Respiratory gating for radiation therapy is not ready for prime time

The Dosimetric and Temporal Effects of Respiratory-Gated, High-Dose-Rate Radiation Therapy in Patients With Lung Cancer

Purpose:

To evaluate the dosimetric and temporal effects of high-dose-rate respiratory-gated radiation therapy in patients with lung cancer.

Methods:

Treatment plans from 5 patients with lung cancer (3 nongated and 2 gated at 80EX-80IN) were retrospectively evaluated. Prescription dose for these patients varied from 8 to 18 Gy/fraction with 3 to 5 treatment fractions. Using the same treatment planning criteria, 4 new treatment plans, corresponding to 4 gating windows (20EX-20IN, 40EX-40IN, 60EX-60IN, and 80EX-80IN), were generated for each patient. Mean tumor dose, mean lung dose, and lung V20 were used to assess the dosimetric effects. A MATLAB algorithm was developed to compute treatment time.

Results:

Mean lung dose and lung V20 were on average reduced between −16.1% to −6.0% and −20.0% to −7.2%, respectively, for gated plans when compared to the corresponding nongated plans, and between −5.8% to −4.2% and −7.0% to −5.4%, respectively, for plans with smaller gating windows when compared to the corresponding plans gated at 80EX-80IN. Treatment delivery times of gated plans using high-dose rate were reduced on average between −19.7% (−0.10 min/100 MU) and −27.2% (−0.13 min/100 MU) for original nongated plans and −15.6% (−0.15 min/100 MU) and −20.3% (−0.19 min/100 MU) for original 80EX-80IN-gated plans.

Conclusion:

Respiratory-gated radiation therapy in patients with lung cancer can reduce lung dose while maintaining tumor dose. Because treatment delivery during gated therapy is discontinuous, total treatment time may be prolonged. However, this increase in treatment time can be offset by increasing the dose delivery rate. Estimation of treatment time may be helpful in selecting patients for respiratory gating and choosing appropriate gating windows.

Dosimetric evaluation of respiratory gated volumetric modulated arc therapy for lung stereotactic body radiation therapy using 3D printing technology

Purpose

This study aimed to evaluate the dosimetric accuracy of respiratory gated volumetric modulated arc therapy (VMAT) for lung stereotactic body radiation therapy (SBRT) under simulation conditions similar to the actual clinical situation using patient-specific lung phantoms and realistic target movements.

Methods

Six heterogeneous lung phantoms were fabricated using a 3D-printer (3DISON, ROKIT, Seoul, Korea) to be dosimetrically equivalent to actual target regions of lung SBRT cases treated via gated VMAT. They were designed to move realistically via a motion device (QUASAR, Modus Medical Devices, Canada). Using the lung phantoms and a homogeneous phantom (model 500–3315, Modus Medical Devices), film dosimetry was performed with and without respiratory gating for VMAT delivery (TrueBeam STx; Varian Medical Systems, Palo Alto, CA, USA). The measured results were analyzed with the gamma passing rates (GPRs) of 2%/1 mm criteria, by comparing with the calculated dose via the AXB and AAA algorithms of the Eclipse Treatment Planning System (version 10.0.28; Varian Medical Systems).

Results

GPRs were greater than the acceptance criteria 80% for all film measurements with the stationary and homogeneous phantoms in conventional QAs. Regardless of the heterogeneity of phantoms, there were no significant differences (p > 0.05) in GPRs obtained with and without target motions; the statistical significance (p = 0.031) was presented between both algorithms under the utilization of heterogeneous phantoms.

Conclusions

Dosimetric verification with heterogeneous patient-specific lung phantoms could be successfully implemented as the evaluation method for gated VMAT delivery. In addition, it could be dosimetrically confirmed that the AXB algorithm improved the dose calculation accuracy under patient-specific simulations using 3D printed lung phantoms.

