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Background: The conventional lying down position for radiation therapy can be challenging for patients due to pain, swallowing or breathing issues. To provide an alternative upright treatment position for these patients, we have developed a portable rotating radiation therapy platform which integrates with conventional photon treatment machines. The device enables cone-beam computed tomography (CBCT) imaging of patients in an upright position, and the future delivery of therapeutic radiation., Purpose: To design, manufacture, and test a device for upright radiation therapy. A collaborative partnership between physicists, engineers, radiation therapists, radiation oncologists, implementation researchers and consumers was established, to create a device that meets both the clinical and technical requirements of upright radiation therapy. The device is central to a clinical trial (ACTRN12623000498695) which will evaluate upright image quality in the context of future image guided radiation therapy for patients with lung cancer or head and neck cancer., Methods: The weight and physical constraints of the device were assessed with respect to the American civilian population. The final design was evaluated with a series of tests to characterize the angular accuracy of the platform rotation and the reproducibility of the platform setup position in a radiation treatment room. To acquire an upright CBCT, the platform movement system was synchronized to the kilo-voltage fluoroscopic imaging on an existing treatment machine. The accuracy of the synchronization was evaluated by assessing the positional reproducibility of upright CBCT imaging of a chest phantom., Results: The platform has a weight limit of up to 125 kg which is suitable for approximately 90% of males and 95% of females. The platform has physical constraints that accommodate approximately 95.6% of males and 99.6% of females: a maximum seated height of 97.5 cm, a maximum hip breadth of 63.0 cm, and maximum elbow to knuckle length of 46.5 cm. The angular accuracy of the motion system is within ±0.15° over a full rotation, which is within the guidelines for machine movement accuracy in radiation therapy (1 mm/1°). The platform is a portable device and can be reproducibly positioned in a radiation therapy treatment room with a translational range within ±0.04 mm and a rotational range within ±0.025°. The CBCT imaging can reproducibly detect the position of a chest phantom with a translational uncertainty of ±0.07 mm and a rotational uncertainly of ±0.22°, when imaging is acquired following a strict procedure., Conclusion: The upright radiation therapy platform is suitable for the evaluation of CBCT imaging in the context of image guided radiation therapy. The platform will allow the investigation of open questions in upright radiation therapy in the areas of patient experience, positional stability, anatomical changes, and treatment delivery. Improvements to the materials in the radiation beam line, synchronization with the existing treatment machine, and increasing the device weight limit are suggested prior to delivery of future upright treatments., (© 2024 The Author(s). Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Purpose: CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities., Methods: The VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA-SPECT, and 4 sheep imaged with Xenon-CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B-splines, Free-form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel-wise Spearman coefficient r S , and Dice similarity coefficients evaluated for low function lung ( DSC low ) and high function lung ( DSC high )., Results: A total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant-submitted DIR motion fields using the in-house software, VESPIR. The r S and DSC results reveal a high degree of inter-algorithm and intersubject variability among the validation subjects, with algorithm rankings changing by up to ten positions depending on the choice of evaluation metric. The algorithm with the highest overall cross-modality correlations used a biomechanical model-based DIR with a hybrid ventilation metric, achieving a median (range) of 0.49 (0.27-0.73) for r S , 0.52 (0.36-0.67) for DSC low , and 0.45 (0.28-0.62) for DSC high . All other algorithms exhibited at least one negative r S value, and/or one DSC value less than 0.5., Conclusions: The VAMPIRE Challenge results demonstrate that the cross-modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a "gold standard," highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic centers to the clinic. It is hoped that the information gleaned from the VAMPIRE Challenge can help inform future validation efforts., (© 2018 American Association of Physicists in Medicine.)

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 (CTVI DIR-HU ), or breathing-induced lung volume changes (CTVI DIR-Jac ) between the 4DCT exhale/inhale phases. A third method calculated the regional product of air-tissue densities (CTVI HU ) 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 (CTVI HU ) did not involve DIR. For nondefect regions, the CTVI HU , CTVI DIR-HU , and CTVI DIR-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 CTVI HU , 0.18 for CTVI DIR-HU , and -0.02 for CTVI DIR-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., (© 2017 American Association of Physicists in Medicine.)

Purpose: Computed tomography ventilation imaging derived from four-dimensional cone beam CT (CTVI 4DCBCT ) can complement existing 4DCT-based methods (CTVI 4 DCT ) to track lung function changes over a course of lung cancer radiation therapy. However, the accuracy of CTVI 4 DCBCT needs to be assessed since anatomic 4DCBCT has demonstrably poor image quality and small field of view (FOV) compared to treatment planning 4DCT. We perform a direct comparison between short interval CTVI 4 DCBCT and CTVI 4 DCT pairs to understand the patient specific image quality factors affecting the intermodality CTVI reproducibility in the clinic., Methods and Materials: We analysed 51 pairs of 4DCBCT and 4DCT scans acquired within 1 day of each other for nine lung cancer patients. To assess the impact of image quality, CTVIs were derived from 4DCBCT scans reconstructed using both standard Feldkamp-Davis-Kress backprojection (CTVIFDK4DCBCT) and an iterative McKinnon-Bates Simultaneous Algebraic Reconstruction Technique (CTVIMKBSART4DCBCT). Also, the influence of FOV was assessed by deriving CTVIs from 4DCT scans that were cropped to a similar FOV as the 4DCBCT scans (CTVIcrop4DCT), or uncropped (CTVIuncrop4DCT). All CTVIs were derived by performing deformable image registration (DIR) between the exhale and inhale phases and evaluating the Jacobian determinant of deformation. Reproducibility between corresponding CTVI 4 DCBCT and CTVI 4 DCT pairs was quantified using the voxel-wise Spearman rank correlation and the Dice similarity coefficient (DSC) for ventilation defect regions (identified as the lower quartile of ventilation values). Mann-Whitney U-tests were applied to determine statistical significance of each reconstruction and cropping condition., Results: The (mean ± SD) Spearman correlation between CTVIFDK4DCBCT and CTVIuncrop4DCT was 0.60 ± 0.23 (range -0.03-0.88) and the DSC was 0.64 ± 0.12 (0.34-0.83). By comparison, correlations between CTVIMKBSART4DCBCT and CTVIuncrop4DCT showed a small but statistically significant improvement with = 0.64 ± 0.20 (range 0.06-0.90, P = 0.03) and DSC = 0.66 ± 0.13 (0.31-0.87, P = 0.02). Intermodal correlations were noted to decrease with an increasing fraction of lung truncation in 4DCBCT relative to 4DCT, albeit not significantly (Pearson correlation R = 0.58, P = 0.002)., Conclusions: This study demonstrates that DIR based CTVIs derived from 4DCBCT can exhibit reasonable to good voxel-level agreement with CTVIs derived from 4DCT. These correlations outperform previous cross-modality comparisons between 4DCT-based ventilation and nuclear medicine. The use of 4DCBCT scans with iterative reconstruction and minimal lung truncation is recommended to ensure better reproducibility between 4DCBCT- and 4DCT-based CTVIs., (© 2017 American Association of Physicists in Medicine.)