Validation of a commercial software dose calculation for Y-90 microspheres.

PURPOSE: Several new commercial software packages have become available that can calculate the tumor and normal tissue dose distributions from post-treatment PET-CT scans for Y-90 microsphere treatments of liver lesions. This work seeks to validate the MIM SurePlan Liver Y90 software by comparing its results to a previously developed Monte Carlo derived voxel dose kernel calculation method. METHODS: We analyzed 10 patients who had treatments for metastatic liver cancer and created contours on post Y-90 treatment PET-CT images. We then performed dose calculations using three methods and compared the results. The first two methods calculated the dose using MIM SurePlan Liver Y90's LDM (Local Deposition Method) and the VSV (Voxel S Value) algorithms. The third method calculated the dose using a publicly available Fluka Monte Carlo-derived dose kernel (MCK) calculation (used as ground truth). We investigated 3D Gamma passing rates and several dosimetric parameters. RESULTS: A total of 3%/3 mm 3D gamma passing rates averaged 99.3% for the VSV and 78.9% for LDM. Compared to the MCK distribution, the differences for combined target GTV V70Gy and normal liver and/or lobe mean doses were small. Larger differences were seen in GTV mean doses and D95, likely due to large dose gradients in the treated regions combined with differences in dose kernel, dose grid and finite volume effects. CONCLUSIONS: The MIM SurePlan Liver Y90 VSV algorithm agreed well with the MCK calculation for patients treated with Y-90 microspheres based on the gamma analysis and several dosimetric parameters. Larger dosimetric differences in lesion mean doses and D95 suggests that these metrics are less robust to changes in calculation grid location and finite volume effects for small lesions.

Assessing Dutch women's experiences of labour and birth: adaptations and psychometric evaluations of the measures Mothers on Autonomy in Decision Making Scale, Mothers on Respect Index, and Childbirth Experience Questionnaire 2.0.

BACKGROUND: The Mothers Autonomy in Decision Making Scale (MADM) assesses women's autonomy and role in decision making. The Mothers on Respect Index (MORi) asseses women's experiences of respect when interacting with their healthcare providers. The Childbirth Experience Questionnaire 2.0 assesses the overall experience of childbirth (CEQ2.0). There are no validated Dutch measures of the quality of women's experiences in the intrapartum period. Therefore, the aim of this study was to evaluate the psychometric properties of these measures in their Dutch translations. METHODS: The available Dutch versions of the MADM and MORi were adapted to assess experiences in the intrapartum period. The CEQ2.0 was translated by using forward-backward procedures. The three measures were included in an online survey including items on individual characteristics (i.e. maternal, birth, birth interventions). Reliability was assessed by calculating Cronbach's alphas. Mann-Whitney, Kruskal Wallis or Student T-tests were applied where appropriate, to assess discrimination between women who differed on individual characteristics (known group validity). We hypothesized that women who experienced pregnancy complications and birth interventions would have statistically lower scores on the MADM, MORi and CEQ2.0, compared with women who had healthy pregnancies and physiological births. Convergent validity was assessed using Spearman Rank correlations between the MADM, MORi and/or CEQ2.0. We hypothesized moderate to strong correlations between these measures. Women's uptake of and feedback on the measures were tracked to assess acceptability and clarity. RESULTS: In total 621 women were included in the cross sectional study. The calculated Cronbach's alphas for the MADM, MORi and CEQ, were ≥ 0.77. Knowngroup validity was confirmed through significant differences on all relevant individual characteristics, except for vaginal laceration repair. Spearman Rank correlations ranged from 0.46-0.80. In total 98% of the included women out of the eligible population completed the MADM and MORi for each healthcare professional they encountered during childbirth. The proportions of MADM and MORi-items which were difficult to complete ranged from 0.0-10.8%, 0.6-2.7%, respectively. CONCLUSIONS: The results of our study showed that the Dutch version of the MADM, MORi and CEQ2.0 in Dutch are valid instruments that can be used to assess women's experiences in the intrapartum period.

