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

A prototype fan-beam optical CT scanner for 3D dosimetry

PURPOSE

The objective of this work is to introduce a prototype fan-beam optical computed tomography scanner for three-dimensional (3D) radiation dosimetry.

METHODS

Two techniques of fan-beam creation were evaluated: a helium-neon laser (HeNe, λ = 543 nm) with line-generating lens, and a laser diode module (LDM, λ = 635 nm) with line-creating head module. Two physical collimator designs were assessed: a single-slot collimator and a multihole collimator. Optimal collimator depth was determined by observing the signal of a single photodiode with varying collimator depths. A method of extending the dynamic range of the system is presented. Two sample types were used for evaluations: nondosimetric absorbent solutions and irradiated polymer gel dosimeters, each housed in 1 liter cylindrical plastic flasks. Imaging protocol investigations were performed to address ring artefacts and image noise. Two image artefact removal techniques were performed in sinogram space. Collimator efficacy was evaluated by imaging highly opaque samples of scatter-based and absorption-based solutions. A noise-based flask registration technique was developed. Two protocols for gel manufacture were examined.

RESULTS

The LDM proved advantageous over the HeNe laser due to its reduced noise. Also, the LDM uses a wavelength more suitable for the PRESAGE(TM) dosimeter. Collimator depth of 1.5 cm was found to be an optimal balance between scatter rejection, signal strength, and manufacture ease. The multihole collimator is capable of maintaining accurate scatter-rejection to high levels of opacity with scatter-based solutions (T < 0.015%). Imaging protocol investigations support the need for preirradiation and postirradiation scanning to reduce reflection-based ring artefacts and to accommodate flask imperfections and gel inhomogeneities. Artefact removal techniques in sinogram space eliminate streaking artefacts and reduce ring artefacts of up to ∼40% in magnitude. The flask registration technique was shown to achieve submillimetre and subdegree placement accuracy. Dosimetry protocol investigations emphasize the need to allow gel dosimeters to cool gradually and to be scanned while at room temperature. Preliminary tests show that considerable noise reduction can be achieved with sinogram filtering and by binning image pixels into more clinically relevant grid sizes.

CONCLUSIONS

This paper describes a new optical CT scanner for 3D radiation dosimetry. Tests demonstrate that it is capable of imaging both absorption-based and scatter-based samples of high opacities. Imaging protocol and gel dosimeter manufacture techniques have been adapted to produce optimal reconstruction results. These optimal results will require suitable filtering and binning techniques for noise reduction purposes.

Lung

The lungs are particularly sensitive to RT, and are often the primary dose-limiting structure during thoracic therapy.

The alveolar/capillary units and pneumocytes within the alveoli appear to be particularly sensitive to RT.

Hypoxia may be important in the underlying physiology of RT-associated lung injury.

The cytokine transforming growth factor-beta (TGF-β), plays an important role in the development of RT-induced fibrosis.

The histopathological changes observed in the lung after RT are broadly characterized as diffuse alveolar damage.

The interaction between pre-treatment PFTs and the risk of symptomatic lung injury is complex. Similarly, the link between changes in PFTs and the development of symptoms is uncertain.

The incidence of symptomatic lung injury increases with increase in most dosimetric parameters. The mean lung dose (MLD) and V20 have been the most-often considered parameters. MLD might be a preferable metric since it considers the entire 3D dose distribution.

Radiation to the lower lobes appears to be more often associated with clinical symptoms than is radiation to the upper lobes. This might be related to incidental cardiac irradiation. In pre-clinical models, there appears to be a complex interaction between lung and heart irradiation.

TGF-β has been suggested in several studies to predict for RT-induced lung injury, but the data are still somewhat inconsistent.

Oral prednisone (Salinas and Winterbauer 1995), typically 40–60 mg daily for 1–2 weeks with a slow taper, is usually effective in treating pneumonitis. There are no widely accepted treatments for fibrosis.

A number of chemotherapeutic agents have been suggested to be associated with a range of pulmonary toxicities.

IMRT treatment planning on 4D geometries for the era of dynamic MLC tracking

The problem addressed here was to obtain optimal and deliverable dynamic multileaf collimator (MLC) leaf sequences from four-dimensional (4D) geometries for dynamic MLC tracking delivery. The envisaged scenario was where respiratory phase and position information of the target was available during treatment, from which the optimal treatment plan could be further adapted in real time. A tool for 4D treatment plan optimization was developed that integrates a commercially available treatment planning system and a general-purpose optimization system. The 4D planning method was applied to the 4D computed tomography planning scans of three lung cancer patients. The optimization variables were MLC leaf positions as a function of monitor units and respiratory phase. The objective function was the deformable dose-summed 4D treatment plan score. MLC leaf motion was constrained by the maximum leaf velocity between control points in terms of monitor units for tumor motion parallel to the leaf travel direction and between phases for tumor motion parallel to the leaf travel direction. For comparison and a starting point for the 4D optimization, three-dimensional (3D) optimization was performed on each of the phases. The output of the 4D IMRT planning process is a leaf sequence which is a function of both monitor unit and phase, which can be delivered to a patient whose breathing may vary between the imaging and treatment sessions. The 4D treatment plan score improved during 4D optimization by 34%, 4%, and 50% for Patients A, B, and C, respectively, indicating 4D optimization generated a better 4D treatment plan than the deformable sum of individually optimized phase plans. The dose-volume histograms for each phase remained similar, indicating robustness of the 4D treatment plan to respiratory variations expected during treatment delivery. In summary, 4D optimization for respiratory phase-dependent treatment planning with dynamic MLC motion tracking improved the 4D treatment plan score by 4–50% compared with 3D optimization. The 4D treatment plans had leaf sequences that varied from phase to phase to account for anatomic motion, but showed similar target dose distributions in each phase. The current method could in principle be generalized for use in offline replanning between fractions or for online 4D treatment planning based on 4D cone-beam CT images. Computation time remains a challenge.