A fast neural network approach to predict lung tumor motion during respiration for radiation therapy applications

During radiotherapy treatment for thoracic and abdomen cancers, for example, lung cancers, respiratory motion moves the target tumor and thus badly affects the accuracy of radiation dose delivery into the target. A real-time image-guided technique can be used to monitor such lung tumor motion for accurate dose delivery, but the system latency up to several hundred milliseconds for repositioning the radiation beam also affects the accuracy. In order to compensate the latency, neural network prediction technique with real-time retraining can be used. We have investigated real-time prediction of 3D time series of lung tumor motion on a classical linear model, perceptron model, and on a class of higher-order neural network model that has more attractive attributes regarding its optimization convergence and computational efficiency. The implemented static feed-forward neural architectures are compared when using gradient descent adaptation and primarily the Levenberg-Marquardt batch algorithm as the ones of the most common and most comprehensible learning algorithms. The proposed technique resulted in fast real-time retraining, so the total computational time on a PC platform was equal to or even less than the real treatment time. For one-second prediction horizon, the proposed techniques achieved accuracy less than one millimeter of 3D mean absolute error in one hundred seconds of total treatment time.

Analysis of changes in dose distribution due to respiration during IMRT

Purpose

Intensity modulated radiation therapy (IMRT) is a high precision therapy technique that can achieve a conformal dose distribution on a given target. However, organ motion induced by respiration can result in significant dosimetric error. Therefore, this study explores the dosimetric error that result from various patterns of respiration.

Materials and Methods

Experiments were designed to deliver a treatment plan made for a real patient to an in-house developed motion phantom. The motion pattern; the amplitude and period as well as inhale-exhale period, could be controlled by in-house developed software. Dose distribution was measured using EDR2 film and analysis was performed by RIT113 software. Three respiratory patterns were generated for the purpose of this study; first the 'even inhale-exhale pattern', second the slightly long exhale pattern (0.35 seconds longer than inhale period) named 'general signal pattern', and third a 'long exhale pattern' (0.7 seconds longer than inhale period). One dimensional dose profile comparisons and gamma index analysis on 2 dimensions were performed

Results

In one-dimensional dose profile comparisons, 5% in the target and 30% dose difference at the boundary were observed in the long exhale pattern. The center of high dose region in the profile was shifted 1 mm to inhale (caudal) direction for the 'even inhale-exhale pattern', 2 mm and 5 mm shifts to exhale (cranial) direction were observed for 'slightly long exhale pattern' and 'long exhale pattern', respectively. The areas of gamma index >1 were 11.88%, 15.11%, and 24.33% for 'even inhale-exhale pattern', 'general pattern', and 'long exhale pattern', respectively. The long exhale pattern showed largest errors.

Conclusion

To reduce the dosimetric error due to respiratory motions, controlling patient's breathing to be closer to even inhaleexhale period is helpful with minimizing the motion amplitude.

Predictive modeling of lung motion over the entire respiratory cycle using measured pressure-volume data, 4DCT images, and finite-element analysis

PURPOSE

Predicting complex patterns of respiration can benefit the management of the respiratory motion for radiation therapy of lung cancer. The purpose of the present work was to develop a patient-specific, physiologically relevant respiratory motion model which is capable of predicting lung tumor motion over a complete normal breathing cycle.

METHODS

Currently employed techniques for generating the lung geometry from four-dimensional computed tomography data tend to lose details of mesh topology due to excessive surface smoothening. Some of the existing models apply displacement boundary conditions instead of the intrapleural pressure as the actual motive force for respiration, while others ignore the nonlinearity of lung tissues or the mechanics of pleural sliding. An intermediate nonuniform rational basis spline surface representation is used to avoid multiple geometric smoothing procedures used in the computational mesh preparation. Measured chest pressure-volume relationships are used to simulate pressure loading on the surface of the model for a given lung volume, as in actual breathing. A hyperelastic model, developed from experimental observations, has been used to model the lung tissue material. Pleural sliding on the inside of the ribcage has also been considered.

