Evaluating motion of pancreatic tumors and anatomical surrogates using cine MRI in 0.35T MRgRT under free breathing conditions.

Treatment tolerability is a significant limitation to pancreatic cancer treatment with radiotherapy due to proximity to highly radiosensitive organs and respiratory motion necessitating expanded target margins. Further, pancreatic tumors are difficult to visualize on conventional radiotherapy systems. Surrogates are often used to locate the tumor but are often inconsistent and do not provide strong positional relations throughout the respiratory cycle. This work utilizes a retrospective dataset of 45 pancreatic cancer patients treated on an MR-Linac system with cine MRI acquired for real-time target tracking. We investigated intra-fraction motion of tumors and two abdominal surrogates, leading to prediction models between the tumor and surrogate. Patient specific motion evaluation and prediction models were generated from 225 cine MRI series acquired during treatment. Tumor contours were used to evaluate the pancreatic tumor motion. Linear regression and principal component analysis (PCA) based models were used to predict tumor position from the anterior-posterior (AP) motion of the abdominal surface, the superior-inferior (SI) motion of the diaphragm, or a combination. Models were evaluated using mean squared error (MSE) and mean absolute error (MAE). Contour analysis showed the average pancreatic tumor motion range was 7.4 ± 2.7 mm and 14.9 ± 5.8 mm in the AP and SI directions, respectively. The PCA model had MSE of 1.4 mm2 and 0.6 mm2 , for the SI and AP directions, respectively, with both surrogates as inputs for the models. When only the abdomen surrogate was used, MSE was 1.3 mm2 and 0.4 mm2 in the SI and AP directions, while it was 0.4 mm2 and 1.3 mm2 when only the diaphragm surrogate was used. We evaluated intra-fraction pancreatic tumor motion and demonstrated prediction models between the tumor and surrogate. The models calculated the pancreatic tumor position from diaphragm, abdominal, or both contours within standard pancreatic cancer target margin, and the process could be applied to other disease sites in the abdominothoracic cavity.

Assessment of a novel commercial large field of view phantom for comprehensive MR imaging quality assurance of a 0.35T MRgRT system.

Consistent quality assurance (QA) programs are vital to MR-guided radiotherapy (MRgRT), for ensuring treatment is delivered accurately and the onboard MRI system is providing the expected image quality. However, daily imaging QA with a dedicated phantom is not common at many MRgRT centers, especially with large phantoms that cover a field of view (FOV), similar to the human torso. This work presents the first clinical experience with a purpose-built phantom for large FOV daily and periodic comprehensive quality assurance (QUASAR™ MRgRT Insight Phantom (beta)) from Modus Medical Devices Inc. (Modus QA) on an MRgRT system. A monthly American College of Radiology (ACR) QA phantom was also imaged for reference. Both phantoms were imaged on a 0.35T MR-Linac, a 1.5T Philips wide bore MRI, and a 3.0T Siemens MRI, with T1-weighted and T2-weighted acquisitions. The Insight phantom was imaged in axial and sagittal orientations. Image quality tests including geometric accuracy, spatial resolution accuracy, slice thickness accuracy, slice position accuracy, and image intensity uniformity were performed on each phantom, following their respective instruction manuals. The geometric distortion test showed similar distortions of -1.7 mm and -1.9 mm across a 190 mm and a 283 mm lengths for the ACR and MRgRT Insight phantoms, respectively. The MRgRT Insight phantom utilized a modulation transform function (MTF) for spatial resolution evaluation, which showed decreased performance on the lower B0 strength MRIs, as expected, and could provide a good daily indicator of machine performance. Both the Insight and ACR phantoms showed a match with scan parameters for slice thickness analysis. During the imaging and analysis of this novel MRgRT Insight phantom the authors found setup to be straightforward allowing for easy acquisition each day, and useful image analysis parameters for tracking MRI performance.

First clinical experience of correcting phantom-based image distortion related to gantry position on a 0.35T MR-Linac.