Upgrade and benchmarking of a 4D treatment planning system for scanned ion beam therapy

PURPOSE

Upgrade and benchmarking of a research 4D treatment planning system (4DTPS) suitable for realistic patient treatment planning and treatment simulations taking into account specific requirements for scanned ion beam therapy, i.e., modeling of dose heterogeneities due to interplay effects and range changes caused by patient motion and dynamic beam delivery.

METHODS

The 4DTPS integrates data interfaces to 4D computed tomography (4DCT), deformable image registration and clinically used motion monitoring devices. The authors implemented a novel data model for 4D image segmentation using Boolean mask volume datasets and developed an algorithm propagating a manually contoured reference contour dataset to all 4DCT phases. They further included detailed treatment simulation and dose reconstruction functionality, based on the irregular patient motion and the temporal structure of the beam delivery. The treatment simulation functionality was validated against experimental data from irradiation of moving radiographic films in air, 3D moving ionization chambers in a water phantom, and moving cells in a biological phantom with a scanned carbon ion beam. The performance of the program was compared to results obtained with predecessor programs.

RESULTS

The measured optical density distributions of the radiographic films were reproduced by the simulations to (-2 ± 12)%. Compared to earlier versions of the 4DTPS, the mean agreement improved by 2%, standard deviations were reduced by 7%. The simulated dose to the moving ionization chambers in water showed an agreement with the measured dose of (-1 ± 4)% for the typical beam configuration. The mean deviation of the simulated from the measured biologically effective dose determined via cell survival was (617 ± 538) mGy relative biological effectiveness corresponding to (10 ± 9)%.

CONCLUSIONS

The authors developed a research 4DTPS suitable for realistic treatment planning on patient data and capable of simulating dose delivery to a moving patient geometry for scanned ion beams. The accuracy and reliability of treatment simulations improved considerably with respect to earlier versions of the 4DTPS.

Validation of Automatic Contour Propagation for 4D Treatment Planning Using Multiple Metrics

The aim of this work is to provide insights into multiple metrics clinical validation of deformable image registration and contour propagation methods in 4D lung radiotherapy planning. The following indices were analyzed and compared: Volume Difference (VD), Dice Similarity Coefficient (DSC), Positive Predictive Value (PPV) and Surface Distances (SD). The analysis was performed on three patient datasets, using as reference a ground-truth volume generated by means of Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm from the outlines of five experts. Significant discrepancies in the quality assessment provided by the different metrics in all the examined cases were found. Metrics sensitivity was more evident in presence of image artifacts and particularly for tubular anatomical structures, such as esophagus or spinal cord. Volume Differences did not account for position and DSC exhibited criticalities due to its intrinsic symmetry ( i.e. over- and under-estimation of the reference contours cannot be discriminated) and dependency on the total volume of the structure. PPV analysis showed more robust performance, as each voxel concurs to the classification of the propagation, but was not able to detect inclusion of propagated and ground-truth volumes. Mesh distances could interpret the actual shape of the structures, but might report higher mismatches in case of large local differences in the contour surfaces. According to our study, the combination of VD and SD for the validation of contour propagation algorithms in 4D could provide the necessary failure detection accuracy.

Quantifying variability of intrafractional target motion in stereotactic body radiotherapy for lung cancers

In lung stereotactic body radiotherapy (SBRT), variability of intrafractional target motion can negate the potential benefits of four‐dimensional (4D) treatment planning that aims to account for the dosimetric impacts of organ motion. This study used tumor motion data obtained from CyberKnife SBRT treatments to quantify the reproducibility of probability motion function (pmf) of 37 lung tumors. The reproducibility of pmf was analyzed with and without subtracting the intrafractional baseline drift from the original motion data. Statistics of intrafractional tumor motion including baseline drift, target motion amplitude and period, were also calculated. The target motion amplitude significantly correlates with variations (1 SD) of motion amplitude and baseline drift. Significant correlation between treatment time and variations (1 SD) of motion amplitude was observed in anterior‐posterior (AP) motion, but not in craniocaudal (CC) and left‐right (LR) motion. The magnitude of AP and LR baseline drifts significantly depend on the treatment time, while the CC baseline drift does not. The reproducibility of pmf as a function of time can be well described by a two‐exponential function with a fast and slow component. The reproducibility of pmf is over 60% for the CC motion and over 50% for the AP and LR motions when baseline variations were subtracted from the original motion data. It decreases to just over 30% for the CC motion and about 20% for the AP and LR motion, otherwise. 4D planning has obvious limitations due to variability of intrafractional target motion. To account for potential risks of overdosing critical organs, it is important to simulate the dosimetric impacts of intra‐ and interfractional baseline drift using population statistics obtained from SBRT treatments.