RESULTS

The finite-element model has been validated using landmarks from four patient CT data sets over 34 breathing phases. The average differences of end-inspiration in position between the landmarks and those predicted by the model are observed to be 0.450 +/- 0.330 cm for Patient P1, 0.387 +/- 0.169 cm for Patient P2, 0.319 +/- 0.186 cm for Patient P3, and 0.204 +/- 0.102 cm for Patient P4 in the magnitude of error vector, respectively. The average errors of prediction at landmarks over multiple breathing phases in superior-inferior direction are less than 3 mm.

CONCLUSIONS

The prediction capability of pressure-volume curve driven nonlinear finite-element model is consistent over the entire breathing cycle. The biomechanical parameters in the model are physiologically measurable, so that the results can be extended to other patients and additional neighboring organs affected by respiratory motion.

Estimation of motion fields by non-linear registration for local lung motion analysis in 4D CT image data

PURPOSE

Motivated by radiotherapy of lung cancer non- linear registration is applied to estimate 3D motion fields for local lung motion analysis in thoracic 4D CT images. Reliability of analysis results depends on the registration accuracy. Therefore, our study consists of two parts: optimization and evaluation of a non-linear registration scheme for motion field estimation, followed by a registration-based analysis of lung motion patterns.

METHODS

The study is based on 4D CT data of 17 patients. Different distance measures and force terms for thoracic CT registration are implemented and compared: sum of squared differences versus a force term related to Thirion's demons registration; masked versus unmasked force computation. The most accurate approach is applied to local lung motion analysis.

RESULTS

Masked Thirion forces outperform the other force terms. The mean target registration error is 1.3 ± 0.2 mm, which is in the order of voxel size. Based on resulting motion fields and inter-patient normalization of inner lung coordinates and breathing depths a non-linear dependency between inner lung position and corresponding strength of motion is identified. The dependency is observed for all patients without or with only small tumors.

CONCLUSIONS

Quantitative evaluation of the estimated motion fields indicates high spatial registration accuracy. It allows for reliable registration-based local lung motion analysis. The large amount of information encoded in the motion fields makes it possible to draw detailed conclusions, e.g., to identify the dependency of inner lung localization and motion. Our examinations illustrate the potential of registration-based motion analysis.

Molecular PET/CT imaging-guided radiation therapy treatment planning

The role of positron emission tomography (PET) during the past decade has evolved rapidly from that of a pure research tool to a methodology of enormous clinical potential. (18)F-fluorodeoxyglucose (FDG)-PET is currently the most widely used probe in the diagnosis, staging, assessment of tumor response to treatment, and radiation therapy planning because metabolic changes generally precede the more conventionally measured parameter of change in tumor size. Data accumulated rapidly during the last decade, thus validating the efficacy of FDG imaging and many other tracers in a wide variety of malignant tumors with sensitivities and specificities often in the high 90 percentile range. As a result, PET/computed tomography (CT) had a significant impact on the management of patients because it obviated the need for further evaluation, guided further diagnostic procedures, and assisted in planning therapy for a considerable number of patients. On the other hand, the progress in radiation therapy technology has been enormous during the last two decades, now offering the possibility to plan highly conformal radiation dose distributions through the use of sophisticated beam targeting techniques such as intensity-modulated radiation therapy (IMRT) using tomotherapy, volumetric modulated arc therapy, and many other promising technologies for sculpted three-dimensional (3D) dose distribution. The foundation of molecular imaging-guided radiation therapy lies in the use of advanced imaging technology for improved definition of tumor target volumes, thus relating the absorbed dose information to image-based patient representations. This review documents technological advancements in the field concentrating on the conceptual role of molecular PET/CT imaging in radiation therapy treatment planning and related image processing issues with special emphasis on segmentation of medical images for the purpose of defining target volumes. There is still much more work to be done and many of the techniques reviewed are themselves not yet widely implemented in clinical settings.