Measuring respect and autonomy in Dutch maternity care: Applicability of two measures.

PROBLEM: In the Netherlands there are no valid measurement tools available to measure respectful maternity care and women's autonomy. BACKGROUND: Respectful maternity care including women's autonomy during childbirth are key components of high quality care. AIM: This study aims to evaluate the applicability of the Canadian measures; the Mothers Autonomy in Decision Making (MADM) scale and the Mothers on Respect index (MORi) measures among pregnant women in the Netherlands. METHODS: We translated the measures MORi and MADM according to the WHO guidelines, adapted them to the Dutch health care system, evaluated their psychometric properties, and pilot tested before administration through an online cross-sectional survey. We assessed feasibility by calculating descriptive statistics on scores, and reliability by calculating Cronbach's alpha. The construct validity was measured by hypotheses on differences between subgroups based on maternal characteristics, pregnancy characteristics and healthcare provision. FINDINGS: Of 557 women included in the study, 83% experienced high respect and 62% experienced high autonomy. Both the MORi and MADM showed feasibility, internal consistency, and with respect to construct validity, both measures discriminated between type of care provision. Compared to women with pregnancy complications, those with a healthy pregnancy reported statistically higher MORi-scores. No differences were observed on MADM-scores. DISCUSSION: Both instruments can be used as quality of care measures aiming to improve care and thus experiences of women. CONCLUSION: The results of this study support the feasibility, reliability, and to a certain extent known group validity of the Dutch MORi and MADM measures in pregnant women.

Deformable image registration for dose mapping between external beam radiotherapy and brachytherapy images of cervical cancer.

For locally advanced cervical cancer (LACC), anatomy correspondence with and without BT applicator needs to be quantified to merge the delivered doses of external beam radiation therapy (EBRT) and brachytherapy (BT). This study proposed and evaluated different deformable image registration (DIR) methods for this application. Twenty patients who underwent EBRT and BT for LACC were retrospectively analyzed. Each patient had a pre-BT CT at EBRT boost (without applicator) and a CT and MRI at BT (with applicator). The evaluated DIR methods were the diffeomorphic Demons, commercial intensity and hybrid methods, and three different biomechanical models. The biomechanical models considered different boundary conditions (BCs). The impact of the BT devices insertion on the anatomy was quantified. DIR method performances were quantified using geometric criteria between the original and deformed contours. The BT dose was deformed toward the pre-CT BT by each DIR method. The impact of boundary conditions to drive the biomechanical model was evaluated based on the deformation vector field and dose differences. The GEC-ESTRO guideline dose indices were reported. Large organ displacements, deformations, and volume variations were observed between the pre-BT and BT anatomies. Rigid registration and intensity-based DIR resulted in poor geometric accuracy with mean Dice similarity coefficient (DSC) inferior to 0.57, 0.63, 0.42, 0.32, and 0.43 for the rectum, bladder, vagina, cervix and uterus, respectively. Biomechanical models provided a mean DSC of 0.96 for all the organs. By considering the cervix-uterus as one single structure, biomechanical models provided a mean DSC of 0.88 and 0.94 for the cervix and uterus, respectively. The deformed doses were represented for each DIR method. Caution should be used when performing DIR for this application as standard techniques may have unacceptable results. The biomechanical model with the cervix-uterus as one structure provided the most realistic deformations to propagate the BT dose toward the EBRT boost anatomy.

A new respiratory monitoring and processing system based on Wii remote: proof of principle.

