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]

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.

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.

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.