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Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy.

ABSTRACT: Respiratory motion management techniques in radiotherapy (RT) planning are primarily focused on maintaining tumor target coverage. An inadequately addressed need is accounting for motion in dosimetric estimations in smaller serial structures. Accurate dose estimations in such structures are more sensitive to motion because respiration can cause them to move completely in or out of a high dose-gradient field. In this work, we study three motion management strategies (m1-m3) to find an accurate method to estimate the dosimetry in airways. To validate these methods, we generated a 'ground truth' digital breathing model based on a 4DCT scan from a lung stereotactic ablative radiotherapy (SAbR) patient. We simulated 225 breathing cycles with??±10% perturbations in amplitude, respiratory period, and time per respiratory phase. A high-resolution breath-hold CT (BHCT) was also acquired and used with a research virtual bronchoscopy software to autosegment 239 airways. Contours for planning target volume (PTV) and organs at risk (OARs) were defined on the maximum intensity projection of the 4DCT (CTMIP) and transferred to the average of the 10 4DCT phases (CTAVG). To design the motion management methods, the RT plan was recreated using different images and structure definitions. Methods m1 and m2 recreated the plan using the CTAVG image. In method m1, airways were deformed to the CTAVG. In m2, airways were deformed to each of the 4DCT phases, and union structures were transferred onto the CTAVG. In m3, the RT plan was recreated on each of the 10 phases, and the dose distribution from each phase was deformed to the BHCT and summed. Dose errors (mean [min, max]) in airways were: m1: 21% (0.001%, 93%); m2: 45% (0.1%, 179%); and m3: 4% (0.006%, 14%). Our work suggests that accurate dose estimation in moving small serial structures requires customized motion management techniques (like m3 in this work) rather than current clinical and investigational approaches.

SUBMITTER: Vicente E

PROVIDER: S-EPMC7363206 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy.

Vicente Esther E Modiri Arezoo A Yu Kun-Chang KC Wibowo Henky H Yan Yulong Y Timmerman Robert R Sawant Amit A

Physics in medicine and biology 20191121 22

Respiratory motion management techniques in radiotherapy (RT) planning are primarily focused on maintaining tumor target coverage. An inadequately addressed need is accounting for motion in dosimetric estimations in smaller serial structures. Accurate dose estimations in such structures are more sensitive to motion because respiration can cause them to move completely in or out of a high dose-gradient field. In this work, we study three motion management strategies (m1-m3) to find an accurate me ...[more]

PMID: 31665703

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Project description:PurposeTo develop a novel four-dimensional (4D) intensity modulated radiation therapy (IMRT) treatment planning methodology based on dynamic virtual patient models.MethodsThe 4D model-based planning (4DMP) is a predictive tracking method which consists of two main steps: (1) predicting the 3D deformable motion of the target and critical structures as a function of time during treatment delivery; (2) adjusting the delivery beam apertures formed by the dynamic multi-leaf collimators (DMLC) to account for the motion. The key feature of 4DMP is the application of a dynamic virtual patient model in motion prediction, treatment beam adjustment, and dose calculation. A lung case was chosen to demonstrate the feasibility of the 4DMP. For the lung case, a dynamic virtual patient model (4D model) was first developed based on the patient's 4DCT images. The 4D model was capable of simulating respiratory motion of different patterns. A model-based registration method was then applied to convert the 4D model into a set of deformation maps and 4DCT images for dosimetric purposes. Based on the 4D model, 4DMP treatment plans with different respiratory motion scenarios were developed. The quality of 4DMP plans was then compared with two other commonly used 4D planning methods: maximum intensity projection (MIP) and planning on individual phases (IP).ResultsUnder regular periodic motion, 4DMP offered similar target coverage as MIP with much better normal tissue sparing. At breathing amplitude of 2 cm, the lung V20 was 23.9% for a MIP plan and 16.7% for a 4DMP plan. The plan quality was comparable between 4DMP and IP: PTV V97 was 93.8% for the IP plan and 93.6% for the 4DMP plan. Lung V20 of the 4DMP plan was 2.1% lower than that of the IP plan and Dmax to cord was 2.2 Gy higher. Under a real time irregular breathing pattern, 4DMP had the best plan quality. PTV V97 was 90.4% for a MIP plan, 88.6% for an IP plan and 94.1% for a 4DMP plan. Lung V20 was 20.1% for the MIP plan, 17.8% for the IP plan and 17.5% for the 4DMP plan. The deliverability of the real time 4DMP plan was proved by calculating the maximum leaf speed of the DMLC.ConclusionsThe 4D model-based planning, which applies dynamic virtual patient models in IMRT treatment planning, can account for the real time deformable motion of the tumor under different breathing conditions. Under regular motion, the quality of 4DMP plans was comparable with IP and superior to MIP. Under realistic motion in which breathing amplitude and period change, 4DMP gave the best plan quality of the three 4D treatment planning techniques.

