Dataset Information

Low-Dose Image-Guided Pediatric CNS Radiation Therapy: Final Analysis From a Prospective Low-Dose Cone-Beam CT Protocol From a Multinational Pediatrics Consortium.

ABSTRACT: BACKGROUND:Lower-dose cone-beam computed tomography protocols for image-guided radiotherapy may permit target localization while minimizing radiation exposure. We prospectively evaluated a lower-dose cone-beam protocol for central nervous system image-guided radiotherapy across a multinational pediatrics consortium. METHODS:Seven institutions prospectively employed a lower-dose cone-beam computed tomography central nervous system protocol (weighted average dose 0.7 mGy) for patients ?21 years. Treatment table shifts between setup with surface lasers versus cone-beam computed tomography were used to approximate setup accuracy, and vector magnitudes for these shifts were calculated. Setup group mean, interpatient, interinstitution, and random error were estimated, and clinical factors were compared by mixed linear modeling. RESULTS:Among 96 patients, with 2179 pretreatment cone-beam computed tomography acquisitions, median age was 9 years (1-20). Setup parameters were 3.13, 3.02, 1.64, and 1.48 mm for vector magnitude group mean, interpatient, interinstitution, and random error, respectively. On multivariable analysis, there were no significant differences in mean vector magnitude by age, gender, performance status, target location, extent of resection, chemotherapy, or steroid or anesthesia use. Providers rated >99% of images as adequate or better for target localization. CONCLUSIONS:A lower-dose cone-beam computed tomography protocol demonstrated table shift vector magnitude that approximate clinical target volume/planning target volume expansions used in central nervous system radiotherapy. There were no significant clinical predictors of setup accuracy identified, supporting use of this lower-dose cone-beam computed tomography protocol across a diverse pediatric population with brain tumors.

SUBMITTER: Alcorn SR

PROVIDER: S-EPMC7225835 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature

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Low-Dose Image-Guided Pediatric CNS Radiation Therapy: Final Analysis From a Prospective Low-Dose Cone-Beam CT Protocol From a Multinational Pediatrics Consortium.

Alcorn Sara R SR Zhou Xian Chiong XC Bojechko Casey C Rubo Rodrigo A RA Chen Michael J MJ Dieckmann Karin K Ermoian Ralph P RP Ford Eric C EC Kobyzeva Daria D MacDonald Shannon M SM McNutt Todd R TR Nechesnyuk Alexey A Nilsson Kristina K Sjostrand Hakan H Smith Koren S KS Stock Markus M Tryggestad Erik J EJ Villar Rosangela C RC Winey Brian A BA Terezakis Stephanie A SA

Technology in cancer research & treatment 20200101

<h4>Background</h4>Lower-dose cone-beam computed tomography protocols for image-guided radiotherapy may permit target localization while minimizing radiation exposure. We prospectively evaluated a lower-dose cone-beam protocol for central nervous system image-guided radiotherapy across a multinational pediatrics consortium.<h4>Methods</h4>Seven institutions prospectively employed a lower-dose cone-beam computed tomography central nervous system protocol (weighted average dose 0.7 mGy) for patien ...[more]