PACS number: 87.55.‐x

Intrafractional setup errors in patients undergoing non-invasive fixation using an immobilization system during hypofractionated stereotactic radiotherapy for lung tumors

Intrafractional setup errors during hypofractionated stereotactic radiotherapy (SRT) were investigated on the patient under voluntary breath-holding conditions with non-invasive immobilization on the CT-linac treatment table. A total of 30 patients with primary and metastatic lung tumors were treated with the hypofractionated SRT with a total dose of 48-60 Gy with four treatment fractions. The patient was placed supine and stabilized on the table with non-invasive patient fixation. Intrafractional setup errors in Right/Left (R.L.), Posterior/Anterior (P.A.), and Inferior/Superior (I.S.) dimensions were analyzed with pre- and post-irradiation CT images. The means and one standard deviation of the intrafractional errors were 0.9 ± 0.7mm (R.L.), 0.9 ± 0.7mm (P.A.) and 0.5 ± 1.0 mm (I.S.). Setup errors in each session of the treatment demonstrated no statistically significant difference in the mean value between any two sessions. The frequency within 3mm displacement was 98% in R.L., 98% in P.A. and 97% in I.S. directions. SRT under the non-invasive patient fixation immobilization system with a comparatively loose vacuum pillow demonstrated satisfactory reproducibility of minimal setup errors with voluntary breath-holding conditions that required a small internal margin.

Respiratory Gating for Radiotherapy: Main Technical Aspects and Clinical Benefits

Respiratory-gated radiotherapy offers a significant potential for improvement in the irradiation of tumor sites affected by respiratory motion such as lung, breast, and liver tumors. An increased conformality of irradiation fields leading to decreased complication rates of organs at risk is expected. Five main strategies are used to reduce respiratory motion effects: integration of respiratory movements into treatment planning, forced shallow breathing with abdominal compression, breath-hold techniques, respiratory gating techniques, and tracking techniques. Measurements of respiratory movements can be performed either in a representative sample of the general population, or directly on the patient before irradiation. Reduction of breathing motion can be achieved by using either abdominal compression, breath-hold techniques, or respiratory gating techniques. Abdominal compression can be used to reduce diaphragmatic excursions. Breath-hold can be achieved with active techniques, in which airflow of the patient is temporarily blocked by a valve, or passive techniques, in which the patient voluntarily breath-holds. Respiratory gating techniques use external devices to predict the phase of the breathing cycle while the patient breathes freely. Another approach is tumor-tracking technique, which consists of a real-time localization of a constantly moving tumor. This work describes these different strategies and gives an overview of the literature.

Dynamically accumulated dose and 4D accumulated dose for moving tumors

PURPOSE

The purpose of this work was to investigate the relationship between dynamically accumulated dose (dynamic dose) and 4D accumulated dose (4D dose) for irradiation of moving tumors, and to quantify the dose uncertainty induced by tumor motion.

METHODS

The authors established that regardless of treatment modality and delivery properties, the dynamic dose will converge to the 4D dose, instead of the 3D static dose, after multiple deliveries. The bounds of dynamic dose, or the maximum estimation error using 4D or static dose, were established for the 4D and static doses, respectively. Numerical simulations were performed (1) to prove the principle that for each phase, after multiple deliveries, the average number of deliveries for any given time converges to the total number of fractions (K) over the number of phases (N); (2) to investigate the dose difference between the 4D and dynamic doses as a function of the number of deliveries for deliveries of a "pulsed beam"; and (3) to investigate the dose difference between 4D dose and dynamic doses as a function of delivery time for deliveries of a "continuous beam." A Poisson model was developed to estimate the mean dose error as a function of number of deliveries or delivered time for both pulsed beam and continuous beam.

RESULTS

The numerical simulations confirmed that the number of deliveries for each phase converges to K∕N, assuming a random starting phase. Simulations for the pulsed beam and continuous beam also suggested that the dose error is a strong function of the number of deliveries and∕or total deliver time and could be a function of the breathing cycle, depending on the mode of delivery. The Poisson model agrees well with the simulation.

CONCLUSIONS

Dynamically accumulated dose will converge to the 4D accumulated dose after multiple deliveries, regardless of treatment modality. Bounds of the dynamic dose could be determined using quantities derived from 4D doses, and the mean dose difference between the dynamic dose and 4D dose as a function of number of deliveries and∕or total deliver time was also established.

