Frederick M Lartey1, Marjan Rafat1, Mohammadreza Negahdar1, Andrey V Malkovskiy2, Xinzhe Dong3, Xiaoli Sun4, Mei Li5, Timothy Doyle6, Jayakumar Rajadas2, Edward E Graves7, Billy W Loo8, Peter G Maxim9. 1. Department of Radiation Oncology, Stanford University School of Medicine, United States. 2. Biomaterials and Advanced Drug Delivery Laboratory, Cardiovascular Pharmacology Division, Cardiovascular Institute, Stanford University School of Medicine, United States. 3. Department of Radiation Oncology, Stanford University School of Medicine, United States; Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, China. 4. Department of Radiation Oncology, Stanford University School of Medicine, United States; Department of Radiation Oncology, The First Affiliated Hospital of Zhejiang University, China. 5. Department of Radiation Oncology, Stanford University School of Medicine, United States; Department of Radiation Oncology, Cancer Hospital, China. 6. Department of Pediatrics, Stanford University School of Medicine, United States. 7. Department of Radiation Oncology, Stanford University School of Medicine, United States; Stanford Cancer Institute, Stanford University School of Medicine, United States. 8. Department of Radiation Oncology, Stanford University School of Medicine, United States; Stanford Cancer Institute, Stanford University School of Medicine, United States. Electronic address: bwloo@stanford.edu. 9. Department of Radiation Oncology, Stanford University School of Medicine, United States; Stanford Cancer Institute, Stanford University School of Medicine, United States. Electronic address: pmaxim@stanford.edu.
Abstract
BACKGROUND AND PURPOSE: A major challenge in CT screening for lung cancer is limited specificity when distinguishing between malignant and non-malignant pulmonary nodules (PN). Malignant nodules have different mechanical properties and tissue characteristics ('stiffness') from non-malignant nodules. This study seeks to improve CT specificity by demonstrating in rats that measurements of volumetric ratios in PNs with varying composition can be determined by respiratory-gated dynamic CT imaging and that these ratios correlate with direct physical measurements of PN stiffness. METHODS AND MATERIALS: Respiratory-gated MicroCT images acquired at extreme tidal volumes of 9 rats with PNs from talc, matrigel and A549 human lung carcinoma were analyzed and their volumetric ratios (δ) derived. PN stiffness was determined by measuring the Young's modulus using atomic force microscopy (AFM) for each nodule excised immediately after MicroCT imaging. RESULTS: There was significant correlation (p=0.0002) between PN volumetric ratios determined by respiratory-gated CT imaging and the physical stiffness of the PNs determined from AFM measurements. CONCLUSION: We demonstrated proof of concept that PN volume changes measured non-invasively correlate with direct physical measurements of stiffness. These results may translate clinically into a means of improving the specificity of CT screening for lung cancer and/or improving individual prognostic assessments based on lung tumor stiffness.
BACKGROUND AND PURPOSE: A major challenge in CT screening for lung cancer is limited specificity when distinguishing between malignant and non-malignant pulmonary nodules (PN). Malignant nodules have different mechanical properties and tissue characteristics ('stiffness') from non-malignant nodules. This study seeks to improve CT specificity by demonstrating in rats that measurements of volumetric ratios in PNs with varying composition can be determined by respiratory-gated dynamic CT imaging and that these ratios correlate with direct physical measurements of PN stiffness. METHODS AND MATERIALS: Respiratory-gated MicroCT images acquired at extreme tidal volumes of 9 rats with PNs from talc, matrigel and A549 human lung carcinoma were analyzed and their volumetric ratios (δ) derived. PN stiffness was determined by measuring the Young's modulus using atomic force microscopy (AFM) for each nodule excised immediately after MicroCT imaging. RESULTS: There was significant correlation (p=0.0002) between PN volumetric ratios determined by respiratory-gated CT imaging and the physical stiffness of the PNs determined from AFM measurements. CONCLUSION: We demonstrated proof of concept that PN volume changes measured non-invasively correlate with direct physical measurements of stiffness. These results may translate clinically into a means of improving the specificity of CT screening for lung cancer and/or improving individual prognostic assessments based on lung tumor stiffness.
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