Patient-specific finite element modeling of respiratory lung motion using 4D CT image data

Development and optimization of methods for adequately accounting for respiratory motion in radiation therapy of thoracic tumors require detailed knowledge of respiratory dynamics and its impact on corresponding dose distributions. Thus, computer aided modeling and simulation of respiratory motion have become increasingly important. In this article a biophysical approach for modeling respiratory lung motion is described: Major aspects of the process of lung ventilation are formulated as a contact problem of elasticity theory which is solved by finite element methods; lung tissue is assumed to be isotropic, homogeneous, and linearly elastic. A main focus of the article is to assess the impact of biomechanical parameters (values of elastic constants) on the modeling process and to evaluate modeling accuracy. Patient-specific models are generated based on 4D CT data of 12 lung tumor patients. Simulated motion patterns of inner lung landmarks are compared with corresponding motion patterns observed in the 4D CT data. Mean absolute differences between model-based predicted landmark motion and corresponding breathing-induced landmark displacements as observed in the CT data sets are in the order of 3 mm (end expiration to end inspiration) and 2 mm (end expiration to midrespiration). Modeling accuracy decreases with increasing tumor size both locally (landmarks close to tumor) and globally (landmarks in other parts of the lung). The impact of the values of the elastic constants appears to be small. Outcomes show that the modeling approach is an adequate strategy in predicting lung dynamics due to lung ventilation. Nevertheless, the decreased prediction quality in cases of large tumors demands further study of the influence of lung tumors on global and local lung elasticity properties.

Dosimetric impact of motion in free-breathing and gated lung radiotherapy: a 4D Monte Carlo study of intrafraction and interfraction effects

The purpose of this study was to investigate if interfraction and intrafraction motion in free-breathing and gated lung IMRT can lead to systematic dose differences between 3DCT and 4DCT. Dosimetric effects were studied considering the breathing pattern of three patients monitored during the course of their treatment and an in-house developed 4D Monte Carlo framework. Imaging data were taken in free-breathing and in cine mode for both 3D and 4D acquisition. Treatment planning for IMRT delivery was done based on the free-breathing data with the CORVUS (North American Scientific, Chatsworth, CA) planning system. The dose distributions as a function of phase in the breathing cycle were combined using deformable image registration. The study focused on (a) assessing the accuracy of the CORVUS pencil beam algorithm with Monte Carlo dose calculation in the lung, (b) evaluating the dosimetric effect of motion on the individual breathing phases of the respiratory cycle, and (c) assessing intrafraction and interfraction motion effects during free-breathing or gated radiotherapy. The comparison between (a) the planning system and the Monte Carlo system shows that the pencil beam algorithm underestimates the dose in low-density regions, such as lung tissue, and overestimates the dose in high-density regions, such as bone, by 5% or more of the prescribed dose (corresponding to approximately 3-5 Gy for the cases considered). For the patients studied this could have a significant impact on the dose volume histograms for the target structures depending on the margin added to the clinical target volume (CTV) to produce either the planning target (PTV) or internal target volume (ITV). The dose differences between (b) phases in the breathing cycle and the free-breathing case were shown to be negligible for all phases except for the inhale phase, where an underdosage of the tumor by as much as 9.3 Gy relative to the free-breathing was observed. The large difference was due to breathing-induced motion/deformation affecting the soft/lung tissue density and motion of the bone structures (such as the rib cage) in and out of the beam. Intrafraction and interfraction dosimetric differences between (c) free-breathing and gated delivery were found to be small. However, more significant dosimetric differences, of the order of 3%-5%, were observed between the dose calculations based on static CT (3DCT) and the ones based on time-resolved CT (4DCT). These differences are a consequence of the larger contribution of the inhale phase in the 3DCT data than in the 4DCT.

Analysis of reproducibility of respiration-triggered gated radiotherapy for lung tumors

PURPOSE

Respiration-gated radiotherapy (RGRT) can decrease the toxicity of chemo-radiotherapy (CT-RT) by allowing use of smaller treatment fields. RGRT requires a predictable relationship between tumor position and external surrogate, which must be verified during treatment. Time-integrated electronic portal imaging (TI-EPI) identifies mean intra-fractional positions of moving structures, and was used to study reproducibility of anatomy during RGRT for lung tumors.