Visualisation of respiratory tumour motion and co-moving isodose lines in the context of respiratory gating, IMRT and flattening-filter-free beams

Respiratory motion during percutaneous radiotherapy can be considered based on respiration-correlated computed tomography (4DCT). However, most treatment planning systems perform the dose calculation based on a single primary CT data set, even though cine mode displays may allow for a visualisation of the complete breathing cycle. This might create the mistaken impression that the dose distribution were independent of tumour motion. We present a movie visualisation technique with the aim to direct attention to the fact that the dose distribution migrates to some degree with the tumour and discuss consequences for gated treatment, IMRT plans and flattening-filter-free beams. This is a feasibility test for a visualisation of tumour and isodose motion. Ten respiratory phases are distinguished on the CT, and the dose distribution from a stationary IMRT plan is calculated on each phase, to be integrated into a movie of tumour and dose motion during breathing. For one example patient out of the sample of five lesions, the plan is compared with a gated treatment plan with respect to tumour coverage and lung sparing. The interplay-effect for small segments in the IMRT plan is estimated. While the high dose rate, together with the cone-shaped beam profile, makes the use of flattening-filter-free beams more problematic for conformal and IMRT treatment, it can be the option of choice if gated treatment is preferred. The different effects of respiratory motion, dose build-up and beam properties (segments and flatness) for gated vs. un-gated treatment can best be considered if planning is performed on the full 4DCT data set, which may be an incentive for future developments of treatment planning systems.

Proof of concept of MRI-guided tracked radiation delivery: tracking one-dimensional motion

In radiotherapy one aims to deliver a radiation dose to a tumour with high geometrical accuracy while sparing organs at risk (OARs). Although image guidance decreases geometrical uncertainties, treatment of cancer of abdominal organs is further complicated by respiratory motion, requiring intra-fraction motion compensation to fulfil the treatment intent. With an ideal delivery system, the optimal method of intra-fraction motion compensation is to adapt the beam collimation to the moving target using a dynamic multi-leaf collimator (MLC) aperture. The many guidance strategies for such tracked radiation delivery tested up to now mainly use markers and are therefore invasive and cannot deal with target deformations or adaptations for OAR positions. We propose to address these shortcomings using the online MRI guidance provided by an MRI accelerator and present a first step towards demonstration of the technical feasibility of this proposal. The position of a phantom subjected to one-dimensional (1D) periodic translation was tracked using a fast 1D MR sequence. Real-time communication with the MR scanner and control of the MLC aperture were established. Based on the time-resolved position of the phantom, tracked radiation delivery to the phantom was realized. Dose distributions for various delivery conditions were recorded on a gafchromic film. Without motion a sharply defined dose distribution is obtained, whereas considerable blur occurs for delivery to a moving phantom. With compensation for motion, the sharpness of the dose distribution is nearly restored. The total latency in our motion management architecture is approximately 200 ms. Combination of the recorded phantom and aperture positions with the planned dose distribution enabled the reconstruction of the delivered dose in all cases, which illustrates the promise of online dose accumulation and confirms that latency compensation could further enhance our results. For a simple 1D tracked delivery scenario, the technical feasibility of MRI-guided tracked radiation delivery is confirmed. More generic tracking scenarios require advanced MRI, leading to increased acquisition time and more challenging image processing problems. Latency compensation is therefore an important subject of future investigations.

Emission guided radiation therapy for lung and prostate cancers: a feasibility study on a digital patient

PURPOSE

Accurate tumor tracking remains a challenge in current radiation therapy. Many strategies including image guided radiation therapy alleviate the problem to certain extents. The authors propose a new modality called emission guided radiation therapy (EGRT) to accurately and directly track the tumor based on its biological signature. This work is to demonstrate the feasibility of EGRT under two clinical scenarios using a 4D digital patient model.

METHODS

EGRT uses lines of response (LOR's) from positron emission events to direct beamlets of therapeutic radiation through the emission sites inside a tumor. This is accomplished by a radiation delivery system consisting of a Linac and positron emission tomography (PET) detectors on a fast rotating closed-ring gantry. During the treatment of radiotracer-administrated cancer patients, PET detectors collect LOR's from tumor uptake sites and the Linac responds in nearly real-time with beamlets of radiation along the same LOR paths. Moving tumors are therefore treated with a high targeting accuracy. Based on the EGRT concept, the authors design a treatment method with additional modulation algorithms including attenuation correction and an integrated boost scheme. Performance is evaluated using simulations of a lung tumor case with 3D motion and a prostate tumor case with setup errors. The emission process is simulated by Geant4 Application for Tomographic Emission package (GATE) and Linac dose delivery is simulated using a voxel-based Monte Carlo algorithm (VMC++).

RESULTS

In the lung case with attenuation correction, compared to a conventional helical treatment, EGRT achieves a 41% relative increase in dose to 95% of the gross tumor volume (GTV) and a 55% increase to 50% of the GTV. All dose distributions are normalized for the same dose to the lung. In the prostate case with the integrated boost and no setup error, EGRT yields a 19% and 55% relative dose increase to 95% and 50% of the GTV, respectively, when all methods are normalized for the same dose to the rectum. In the prostate case with integrated boost where setup error is present, EGRT contributes a 21% and 52% relative dose increase to 95% and 50% of the GTV, respectively.