PURPOSE: To create a patient respiratory management system and patient self-practice tool using the Wii remote, a widely available consumer hardware product. METHODS: The Wii remote (Wiimote) (Nintendo, Redmond, WA) contains an infrared (IR) camera that can track up to four spots whose coordinates are reported to a host computer via Bluetooth. The Wiimote is capable of tracking a fiducial box currently used by a commercial monitoring system [Real-time Position Management(TM) (RPM) system, Varian Associates, Palo Alto, CA], if the correct IR source is used. The authors validated the Wiimote tracking by comparing the amplitude and frequency of signals among those reported by Wiimote with known movements from an inhouse servo-driven respiratory simulator, as well as with those measured using the RPM. The simulator comparison was done using standard sinusoid signals with amplitude of 2.0 cm as well as recorded patient respiratory traces. The RPM comparisons were done by simultaneously recording the RPM reflective box position with the Wiimote and the RPM. Timing was compared between these two systems by using the digital beam-on signal from the CT scanner, for the 4DCT to synchronize these acquisitions. RESULTS: The data acquisition rate from the Wiimote was 100.0 ± 0.4 Hz with a version 2.1 Bluetooth adaptor. The standard deviation of the height of the motion extrema was 0.06 and 1.1 mm when comparing those measured by the Wiimote and the servomotor encoder for standard sinusoid signal and prerecorded patient respiratory signal, respectively. The standard deviation of the amplitude of motion extrema between the Wiimote and RPM was 0.9 mm and the timing difference was 253 ms. CONCLUSION: The performance of Wiimote shows promise for respiratory monitoring for its faster sampling rate as well as the potential optical and GPU abilities. If used with care it can deliver reasonable spatial and temporal accuracy.

Investigating the temporal effects of respiratory-gated and intensity-modulated radiotherapy treatment delivery on in vitro survival: an experimental and theoretical study.

PURPOSE: To experimentally and theoretically investigate the temporal effects of respiratory-gated and intensity-modulated radiotherapy (IMRT) treatment delivery on in vitro survival. METHODS AND MATERIALS: Experiments were designed to isolate the effects of periodic irradiation (gating), partial tumor irradiation (IMRT), and extended treatment time (gating and IMRT). V79 Chinese hamster lung fibroblast cells were irradiated to 2 Gy with four delivery methods and a clonogenic assay performed. Theoretical incomplete repair model calculations were performed using the incomplete repair model. RESULTS: Treatment times ranged from 1.67 min (conformal radiotherapy, CRT) to 15 min (gated IMRT). Survival fraction calculations ranged from 68.2% for CRT to 68.7% for gated IMRT. For the same treatment time (5 min), gated delivery alone and IMRT delivery alone both had a calculated survival fraction of 68.3%. The experimental values ranged from 65.7% +/- 1.0% to 67.3% +/- 1.3%, indicating no significant difference between the experimental observations and theoretical calculations. CONCLUSION: The theoretical results predicted that of the three temporal effects of radiation delivery caused by gating and IMRT, extended treatment time was the dominant effect. Care should be taken clinically to ensure that the use of gated IMRT does not significantly increase treatment times, by evaluating appropriate respiratory gating duty cycles and IMRT delivery complexity.

Determination of prospective displacement-based gate threshold for respiratory-gated radiation delivery from retrospective phase-based gate threshold selected at 4D CT simulation.

