Tumor Motion Characteristics Research Articles

Toward Global Consensus for MR-Guided Treatment Planning for Pancreatic Tumors on a 1.5 T MR-Linac

MR-guided SBRT with a 1.5 T MR-Linac is a relatively new therapy for pancreatic tumors with varying expertise levels. Moreover, treatment planning in the upper abdomen can be challenging as target coverage is often compromised by dosimetric constraints of abutting bowel structures. This may lead to large differences between centers in protocols, practices. To increase harmonization a worldwide consortium was founded among 1.5 T MR-Linac users. In this work we report on the outcome of the first phase within this collaboration, which is the assessment of the baseline variation between the treatment planning protocols and subsequent dose distributions. Twelve centers across three continents (North America, Europe, and Australia) participated in this consortium. Each center was sent the same two anonymized data sets reflecting two cases of locally advanced pancreatic cancer of different complexity levels. The data sets included a CT scan, a predefined structure set containing the gross target volume (GTV) and the OARs, a brief medical history, tumor motion characteristics, and auxiliary CT and MR imaging. Centers were asked to create an MRgRT treatment plan according to their clinical five-fraction SBRT protocol, using their institutional margin structures, beam setup, target prescriptions, and OAR constraints. Key DVH parameters that were evaluated are D99%, D90%, D50%, D1% for the GTV and D0.5cc for the duodenum, small bowel, and stomach. In general, large variations were observed in planning objectives and machine settings yielding widely varying inhomogeneous dose distributions to both the tumor and organs at risk (Table 1). This was especially manifest for case 2 where the tumor abutted with both the duodenum and small bowel over a trajectory of multiple centimeters. Not only were different trade-offs between target coverage and OAR sparing observed, but also different strategies for optimizing the integral dose to the tumor. These results indicate a large variety in the treatment planning strategies that could well translate to differences in outcome. Based on this first evaluation, the consortium will work towards a collective consensus protocol with a second evaluation round after internal discussions.

Machine Learning Radiomics Model for External and Internal Respiratory Motion Correlation Prediction in Lung Tumor.

Objectives: The complexity and specificity of lung tumor motion render it necessary to determine the external and internal correlation individually before applying indirect tumor tracking. However, the correlation cannot be determined from patient respiratory and tumor clinical characteristics before treatment. The purpose of this study is to present a machine learning model for an external/internal correlation prediction that is based on computed tomography (CT) radiomic features. Methods: 4-dimensional computed tomography (4DCT) images of 67 patients were collected retrospectively, and the external/internal correlation of lung tumor was calculated based on Spearman's rank correlation coefficient. Radiomic features were extracted from average intensity projection and the light gradient boosting machine (LightGBM)-based cross-validation (the recursive elimination method) was used for feature selection. The LightGBM framework forecasting models with classification thresholds 0.7, 0.8, and 0.9 are established using stratified 5-fold cross-validation. Model performance was assessed using receiver operating characteristics, sensitivity, and specificity. Results: There were 16, 18, and 13 features selected for models 0.7, 0.8, and 0.9, respectively. Texture features are of great importance in external/internal correlation prediction compared to other features in all models. The sensitivities of the predictions in models 0.7, 0.8, and 0.9 were 0.800 ± 0.126, 0.829 ± 0.140, and 0.864 ± 0.086, respectively. The specificities were 0.771 ± 0.114, 0.936 ± 0.0581, and 0.839 ± 0.101, whereas the area under the curve (AUC) was 0.837, 0.946, and 0.877, respectively. Conclusions: Our findings indicate that radiomics is an effective tool for respiratory motion correlation prediction, which can extract tumor motion characteristics. We proposed a machine learning framework for correlation prediction in the motion management strategy for lung tumor patients.

A particle filter motion prediction algorithm based on an autoregressive model for real-time MRI-guided radiotherapy of lung cancer

This work introduces a 2D motion prediction algorithm for lung tumors applied to dynamic MR images that combines intrafractional tumor deformations. It is developed in the context of MR-linac treatments and evaluates uniform and patient-specific margins about the gross tumor volume to optimize the tumor coverage. Seven early stage non-small cell lung cancer patients were imaged in treatment position with a 1.5 T magnetic resonance using a balanced steady-state free precession sequence for one minute at a rate of four images per second and were instructed to breathe normally. The particle filter, in combination with the autoregressive model, is used to sequentially track and predict the tumor position 250 ms in the future from the current image. In addition, the autocontour extracted from a previous study (Bourque et al 2016 Med. Phys. 43 5161–9) is projected to the predicted position and various margins are evaluated. Averaged over all patients, the root mean square errors are (1.3 ± 0.5) mm and (2.0 ± 0.8) mm with and without prediction, respectively, and the difference in centroid position is (1.1 ± 0.4) mm with the prediction. The addition of the prediction algorithm leads to inferior errors for all cases. With such predictor, enlarging the propagated contour by a uniform 2 mm margin leads to a minimum recall of 97% over the entire patient population. Considering patient-specific margins based on of the Gaussian distribution around the mean error, the margins vary from 0.8 to 3.0 mm in anterior–posterior direction and from 1.2 to 3.2 mm in the superior–inferior direction. This study concludes that the advantage of such prediction algorithm highly depends on the tumor motion characteristics. For both uniform and patient-specific margins evaluation, smaller treatment margins could be used when combined to an accurate tracking and motion prediction algorithm. These results could offer guidance for future MR-guided lung tumor treatments.

