Dual-energy CT multiparametric analysis improves diagnostic accuracy and reduces complications in percutaneous...

Lung cancer is a leading cause of cancer death worldwide. To plan treatment, doctors need an accurate tissue diagnosis. Percutaneous transthoracic needle biopsy (PTNB) is one of the main ways to obtain tissue samples, but the procedure often causes problems such as pneumothorax and bleeding in the lungs. Conventional contrast-enhanced computed tomography (CECT) is commonly used before biopsy to visualize the lesion's morphology and location, but it does not reliably delineate small vessels or internal tumor heterogeneity. Dual-energy computed tomography (DECT) can provide more information by using two energy levels to create virtual monochromatic images and iodine maps. These data facilitate the selection of a safer and more accurate biopsy path by more clearly revealing blood supply and tissue composition. This study aimed to evaluate whether DECT multiparametric analysis can improve diagnostic accuracy and reduce procedure-related complications compared with CECT in PTNB.

A retrospective analysis was conducted on 165 patients who underwent PTNB. The patients were divided into two groups: Group A (n=98) underwent CECT, while Group B (n=67) received DECT with advanced material decomposition analysis. Comprehensive quantitative parameters, including virtual monochromatic imaging and iodine concentration maps, were utilized in Group B to guide individualized biopsy trajectory planning and risk assessment.

In Group A, positive pathological results were obtained in 80 cases (81.6%), with pneumothorax and pulmonary hemorrhage occurring in 33 (33.7%) and 24 (24.5%) cases, respectively. In Group B, 62 cases (92.5%) yielded a positive pathological result, while 13 patients (19.4%) developed pneumothorax and 7 (10.4%) experienced pulmonary hemorrhage. The differences in diagnostic yield and complication rates between the two groups were statistically significant (P<0.05).

DECT-guided multiparametric quantitative analysis significantly improves the accuracy of PTNB and reduces procedure-related complications, demonstrating its clinical value in thoracic interventional imaging.