The applications of augmented reality in image-guided tumor ablations: A scoping review.

BACKGROUND: Interventional radiology employs minimally invasive image-guided procedures for diagnosing and treating various conditions. Among these procedures, alcohol and thermal ablation techniques have shown high efficacy. However, these procedures present challenges such as increased procedure time, radiation dose, and risk of tissue injury. This scoping review aims to explore how augmented reality (AR) can mitigate these challenges and improve the accuracy, precision, and efficiency of image-guided tumor ablation while improving patient outcomes. METHODS: A scoping review of the literature was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline to identify published literature investigating AR in image-guided tumor ablations. We conducted our electronic searches using PubMed, Scopus, Web of Sciences and CINAHL from inception to April 27th, 2023. The following Boolean terms were used for the search: ("augmented reality" OR "AR" OR "navigation system" OR "head mounted device" OR "HMD") AND ("tumor ablation" OR "radiofrequency tumor ablation" OR "microwave tumor ablation" OR "cryoablation"). We considered articles eligible for our scoping review if they met the following conditions: (1) published in English only, (2) focused on image-guided tumour ablations, (3) incorporated AR techniques in their methodology, (4) employed an aspect of AR in image-guided tumour ablations, and (5) exclusively involved human subjects. Publications were excluded if there was no mention of applying AR, or if the study investigated interventions other than image-guided tumour ablations. RESULTS: Our search results yielded 1,676 articles in our initial search of the databases. Of those, 409 studies were removed as duplicates. 1,243 studies were excluded during the title and abstract screening. 24 studies were assessed for eligibility in the full-text stage. 19 studies were excluded, resulting in a final selection of only five studies that satisfied our inclusion criteria. The studies aimed to assess AR's efficacy in tumor ablations. Two studies compared an optical-based AR system with CT guidance. Two studies used a head-mounted AR device, while one used a dual-camera setup. Various tumor types were examined, including bone, abdominal soft tissue, breast, hepatic, renal, colorectal, and lung lesions. All studies showed positive results, including reduced radiation exposure, shorter procedures, and improved navigation, and targeting assistance. CONCLUSION: AR systems enhance image-guided tumor ablations by improving the accuracy of ablation probe placements and increasing efficiency. They offer real-time guidance, enhanced visualization, and improved navigation, resulting in optimal needle placement. AR reduces radiation exposure and shortens procedure times compared to traditional CT-guided techniques. However, limitations like small sample sizes and technical challenges require further research. Despite this, AR shows potential benefits and larger, diverse studies are needed for validation.

Analytical modelling of regional radiotherapy dose response of lung.

Knowledge of the dose-response of radiation-induced lung disease (RILD) is necessary for optimization of radiotherapy (RT) treatment plans involving thoracic cavity irradiation. This study models the time-dependent relationship between local radiation dose and post-treatment lung tissue damage measured by computed tomography (CT) imaging. Fifty-eight follow-up diagnostic CT scans from 21 non-small-cell lung cancer patients were examined. The extent of RILD was segmented on the follow-up CT images based on the increase of physical density relative to the pre-treatment CT image. The segmented RILD was locally correlated with dose distribution calculated by analytical anisotropic algorithm and the Monte Carlo method to generate the corresponding dose-response curves. The Lyman-Kutcher-Burman (LKB) model was fit to the dose-response curves at six post-RT time periods, and temporal change in the LKB parameters was recorded. In this study, we observed significant correlation between the probability of lung tissue damage and the local dose for 96% of the follow-up studies. Dose-injury correlation at the first three months after RT was significantly different from later follow-up periods in terms of steepness and threshold dose as estimated from the LKB model. Dependence of dose response on superior-inferior tumour position was also observed. The time-dependent analytical modelling of RILD might provide better understanding of the long-term behaviour of the disease and could potentially be applied to improve inverse treatment planning optimization.