TU‐PIS‐Exhibit Hall‐5: Use of the Enterprise‐wide Dose Tracking Software Radimetrics In an Academic Medical System

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐F‐BRB‐02: Motion Artifacts and Suppression in MRI

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐PIS‐Exhibit Hall‐3: Simultaneous tracking of patient and real time staff dose to optimize interventional workflow

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐PIS‐Exhibit Hall‐1: Tools for Collecting and Analyzing Patient Dose Index Information from Imaging Equipment

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐PIS‐Exhibit Hall‐4: How to implement a dose monitoring solution in the real world: a technical perspective

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐F‐BRB‐03: Clinical Implementation of MR‐Based Motion Management

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

MO‐PIS‐Exhibit Hall‐1: Tools for Collecting and Analyzing Patient Dose Index Information from Imaging Equipment

No Abstract provided

TU‐F‐BRB‐01: Resolving and Characterizing Breathing Motion for Radiotherapy with MRI

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐F‐BRB‐00: MRI‐Based Motion Management for RT

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TU‐PIS‐Exhibit Hall‐2: How to Move Beyond Dose Monitoring to Imaging Performance Utilization

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.Learning Objectives: Discuss the need of MR‐based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

TH-CD-204-01: FEATURED PRESENTATION and BEST IN PHYSICS (JOINT IMAGING-THERAPY): Novel SG-KS-4D-MRI Sequence Reduces 4D Rebinning Artifacts and Improves GTV Contouring Consistency for Pancreatic Cancer Patients

Purpose: Dynamic magnetic resonance imaging (MRI) has been used to characterize tumor motion but real time acquisition has been limited to 2-dimensions. Methods have been developed to reconstruct four-dimensional MRI (4D-MRI) based on time-stamped 2D images or 2D K-space data. These methods suffer from anisotropic resolution and rebinning artifacts. We have developed a self-gating based K-space sorted 4D-MRI (SG-KS-4D-MRI) method to overcome these limitations and in this study apply it to monitoring organ motion of pancreatic cancer patients. Methods: Ten patients were imaged using 4D-CT, cine 2D-MRI and the SG-KS-4D-MRI method, which is a spoiled gradient recalled echo (GRE) sequence with 3D radial-sampling K-space projections and 1D projection-based self-gating. Tumor volumes were drawn at the end of exhalation phases in the 4D-MRI and 4D-CT, and mapped to the other phases using deformable registration. The tumor volumes and motion trajectories were compared. Results: An isotropic resolution of 1.6 mm was achieved in the SG-KS-4D-MRI images, which showed superior soft tissue contrast to 4D-CT and appeared to be free of rebinning artifacts. SG-KS-4D-MRI was able to detect out-of-plane tumor motion and showed good correlation with 4D-CT and cine 2D-MRI in superior-inferior direction with a correlation coefficient of 0.91±0.06 and 0.93±0.03, respectively. The average standard deviation of GTV (GTV_σ) calculated from ten breathing phases were 0.81 cc and 1.02 cc for SG-KS-4D-MRI and 4D-CT (p=0.004) respectively. Conclusion: A novel SG-KS-4D-MRI acquisition method capable of reconstructing rebinning-artifact-free high resolution 4D-MRI images was used to quantify pancreas tumor motion. The resultant pancreatic tumor motion trajectories better agreed with 2D-cine-MRI and 4D-CT in the SI direction than the other 2 directions due to smaller motions in those directions. The pancreatic tumor volumes derived using SG-KS-4D-MRI were significantly more consistent than those from the 4D-CT.This work is supported in part by NIH grant 1R03CA173273-01. This study is supported in part by NIH 1R03CA173273

Integration of a real‐time tumor monitoring system into gated proton spot‐scanning beam therapy: An initial phantom study using patient tumor trajectory data

