Ergun E Ahunbay1, Ranjeeta Thapa2, Xinfeng Chen2, Eric Paulson2, X Allen Li2. 1. Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin. Electronic address: eahunbay@mcw.edu. 2. Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin.
Abstract
PURPOSE: To develop an automatic, accurate, atlas-based technique for synthetic computed tomography (sCT) generation to be used for online adaptive replanning during magnetic resonance imaging (MRI)-guided radiation therapy (RT). METHODS AND MATERIALS: The proposed method uses deformable image registration (DIR) of daily MRI and reference computed tomography (CT) with additional corrections to maintain bone rigidity and to transfer random air regions by thresholding. The DIR is performed with constraints on the bony structures using a special algorithm of ADMIRE (Elekta). The air regions are delineated from low-signal regions on the daily MRI and forced to air density. The bone regions in the MRI (already determined from the CT) are separated from the air regions because both bone and air have low signal density in MRI. All these steps are automated. The generated sCT is compared with reference CT and the alternative voxel-based CT (bCT) for 4 extracranial sites (head and neck, thorax, abdomen, pelvis) in terms of mean absolute error (MAE), gamma analysis of 3-dimensional doses, and dose volume histogram parameters. RESULTS: Both MAE and dosimetric analysis results were favorable for the proposed sCT generation method. The average MAE for the sCT/bCT were 25.5/66.7, 25.9/65.3, 24.8/44.2 and 16.6/47.7 for head and neck, thorax, abdomen, and pelvis, respectively, and the gamma analysis (1.5%, 2 mm) yielded 98.7/97.1, 99.1/93.9, 99.5/99.4, 99.7/99.4, respectively, for those sites. CONCLUSIONS: The proposed method generates equal or more accurate sCT than those from the bulk density assignment, without the need for multiple MRI sequences. This method can be fully automated and applicable for online adaptive replanning.
PURPOSE: To develop an automatic, accurate, atlas-based technique for synthetic computed tomography (sCT) generation to be used for online adaptive replanning during magnetic resonance imaging (MRI)-guided radiation therapy (RT). METHODS AND MATERIALS: The proposed method uses deformable image registration (DIR) of daily MRI and reference computed tomography (CT) with additional corrections to maintain bone rigidity and to transfer random air regions by thresholding. The DIR is performed with constraints on the bony structures using a special algorithm of ADMIRE (Elekta). The air regions are delineated from low-signal regions on the daily MRI and forced to air density. The bone regions in the MRI (already determined from the CT) are separated from the air regions because both bone and air have low signal density in MRI. All these steps are automated. The generated sCT is compared with reference CT and the alternative voxel-based CT (bCT) for 4 extracranial sites (head and neck, thorax, abdomen, pelvis) in terms of mean absolute error (MAE), gamma analysis of 3-dimensional doses, and dose volume histogram parameters. RESULTS: Both MAE and dosimetric analysis results were favorable for the proposed sCT generation method. The average MAE for the sCT/bCT were 25.5/66.7, 25.9/65.3, 24.8/44.2 and 16.6/47.7 for head and neck, thorax, abdomen, and pelvis, respectively, and the gamma analysis (1.5%, 2 mm) yielded 98.7/97.1, 99.1/93.9, 99.5/99.4, 99.7/99.4, respectively, for those sites. CONCLUSIONS: The proposed method generates equal or more accurate sCT than those from the bulk density assignment, without the need for multiple MRI sequences. This method can be fully automated and applicable for online adaptive replanning.
Authors: Maureen L Groot Koerkamp; Jeanine E Vasmel; Nicola S Russell; Simona F Shaitelman; Carmel N Anandadas; Adam Currey; Danny Vesprini; Brian M Keller; Chiara De-Colle; Kathy Han; Lior Z Braunstein; Faisal Mahmood; Ebbe L Lorenzen; Marielle E P Philippens; Helena M Verkooijen; Jan J W Lagendijk; Antonetta C Houweling; H J G Desiree van den Bongard; Anna M Kirby Journal: Front Oncol Date: 2020-07-28 Impact factor: 6.244