(Thursday, 7/16/2020) 10:30 AM - 12:30 PM [Eastern Time (GMT-4)]
Room: Track 4
Purpose: Clinical trials are underway to use 4DCT data to calculate ventilation (4DCT-ventilation) and to use 4DCT-ventilation data to generate functional avoidance radiotherapy plans for lung cancer patients. With current 4DCT-ventilation formulations, only ventilation information is generated. A complete picture of lung function includes ventilation (airflow) and perfusion (blood flow). Current 4DCT-ventilation work assumes that patients have spatially similar ventilation and perfusion profiles; however, no studies have been done that quantitatively characterize potential spatial differences between ventilation and perfusion in lung cancer patients. The purpose of this study was to use nuclear medicine SPECT-CT imaging to evaluate the spatial agreement between ventilation and perfusion for lung cancer imaging.
Methods: SPECT-CT ventilation and perfusion images of 10 lung cancer patients acquired on a prospective protocol (IRB 14-1586) were used for the study. Ventilation/perfusion images were converted to percentile images and quantitatively compared using MIM-extensions. The ventilation to perfusion spatial comparisons were done using voxel-based Spearman correlation coefficients and Dice similarity coefficients (DSC) using 4 functional zones (0-25, 25-50, 50-75, 75-100 percentiles). Results are reported as mean ± standard deviation (range).
Results: The average correlation comparing SPECT-ventilation to SPECT-perfusion was 0.70±0.12 (0.42-0.80). The DSC for the four functional regions were 0.70±0.11 (0.43-0.82), 0.39±0.08 (0.23-0.49), 0.36±0.06 (0.24-0.47), and 0.56±0.06 (0.44-0.64) for the low, middle-low, middle-high, and high functional zones respectively.
Conclusion: Our data suggest that ventilation and perfusion agreement can vary for different lung regions and among different patients; thus indicating that perfusion images can provide unique information (when compared to ventilation) in the context of functional avoidance radiotherapy. Data will be presented for a larger, 50 patient prospective cohort using quantitative spatial assessments and radiologist evaluations. The current study will provide quantitative and clinical data that can inform the proper clinical integration of functional avoidance thoracic radiotherapy.
Funding Support, Disclosures, and Conflict of Interest: NIH: Grant number = R01CA236857
Keywords
Taxonomy
IM/TH- Image Analysis (Single Modality or Multi-Modality): Quantitative imaging
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