In-vivo-Gewebearten und onkologischer Resektate mit einer HSI-Kamera aufgenommen. Verschiedene KI-Algorithmen wurden zur Identifikation und Diskriminierung von Organen, Risikostrukturen und Tumoren evaluiert.Im Tierversuch konnten 20 verschiedene Organe mit hoher Genauigkeit ( 95 %) mittels KI differenziert werden. In-vivo konnten die Nebenschilddrüse mit einem F1-Score von 47 % und einer Sensitivität von 75 % sowie der Gallengang mit einem F1-Score von 79 % und einer Sensitivität von 90 % vom umliegenden Gewebe diskriminiert werden. Des Weiteren konnte Ex-vivo-Tumorgewebe mit einer Fläche unter der „Receiver-operating-characteristic“(ROC)-Kurve (AUC) größer als 0,91 erfolgreich erkannt werden.Die vorliegenden Arbeiten zeigen die Eignung intelligenter HSI zur automatischen Gewebeerkennung. Trotz großer Fortschritte in den letzten zehn Jahren zeigt intelligentes HSI noch Einschränkungen. So sind genauere und für den Benutzer verständlichere KI-Algorithmen sowie umfangreiche standardisierte und kontinuierlich wachsende Datenbanken notwendig. Weitere klinische Studien sollten die vielseitigen Anwendungen stützen und den Einsatz im klinischen Alltag fest etablieren.