CONCLUSIONS

As a new radiation therapy modality with inherent tumor tracking, EGRT has the potential to substantially improve targeting in radiation therapy in the presence of intrafractional and interfractional motion.

A novel four-dimensional radiotherapy planning strategy from a tumor-tracking beam's eye view

To investigate the feasibility of four-dimensional radiotherapy (4DRT) planning from a tumor-tracking beam's eye view (ttBEV) with reliable gross tumor volume (GTV) delineation, realistic normal tissue representation, high planning accuracy and low clinical workload, we propose and validate a novel 4D conformal planning strategy based on a synthesized 3.5D computed tomographic (3.5DCT) image with a motion-compensated tumor. To recreate patient anatomy from a ttBEV in the moving tumor coordinate system for 4DRT planning (or 4D planning), the centers of delineated GTVs in all phase CT images of 4DCT were aligned, and then the aligned CTs were averaged to produce a new 3.5DCT image. This GTV-motion-compensated CT contains a motionless target (with motion artifacts minimized) and motion-blurred normal tissues (with a realistic temporal density average). Semi-automatic threshold-based segmentation of the tumor, lung and body was applied, while manual delineation was used for other organs at risk (OARs). To validate this 3.5DCT-based 4D planning strategy, five patients with peripheral lung lesions of small size (<5 cm(3)) and large motion range (1.2-3.5 cm) were retrospectively studied for stereotactic body radiotherapy (SBRT) using 3D conformal radiotherapy planning tools. The 3.5DCT-based 4D plan (3.5DCT plan) with 9-10 conformal beams was compared with the 4DCT-based 4D plan (4DCT plan). The 4DCT plan was derived from multiple 3D plans based on all phase CT images, each of which used the same conformal beam configuration but with an isocenter shift to aim at the moving tumor and a minor beam aperture and weighting adjustment to maintain plan conformality. The dose-volume histogram (DVH) of the 4DCT plan was created with two methods: one is an integrated DVH (iDVH(4D)), which is defined as the temporal average of all 3D-phase-plan DVHs, and the other (DVH(4D)) is based on the dose distribution in a reference phase CT image by dose warping from all phase plans using the displacement vector field (DVF) from a free-form deformable image registration (DIR). The DVH(3.5D) (for the 3.5DCT plan) was compared with both iDVH(4D) and DVH(4D). To quantify the DVH difference between the 3.5DCT plan and the 4DCT plan, two methods were used: relative difference (%) of the areas underneath the DVH curves and the volumes receiving more than 20% (V20) and 50% (V50) of prescribed dose of these 4D plans. The volume of the delineated GTV from different phase CTs varied dramatically from 24% to 112% among the five patients, whereas the GTV from 3.5DCT deviated from the averaged GTV in 4DCT by only -6%±6%. For planning tumor volume (PTV) coverage, the difference between the DVH(3.5D) and iDVH(4D) was negligible (<1% area), whereas the DVH(3.5D) and DVH(4D) were quite different, due to DIR uncertainty (∼2 mm), which propagates to PTV dose coverage with a pronounced uncertainty for small tumors (0.3-4.0 cm(3)) in stereotactic plans with sharp dose falloff around PTV. For OARs, such as the lung, heart, cord and esophagus, the three DVH curves (DVH(3.5D), DVH(4D) and iDVH(4D)) were found to be almost identical for the same patients, especially in high-dose regions. For the tumor-containing lung, the relative difference of the areas underneath the DVH curves was found to be small (5.3% area on average), of which 65% resulted from the low-dose region (D < 20%). The averaged V20 difference between the two 4D plans was 1.2% ± 0.8%. For the mean lung dose (MLD), the 3.5DCT plan differed from the 4DCT plan by -1.1%±1.3%. GTV-motion-compensated CT (3.5DCT) produces an accurate and reliable GTV delineation, which is close to the mean GTV from 4DCT. The 3.5DCT plan is equivalent to the 4DCT plan with <1% dose difference to the PTV and negligible dose difference in OARs. The 3.5DCT approach simplifies 4D planning and provides accurate dose calculation without a substantial increase of clinical workload for motion-tracking delivery to treat small peripheral lung tumors with large motion.

Challenges and opportunities in patient-specific, motion-managed and PET/CT-guided radiation therapy of lung cancer: review and perspective

The increasing interest in combined positron emission tomography (PET) and computed tomography (CT) to guide lung cancer radiation therapy planning has been well documented. Motion management strategies during treatment simulation PET/CT imaging and treatment delivery have been proposed to improve the precision and accuracy of radiotherapy. In light of these research advances, why has translation of motion-managed PET/CT to clinical radiotherapy been slow and infrequent? Solutions to this problem are as complex as they are numerous, driven by large inter-patient variability in tumor motion trajectories across a highly heterogeneous population. Such variation dictates a comprehensive and patient-specific incorporation of motion management strategies into PET/CT-guided radiotherapy rather than a one-size-fits-all tactic. This review summarizes challenges and opportunities for clinical translation of advances in PET/CT-guided radiotherapy, as well as in respiratory motion-managed radiotherapy of lung cancer. These two concepts are then integrated into proposed patient-specific workflows that span classification schemes, PET/CT image formation, treatment planning, and adaptive image-guided radiotherapy delivery techniques.

Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model

PURPOSE

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data.

METHODS

Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans.

RESULTS

Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states.

CONCLUSIONS

Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data.

Extracting fuzzy classification rules from texture segmented HRCT lung images

Automatic tools for detection and identification of lung and lesion from high-resolution CT (HRCT) are becoming increasingly important both for diagnosis and for delivering high-precision radiation therapy. However, development of robust and interpretable classifiers still presents a challenge especially in case of non-small cell lung carcinoma (NSCLC) patients. In this paper, we have attempted to devise such a classifier by extracting fuzzy rules from texture segmented regions from HRCT images of NSCLC patients. A fuzzy inference system (FIS) has been constructed starting from a feature extraction procedure applied on overlapping regions from the same organs and deriving simple if-then rules so that more linguistically interpretable decisions can be implemented. The proposed method has been tested on 138 regions extracted from CT scan images acquired from patients with lung cancer. Assuming two classes of tissues C1 (healthy tissues) and C2 (lesion) as negative and positive, respectively; preliminary results report an AUC = 0.98 for lesions and AUC = 0.93 for healthy tissue, with an optimal operating condition related to sensitivity = 0.96, and specificity = 0.98 for lesions and sensitivity 0.99, and specificity = 0.94 for healthy tissue. Finally, the following results have been obtained: false-negative rate (FNR) = 6 % (C1), FNR = 2 % (C2), false-positive rate (FPR) = 4 % (C1), FPR = 3 % (C2), true-positive rate (TPR) = 94 %, (C1) and TPR = 98 % (C2).

A method to evaluate dose errors introduced by dose mapping processes for mass conserving deformations

PURPOSE

To present a method to evaluate the dose mapping error introduced by the dose mapping process. In addition, apply the method to evaluate the dose mapping error introduced by the 4D dose calculation process implemented in a research version of commercial treatment planning system for a patient case.

METHODS

The average dose accumulated in a finite volume should be unchanged when the dose delivered to one anatomic instance of that volume is mapped to a different anatomic instance-provided that the tissue deformation between the anatomic instances is mass conserving. The average dose to a finite volume on image S is defined as d(S)=e(s)/m(S), where e(S) is the energy deposited in the mass m(S) contained in the volume. Since mass and energy should be conserved, when d(S) is mapped to an image R(d(S→R)=d(R)), the mean dose mapping error is defined as Δd(m)=|d(R)-d(S)|=|e(R)/m(R)-e(S)/m(S)|, where the e(R) and e(S) are integral doses (energy deposited), and m(R) and m(S) are the masses within the region of interest (ROI) on image R and the corresponding ROI on image S, where R and S are the two anatomic instances from the same patient. Alternatively, application of simple differential propagation yields the differential dose mapping error, Δd(d)=|∂d∂e*Δe+∂d∂m*Δm|=|(e(S)-e(R))m(R)-(m(S)-m(R))m(R) (2)*e(R)|=α|d(R)-d(S)| with α=m(S)/m(R). A 4D treatment plan on a ten-phase 4D-CT lung patient is used to demonstrate the dose mapping error evaluations for a patient case, in which the accumulated dose, D(R)=∑(S=0) (9)d(S→R), and associated error values (ΔD(m) and ΔD(d)) are calculated for a uniformly spaced set of ROIs.

RESULTS

For the single sample patient dose distribution, the average accumulated differential dose mapping error is 4.3%, the average absolute differential dose mapping error is 10.8%, and the average accumulated mean dose mapping error is 5.0%. Accumulated differential dose mapping errors within the gross tumor volume (GTV) and planning target volume (PTV) are lower, 0.73% and 2.33%, respectively.

CONCLUSIONS

A method has been presented to evaluate the dose mapping error introduced by the dose mapping process. This method has been applied to evaluate the 4D dose calculation process implemented in a commercial treatment planning system. The method could potentially be developed as a fully-automatic QA method in image guided adaptive radiation therapy (IGART).

4D CT image acquisition errors in SBRT of liver identified using correlation

In the AAPM Report 80,⁽¹⁾ the imaging modality of 4D CT and respiration‐correlated CT was declared a “promising solution for obtaining high‐quality CT data in the presence of respiratory motion”. To gather anatomically correct data over time, the existence of correlation between the internal organ movement and an external surrogate has to be assumed. For the in‐house evaluation of such correlation, we retrospectively analyzed 21 four‐dimensional computer tomography (4D CT) scans of five patients, out of which the artifacts experienced in three patients are shown here. To provide context and a baseline for the analysis of patient motion, a real‐tissue liver phantom was used with a solid water block and liver tissue. The superior–inferior motion of fiducials in phantom and patients was correlated to the recorded anterior–posterior motion of an external surrogate marker on the chest. The use of a solid water block yielded a measurable correlation coefficient of 0.98 or better using a sinusoidal animation pattern. With sinusoidally‐animated liver tissue, the minimum correlation observed was 0.96. Comparing this to retrospective patient data, we found three cases of a change in the correlation coefficient, or simply a low correlation. The source of this low correlation was investigated by careful examination of the breathing traces and the CT‐phase assignments used to reconstruct the datasets. Consequences of nonregular breathing are elaborated on. We demonstrate the impact of wrong phase assignments and missing image information in the 4D CT phase sampling processes. We also show how daily patient‐based correlation analysis can indicate changes in breathing traces, which can be significant enough to decrease, or completely eliminate, previously existing correlation.