MATERIALS AND METHODS

TI-EPIs were acquired using an amorphous silicon-based electronic portal imaging system (EPID, aS500) in continuous image acquisition mode in 11 patients treated with audio-coached RGRT at end-inspiration. The Varian Real-time Position Management (RPM) system was used for 4DCT imaging and RGRT delivery. All TI-EPI portals were co-registered to corresponding digitally reconstructed radiographs (DRR) of the planning 4DCT using the spinal column. Displacements in tumor position or that of an adjacent bronchus during RGRT was measured relative to the reference structure on the DRR.

RESULTS

Vertebra-matched portals revealed systematic (Sigma) and random (sigma) errors of 1.8 and 1.3mm in medial-lateral direction and 1.7 and 1.7 mm in cranial-caudal direction, indicating a reproducible tumor/bronchus position during the RPM-triggered gates.

CONCLUSIONS

RGRT delivery at end-inspiration can achieve reproducible internal anatomy in 'gated' fields delivered with audio-coaching.

Verifying 4D gated radiotherapy using time-integrated electronic portal imaging: a phantom and clinical study

Background

Respiration-gated radiotherapy (RGRT) can decrease treatment toxicity by allowing for smaller treatment volumes for mobile tumors. RGRT is commonly performed using external surrogates of tumor motion. We describe the use of time-integrated electronic portal imaging (TI-EPI) to verify the position of internal structures during RGRT delivery

Methods

TI-EPI portals were generated by continuously collecting exit dose data (aSi500 EPID, Portal vision, Varian Medical Systems) when a respiratory motion phantom was irradiated during expiration, inspiration and free breathing phases. RGRT was delivered using the Varian RPM system, and grey value profile plots over a fixed trajectory were used to study object positions. Time-related positional information was derived by subtracting grey values from TI-EPI portals sharing the pixel matrix. TI-EPI portals were also collected in 2 patients undergoing RPM-triggered RGRT for a lung and hepatic tumor (with fiducial markers), and corresponding planning 4-dimensional CT (4DCT) scans were analyzed for motion amplitude.

Results

Integral grey values of phantom TI-EPI portals correlated well with mean object position in all respiratory phases. Cranio-caudal motion of internal structures ranged from 17.5–20.0 mm on planning 4DCT scans. TI-EPI of bronchial images reproduced with a mean value of 5.3 mm (1 SD 3.0 mm) located cranial to planned position. Mean hepatic fiducial markers reproduced with 3.2 mm (SD 2.2 mm) caudal to planned position. After bony alignment to exclude set-up errors, mean displacement in the two structures was 2.8 mm and 1.4 mm, respectively, and corresponding reproducibility in anatomy improved to 1.6 mm (1 SD).

Conclusion

TI-EPI appears to be a promising method for verifying delivery of RGRT. The RPM system was a good indirect surrogate of internal anatomy, but use of TI-EPI allowed for a direct link between anatomy and breathing patterns.

Optimisation of whole-body PET/CT scanning protocols

Positron emission tomography (PET) has become one of the major tools for the in vivo localisation of positron-emitting tracers and now is performed routinely using (18)F-fluorodeoxyglucose (FDG) to answer important clinical questions including those in cardiology, neurology, psychiatry, and oncology. The latter application contributed largely to the wide acceptance of this imaging modality and its use in clinical diagnosis, staging, restaging, and assessment of tumour response to treatment. Dual-modality PET/CT systems have been operational for almost a decade since their inception. The complementarity between anatomic (CT) and functional or metabolic (PET) information provided in a "one-stop shop" has been the driving force of this technology. Although combined anato-metabolic imaging is an obvious choice, the way to perform imaging is still an open issue. The tracers or combinations of tracers to be used, how the imaging should be done, when contrast-enhanced CT should be performed, what are the optimal acquisition and processing protocols, are all unanswered questions. Moreover, each data acquisition-processing combination may need to be independently optimised and validated. This paper briefly reviews the basic principles of dual-modality imaging and addresses some of the practical issues involved in optimising PET/CT scanning protocols in a clinical environment.