Lung Cancer (Suspected or Confirmed)

Lung cancer remains the leading cause of cancer-related death in the UK, with over 35,000 deaths annually and most cases diagnosed at a late stage. Current screening programmes using low-dose CT scans target only high-risk individuals, missing around 30% of lung cancer cases, including many women and never-smokers. There is no simple, non-invasive tool to help triage patients with persistent respiratory symptoms who fall outside formal screening criteria. Inflammacheck® measures hydrogen peroxide and other breath biomarkers linked to airway inflammation and oxidative stress. Preliminary studies (VICTORY and ExPeL) have shown strong diagnostic performance for distinguishing lung cancer from other respiratory conditions. VICTORY 2 aims to validate and refine the AI model supporting Inflammacheck®, enabling accurate, rapid, and affordable triage for suspected lung cancer in NHS settings.

Using RBS as the navigation and treatment platform, precisely navigate to the target lesion. Utilize r-EUBS and nCLE to identify the lesion, and when the confocal AI model recognizes the lesion as malignant, perform a biopsy. Subsequently, under the guidance of OBCT, carry out ablation treatment of the lesion.

This study aims at evaluating whether music therapy intervention is effective in decreasing psychological (distress) and physical symptoms (pain) in patients with suspected or diagnosed lung cancer undergoing minimally invasive lung surgery.

This is a single-center, prospective, single-arm clinical study conducted at Beijing Cancer Hospital to evaluate the effectiveness, safety, and learning curve of preoperative indocyanine green (ICG) dye marking mixed with iodinated contrast agent under Monarch Robotic Assisted Bronchoscopy (RAB) with Cone-Beam CT (CBCT) for small pulmonary nodules that are difficult to locate during video-assisted thoracic surgery (VATS) sublobectomy. Eligible patients will undergo RAB localization immediately followed by VATS in the same operative session. The primary endpoints include the success rate of localization, effective localization, and VATS sublobar resection. Secondary endpoints include navigation success rate, operation times, reaching depth, complication rates, and health economic outcomes. The learning curve will be analyzed using the cumulative sum (CUSUM) method. A total of 50 patients will be enrolled and followed up for 14 days postoperatively.