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ResNet-Based Marker-Free Prostate 6D Auto-Setup in the Cone-Beam CT Guided Radiation Therapy

X Liang1,2*, W Zhao1 , Y Xie2 , L Xing1 , (1) Stanford Univ School of Medicine, Stanford, CA, (2) Shenzhen Institutes of Advanced Technology, Shenzhen, Guangdong

Presentations

(Monday, 7/15/2019) 7:30 AM - 9:30 AM

Room: 221AB

Purpose: The precise prostate auto-setup in the cone-beam CT (CBCT) guided radiotherapy is complicated by two factors: (1) the low image contrast of the marker-free prostate; (2) and the variations between the planning CT (pCT) and CBCT acquired at the different time. To address these problems, we propose a novel patient-specific residual network strategy to achieve Six-Degrees-of-freedom (6D) auto-setup for the marker-free prostate.

Methods: The proposed method includes four parts: (1) Training data generation: an image augmentation model was applied to the pCT to generate the training dataset with the corresponding prostate bounding and landmarks. (2) Network training: we developed a two-step task-based residual network (T2RN) to localize the prostate and then detect the landmarks inside the localized region. (3) Prediction on the CBCT: an iterative filter scheme was presented to find a transformation to the CBCT so that the gray value distribution can match well with the training image. (4) Determination of the 6D shift: The translation and rotation errors in CBCT were determined using the transformation matrix from the landmarks in the pCT.

Results: For the clinical study, the evaluations were carried on the 80 cases of CBCT, which were augmented from the patient with 20 cases of CBCT acquired at a different time. The mean and standard deviation errors in the anterior-posterior, left-right, superior-inferior, yaw, pitch, and roll were 0.64±1.40 mm, 0.15±1.28 mm, -0.46±1.17 mm, 0.21º±0.60º, -0.61º±0.48º, and 0.23º±0.44º, respectively. The correlation coefficients are 0.99, 0.99, 0.99, 0.91, 0.94, and 0.95. The prediction time for the per case of CBCT was less than 0.5s.

Conclusion: Prostate setup has been mainly investigated so far using the image registration which suffers from either low accuracy or long processing time. T2RN presents a very promising alternative which can offer simultaneously high precision and fast processing for marker-free prostate 6D auto-setup.

Keywords

Cone-beam CT, Setup Errors, Prostate Therapy

Taxonomy

TH- RT Interfraction motion management : X-ray projection/CBCT-based

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