SEP-induced activity and its thermographic cortical representation in a murine model

Thermosensitive/thermochromic silicone and infrared thermography mapping in 60 consecutive cases of epilepsy surgery

Background

Epilepsy surgery represents a therapeutic opportunity for those patients who do not respond to drug therapy. However, an important challenge is the precise identification of the epileptogenic area during surgery. Since it can be hard to delineate, it makes it necessary to use auxiliary tools as a guide during the surgical procedure. Electrocorticography (ECoG), despite having shown favorable results in terms of reducing post-surgical seizures, have certain limitations. Brain mapping using infrared thermography mapping and a new thermosensitive/thermochromic silicone (TTS) in epilepsy surgery has introduced a new resource of noninvasive and real-time devices that allow the localization of irritative zones.

Methods

Sixty consecutive patients with drug-resistant epilepsy with surgical indications who decided to participate voluntarily in the study were included in the study. We measured brain temperature using two quantitative methods and a qualitative method: the TTS sheet. In all cases, we used ECoG as the gold standard to identify irritative areas, and all brain tissue samples obtained were sent to pathology for diagnosis.

Results

In the subgroup in which the ECoG detected irritative areas (n = 51), adding the results in which there was a correlation with the different methods, the efficiency obtained to detect irritative areas is 94.11% (n = 48/51, P ≤ 0.0001) while the infrared thermography mapping method independently has an efficiency of 91.66% (P ≤ 0.0001). The TTS has a sensitivity of 95.71% and a specificity of 97.9% (P ≤ 0.0001) to detect hypothermic areas that correlate with the irritative zones detected by ECoG. No postoperative infections or wound dehiscence were documented, so the different methodologies used do not represent an additional risk for the surgical proceedings.

Conclusion

We consider that the infrared thermography mapping using high-resolution infrared thermography cameras and the TTS are both accurate and safe methods to identify irritative areas in epilepsy surgeries.

Segmentation Approaches for Diabetic Foot Disorders

Thermography enables non-invasive, accessible, and easily repeated foot temperature measurements for diabetic patients, promoting early detection and regular monitoring protocols, that limit the incidence of disabling conditions associated with diabetic foot disorders. The establishment of this application into standard diabetic care protocols requires to overcome technical issues, particularly the foot sole segmentation. In this work we implemented and evaluated several segmentation approaches which include conventional and Deep Learning methods. Multimodal images, constituted by registered visual-light, infrared and depth images, were acquired for 37 healthy subjects. The segmentation methods explored were based on both visual-light as well as infrared images, and optimization was achieved using the spatial information provided by the depth images. Furthermore, a ground truth was established from the manual segmentation performed by two independent researchers. Overall, the performance level of all the implemented approaches was satisfactory. Although the best performance, in terms of spatial overlap, accuracy, and precision, was found for the Skin and U-Net approaches optimized by the spatial information. However, the robustness of the U-Net approach is preferred.

Motion Correction in Multimodal Intraoperative Imaging

Thermographic imaging accompanied with time-resolved analysis is a promising technique for intraoperative imaging in neurosurgery. However, motion due to breathing and pulse of the patient introduces large inaccuracies to the demarcation of normal and pathological brain tissue. Since movements and physiological processes are both manifested as temperature variations, we employ co-registered visual-light images to unambiguously detect motion. In this article, we propose a feature-based approach which is selected from four best-known methods after thorough performance comparison. Complementing our previous work, we evaluate the performance of our methods by applying a frequency analysis and similarity measurements. Our approach enables an accurate motion correction without affecting physiological temperature shifts. Furthermore, real-time performance of the implementation is enabled by serial acceleration and parallelization methods.

Registration and Fusion of Thermographic and Visual-Light Images in Neurosurgery

An intraoperative imaging system facilitating the localisation and characterisation of functional areas, pathological tissue, or perfusion disorders, could enormously support medical decisions during neurosurgical interventions and, thus, reduce the risk for the patients. To provide both structural and functional information of the brain tissue to the surgeon, a novel multimodal approach based on the measurement of long-wave infrared radiation and visual-light imaging is very promising. In this contribution, we discuss various methods for the registration and fusion of thermographic and visual-light images. The methods are evaluated quantitatively and qualitatively regarding their practicability during surgery. Furthermore, we introduce appropriate architectures for a digital hardware implementation of the registration and fusion algorithms. The designs are implemented on our reconfigurable intraoperative imaging system, revealing real-time processing performance.