Investigators call for further research focusing on refining candidate selection for screening, improving the accuracy of LDCT scan reading, and integrating clinical risk models, imaging techniques, and biomarker research to enhance the probability evaluation of pulmonary nodule malignancy.
A team of investigators led by Wieland Voigt, Medical Innovation and Management, Steinbeis University Berlin, published a review that summarized the current limitations and advances in different aspects of lung cancer screening. Included in the review was candidate selection, technical aspects of screening, and probability evaluation of CT-detected pulmonary nodules (PN) management.
According to the article, lung cancer is the leading cause of cancer-related deaths worldwide, with the majority of cases diagnosed at advanced and incurable stages. Early detection of lung cancer is essential to improve the chances of successful treatment and survival rates.
A powerful tool mentioned by the investigators for early detection of lung cancer is low dose computed tomography (LDCT) screening. However, they acknowledged several factors that need to be considered to select the candidates who could benefit most from screening.
Selecting candidates to be screened for lung cancer is crucial to ensure that the benefits of screening outweigh the harms. Current eligibility criteria for screening include age, smoking history, and smoking cessation time.
These criteria have limitations because some individuals who do not meet the criteria could still be at high risk of developing lung cancer. Advanced clinical scores and biomarker assessments have the potential to refine candidate selection for screening by incorporating additional risk factors, such as family history and exposure to environmental toxins.
Investigators noted that the accuracy of LDCT scan reading is imperative for the success of lung cancer screening. As the workload of radiologists has increased with the adoption of LDCT screening, IT tools can help to improve scan reading accuracy.
Computer-aided detection (CAD) and computer-aided diagnosis were also acknowledged as (CADx) tools that provide assistance in identifying and characterizing lung nodules, reducing false positives and false negatives.
Following identification, the management of CT-detected pulmonary nodules is critical to the success of lung cancer screening. The probability of malignancy of pulmonary nodules needs to be precisely assessed in order to determine the appropriate approach going forward.
Semi-automatic volume measurements of CT-detected pulmonary nodules can improve the precision of follow-up scans, reducing the need for unnecessary invasive procedures. The article stated that integrating clinical risk models, current imaging techniques, and advancing biomarker research can improve the accuracy of probability evaluation of pulmonary nodule malignancy.
These diagnostic approaches require additional validation studies to confirm their effectiveness and safety. Investigators called for future research to focus on refining candidate selection for screening, improving the accuracy of LDCT scan reading, and integrating clinical risk models, imaging techniques, and biomarker research to enhance the probability evaluation of pulmonary nodule malignancy.
The integration of scientific and technological progress can improve the performance of lung cancer screening, ultimately leading to earlier detection and better outcomes for patients.