In spot-scanning proton therapy, the interplay effect between tumor motion and beam delivery leads to deterioration of the dose distribution. To mitigate the impact of tumor motion, gating in combination with repainting is one of the most promising methods that have been proposed. This study focused on a synchrotron-based spot-scanning proton therapy system integrated with real-time tumor monitoring. The authors investigated the effectiveness of gating in terms of both the delivered dose distribution and irradiation time by conducting simulations with patients' motion data. The clinically acceptable range of adjustable irradiation control parameters was explored. Also, the relation between the dose error and the characteristics of tumor motion was investigated. A simulation study was performed using a water phantom. A gated proton beam was irradiated to a clinical target volume (CTV) of 5 × 5 × 5 cm(3), in synchronization with lung cancer patients' tumor trajectory data. With varying parameters of gate width, spot spacing, and delivered dose per spot at one time, both dose uniformity and irradiation time were calculated for 397 tumor trajectory data from 78 patients. In addition, the authors placed an energy absorber upstream of the phantom and varied the thickness to examine the effect of changing the size of the Bragg peak and the number of required energy layers. The parameters with which 95% of the tumor trajectory data fulfill our defined criteria were accepted. Next, correlation coefficients were calculated between the maximum dose error and the tumor motion characteristics that were extracted from the tumor trajectory data. With the assumed CTV, the largest percentage of the data fulfilled the criteria when the gate width was ± 2 mm. Larger spot spacing was preferred because it increased the number of paintings. With a prescribed dose of 2 Gy, it was difficult to fulfill the criteria for the target with a very small effective depth (the sum of an assumed energy absorber's thickness and the target depth in the phantom) because of the sharpness of the Bragg peak. However, even shallow targets could be successfully irradiated by employing an adequate number of paintings and by placing an energy absorber of sufficient thickness to make the effective target depth more than 12 cm. The authors also observed that motion in the beam direction was the main cause of dose distortion, followed by motion in the lateral plane perpendicular to the scan direction. The results suggested that by properly adjusting irradiation control parameters, gated proton spot-scanning beam therapy can be robust to target motion. This is an important first step toward establishing treatment plans in real patient geometry.

Assessment of Respiration-Induced Motion and Its Impact on Treatment Outcome for Lung Cancer

This study presented the analysis of free-breathing lung tumor motion characteristics using GE 4DCT and Varian RPM systems. Tumor respiratory movement was found to be associated with GTV size, the superior-inferior tumor location in the lung, and the attachment degree to rigid structure (e.g., chest wall, vertebrae, or mediastinum), with tumor location being the most important factor among the other two. Improved outcomes in survival and local control of 43 lung cancer patients were also reported. Consideration of respiration-induced motion based on 4DCT for lung cancer yields individualized margin and more accurate and safe target coverage and thus can potentially improve treatment outcome.

Cumulative dose on fractional delivery of tomotherapy to periodically moving organ: A phantom QA suggestion

This study was conducted to evaluate the cumulative dosimetric error that occurs in both target and surrounding normal tissues when treating a moving target in multifractional treatment with tomotherapy. An experiment was devised to measure cumulative error in multifractional treatments delivered to a horseshoe-shaped clinical target volume (CTV) surrounding a cylinder shape of organ at risk (OAR). Treatments differed in jaw size (1.05 vs 2.5cm), pitch (0.287 vs 0.660), and modulation factor (1.5 vs 2.5), and tumor motion characteristics differing in amplitude (1 to 3cm), period (3 to 5 second), and regularity (sinusoidal vs irregular) were tested. Treatment plans were delivered to a moving phantom up to 5-times exposure. Dose distribution on central coronal plane from 1 to 5 times exposure was measured with GAFCHROMIC EBT film. Dose differences occurring across 1 to 5 times exposure of treatment and between treatment plans were evaluated by analyzing measurements of gamma index, gamma index histogram, histogram changes, and dose at the center of the OAR. The experiment showed dose distortion due to organ motion increased between multiexposure 1 to 3 times but plateaued and remained constant after 3-times exposure. In addition, although larger motion amplitude and a longer period of motion both increased dosimetric error, the dose at the OAR was more significantly affected by motion amplitude rather than motion period. Irregularity of motion did not contribute significantly to dosimetric error when compared with other motion parameters. Restriction of organ motion to have small amplitude and short motion period together with larger jaw size and small modulation factor (with small pitch) is effective in reducing dosimetric error. Pretreatment measurements for 3-times exposure of treatment to a moving phantom with patient-specific tumor motion would provide a good estimation of the delivered dose distribution.