PMID: 32329413

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Project description:BackgroundThe imaging dose of cone-beam computed tomography (CBCT) in image-guided radiotherapy (IGRT) poses adverse effects on patient health. To improve the quality of sparse-view low-dose CBCT images, a projection synthesis convolutional neural network (SynCNN) model is proposed.MethodsIncluded in this retrospective, single-center study were 223 patients diagnosed with brain tumours from Beijing Cancer Hospital. The proposed SynCNN model estimated two pairs of orthogonally direction-separable spatial kernels to synthesize the missing projection in between the input neighboring sparse-view projections via local convolution operations. The SynCNN model was trained on 150 real patients to learn patterns for inter-view projection synthesis. CBCT data from 30 real patients were used to validate the SynCNN, while data from a phantom and 43 real patients were used to test the SynCNN externally. Sparse-view projection datasets with 1/2, 1/4, and 1/8 of the original sampling rate were simulated, and the corresponding full-view projection datasets were restored using the SynCNN model. The tomographic images were then reconstructed with the Feldkamp-Davis-Kress algorithm. The root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) metrics were measured in both the projection and image domains. Five experts were invited to grade the image quality blindly for 40 randomly selected evaluation groups with a four-level rubric, where a score greater than or equal to 2 was considered acceptable image quality. The running time of the SynCNN model was recorded. The SynCNN model was directly compared with the three other methods on 1/4 sparse-view reconstructions.ResultsThe phantom and patient studies showed that the missing projections were accurately synthesized. In the image domain, for the phantom study, compared with images reconstructed from sparse-view projections, images with SynCNN synthesis exhibited significantly improved qualities with decreased values in RMSE and increased values in PSNR and SSIM. For the patient study, between the results with and without the SynCNN synthesis, the averaged RMSE decreased by 3.4×10-4, 10.3×10-4, and 21.7×10-4, the averaged PSNR increased by 3.4, 6.6, and 9.4 dB, and the averaged SSIM increased by 5.2×10-2, 18.9×10-2 and 33.9×10-2, for the 1/2, 1/4, and 1/8 sparse-view reconstructions, respectively. In expert subjective evaluation, both the median scores and acceptance rates of the images with SynCNN synthesis were higher than those reconstructed from sparse-view projections. It took the model less than 0.01 s to synthesize an inter-view projection. Compared with the three other methods, the SynCNN model obtained the best scores in terms of the three metrics in both domains.ConclusionsThe proposed SynCNN model effectively improves the quality of sparse-view CBCT images at a low time cost. With the SynCNN model, the CBCT imaging dose in IGRT could be reduced potentially.

Project description:X-ray scatter is a major detriment to image quality in cone-beam CT (CBCT). Existing geometries exhibit strong differences in scatter susceptibility with more compact geometries, e.g., dental or musculoskeletal, benefiting from antiscatter grids, whereas in more extended geometries, e.g., IGRT, grid use carries tradeoffs in image quality per unit dose. This work assesses the tradeoffs in dose and image quality for grids applied in the context of low-dose CBCT on a mobile C-arm for image-guided surgery.Studies were performed on a mobile C-arm equipped with a flat-panel detector for high-quality CBCT. Antiscatter grids of grid ratio (GR) 6:1-12:1, 40 lp∕cm, were tested in "body" surgery, i.e., spine, using protocols for bone and soft-tissue visibility in the thoracic and abdominal spine. Studies focused on grid orientation, CT number accuracy, image noise, and contrast-to-noise ratio (CNR) in quantitative phantoms at constant dose.There was no effect of grid orientation on possible gridline artifacts, given accurate angle-dependent gain calibration. Incorrect calibration was found to result in gridline shadows in the projection data that imparted high-frequency artifacts in 3D reconstructions. Increasing GR reduced errors in CT number from 31%, thorax, and 37%, abdomen, for gridless operation to 2% and 10%, respectively, with a 12:1 grid, while image noise increased by up to 70%. The CNR of high-contrast objects was largely unaffected by grids, but low-contrast soft-tissues suffered reduction in CNR, 2%-65%, across the investigated GR at constant dose.While grids improved CT number accuracy, soft-tissue CNR was reduced due to attenuation of primary radiation. CNR could be restored by increasing dose by factors of ~1.6-2.5 depending on GR, e.g., increase from 4.6 mGy for the thorax and 12.5 mGy for the abdomen without antiscatter grids to approximately 12 mGy and 30 mGy, respectively, with a high-GR grid. However, increasing the dose poses a significant impediment to repeat intraoperative CBCT and can cause the cumulative intraoperative dose to exceed that of a single diagnostic CT scan. This places the mobile C-arm in the category of extended CBCT geometries with sufficient air gap for which the tradeoffs between CNR and dose typically do not favor incorporation of an antiscatter grid.

Dataset Information

Low-Dose Image-Guided Pediatric CNS Radiation Therapy: Final Analysis From a Prospective Low-Dose Cone-Beam CT Protocol From a Multinational Pediatrics Consortium.

Publications

Low-Dose Image-Guided Pediatric CNS Radiation Therapy: Final Analysis From a Prospective Low-Dose Cone-Beam CT Protocol From a Multinational Pediatrics Consortium.

Similar Datasets

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