CBCT-based synthetic MRI generation for target localization during deep inspiration breath hold (DIBH) abdominal radiotherapy.
Authors
Affiliations (5)
Affiliations (5)
- Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, New York, 10065, United States.
- Medical Physics, Memorial Sloan Kettering Cancer Center, 321 East 61st Street, New York, New York, 10065, United States.
- Medical Physics, Memorial Sloan Kettering Cancer Center, 321 E 61st St, New York, 10065-6007, United States.
- Medical Physics, Memorial Sloan-Kettering Cancer Center, 321 E 61st St, New York, New York, 10065, United States.
- Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, New York, 10065-6007, United States.
Abstract
This study aims to generate synthetic-MRI(synMRI) for abdominal patients undergoing radiotherapy using Deep Inspiration Breath Hold(DIBH) on a conventional Linac.
Methods: XCAT phantom and patient data were used to develop and test a patient-specific model to generate synMRI. During patient simulation, 6 DIBH-MRIs and 1 DIBH-CT were acquired. One DIBH-MRI was set as the reference MRI(refMRI) and Principal Component Analysis(PCA) was performed using five Deformation Field Maps(DFMs) by applying deformable image registration between refMRI and the other DIBH-MRIs. PCA eigenvalues were sampled 1,000 times to generate new deformations applied to a synthetic-CT with the same anatomic conditions as refMRI. A convolutional neural network was trained to predict the eigenvalues corresponding to on-board conditions from a CBCT to generate a final synMRI with the new DFM. Four XCAT scenarios simulated changes from simulation to treatment. The model was evaluated using mean-absolute-error(MAE) and root-mean-square-error(RMSE), and the image quality was evaluated by structure-similarity-index metric(SSIM) and normalized RMSE(nRMSE). The accuracy of the predicted target volume for XCAT and fiducial clips for each patient was analyzed using center-of-mass-shift(COMS) between on-board conditions (ground-truth synMRI for XCAT and CBCT for patients) and the predicted synMRI. The liver dome difference was also evaluated.
Results: Model performance yielded an MAE of 0.11±0.02 for XCAT, and 0.15±0.01, 0.15±0.02, 0.10±0.03, 0.12±0.09 for four patients, respectively. RMSE values were 0.11±0.07, 0.16±0.03, 0.19±0.01, 0.13±0.07, and 0.14±0.04. For image quality, SSIM values were 0.999±0.001 for XCAT, and 0.998±0.001, 0.995±0.002, 0.996±0.001, 0.998±0.001 for the patients. The nRMSE were 0.10±0.06, 0.58±0.03, 0.87±0.06, 0.39±0.04, and 0.35±0.02, respectively. For XCAT, the liver dome difference and tumor COMS were <0.5 mm in all scenarios. For all patients, liver dome differences were <1 mm, and fiducial COMSs were <1.2 mm.
Conclusions: The novel method generates synMRI using on-board conditions in DIBH abdominal treatments performed on a conventional LINAC.
.