MR-guided radiotherapy requires strong imaging spatial integrity to deliver high quality plans and provide accurate dose calculation. The MRI system, however, can be compromised by the integrated linear accelerator (Linac), resulting in inaccurate imaging isocenter position and geometric distortion. Dependence on gantry position further complicates the correction of distortions. This work presents a new clinical application of a commercial phantom and software system that quantifies isocenter alignment and geometric distortion, as well as providing a deformation vector field (DVF). A large distortion phantom and a smaller grid phantom were imaged at multiple gantry angles from 0 to 330° on a 0.35 T integrated MR-Linac. The software package was used to assess geometric distortion and generate DVFs to correct distortions within the phantom volume. The DVFs were applied to the grid phantom with resampling software then evaluated using structural similarity index measure (SSIM). Scans were also performed with a ferromagnetic clip near the phantom to investigate the correction of more severe artifacts. The mean magnitude isocenter shift was 0.67 mm, ranging from 0.25 to 1.04 mm across all angles. The DVF had a mean component value of 0.27 ± 0.02, 0.24 ± 0.01, and 0.19 ± 0.01 mm in the right-left (RL), anterior-posterior (AP), and superior-inferior (SI) directions. The ferromagnetic clip increased isocenter position error from 1.98 mm to 2.20 mm and increased mean DVF component values in the RL and AP directions. The resampled grid phantom had an increased SSIM for all gantry angles compared to original images, increasing from 0.26 ± 0.001 to 0.70 ± 0.004. Through this clinical assessment, we were able to correct geometric distortion and isocenter shift related to gantry position on a 0.35 T MR-Linac using the distortion phantom and software package. This provides encouragement that it could be used for quality assurance and clinically to correct systematic distortion caused by imaging at different gantry angles.

Evaluation of super-resolution on 50 pancreatic cancer patients with real-time cine MRI from 0.35T MRgRT.

MR-guided radiotherapy (MRgRT) systems provide excellent soft tissue imaging immediately prior to and in real time during radiation delivery for cancer treatment. However, 2D cine MRI often has limited spatial resolution due to high temporal resolution. This work applies a super resolution machine learning framework to 3.5 mm pixel edge length, low resolution (LR), sagittal 2D cine MRI images acquired on a MRgRT system to generate 0.9 mm pixel edge length, super resolution (SR), images originally acquired at 4 frames per second (FPS). LR images were collected from 50 pancreatic cancer patients treated on a ViewRay MR-LINAC. SR images were evaluated using three methods. 1) The first method utilized intrinsic image quality metrics for evaluation. 2) The second used relative metrics including edge detection and structural similarity index (SSIM). 3) Finally, automatically generated tumor contours were created on both low resolution and super resolution images to evaluate target delineation and compared with DICE and SSIM. Intrinsic image quality metrics all had statistically significant improvements for SR images versus LR images, with mean (±1 SD) BRISQUE scores of 29.65 ± 2.98 and 42.48 ± 0.98 for SR and LR, respectively. SR images showed good agreement with LR images in SSIM evaluation, indicating there was not significant distortion of the images. Comparison of LR and SR images with paired high resolution (HR) 3D images showed that SR images had a mean (±1 SD) SSIM value of 0.633 ± 0.063 and LR a value of 0.587 ± 0.067 (p ≪ 0.05). Contours generated on SR images were also more robust to noise addition than those generated on LR images. This study shows that super resolution with a machine learning framework can generate high spatial resolution images from 4fps low spatial resolution cine MRI acquired on the ViewRay MR-LINAC while maintaining tumor contour quality and without significant acquisition or post processing delay.

Big Data Analysis of Media Reports Related to COVID-19.

COVID-19 is lasting longer than expected, which has a huge impact on the economy and on personal life. Each country has a different response method, and the damage scale is also distinct. This study aims to find out how COVID-19-related news was handled in the domestic media to seek ways to minimize the pandemic. The paper focuses on the number of news features by period and by disaster and analyzes related words based on big data. The results of the analysis are as follows. First, in the initial response phase, keywords to identify accurate sources of actual broadcast contents, fake news, social networking service (SNS), etc. were also ranked in the top 20. Second, in the active response phase, when the number of confirmed persons and the government's countermeasures were announced, more than 100 COVID-19-related articles were issued, and the related words increased rapidly from the initial response stage. Therefore, the fact that COVID-19 has been expressed as a keyword indicates that our society is watching with great interest in the government's response to the disease.

Clinical Evaluation of Commercial Atlas-Based Auto-Segmentation in the Head and Neck Region.

