Combined indocyanine green and quantitative perfusion assessment with hyperspectral imaging during colorectal resections.

Anastomotic insufficiencies still represent one of the most severe complications in colorectal surgery. Since tissue perfusion highly affects anastomotic healing, its objective assessment is an unmet clinical need. Indocyanine green-based fluorescence angiography (ICG-FA) and hyperspectral imaging (HSI) have received great interest in recent years but surgeons have to decide between both techniques. For the first time, two data processing pipelines capable of reconstructing an ICG-FA correlating signal from hyperspectral data were developed. Results were technically evaluated and compared to ground truth data obtained during colorectal resections. In 87% of 46 data sets, the reconstructed images resembled the ground truth data. The combined applicability of ICG-FA and HSI within one imaging system might provide supportive and complementary information about tissue vascularization, shorten surgery time, and reduce perioperative mortality.

[Possibilities and perspectives of hyperspectral imaging in visceral surgery]. / Möglichkeiten und Perspektiven der Hyperspektralbildgebung in der Viszeralchirurgie.

HyperSpectral Imaging (HSI) technology enables quantitative tissue analyses beyond the limitations of the human eye. Thus, it serves as a new diagnostic tool for optical properties of diverse tissues. In contrast to other intraoperative imaging methods, HSI is contactless, noninvasive, and the administration of a contrast medium is not necessary. The duration of measurements takes only a few seconds and the surgical procedure is only marginally disturbed. Preliminary HSI applications in visceral surgery are promising with the potential of optimized outcomes. Current concepts, possibilities and new perspectives regarding HSI technology together with its limitations are discussed in this article.

Determination of the transection margin during colorectal resection with hyperspectral imaging (HSI).

PURPOSE: This study evaluated the use of hyperspectral imaging for the determination of the resection margin during colorectal resections instead of clinical macroscopic assessment. METHODS: The used hyperspectral camera is able to record light spectra from 500 to 1000 nm and provides information about physiologic parameters of the recorded tissue area intraoperatively (e.g., tissue oxygenation and perfusion). We performed an open-label, single-arm, and non-randomized intervention clinical trial to compare clinical assessment and hyperspectral measurement to define the resection margin in 24 patients before and after separation of the marginal artery over 15 min; HSI was performed each minute to assess the parameters mentioned above. RESULTS: The false color images calculated from the hyperspectral data visualized the margin of perfusion in 20 out of 24 patients precisely. In the other four patients, the perfusion difference could be displayed with additional evaluation software. In all cases, there was a deviation between the transection line planed by the surgeon and the border line visualized by HSI (median 1 mm; range - 13 to 13 mm). Tissue perfusion dropped up to 12% within the first 10 mm distal to the border line. Therefore, the resection area was corrected proximally in five cases due to HSI record. The biggest drop in perfusion took place in less than 2 min after devascularization. CONCLUSION: Determination of the resection margin by HSI provides the surgeon with an objective decision aid for assessment of the best possible perfusion and ideal anastomotic area in colorectal surgery.

[Hyperspectral imaging of gastrointestinal anastomoses]. / Hyperspektral-Imaging bei gastrointestinalen Anastomosen.

INTRODUCTION: Anastomotic insufficiency (AI) remains the most feared surgical complication in gastrointestinal surgery, which is closely associated with a prolonged inpatient hospital stay and significant postoperative mortality. Hyperspectral imaging (HSI) is a relatively new medical imaging procedure which has proven to be promising in tissue identification as well as in the analysis of tissue oxygenation and water content. Until now, no data exist on the in vivo HSI analysis of gastrointestinal anastomoses. METHODS: Intraoperative images were obtained using the TIVITA™ tissue system HSI camera from Diaspective Vision GmbH (Pepelow, Germany). In 47 patients who underwent gastrointestinal surgery with esophageal, gastric, pancreatic, small bowel or colorectal anastomoses, 97 assessable recordings were generated. Parameters obtained at the sites of the anastomoses included tissue oxygenation (StO2), the tissue hemoglobin index (THI), near-infrared (NIR) perfusion index, and tissue water index (TWI). RESULTS: Obtaining and analyzing the intraoperative images with this non-invasive imaging system proved practicable and delivered good results on a consistent basis. A NIR gradient along and across the anastomosis was observed and, furthermore, analysis of the tissue water and oxygenation content showed specific changes at the site of anastomosis. CONCLUSION: The HSI method provides a non-contact, non-invasive, intraoperative imaging procedure without the use of a contrast medium, which enables a real-time analysis of physiological anastomotic parameters, which may contribute to determine the "ideal" anastomotic region. In light of this, the establishment of this methodology in the field of visceral surgery, enabling the generation of normal or cut off values for different gastrointestinal anastomotic types, is an obvious necessity.