Four-dimensional (4D) computed tomography (CT) imaging has found increasing importance in the localization of tumor and surrounding normal structures throughout the respiratory cycle. Based on such tumor motion information, it is possible to identify the appropriate phase interval for respiratory gated treatment planning and delivery. Such a gating phase interval is determined retrospectively based on tumor motion from internal tumor displacement. However, respiratory-gated treatment is delivered prospectively based on motion determined predominantly from an external monitor. Therefore, the simulation gate threshold determined from the retrospective phase interval selected for gating at 4D CT simulation may not correspond to the delivery gate threshold that is determined from the prospective external monitor displacement at treatment delivery. The purpose of the present work is to establish a relationship between the thresholds for respiratory gating determined at CT simulation and treatment delivery, respectively. One hundred fifty external respiratory motion traces, from 90 patients, with and without audio-visual biofeedback, are analyzed. Two respiratory phase intervals, 40%-60% and 30%-70%, are chosen for respiratory gating from the 4D CT-derived tumor motion trajectory. From residual tumor displacements within each such gating phase interval, a simulation gate threshold is defined based on (a) the average and (b) the maximum respiratory displacement within the phase interval. The duty cycle for prospective gated delivery is estimated from the proportion of external monitor displacement data points within both the selected phase interval and the simulation gate threshold. The delivery gate threshold is then determined iteratively to match the above determined duty cycle. The magnitude of the difference between such gate thresholds determined at simulation and treatment delivery is quantified in each case. Phantom motion tests yielded coincidence of simulation and delivery gate thresholds to within 0.3%. For patient data analysis, differences between simulation and delivery gate thresholds are reported as a fraction of the total respiratory motion range. For the smaller phase interval, the differences between simulation and delivery gate thresholds are 8 +/- 11% and 14 +/- 21% with and without audio-visual biofeedback, respectively, when the simulation gate threshold is determined based on the mean respiratory displacement within the 40%-60% gating phase interval. For the longer phase interval, corresponding differences are 4 +/- 7% and 8 +/- 15% with and without audiovisual biofeedback, respectively. Alternatively, when the simulation gate threshold is determined based on the maximum average respiratory displacement within the gating phase interval, greater differences between simulation and delivery gate thresholds are observed. A relationship between retrospective simulation gate threshold and prospective delivery gate threshold for respiratory gating is established and validated for regular and nonregular respiratory motion. Using this relationship, the delivery gate threshold can be reliably estimated at the time of 4D CT simulation, thereby improving the accuracy and efficiency of respiratory-gated radiation delivery.

Respiratory regularity gated 4D CT acquisition: concepts and proof of principle.

Four-dimensional CT images are generally sorted through a post-acquisition procedure correlating images with a time-synchronized external respiration signal. The patient's ability to maintain reproducible respiration is the limiting factor during 4D CT, where artifacts occur in approximately 85% of scans with current technology. To reduce these artifacts and their subsequent effects during radiotherapy planning, a method for improved 4D CT image acquisition that relies on gating 4D CT acquisition based on the real time monitoring of the respiration signal has been proposed. The respiration signal and CT data acquisition are linked, such that data from irregular breathing cycles, which cause artifacts, are not acquired by gating CT acquisition by the respiratory signal. A proof-of-principle application of the respiratory regularity gated 4D CT method using patient respiratory signals demonstrates the potential of this method to reduce artifacts currently found in 4D CT scans. Numerical simulations indicate a potential reduction in motion within a respiratory phase bin by 20-40% depending on tolerances chosen. Additional advantages of the proposed method are dose reduction by eliminating unnecessary oversampling and obviating the need for post-processing to create the 4D CT data set.

The management of respiratory motion in radiation oncology report of AAPM Task Group 76.

This document is the report of a task group of the AAPM and has been prepared primarily to advise medical physicists involved in the external-beam radiation therapy of patients with thoracic, abdominal, and pelvic tumors affected by respiratory motion. This report describes the magnitude of respiratory motion, discusses radiotherapy specific problems caused by respiratory motion, explains techniques that explicitly manage respiratory motion during radiotherapy and gives recommendations in the application of these techniques for patient care, including quality assurance (QA) guidelines for these devices and their use with conformal and intensity modulated radiotherapy. The technologies covered by this report are motion-encompassing methods, respiratory gated techniques, breath-hold techniques, forced shallow-breathing methods, and respiration-synchronized techniques. The main outcome of this report is a clinical process guide for managing respiratory motion. Included in this guide is the recommendation that tumor motion should be measured (when possible) for each patient for whom respiratory motion is a concern. If target motion is greater than 5 mm, a method of respiratory motion management is available, and if the patient can tolerate the procedure, respiratory motion management technology is appropriate. Respiratory motion management is also appropriate when the procedure will increase normal tissue sparing. Respiratory motion management involves further resources, education and the development of and adherence to QA procedures.

