Evaluating the accuracy of 4D‐CT ventilation imaging: First comparison with Technegas SPECT ventilation. Issue 8 (16th June 2017)

• Record Type: Journal Article
• Authors: Hegi‐Johnson, Fiona; Keall, Paul; Barber, Jeff; Bui, Chuong; Kipritidis, John
• Is Part Of: Medical physics. Volume 44:Issue 8(2017)
• Page Start: 4045
• Page End: 4055
• Publication Date: 2017-06-16
• Subjects: 4DCT -- CT ventilation imaging -- deformable image registration -- functional lung imaging -- lung cancer; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.12317
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Computed tomography ventilation imaging (CTVI) is a highly accessible functional lung imaging modality that can unlock the potential for functional avoidance in lung cancer radiation therapy. Previous attempts to validate CTVI against clinical ventilation single‐photon emission computed tomography (V‐SPECT) have been hindered by radioaerosol clumping artifacts. This work builds on those studies by performing the first comparison of CTVI with 99m Tc‐carbon ('Technegas'), a clinical V‐SPECT modality featuring smaller radioaerosol particles with less clumping. Methods: Eleven lung cancer radiotherapy patients with early stage (T1/T2N0) disease received treatment planning four‐dimensional CT (4DCT) scans paired with Technegas V/Q‐SPECT/CT. For each patient, we applied three different CTVI methods. Two of these used deformable image registration (DIR) to quantify breathing‐induced lung density changes (CTVIDIR‐HU ), or breathing‐induced lung volume changes (CTVIDIR‐Jac ) between the 4DCT exhale/inhale phases. A third method calculated the regional product of air‐tissue densities (CTVIHU ) and did not involve DIR. Corresponding CTVI and V‐SPECT scans were compared using the Dice similarity coefficient (DSC) for functional defect and nondefect regions, as well as the Spearman's correlation r computed over the whole lung. The DIR target registration error (TRE) was quantified using both manual and computer‐selected anatomic landmarks. Results: Interestingly, the overall best performing method (CTVIHU ) did not involve DIR. For nondefect regions, the CTVIHU, CTVIDIR‐HU, and CTVIDIR‐Jac methods achieved mean DSC values of 0.69, 0.68, and 0.54, respectively. For defect regions, the respective DSC values were moderate: 0.39, 0.33, and 0.44. The Spearman r ‐values were generally weak: 0.26 for CTVIHU, 0.18 for CTVIDIR‐HU, and −0.02 for CTVIDIR‐Jac . The spatial accuracy of CTVI was not significantly correlated with TRE, however the DIR accuracy itself was poor with TRE > 3.6 mm on average, potentially indicative of poor quality 4DCT. Q‐SPECT scans achieved good correlations with V‐SPECT (mean r > 0.6), suggesting that the image quality of Technegas V‐SPECT was not a limiting factor in this study. Conclusions: We performed a validation of CTVI using clinically available 4DCT and Technegas V/Q‐SPECT for 11 lung cancer patients. The results reinforce earlier findings that the spatial accuracy of CTVI exhibits significant interpatient and intermethod variability. We propose that the most likely factor affecting CTVI accuracy was poor image quality of clinical 4DCT.