Dynamic infrared thermography (DIRT) for assessment of skin blood perfusion in cranioplasty: a proof of concept for qualitative comparison with the standard indocyanine green video angiography (ICGA).

PURPOSE: Complications in wound healing after neurosurgical operations occur often due to scarred dehiscence with skin blood perfusion disturbance. The standard imaging method for intraoperative skin perfusion assessment is the invasive indocyanine green video angiography (ICGA). The noninvasive dynamic infrared thermography (DIRT) is a promising alternative modality that was evaluated by comparison with ICGA. METHODS: The study was carried out in two parts: (1) investigation of technical conditions for intraoperative use of DIRT for its comparison with ICGA, and (2) visual and quantitative comparison of both modalities in a proof of concept on nine patients. Time-temperature curves in DIRT and time-intensity curves in ICGA for defined regions of interest were analyzed. New perfusion parameters were defined in DIRT and compared with the usual perfusion parameters in ICGA. RESULTS: The visual observation of the image data in DIRT and ICGA showed that operation material, anatomical structures and skin perfusion are represented similarly in both modalities. Although the analysis of the curves and perfusion parameter values showed differences between patients, no complications were observed clinically. These differences were represented in DIRT and ICGA equivalently. CONCLUSIONS: DIRT has shown a great potential for intraoperative use, with several advantages over ICGA. The technique is passive, contactless and noninvasive. The practicability of the intraoperative recording of the same operation field section with ICGA and DIRT has been demonstrated. The promising results of this proof of concept provide a basis for a trial with a larger number of patients.

Aortic valve prosthesis tracking for transapical aortic valve implantation.

PURPOSE: Transapical aortic valve implantation (TA-AVI) is a new minimally invasive surgical treatment of aortic stenosis for high-risk patients. The placement of aortic valve prosthesis (AVP) is performed under 2D X-ray fluoroscopic guidance. Difficult clinical complications can arise if the implanted valve is misplaced. Therefore, we present a method to track the AVP in 2D X-ray fluoroscopic images in order to improve the accuracy of the TA-AVI. METHODS: The proposed tracking method includes the template matching approach to estimate the position of AVP and a shape model of the prosthesis to extract the corner points of the AVP in each image of sequence. To start the AVP tracking procedure, an initialization step is performed by manually defining the corner points of the prosthesis in the first image of sequence to provide the required algorithm parameters such as the AVP model parameters. RESULTS: We evaluated the AVP tracking method on six 2D intra-operative fluoroscopic image sequences. The results of automatic AVP localization agree well with manually defined AVP positions. The maximum localization errors of tracked prosthesis are less than 1 mm and within the clinical accepted range. CONCLUSIONS: For assisting the TA-AVI, a method for tracking the AVP in 2D X-ray fluoroscopic image sequences has been developed. Our AVP tracking method is a first step toward automatic optimal placement of the AVP during the TA-AVI.

Modeling the 3D coronary tree for labeling purposes.

Coronary artery diseases are usually revealed using X-ray angiographies. Such images are complex to analyze because they provide a 2D projection of a 3D object. Medical diagnosis suffers from inter- and intra-clinician variability. Therefore, reliable software for the 3D reconstruction and labeling of the coronary tree is strongly desired. It requires the matching of the vessels in the different available angiograms, and an approach which identifies the arteries by their anatomical names is a way to solve this difficult problem. This paper focuses on the automatic labeling of the left coronary tree in X-ray angiography. Our approach is based on a 3D topological model, built from the 3D anthropomorphic phantom, Coronix. The phantom is projected under different angles of view to provide a data base of 2D topological models. On the other hand, the vessel skeleton is extracted from the patient's angiogram. The algorithm compares the skeleton with the 2D topological model which has the most similar vascular net shape. The method performs in a hierarchical manner, first labeling the main artery, then the sub-branches. It handles inter-individual anatomical variations, segmentation errors and image ambiguities. We tested the method on standard angiograms of Coronix and on clinical examinations of nine patients. We demonstrated successful scores of 90% correct labeling for the main arteries and 60% for the sub-branches. The method appears to be particularly efficient for the arteries in focus. It is therefore a very promising tool for the automatic 3D reconstruction of the coronary tree from monoplane temporal angiographic clinical sequences.