Geometric accuracy of a real-time target tracking system with dynamic multileaf collimator tracking system.

PURPOSE: Dynamically compensating for target motion during radiotherapy will increase treatment accuracy. A laboratory system for real-time target tracking with a dynamic MLC has been developed. In this study, the geometric accuracy limits of this DMLC target tracking system were evaluated. METHODS AND MATERIALS: A motion simulator was programmed to follow patient-derived tumor motion paths, parallel to the leaf motion direction. A target attached to the simulator was optically tracked, and the leaf positions adjusted to continually align the DMLC beam aperture to the target. Analysis of the tracking accuracy was based on video images of the target and beam alignment. The system response time was determined and the tracking error measured. Response time-corrected tracking accuracy was also calculated to investigate the accuracy limits of an improved system. RESULTS: The response time of the system is 160 +/- 2 ms. The geometric precision for tracking patient motion is 0.6 to 1.1 mm (1 sigma) for the 3 patient datasets tested, with tracking errors relative to the original patient motion of 35, 40, and 100%. CONCLUSIONS: A DMLC target tracking system has been developed that can account for detected motion parallel to the leaf motion direction. The tracking error has a negligible systematic component. Reducing the response time will further increase the overall system accuracy.

The application of the sinusoidal model to lung cancer patient respiratory motion.

Accurate modeling of the respiratory cycle is important to account for the effect of organ motion on dose calculation for lung cancer patients. The aim of this study is to evaluate the accuracy of a respiratory model for lung cancer patients. Lujan et al. [Med. Phys. 26(5), 715-720 (1999)] proposed a model, which became widely used, to describe organ motion due to respiration. This model assumes that the parameters do not vary between and within breathing cycles. In this study, first, the correlation of respiratory motion traces with the model f(t) as a function of the parameter n (n = 1, 2, 3) was undertaken for each breathing cycle from 331 four-minute respiratory traces acquired from 24 lung cancer patients using three breathing types: free breathing, audio instruction, and audio-visual biofeedback. Because cos2 and cos4 had similar correlation coefficients, and cos2 and cos1 have a trigonometric relationship, for simplicity, the cos1 value was consequently used for further analysis in which the variations in mean position (z0), amplitude of motion (b) and period (tau) with and without biofeedback or instructions were investigated. For all breathing types, the parameter values, mean position (z0), amplitude of motion (b), and period (tau) exhibited significant cycle-to-cycle variations. Audio-visual biofeedback showed the least variations for all three parameters (z0, b, and tau). It was found that mean position (z0) could be approximated with a normal distribution, and the amplitude of motion (b) and period (tau) could be approximated with log normal distributions. The overall probability density function (pdf) of f(t) for each of the three breathing types was fitted with three models: normal, bimodal, and the pdf of a simple harmonic oscillator. It was found that the normal and the bimodal models represented the overall respiratory motion pdfs with correlation values from 0.95 to 0.99, whereas the range of the simple harmonic oscillator pdf correlation values was 0.71 to 0.81. This study demonstrates that the pdfs of mean position (z0), amplitude of motion (b), and period (tau) can be used for sampling to obtain more realistic respiratory traces. The overall standard deviations of respiratory motion were 0.48, 0.57, and 0.55 cm for free breathing, audio instruction, and audio-visual biofeedback, respectively.

Dosimetric impact of geometric errors due to respiratory motion prediction on dynamic multileaf collimator-based four-dimensional radiation delivery.

The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

Determination of maximum leaf velocity and acceleration of a dynamic multileaf collimator: implications for 4D radiotherapy.