Project description:BACKGROUND:Most electronic health (eHealth) interventions offered to patients serve a single purpose and lack integration with other tools or systems. This is problematic because the majority of patients experience comorbidity and chronic disease, see multiple specialists, and therefore have different needs regarding access to patient data, communication with peers or providers, and self-monitoring of vital signs. A multicomponent digital health cloud service that integrates data sharing, collection, and communication could facilitate patient-centered care in combination with a hospital patient portal and care professionals. OBJECTIVE:This study aimed to assess the feasibility and functionality of a new cloud-based and multicomponent outpatient clinic, the "Virtual Outpatient Clinic" (VOC). METHODS:The VOC consists of 6 digital tools that facilitate self-monitoring (blood pressure, weight, and pain) and communication with peers and providers (chat and videoconferencing) connected to a cloud-based platform and the hospital patient portal to facilitate access to (self-collected) medical data. In this proof-of-concept study, 10 patients from both Departments of Internal Medicine and Dermatology (N=20) used all options of the VOC for 6 weeks. An eNurse offered support to participants during the study. We assessed the feasibility, usage statistics, content, adherence, and identified technical issues. Moreover, we conducted qualitative interviews with all participants by following a standard interview guide to identify user experiences, including barriers, facilitators, and potential effects. RESULTS:Most participants successfully used all options of the VOC and were positive about different tools and apps and the integral availability of their information. The adherence was 37% (7/19) for weight scale, 58% (11/19) for blood pressure monitor, and 70% (14/20) and 85% (17/20) for pain score and daily questions, respectively. The adherence for personal health record was 65% (13/20) and 60% (12/20) for the patient portal system. Qualitative data showed that performance and effort expectancy scored high among participants, indicating that using the VOC is convenient, easy, and time-saving. CONCLUSIONS:The VOC is a promising integrated Web-based technology that combines self-management, data sharing, and communication between patients and professionals. The system can be personalized by connecting various numbers of components, which could make it a relevant tool for other patient groups. Before a system, such as the VOC, can be implemented in daily practice, prospective studies focused on evaluating outcomes, costs, and patient-centeredness are needed.

Project description:PurposeRadiation injury to the bronchial tree is an important yet poorly understood potential side effect in lung stereotactic ablative radiation therapy (SAbR). We investigate the integration of virtual bronchoscopy in radiation therapy planning to quantify dosage to individual airways. We develop a risk model of airway collapse and develop treatment plans that reduce the risk of radiation-induced airway injury.Methods and materialsPre- and post-SAbR diagnostic-quality computerized tomography (CT) scans were retrospectively collected from 26 lung cancer patients. From each scan, the bronchial tree was segmented using a virtual bronchoscopy system and registered deformably to the planning CT. Univariate and stepwise multivariate Cox regressions were performed, examining factors such as age, comorbidities, smoking pack years, airway diameter, and maximum point dosage (Dmax). Logistic regression was utilized to formulate a risk function of segmental collapse based on Dmax and diameter. The risk function was incorporated into the objective function along with clinical dosage volume constraints for planning target volume (PTV) and organs at risk (OARs).ResultsUnivariate analysis showed that segmental diameter (P = .014) and Dmax (P = .007) were significantly correlated with airway segment collapse. Multivariate stepwise Cox regression showed that diameter (P = .015), Dmax (P < .0001), and pack/years of smoking (P = .02) were significant independent factors associated with collapse. Risk management-based plans enabled significant dosage reduction to individual airway segments while fulfilling clinical dosimetric objectives.ConclusionTo our knowledge, this is the first systematic investigation of functional avoidance in lung SAbR based on mapping and minimizing doses to individual bronchial segments. Our early results show that it is possible to substantially lower airway dosage. Such dosage reduction may potentially reduce the risk of radiation-induced airway injury, while satisfying clinically prescribed dosimetric objectives.

Dataset Information

Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy.

Publications

Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy.

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