New artificial intelligence system for accurate detection of lung nodules
Lung cancer is one of the most difficult malignancies to manage worldwide, as it is the first and leading cause of death from malignancy in Europe.
If cancer is diagnosed based on the symptoms it causes in the patient, it is usually in advanced stages, which makes its treatment extremely ineffective.
Lung cancer screening is performed on people without symptoms, with specific characteristics, such as age and smoking, and can diagnose the malignancy at a very early stage, so treatment will have clearly better results.
The main examination is low-dose CT scanning, which detects early damage to the lung. The most common form in which these early lesions appear is nodules. However, not all nodules are malignant. In order to draw up a treatment plan, the findings must be identified histologically, that is, a biopsy must be taken. Bronchoscopy is the examination used to obtain the biopsy material.
Most of these nodules are difficult to locate, as they are small and usually located in the periphery.
In order to take the biopsy, therefore, a path needs to be carved into the bronchi, which will guide the bronchoscope to the correct location. For this reason, the Medical Group purchased an artificial intelligence system (AI Synapse Fujifilm), which provides information on where the nodule is located and how we can reach that point with the bronchoscope.
The localization of the nodule is completed with other systems, such as remote endobronchial ultrasound, as well as the marking of the lesion on fluoroscopy with the latest technology Cone Beam CT, in the special high-tech area of the hybrid surgery. In this way, biopsies are taken from even very small nodules safely, while this small lesion can be marked with special material, so that it is clear to the surgeon.
Thus, the control of the nodules found during the low-dose CT scan is completed and, if a cancerous lesion is identified, the patient is taken to the operating room for its removal.
The nodules can be removed in sections, with very little loss of lung tissue, robotically or thoracoscopically, with methods that allow for shorter recovery time and hospitalization, as well as fewer complications.