The dynamic multileaf collimator (MLC) can be used for four-dimensional (4D), or tumor tracking radiotherapy. However, the leaf velocity and acceleration limitations become a crucial factor as the MLC leaves need to respond in near real time to the incoming respiration signal. The aims of this paper are to measure maximum leaf velocity, acceleration, and deceleration to obtain the mechanical response times for the MLC, and determine whether the MLC is suitable for 4D radiotherapy. MLC leaf sequence files, requiring the leaves to reach maximum acceleration and velocity during motion, were written. The leaf positions were recorded every 50 ms, from which the maximum leaf velocity, acceleration, and deceleration were derived. The dependence on the velocity and acceleration of the following variables were studied: leaf banks, inner and outer leaves, MLC-MLC variations, gravity, friction, and the stability of measurements over time. Measurement results show that the two leaf banks of a MLC behave similarly, while the inner and outer leaves have significantly different maximum leaf velocities. The MLC-MLC variations and the dependence of gravity on maximum leaf velocity are statistically significant. The average maximum leaf velocity at the isocenter plane of the MLC ranged from 3.3 to 3.9 cm/s. The acceleration and deceleration at the isocenter plane of the MLC ranged from 50 to 69 cm/s2 and 46 to 52 cm/s2, respectively. Interleaf friction had a negligible effect on the results, and the MLC parameters remained stable with time. Equations of motion were derived to determine the ability of the MLC response to fluoroscopymeasured diaphragm motion. Given the present MLC mechanical characteristics, 4D radiotherapy is feasible for up to 97% of respiratory motion. For the largest respiratory motion velocities observed, beam delivery should be temporarily stopped (beam hold).

Four-dimensional radiotherapy planning for DMLC-based respiratory motion tracking.

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation is respiration motion for lung tumors. The aim of this study was to develop 4D radiotherapy treatment-planning methodology for DMLC-based respiratory motion tracking. A 4D computed tomography (CT) scan consisting of a series of eight 3D CT image sets acquired at different respiratory phases was used for treatment planning. Deformable image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding to subsequent respiration phases. Deformable registration allows the contours defined on the peak-inhale CT to be automatically transferred to the other respiratory phase CT image sets. Treatment planning was simultaneously performed on each of the eight 3D image sets via automated scripts in which the MLC-defined beam aperture conforms to the PTV (which in this case equaled the GTV due to CT scan length limitations) plus a penumbral margin at each respiratory phase. The dose distribution from each respiratory phase CT image set was mapped back to the peak-inhale CT image set for analysis. The treatment intent of 4D planning is that the radiation beam defined by the DMLC tracks the respiration-induced target motion based on a feedback loop including the respiration signal to a real-time MLC controller. Deformation with respiration was observed for the lung tumor and normal tissues. This deformation was verified by examining the mapping of high contrast objects, such as the lungs and cord, between image sets. For the test case, dosimetric reductions for the cord, heart, and lungs were found for 4D planning compared with 3D planning. 4D radiotherapy planning for DMLC-based respiratory motion tracking is feasible and may offer tumor dose escalation and/or a reduction in treatment-related complications. However, 4D planning requires new planning tools, such as deformable registration and automated treatment planning on multiple CT image sets.

Is the diaphragm motion probability density function normally distributed?

