A kV-MV approach to CBCT metal artifact reduction using multi-layer MV-CBCT.
Matthew W JacobsonThomas C HarrisMarios MyronakisMathias LehmannPascal HuberIkechi OzoemelamYue-Houng HuDianne FergusonRony FueglistallerDaniel MorfRoss BerbecoPublished in: Physics in medicine and biology (2024)
Objective . To demonstrate that complete cone beam CT (CBCT) scans from both MV-energy and kV-energy LINAC sources can reduce metal artifacts in radiotherapy guidance, while maintaining standard-of-care x-ray doses levels. Approach . MV-CBCT and kV-CBCT scans are acquired at half normal dose. The impact of lowered dose on MV-CBCT data quality is mitigated by the use of a 4-layer MV-imager prototype and reduced LINAC energy settings (2.5 MV) to improve photon capture. Additionally, the MV-CBCT is used to determine the 3D position and pose of metal implants, which in turn is used to guide model-based poly-energetic correction and interleaving of the kV-CBCT and MV-CBCT data. Certain edge-preserving regularization steps incorporated into the model-based correction algorithm further reduce MV data noise. Main results . The method was tested in digital phantoms and a real pelvis phantom with large 2.5″ spherical inserts, emulating hip replacements of different materials. The proposed method demonstrated an appealing compromise between the high contrast of kV-CBCT and low artifact content of MV-CBCT. Contrast-to-noise improved 3-fold compared to MV-CBCT with a clinical 1-layer architecture at matched dose (37 mGy) and edge blur levels. Visual delineation of the bladder and prostate improved noteably over kV- or MV-CBCT alone. Significance . The proposed method demonstrates that a full MV-CBCT scan can be combined with kV-CBCT to reduce metal artifacts without resorting to complicated beam collimation strategies to limit the MV-CBCT dose contribution. Additionally, significant improvements in CNR can be achieved as compared to metal artifact reduction through current clinical MV-CBCT practices.
Keyphrases
- image quality
- dual energy
- computed tomography
- cone beam computed tomography
- healthcare
- contrast enhanced
- early stage
- magnetic resonance imaging
- prostate cancer
- electronic health record
- machine learning
- primary care
- palliative care
- radiation therapy
- air pollution
- pain management
- high resolution
- neural network
- pet ct
- data analysis
- fluorescent probe
- sensitive detection