PACS numbers: 87.57.‐s, 87.57.Q‐, 87.57.cp, 87.57.N‐, 87.55.Qr

Real time 4D IMRT treatment planning based on a dynamic virtual patient model: proof of concept

PURPOSE

To develop a novel four-dimensional (4D) intensity modulated radiation therapy (IMRT) treatment planning methodology based on dynamic virtual patient models.

METHODS

The 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).

RESULTS

Under 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.

CONCLUSIONS

The 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.

Three-dimensional characterization of regional lung deformation

The deformation of the lung during inspiration and expiration involves regional variations in volume change and orientational preferences. Studies have reported techniques for measuring the displacement field in the lung based on imaging or image registration. However, means of interpreting all the information in the displacement field in a physiologically relevant manner is lacking. We propose three indices of lung deformation that are determinable from the displacement field: the Jacobian--a measure of volume change, the anisotropic deformation index--a measure of the magnitude of directional preference in volume change and a slab-rod index--a measure of the nature of directional preference in volume change. To demonstrate the utility of these indices, they were determined for six human subjects using deformable image registration on static CT images, registered from FRC to TLC. Volume change was elevated in the inferior-dorsal region as should be expected for breathing in the supine position. The anisotropic deformation index was elevated in the inferior region owing to proximity to the diaphragm and in the lobar fissures owing to sliding. Vessel regions in the lung had a significantly rod-like deformation compared to the whole lung. Compared to upper lobes, lower lobes exhibited significantly greater volume change (19.4% and 21.3% greater in the right and left lungs on average; p<0.005) and anisotropy in deformation (26.3% and 21.8% greater in the right and left lungs on average; p<0.05) with remarkable consistency across subjects. The developed deformation indices lend themselves to exhaustive and physiologically intuitive interpretations of the displacement fields in the lung determined through image-registration techniques or finite element simulations.

Characterization and identification of spatial artifacts during 4D-CT imaging

PURPOSE

The purpose of this work is twofold: First, to characterize the artifacts occurring in helical 4D-CT imaging; second, to propose a method that can automatically identify the artifacts in 4D-CT images. The authors have designed a process that can automatically identify the artifacts in 4D-CT images, which may be invaluable in quantifying the quality of 4D-CT images and reducing the artifacts from the reconstructed images on a large dataset.

METHODS

Given two adjacent stacks obtained from the same respiration phase, the authors determine if there are artifacts between them. The proposed method uses a "bridge" stack strategy to connect the two stacks. Using normalized cross correlation convolution (NCCC), the two stacks are mapped to the bridge stack and the best matching positions can be located. Using this position information, the authors can then determine if there are artifacts between the two stacks. By combining the matching positions with NCCC values, the performance can be improved.

RESULTS

To validate the method, three expert observers independently labeled over 600 stacks on five patients. The results confirmed that high performance was obtained using the proposed method. The average sensitivity was about 0.87 and the average specificity was 0.82. The proposed method also outperformed the method of using respiratory signal (sensitivity increased from 0.50 to 0.87 and specificity increased from 0.70 to 0.82).

CONCLUSIONS

This study shows that the spatial artifacts during 4D-CT imaging are characterized and can be located automatically by the proposed method. The method is relatively simple but effective. It provides a way to evaluate the artifacts more objectively and accurately. The reported approach has promising potential for automatically identifying the types and frequency of artifacts on large scale 4D-CT image dataset.

Pulmonary kinematics from image data: a review

The effects of certain lung pathologies include alterations in lung physiology negatively affecting pulmonary compliance. Current approaches to diagnosis and treatment assessment of lung disease commonly rely on pulmonary function testing. Such testing is limited to global measures of lung function, neglecting regional measurements, which are critical for early diagnosis and localization of disease. Increased accessibility to medical image acquisition strategies with high spatiotemporal resolution coupled with the development of sophisticated intensity-based and geometric registration techniques has resulted in the recent exploration of modeling pulmonary motion for calculating local measures of deformation. In this review, the authors provide a broad overview of such research efforts for the estimation of pulmonary deformation. This includes discussion of various techniques, current trends in validation approaches, and the public availability of software and data resources.

Semiautomatic method to identify the best phase for gated RT in lung region by 4D-PET/CT acquisitions

PURPOSE

Delineating tumor motion by four-dimensional positron emission tomography/computed tomography (4D-PET/CT) is a crucial step for gated radiotherapy (RT). This article quantitatively evaluates semiautomatic algorithms for tumor shift estimation in the lung region due to patient respiration by 4D-PET/CT, in order to support the selection of the best phases for gated RT, by considering the most stable phases of the breathing cycle.