During radiotherapy treatment planning, the margins given to the clinical target volume to form the planning target volume accounts for internal motion and set-up error. Most margin formulas assume that the underlying distributions are independent and normal. Clinical data suggests that the set-up error probability density function (pdf) can be considered to have an approximately normal distribution. However, there is evidence that internal motion does not have a normal distribution. Thus, in general, a convolution of the two pdfs should be performed to determine the total geometric error. The goals of this article were to (1) determine if the internal motion pdf due to respiration can be characterized using a normal distribution, and (2) if not, determine if the total geometric uncertainty for combining internal motion and set-up error can be characterized by a normal distribution. Sixty fluoroscopy diaphragm motion data sets were obtained using three breathing training types: free breathing, audio instruction, and visual feedback. Diaphragm motion was used as a surrogate for liver and lung cancer motion. The data were analyzed with normality tests in the following groups: (1) single motion measurements, (2) combined motion measurements for each patient, and (3) combined motion measurements for all patients. Following this analysis, the diaphragm motion pdfs were convolved with a set-up error pdf, and the standard deviation of the set-up error pdf at which the total geometric error pdf became normal was determined. At set-up error standard deviation values of at least 0.27 and 0.1 cm for free breathing, 0.57 and 0.42 cm for audio instruction, and 0.55 and 0 cm for visual feedback, for single motion measurements and combined motion measurements for each patient, respectively, total geometric error pdfs became approximately normal. When the motion measurements for all the patients were combined, diaphragm motion pdfs were approximately normal for all feedback types. Therefore, for treatment planning purposes in the absence of individual patient measurements, the diaphragm motion pdf can be considered an approximately normal distribution. However, care should be taken when determining a margin based on individual patients measurements as the total geometric error will, in general, not be normally distributed.

Predicting respiratory motion for four-dimensional radiotherapy.

Adapting radiation delivery to respiratory motion is made possible through corrective action based on real-time feedback of target position during respiration. The advantage of this approach lies with its ability to allow tighter margins around the target while simultaneously following its motion. A significant hurdle to the successful implementation of real-time target-tracking-based radiation delivery is the existence of a finite time delay between the acquisition of target position and the mechanical response of the system to the change in position. Target motion during the time delay leads to a resultant lag in the system's response to a change in tumor position. Predicting target position in advance is one approach to ensure accurate delivery. The aim of this manuscript is to estimate the predictive ability of sinusoidal and adaptive filter-based prediction algorithms on multiple sessions of patient respiratory patterns. Respiratory motion information was obtained from recordings of diaphragm motion for five patients over 60 sessions. A prediction algorithm that employed both prediction models-the sinusoidal model and the adaptive filter model-was developed to estimate prediction accuracy over all the sessions. For each session, prediction error was computed for several time instants (response time) in the future (0-1.8 seconds at 0.2-second intervals), based on position data collected over several signal-history lengths (1-7 seconds at 1-second intervals). Based on patient data included in this study, the following observations are made. Qualitative comparison of predicted and actual position indicated a progressive increase in prediction error with an increase in response time. A signal-history length of 5 seconds was found to be the optimal signal history length for prediction using the sinusoidal model for all breathing training modalities. In terms of overall error in predicting respiratory motion, the adaptive filter model performed better than the sinusoidal model. With the adaptive filter, average prediction errors of less than 0.2 cm (1sigma) are possible for response times less than 0.4 seconds. In comparing prediction error with system latency error (no prediction), the adaptive filter model exhibited lesser prediction errors as compared to the sinusoidal model, especially for longer response time values (>0.4 seconds). At smaller response time values (<0.4 seconds), improvements in prediction error reduction are required for both predictive models in order to maximize gains in position accuracy due to prediction. Respiratory motion patterns are inherently complex in nature. While linear prediction-based prediction models perform satisfactorily for shorter response times, their prediction accuracy significantly deteriorates for longer response times. Successful implementation of real-time target-tracking-based radiotherapy requires response times less than 0.4 seconds or improved prediction algorithms.

Acquiring 4D thoracic CT scans using a multislice helical method.

Respiratory motion degrades anatomic position reproducibility during imaging, necessitates larger margins during radiotherapy planning and causes errors during radiation delivery. Computed tomography (CT) scans acquired synchronously with the respiratory signal can be used to reconstruct 4D CT scans, which can be employed for 4D treatment planning to explicitly account for respiratory motion. The aim of this research was to develop, test and clinically implement a method to acquire 4D thoracic CT scans using a multislice helical method. A commercial position-monitoring system used for respiratory-gated radiotherapy was interfaced with a third generation multislice scanner. 4D cardiac reconstruction methods were modified to allow 4D thoracic CT acquisition. The technique was tested on a phantom under different conditions: stationary, periodic motion and non-periodic motion. 4D CT was also implemented for a lung cancer patient with audio-visual breathing coaching. For all cases, 4D CT images were successfully acquired from eight discrete breathing phases, however, some limitations of the system in terms of respiration reproducibility and breathing period relative to scanner settings were evident. Lung mass for the 4D CT patient scan was reproducible to within 2.1% over the eight phases, though the lung volume changed by 20% between end inspiration and end expiration (870 cm3). 4D CT can be used for 4D radiotherapy, respiration-gated radiotherapy, 'slow' CT acquisition and tumour motion studies.

