Technology in Cancer Research & Treatment (Apr 2023)
Could Maximum SUV be Used as Imaging Guidance in Large Lung Lesions Biopsies? Double Sampling Under PET-CT/XperGuide Fusion Imaging in Inhomogeneous Lung Uptaking Lesions to Show That it can Make a Difference
Abstract
Introduction: The purpose of this study is to evaluate the diagnostic value of positron emission computed tomography-cone beam computed tomography (PET/CT-CBCT) fusion guided percutaneous biopsy, targeted to the maximum standardized uptake value (SUVmax) and minimum standardized uptake value (SUVmin) of large lung lesions. Materials and Methods: Inside a larger cohort of PET/CT-CBCT guided percutaneous lung biopsies, 10 patients with large pulmonary lesions (diameter > 30 mm) were selected retrospectively. These patients have been subjected to double biopsy sampling respectively in the SUVmax area and in the SUVmin area of the lesion. Technical success has been calculated. For each sample, the percentage of neoplastic, inflammatory, and fibrotic cells was reported. Furthermore, the possibility of performing immunohistochemical or molecular biology investigations to specifically define the biomolecular tumor profile was analyzed. Results: Nine lesions were found to be malignant, one benign (inflammation). Technical success was 100% (10/10) in the SUVmax samples and 70% (7/10) in the SUVmin samples ( P-value: .21 ). In the first group, higher percentages of neoplastic cells were found at pathologic evaluation, while in the second group areas of inflammation and fibrosis were more represented. The biomolecular profile was obtained in 100% of cases (9/9) of the first group, while in the second group only in 33.3% of cases (2/6), with a statistically significant difference between the 2 groups ( P-value: .011 ). Conclusion: A correlation between the standardized uptake value value and the technical success of the biopsy sample has been identified. PET/CT-CBCT guidance allows to target the biopsy in the areas of the tumor which are richer in neoplastic cells, thus obtaining more useful information for the planning of patient-tailored cancer treatments.