High‐resolution model‐based material decomposition in dual‐layer flat‐panel CBCT. Issue 10 (17th July 2021)

• Record Type: Journal Article
• Authors: Wang, Wenying; Ma, Yiqun; Tivnan, Matthew; Li, Junyuan; Gang, Grace J.; Zbijewski, Wojciech; Lu, Minghui; Zhang, Jin; Star‐Lack, Josh; Colbeth, Richard E.; Stayman, J. Webster
• Is Part Of: Medical physics. Volume 48:Issue 10(2021)
• Page Start: 6375
• Page End: 6387
• Publication Date: 2021-07-17
• Subjects: dual‐layer detector -- material decomposition -- model‐based iterative reconstruction -- spectral CT; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.14894
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Spectral CT uses energy‐dependent measurements that enable material discrimination in addition to reconstruction of structural information. Flat‐panel detectors (FPDs) have been widely used in dedicated and interventional systems to deliver high spatial resolution, volumetric cone‐beam CT (CBCT) in compact and OR‐friendly designs. In this work, we derive a model‐based method that facilitates high‐resolution material decomposition in a spectral CBCT system equipped with a prototype dual‐layer FPD. Through high‐fidelity modeling of multilayer detector, we seek to avoid resolution loss that is present in more traditional processing and decomposition approaches. Method: A physical model for spectral measurements in dual‐layer flat‐panel CBCT is developed including layer‐dependent differences in system geometry, spectral sensitivities, and detector blur (e.g., due to varied scintillator thicknesses). This forward model is integrated into a model‐based material decomposition (MBMD) method based on minimization of a penalized weighted least‐squared (PWLS) objective function. The noise and resolution performance of this approach was compared with traditional projection‐domain decomposition (PDD) and image‐domain decomposition (IDD) approaches as well as one‐step MBMD with lower‐fidelity models that use approximated geometry, projection interpolation, or an idealized system geometry without system blur model. Physical studies using high‐resolution three‐dimensional (3D)‐printed water‐iodine phantoms were conducted to demonstrate the high‐resolution imaging performance of the compared decomposition methods in iodine basis images and synthetic monoenergetic images. Results: Physical experiments demonstrate that the MBMD methods incorporating an accurate geometry model can yield higher spatial resolution iodine basis images and synthetic monoenergetic images than PDD and IDD results at the same noise level. MBMD with blur modeling can further improve the spatial‐resolution compared with the decomposition results obtained with IDD, PDD, and MBMD methods with lower‐fidelity models. Using the MBMD without or with blur model can increase the absolute modulation at 1.75 lp/mm by 10% and 22% compared with IDD at the same noise level. Conclusion: The proposed model‐based material decomposition method for a dual‐layer flat‐panel CBCT system has demonstrated an ability to extend high‐resolution performance through sophisticated detector modeling including the layer‐dependent blur. The proposed work has the potential to not only facilitate high‐resolution spectral CT in interventional and dedicated CBCT systems, but may also provide the opportunity to evaluate different flat‐panel design trade‐offs including multilayer FPDs with mismatched geometries, scintillator thicknesses, and spectral sensitivities.