A comparison of tumor motion characteristics between early stage and locally advanced stage lung cancers

PurposeWith the increasing use of conformal radiation therapy methods for non-small cell lung cancer (NSCLC), it is necessary to accurately determine respiratory-induced tumor motion. The purpose of this study is to analyze and compare the motion characteristics of early and locally advanced stage NSCLC tumors in a large population and correlate tumor motion with position, volume, and diaphragm motion. Methods and materialsA total of 191 (94 early stage, 97 locally advanced) non-small cell lung tumors were analyzed for this study. Each patient received a four-dimensional CT scan prior to receiving radiation treatment. A soft-tissue-based rigid registration algorithm was used to track the tumor motion. Tumor volumes were determined based on the gross tumor volume delineated by physicians in the end of expiration phase. Tumor motion characteristics were correlated with their standardized tumor locations, lobe location, and clinical staging. Diaphragm motion was calculated by subtracting the diaphragm location between the expiration and the inspiration phases. ResultsMedian, max, and 95th percentile of tumor motion for early stage tumors were 5.9mm, 31.0mm, and 20.0mm, which were 1.2mm, 12mm, and 7mm more than those in locally advanced NSCLC, respectively. The range of motion at 95th percentile is more than 50% larger in early stage lung cancer group than in the locally advanced lung cancer group. Early stage tumors in the lower lobe showed the largest motion with a median motion of 9.2mm, while upper/mid-lobe tumors exhibited a median motion of 3.3mm. Tumor volumes were not correlated with motion. ConclusionThe range of tumor motion differs depending on tumor location and staging of NSCLC. Early stage tumors are more mobile than locally advanced stage NSCLC. These factors should be considered for general motion management strategies when 4D simulation is not performed on individual basis.

A novel simple approach for incorporation of respiratory motion in stereotactic treatments of lung tumors

Purpose An internal target volume (ITV) is often used for incorporating tumor motion into radiotherapy planning but it overestimates the margins necessary for breathing motion. We describe a pragmatic approach using maximum- and minimum-intensity projections (MIP and Min-IP) only, for reducing ITVs in stereotactic radiotherapy by using dosimetric margins that compensate for motion-induced dose blurring. Patients and method We studied tumor motion characteristics from 26 repeat 4DCT scans derived from 10 patients. These were used to calculate the shift in cranio-caudal direction of the 80% isodose due to dose blurring of the time-averaged dose distribution caused by respiratory motion. The dosimetric margins necessary to compensate for dose blurring were calculated relative to the ITV, which can be determined efficiently using the MIP. Peak-to-peak motion amplitude was determined using the MIP and Min-IP. A programmable respiratory motion phantom was used to investigate imaging artifacts in determining the ITV for realistic motion patterns. Dose profiles were both calculated and measured in lung- and water-equivalent tissue. Results Using margins for the 80% dose level permitted the use of smaller target volumes relative to the use of ITV-based volumes, with (i) greater reductions seen at the end-inspiration edge than at expiration side due to asymmetric breathing motion patterns and (ii) a linear relationship seen with breathing amplitude. The average reduction of the ITV at a 95% confidence level is given by 0.2 × A pp − 1.3 mm at expiration side, where A pp is the peak-to-peak breathing amplitude, and 0.3 × A pp − 2.2 mm at inspiration side. Dosimetric margins did not differ significantly between water-equivalent and lung tissue for 80% isodose. Conclusion A simple margin recipe for breathing motion linear with breathing amplitude can be used to calculate the ITV reductions achievable for stereotactic radiotherapy of lung tumors.

TU‐C‐303A‐10: Site‐Specific Volumetric Analysis of Lung Tumor Motion

Purpose: To develop a Hidden Markov Model (HMM) of tumor motion behavior for use in adaptive image‐guided radiation therapy (IGRT) to overcome the beam delivery system's inherent mechanical and imaging‐rate latency. As input to the HMM we investigated clinically defined parameters and tumor motion characteristics. Method and Materials: Motion data from 43 lung tumors were collected by tracking an implanted fiducial using a fluoroscopic real‐time tracking system. Data on a total of 1297 radiotherapy fractions were collected and for 637 fractions a convex hull was created over the data points for three consecutive breathing cycles. Statistical analysis led to the removal of outlier points, then the volumes of the hulls were calculated and their shapes visually examined. Tumor location in the lung as defined by bronchial segments was related to the volume and shape of the tumor movement envelope. Results: Outlier points were removed based on data density and tumor velocity limits. It was found that tumors located in the upper apex had smaller volume of movement envelope (<50 mm≈3), whereas tumors located near the chest wall or diaphragm were larger (>70 mm≈3). Tumors attached to fixed anatomical structures had a small volume of movement envelope (<30 mm≈3). Three general shapes described the tumor motion envelopes. Envelope volume and shape was inter‐fractionally consistent. Fifty percent of tumors exhibited largely 1D oscillation; Thirty‐eight percent of tumors had motion enclosed by an ellipsoid envelop with few data points in the center region, six percent of tumors moved in an arc‐like defining a concave shaped movement envelope, and six percent defined a movement envelope that was of hybrid shape. Conclusions: The location‐space correlation and the inter‐fractional consistency of the movement envelope shapes will, in part, inform the development of a HMM to predict lung tumor motion for real‐time beam adjustments in IGRT.