Intelligent optical diagnosis and treatment system for automated image-guided laser ablation of tumors

Performance analysis of a liquid lens for laser ablation using OCT imaging

Laser ablation has been used in different surgical procedures to perform precise treatments. Compared with previous free-beam laser delivery systems, flexible-optical-fiber-based systems can deliver laser energy to a curved space, avoiding the requirement of a straight working path to the target. However, the fiber tip maintains direct contact with the tissue to prevent laser divergence, resulting in fiber damage, uneven ablation, and tissue carbonization. Here, a liquid lens is used to address the problem of laser defocusing when radiating targets at different depths for flexible-optical-fiber-based systems. The liquid lens focuses a laser with a maximum power of 3 W onto a medium-density fiberboard at a focal length of 40-180 mm. The relationships between the ablation crater diameter and depth with the radiation time and laser power have been quantitatively evaluated through OCT (optical coherence tomography) imaging. Experiments demonstrate that the liquid lens can continuously focus the high-power laser to different depths, with the advantages of compact size, fast response, light weight, and easy operation. This study explores liquid-lens-based focused laser ablation, which can potentially improve the performance of future medical image-guided laser ablation.

The State-of-the-Art and Perspectives of Laser Ablation for Tumor Treatment

Tumors significantly impact individuals' physical well-being and quality of life. With the ongoing advancements in optical technology, information technology, robotic technology, etc., laser technology is being increasingly utilized in the field of tumor treatment, and laser ablation (LA) of tumors remains a prominent area of research interest. This paper presents an overview of the recent progress in tumor LA therapy, with a focus on the mechanisms and biological effects of LA, commonly used ablation lasers, image-guided LA, and robotic-assisted LA. Further insights and future prospects are discussed in relation to these aspects, and the paper proposed potential future directions for the development of tumor LA techniques.

Self-supervised speckle noise reduction of optical coherence tomography without clean data

Optical coherence tomography (OCT) is widely used in clinical diagnosis due to its non-invasive, real-time, and high-resolution characteristics. However, the inherent speckle noise seriously degrades the image quality, which might damage the fine structures in OCT, thus affecting the diagnosis results. In recent years, supervised deep learning-based denoising methods have shown excellent denoising ability. To train a deep denoiser, a large number of paired noisy-clean images are required, which is difficult to achieve in clinical practice, since acquiring a speckle-free OCT image requires dozens of repeated scans and image registration. In this research, we propose a self-supervised strategy that helps build a despeckling model by training it to map neighboring pixels in a single noisy OCT image. Adjacent pixel patches are randomly selected from the original OCT image to generate two similar undersampled images, which are respectively used as the input and target images for training a deep neural network. To ensure both the despeckling and the structure-preserving effects, a multi-scale pixel patch sampler and corresponding loss functions are adopted in our practice. Through quantitative evaluation and qualitative visual comparison, we found that the proposed method performs better than state-of-the-art methods regarding despeckling effects and structure preservation. Besides, the proposed method is much easier to train and deploy without the need for clean OCT images, which has great significance in clinical practice.

OCT-Guided Surgery for Gliomas: Current Concept and Future Perspectives

Optical coherence tomography (OCT) has been recently suggested as a promising method to obtain in vivo and real-time high-resolution images of tissue structure in brain tumor surgery. This review focuses on the basics of OCT imaging, types of OCT images and currently suggested OCT scanner devices and the results of their application in neurosurgery. OCT can assist in achieving intraoperative precision identification of tumor infiltration within surrounding brain parenchyma by using qualitative or quantitative OCT image analysis of scanned tissue. OCT is able to identify tumorous tissue and blood vessels detection during stereotactic biopsy procedures. The combination of OCT with traditional imaging such as MRI, ultrasound and 5-ALA fluorescence has the potential to increase the safety and accuracy of the resection. OCT can improve the extent of resection by offering the direct visualization of tumor with cellular resolution when using microscopic OCT contact probes. The theranostic implementation of OCT as a part of intelligent optical diagnosis and automated lesion localization and ablation could achieve high precision, automation and intelligence in brain tumor surgery. We present this review for the increase of knowledge and formation of critical opinion in the field of OCT implementation in brain tumor surgery.