Endoscopic spine surgery (ESS) has traditionally been employed for lumbar disc herniation (LDH). Recent innovations in surgical methods and technologies have expanded its range to address other spinal pathologies, providing minimally invasive solutions with potential clinical benefits. Our review aims to summarize the applications, clinical outcomes, and limitations of ESS beyond LDH, focusing on its role in complex spinal conditions such as stenosis, thoracic disc herniation, spinal tumors, synovial cysts, and failed back surgery syndrome. A thorough review of the literature was conducted to assess and summarize the current evidence regarding ESS applications for spinal conditions beyond LDH surgery. Areas of focus included innovations in technology and technique, as well as comparisons with conventional open surgical methods. ESS shows notable potential across different spinal conditions by providing minimally invasive alternatives to traditional open surgery. Its use could be associated with reduced surgical morbidity, shorter recovery times, and improved patient outcomes. In particular, ESS is versatile in addressing both degenerative and neoplastic conditions of the spine. Despite this, challenges such as technical complexity, steep learning curves, and limited indications for certain pathologies remain as barriers to wider adoption. ESS is evolving in spine surgery, extending its utility beyond LDH surgery. While the current evidence largely supports its clinical efficacy, further studies are needed to address the present limitations and optimize its application. Future developments in surgical training and technology will likely enhance its adoption and broaden its clinical indications.

Background: Radiotherapy for thymoma is delivered post-operatively in selected cases. Given the particular location of the thymic bed and the excellent prognosis, late cardiac toxicities may be an issue. The purpose of this retrospective dosimetric study is to investigate whether intensity-modulated proton beam therapy (IMPT) compared to photon therapy could better spare cardiac substructures, given prespecified dose constraints. Methods: We retrospectively selected patients treated with adjuvant radiotherapy for thymoma in our institution. We manually contoured fourteen cardiac substructures (CSs), with the supervision of a team of cardioradiologists. The photon-based plans were re-optimized in adherence to the volumetric modulated arc therapy (VMAT) technique with specific dose constraints for the new contoured structures. The proton-based plans were optimized in adherence to intensity-modulated proton therapy (IMPT) using the beam spot scanning technique. Results: Twenty-nine patients treated with adjuvant radiotherapy with a prescribed dose of 50 Gy in 25 daily fractions for radically resected thymoma were selected. IMPT demonstrated better sparing of most cardiac substructures in terms of Dmax, Dmean and V5Gy. Finally, IMPT plans more easily achieved the proposed dose constraints. Conclusions: Cardiac substructures can be successfully spared with IMPT. Clinical studies are needed to establish a relationship between dose parameters and the development of cardiac events.

Augmented reality (AR) is an emerging technology in spine surgery with the potential to enhance intraoperative visualization and precision by overlaying virtual images on anatomical structures. This bibliometric review analyzes trends in research and publication growth related to AR in spinal neurosurgery between 2013 and 2024. A search across PubMed identified 267 articles. After screening, we analyzed 98 relevant studies, revealing exponential growth in AR research, with publications increasing from 1 in 2013 to 28 in 2024. The focus of research evolved over the years, with instrumentation being the dominant topic in 2020, and a broader emphasis on multi-domain AR applications in 2024. The United States led in publication output, followed by Germany, Sweden, and Switzerland. The increasing number of studies reflects AR's growing adoption in both specialized and broad spine surgery applications. Although AR has demonstrated its potential to improve surgical precision and education, further research is needed to assess long-term clinical outcomes and overcome barriers to widespread implementation.

To the Editor of the Journal of Cardiovascular Electrophysiology, We read with great interest the article the recent publication titled ”Impact of Artificial Intelligence Arrhythmia Mapping on Time to First Ablation, Procedure Duration, and Fluoroscopy Use” by Fox et al [1]. The study investigates the effectiveness of AI-driven arrhythmia mapping in reducing time to first ablation, procedure duration, and fluoroscopy use in patients undergoing cardiac ablation. The authors conducted a retrospective analysis of 28 patients treated with traditional methods and compared the outcomes with those of 28 patients treated using the new AI mapping technology. They observed significant improvements in procedural efficiency and safety with the AI approach. While the results presented are promising, several aspects of the study deserve careful consideration to understand its full impact and limitations. First, the retrospective design of this study introduces potential biases, such as selection bias and information bias.Patients were not randomized, which could lead to differences between the control and experimental groups that are not related to the intervention. RCTs are needed to validate these findings and minimize these biases. Second, the study relies on historical controls, comparing patients treated with traditional methods in the past to those treated with AI mapping more recently. These temporal differences could introduce confounding variables, making it unclear whether the improvements are due to the AI mapping or other advancements in the field. Furthermore, the study does not provide detailed information on the specific AI algorithms used for arrhythmia mapping.Understanding the underlying technology is crucial for assessing the broader applicability of the results. Different AI models may have varying levels of effectiveness, and their performance can be influenced by the quality and type of data used for training and validation [2]. Finally, the study’s findings may not be generalizable to all clinical settings. The patient population, procedural techniques, and operator expertise at the study site may differ from those at other institutions. Further studies involving multiple centers and diverse patient populations are needed to confirm the broad applicability of the results. While the study by Fox et al. provides promising evidence of the benefits of AI in arrhythmia mapping, critical evaluation of the study design and methodology reveals several limitations that need to be addressed. Further prospective,randomized controlled trials are essential to validate these findings and ensure the robustness and generalizability of AI applications in clinical practice. This study represents an important step towards integrating AI into routine clinical practice, with the potential for significant improvements in patient outcomes and procedural efficiency. Sincerely, Federico Guerini References 1. Fox SR, Toomu A, Gu K, Kang J, Sung K, Han FT, Hoffmayer KS, Hsu JC, Raissi F, Feld GK, McCulloch AD, Ho G, Krummen DE. Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration,and fluoroscopy use. J Cardiovasc Electrophysiol. 2024 May;35(5):916-928. doi: 10.1111/jce.16237. Epub 2024 Mar 4. PMID: 38439119. 2. Loeffler SE, Trayanova N. Primer on Machine Learning in Electrophysiology. Arrhythm Electrophysiol Rev. 2023 Mar 28;12:e06. doi: 10.15420/aer.2022.43. PMID: 37427298; PMCID: PMC10323871.