Abbreviated on-treatment CBCT using roughness penalized mono-energization of kV-MV data and a multi-layer MV imager.
Matthew W JacobsonMathias LehmannPascal HuberAdam WangMarios MyronakisMengying ShiDianne FergusonI Valencia LozanoYue-Houng HuPaul BaturinTom HarrisRony FueglistallerChristopher WilliamsDaniel MorfRoss BerbecoPublished in: Physics in medicine and biology (2021)
Simultaneous acquisition of cone beam CT (CBCT) projections using both the kV and MV imagers of an image guided radiotherapy system reduces set-up scan times-a benefit to lung cancer radiation oncology patients-but increases noise in the 3D reconstruction. In this article, we present a kV-MV scan time reduction technique that uses two noise-reducing measures to achieve superior performance. The first is a high-DQE multi-layer MV imager prototype. The second is a beam hardening correction algorithm which combines poly-energetic modeling with edge-preserving, regularized smoothing of the projections. Performance was tested in real acquisitions of the Catphan 604 and a thorax phantom. Percent noise was quantified from voxel values in a soft tissue volume of interest (VOI) while edge blur was quantified from a VOI straddling a boundary between air and soft material. Comparisons in noise/resolution performance trade-off were made between our proposed approach, a dose-equivalent kV-only scan, and a kV-MV reconstruction technique previously published by Yinet al(2005Med. Phys.329). The proposed technique demonstrated lower noise as a function of spatial resolution than the baseline kV-MV method, notably a 50% noise reduction at typical edge blur levels. Our proposed method also exhibited fainter non-uniformity artifacts and in some cases superior contrast. Overall, we find that the combination of a multi-layer MV imager, acquiring at a LINAC source energy of 2.5 MV, and a denoised beam hardening correction algorithm enables noise, resolution, and dose performance comparable to standard kV-imager only set-up CBCT, but with nearly half the gantry rotation time.
Keyphrases
- image quality
- computed tomography
- dual energy
- air pollution
- positron emission tomography
- contrast enhanced
- magnetic resonance imaging
- magnetic resonance
- soft tissue
- end stage renal disease
- early stage
- newly diagnosed
- machine learning
- squamous cell carcinoma
- prognostic factors
- cone beam
- randomized controlled trial
- patient reported outcomes
- monte carlo