On the use of EPID-based implanted marker tracking for 4D radiotherapy.

Four-dimensional (4D) radiotherapy delivery to dynamically moving tumors requires a real-time signal of the tumor position as a function of time so that the radiation beam can continuously track the tumor during the respiration cycle. The aim of this study was to develop and evaluate an electronic portal imaging device (EPID)-based marker-tracking system that can be used for real-time tumor targeting, or 4D radiotherapy. Three gold cylinders, 3 mm in length and 1 mm in diameter, were implanted in a dynamic lung phantom. The phantom range of motion was 4 cm with a 3-s "breathing" period. EPID image acquisition parameters were modified, allowing image acquisition in 0.1 s. Images of the stationary and moving phantom were acquired. Software was developed to segment automatically the marker positions from the EPID images. Images acquired in 0.1 s displayed higher noise and a lower signal-noise ratio than those obtained using regular (> 1 s) acquisition settings. However, the markers were still clearly visible on the 0.1-s images. The motion of the phantom blurred the images of the markers and further reduced the signal-noise ratio, though they could still be successfully segmented from the images in 10-30 ms of computation time. The positions of gold markers placed in the lung phantom were detected successfully, even for phantom velocities substantially higher than those observed for typical lung tumors. This study shows that using EPID-based marker tracking for 4D radiotherapy is feasible, however, changes in linear accelerator technology and EPID-based image acquisition as well as patient studies are required before this method can be implemented clinically.

Quantifying the predictability of diaphragm motion during respiration with a noninvasive external marker.

The aim of this work was to quantify the ability to predict intrafraction diaphragm motion from an external respiration signal during a course of radiotherapy. The data obtained included diaphragm motion traces from 63 fluoroscopic lung procedures for 5 patients, acquired simultaneously with respiratory motion signals (an infrared camera-based system was used to track abdominal wall motion). During these sessions, the patients were asked to breathe either (i) without instruction, (ii) with audio prompting, or (iii) using visual feedback. A statistical general linear model was formulated to describe the relationship between the respiration signal and diaphragm motion over all sessions and for all breathing training types. The model parameters derived from the first session for each patient were then used to predict the diaphragm motion for subsequent sessions based on the respiration signal. Quantification of the difference between the predicted and actual motion during each session determined our ability to predict diaphragm motion during a course of radiotherapy. This measure of diaphragm motion was also used to estimate clinical target volume (CTV) to planning target volume (PTV) margins for conventional, gated, and proposed four-dimensional (4D) radiotherapy. Results from statistical analysis indicated a strong linear relationship between the respiration signal and diaphragm motion (p<0.001) over all sessions, irrespective of session number (p=0.98) and breathing training type (p=0.19). Using model parameters obtained from the first session, diaphragm motion was predicted in subsequent sessions to within 0.1 cm (1 sigma) for gated and 4D radiotherapy. Assuming a 0.4 cm setup error, superior-inferior CTV-PTV margins of 1.1 cm for conventional radiotherapy could be reduced to 0.8 cm for gated and 4D radiotherapy. The diaphragm motion is strongly correlated with the respiration signal obtained from the abdominal wall. This correlation can be used to predict diaphragm motion, based on the respiration signal, to within 0.1 cm (1 sigma) over a course of radiotherapy.