Lanevega1587

In the deformed dose distribution there were differences in the measured and calculated field position of up to 0.8 mm and differences in the measured in calculated field size of up to 11.9 mm. Gamma pass rates were 60.0% using a 3%/3 mm criterion and 56.8% using a 3%/2 mm criterion for the deforming measurements representing a decrease in agreement compared to the control measurements. Further analysis showed that passing rates increased to 86.5% using a 3%/3 mm criterion and 70.5% using a 3%/2 mm criterion in voxels within 5 mm of fiducial markers used to guide the deformable image registration. This work represents the first measurement of deformed dose using x-ray CT polymer gel dosimetry. Overall these results highlight some of the challenges in the calculation and measurement of deforming dose and provide insight into possible strategies for improvement.Motor imagery (MI) constitutes a recurrent strategy for signals generation in brain-computer interfaces (BCIs) - systems that aim to control external devices by directly associating brain responses to distinct commands. Although great improvement has been achieved in MI-BCIs performance over recent years, they still suffer from inter- and intra-subject variability issues. GDC-0980 order As an attempt to cope with this, some studies have suggested that MI training should aid users to appropriately modulate their response for BCI usage generally, this training is performed based on the sensorimotor rhythms' modulation over the primary sensorimotor cortex (PMC), with the signal being feedbacked to the user. Nonetheless, recent studies have revisited the actual involvement of the PMC into MI, and little to no attention has been devoted to understanding the participation of other cortical areas into training protocols. Therefore, in this work, our aim was to analyze the response induced by hands MI of 10 healthy subjects in the form of event-related desynchronizations (ERDs) and to assess whether features from beyond the PMC might be useful for hands MI classification. We investigated how this response occurs for distinct frequency intervals between 7-30 Hz, and ex0plored changes in their evocation pattern across 12 MI training sessions without feedback. Overall, we found that ERD patterns occur differently for the frequencies encompassed by the μ and β bands, with its evocation being favored for the first band. Over time, the no-feedback approach was inefficient to aid in enhancing ERD evocation (EO). Moreover, to some extent, EO tends to decrease over blocks within a given run, and runs within an MI session, but remains stable within an MI block. We also found that the C3/C4 pair is not necessarily optimal for data classification, and both spectral and spatial subjects' specificities should be considered when designing training protocols.Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-view at native gantry angles. However, PPI has poor inherent contrast and spatial resolution. To deal with this issue, we propose a deep-learning-based method to use kV digitally reconstructed radiographs (DRR) to improve PPI image quality. Method; We used a residual generative adversarial network (GAN) framework to learn the nonlinear mapping between PPIs and DRRs. Residual blocks were used to force the model to focus on the structural differences between DRR and PPI. To assess the accuracy of our method, we used 149 images for training and 30 images for testing. PPIs were acquired using a double-scattered proton beam. The DRRs acquired from CT acted as learning targets in the training process and were used to evaluate results from the proposed method using a six-fold cross-validation scheme. Results; Qualitatively, the corrected PPIs showed enhanced spatial resolution and captured fine details present in the DRRs that are missed in the PPIs. The quantitative results for corrected PPIs show average normalized mean error (NME), normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index of -0.1%, 0.3%, 39.14 dB, and 0.987, respectively. Conclusion; The results indicate the proposed method can generate high quality corrected PPIs and this work shows the potential to use a deep-learning model to make PPI available in proton radiotherapy. This will allow for beam's-eye-view (BEV) imaging with the particle used for treatment, leading to a valuable alternative to orthogonal x-rays or cone-beam CT for patient position verification.The displacement of tumor bed walls during oncoplastic breast surgery (OBS) decreases the accuracy of using surgical clips as the sole surrogate for tumor bed location. This highlights the need for better communication of OBS techniques to radiation oncologists. To facilitate OBS practice and investigate clip placement reliability, a realistic silicone-based breast phantom was constructed with components emulating a breast parenchyma, epidermis, areola, nipple, chest wall, and a tumor. OBS was performed on the phantom and surgical clips were placed to mark the tumor bed. The phantom was imaged with CT, MRI, and ultrasound (US). The parenchyma's signal-to-noise ratio (SNR) and clips to parenchyma's contrast-to-noise ratio (CNR) were measured. The phantom's CT Hounsfield Unit (HU), relative electron density (RED), and mass density were determined. 6 and 10 MV photon beam attenuation measurements were performed in phantom material. The Young's Modulus and ultimate tensile strength (UTS) of the phantom parenchyma and epidermis were measured. Results showed that the breast phantom components were visible on all imaging modalities with adequate SNR and CNR. The phantom's HU is 130 ± 10. The RED is 0.983. Its mass density is 1.01 ± 0.01 g cm-3. Photon attenuation measurements in phantom material were within 1% of those in water. The Young's Moduli were 13.4 ± 4.2 kPa (mechanical) and 30.2 ± 4.1 kPa (US elastography) for the phantom parenchyma. The UTS' were 0.05 ± 0.01 MPa (parenchyma) and 0.23 ± 0.12 MPa (epidermis). We conclude that the phantom's imaging characteristics resemble a fibroglandular breast's and allow clear visualization of high-density markers used in radiation therapy. The phantom material is suitable for dose measurements in MV photon beams. Mechanical results confirmed the phantom's similarity to breast tissue. The phantom enables investigation of surgical clip displacements pre- and post-OBS, and is useful for radiation therapy quality assurance applications.