Background: While atlas segmentation (AS) has proven to be a time-saving and promising method for radiation therapy contouring, optimal methods for its use have not been well-established. Therefore, we investigated the relationship between the size of the atlas patient population and the atlas segmentation auto contouring (AC) performance. Methods: A total of 110 patients' head planning CT images were selected. The mandible and thyroid were selected for this study. The mandibles and thyroids of the patient population were carefully segmented by two skilled clinicians. Of the 110 patients, 100 random patients were registered to 5 different atlas libraries as atlas patients, in groups of 20 to 100, with increments of 20. AS was conducted for each of the remaining 10 patients, either by simultaneous atlas segmentation (SAS) or independent atlas segmentation (IAS). The AS duration of each target patient was recorded. To validate the accuracy of the generated contours, auto contours were compared to manually generated contours (MC) using a volume-overlap-dependent metric, Dice Similarity Coefficient (DSC), and a distance-dependent metric, Hausdorff Distance (HD). Results: In both organs, as the population increased from n = 20 to n = 60, the results showed better convergence. Generally, independent cases produced better performance than simultaneous cases. For the mandible, the best performance was achieved by n = 60 [DSC = 0.92 (0.01) and HD = 6.73 (1.31) mm] and the worst by n = 100 [DSC = 0.90 (0.03) and HD = 10.10 (6.52) mm] atlas libraries. Similar results were achieved with the thyroid; the best performance was achieved by n = 60 [DSC = 0.79 (0.06) and HD = 10.17 (2.89) mm] and the worst by n = 100 [DSC = 0.72 (0.13) and HD = 12.88 (3.94) mm] atlas libraries. Both IAS and SAS showed similar results. Manual contouring of the mandible and thyroid required an average of 1,044 (±170.15) seconds, while AS required an average of 46.4 (±2.8) seconds. Conclusions: The performance of AS AC generally increased as the population of the atlas library increased. However, the performance does not drastically vary in the larger atlas libraries in contrast to the logic that bigger atlas library should lead to better results. In fact, the results do not vary significantly toward the larger atlas library. It is necessary for the institutions to independently research the optimal number of subjects.

Analysis of Neutron Production in Passively Scattered Ion-Beam Therapy.

A new treatment facility for heavy ion therapy since 2010 was constructed. In the broad beam, a range shifter, ridge filter and multi leaf collimator (MLC) for the generation of the spread-out Bragg peak is used. In this case, secondary neutrons produced by the interactions of the ion field with beam-modifying devices (e.g. double-scattering system, beam shaping collimators and range compensators) are very important for patient safety. Therefore, these components must be carefully examined in the context of secondary neutron yield and associated secondary cancer risk. In this article, Monte Carlo simulation has been carried out with the FLUktuierende KAskade particle transport code, the fluence and distribution of neutron generation and the neutron dose equivalent from the broad beam components are compared using carbon and proton beams. As a result, it is confirmed that the yield of neutron production using a carbon beam from all components of the broad beam was higher than using a proton beam. The ambient dose by neutrons per heavy ion and proton ion from the MLC surface was 0.12-0.18 and 0.0067-0.0087 pSv, respectively, which shows that heavy ions generate more neutrons than protons. However, ambient dose per treatment 2 Gy, which means physical dose during treatment by ion beam, is higher than carbon beam because proton therapy needs more beam flux to make 2-Gy prescription dose. Therefore, the neutron production from the MLC, which is closed to the patient, is a very important parameter for patient safety.

Proton-radiography-based quality assurance of proton range compensator.

The aim of this work was to study the feasibility of proton radiography (pRad) as a patient-specific range compensator (RC) quality assurance (QA) tool and to validate its clinical utility by performing QA on RCs having three kinds of possible defects. In order to achieve pRad for a single EBT film, proton beam currents were modulated with new weighting factors, maximizing the linearity of optical-density-to-thickness ratio. Two RCs, examined to be accurately manufactured as planned, were selected to estimate the feasibility of our pRad. The optical densities of the EBT film on which the RC was irradiated with the modulated proton beam were digitized to pixel values (pv) and then converted to thickness using a thickness-pv calibration curve. The thickness information on the pRad was compared with plan data that had been extracted from treatment planning system. The mean thickness difference (TD) over the flat RC regions was calculated as 0.39 mm, and the standard deviation as 0.22 mm, and the proton scattering effect was analyzed by step phantom measurement. Even proton scattering effected a TD of over 1 mm in the large gradient region, the percentage of pixels over the acceptance criterion was only within 1.11% and 3.49%, respectively, when a 1 mm distance to agreement tolerance limit was applied. The QA results for both precisely and imprecisely manufactured RCs demonstrated the high potential utility and clinical applicability of the pRad-based RC QA tool.