METHODS

Three mobile spheres and ten selected lesions were included in this study. 4D-PET/CT data were reconstructed and classified into six/ten phases. The semiautomatic algorithms required the generation of single sets of images representative of the full target motion, used as masks for segmenting the phases. For 4D-CT, a pre-established HU range was used, whereas three thresholds (100%, 80%, and 40%) were evaluated for 4D-PET. By using these segmentations, the authors estimated the lesion motion from the shifting centroids, and the phases with the least motion were also deduced including the phases with a curve slope less than 2 mm/ delta phase. The proposed algorithms were validated by comparing the results to those generated entirely by manual contouring.

RESULTS

In the phantom study, the mean difference between the manual contour and the semiautomatic technique was 0.1 +/- 0.1 mm for 4D-CT and 0.2 +/- 0.1 mm for the 4D-PET based on 40% threshold. In the patients' series, the mean difference was 0.9 +/- 0.6 mm for 4D-CT and 0.8 +/- 0.2 mm for the 4D-PET based on 40% threshold.

CONCLUSIONS

Estimation of lesion motion by the proposed semiautomatic algorithm can be used to evaluate tumor motion due to breathing.

Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration

Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory motion model is capable of providing valuable prior knowledge in many fields of applications. We present two examples of possible applications in radiation therapy and image guided diagnosis.

Monte Carlo dose calculation on deforming anatomy

This article presents the implementation and validation of a dose calculation approach for deforming anatomical objects. Deformation is represented by deformation vector fields leading to deformed voxel grids representing the different deformation scenarios. Particle transport in the resulting deformed voxels is handled through the approximation of voxel surfaces by triangles in the geometry implementation of the Swiss Monte Carlo Plan framework. The focus lies on the validation methodology which uses computational phantoms representing the same physical object through regular and irregular voxel grids. These phantoms are chosen such that the new implementation for a deformed voxel grid can be compared directly with an established dose calculation algorithm for regular grids. Furthermore, separate validation of the aspects voxel geometry and the density changes resulting from deformation is achieved through suitable design of the validation phantom. We show that equivalent results are obtained with the proposed method and that no statistically significant errors are introduced through the implementation for irregular voxel geometries. This enables the use of the presented and validated implementation for further investigations of dose calculation on deforming anatomy.

[4D-CT scan and radiotherapy for hepatocellular carcinoma: role in the definition of internal target volume (ITV)]

PURPOSE

To evaluate the role of 4D-CT scan and the breath-related margins in the definition of internal target volume (ITV) during radiotherapy for hepatocellular carcinoma.

PATIENTS AND METHODS

All patients treated for hepatocellular carcinoma that underwent a 4D-CT simulation scan were retrospectively analysed in order to assess breath-related movements of GTV in the 3-D directions. After a standard CT-scan simulation performed to contour GTV and organs at risk (OARs), a 4D-scan simulation was then realized in order to contour ITV. Margins to be added for every patient to pass from GTV to ITV were calculated and evaluated also regarding liver lobe and GTV size (< or>5 cm).

RESULTS

Twenty-seven hepatocellular carcinoma patients were evaluated (total: 28 lesions). Median tumor movements in the craniocaudal, lateral and anteroposterior direction were 8.6mm (range: 0-72.9 mm), 6.5mm (range: 1-68.1mm) and 9.1mm (range: 1-34 mm), respectively. ITV had a median volume increase of 94% (range: 8-403%).

CONCLUSION

Tumour breath-related displacements are significant. 4D-CT simulation scan allows to precisely define these displacements and to tailor the treatment. A precise evaluation of breath-related effects on GTV is essential, particularly with new conformal radiotherapy techniques as intensity modulated radiotherapy (IMRT) and/or stereotactic body radiotherapy.

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.

[Radiotherapy of hepatic metastases]

Non-invasive treatment of hepatic metastases has become a focal point of interdisciplinary oncology especially since the advent of stereotactic radiation techniques. Worldwide several centers have shown that this treatment is a curative and well tolerated regimen with excellent rates of local control. Modern devices which combine radiation therapy with imaging techniques (image-guided radiotherapy) in particular allow precise dose application, especially for hypofractionated treatment concepts requiring daily repositioning.

Imaging in radiation oncology: a perspective

This paper reviews the integration of imaging and radiation oncology, and discusses challenges and opportunities for improving the practice of radiation oncology with imaging.

An inherent goal of radiation therapy is to deliver enough dose to the tumor to eradicate all cancer cells or to palliate symptoms, while avoiding normal tissue injury. Imaging for cancer diagnosis, staging, treatment planning, and radiation targeting has been integrated in various ways to improve the chance of this occurring. A large spectrum of imaging strategies and technologies has evolved in parallel to advances in radiation delivery. The types of imaging can be categorized into offline imaging (outside the treatment room) and online imaging (inside the treatment room, conventionally termed image-guided radiation therapy). The direct integration of images in the radiotherapy planning process (physically or computationally) often entails trade-offs in imaging performance. Although such compromises may be acceptable given specific clinical objectives, general requirements for imaging performance are expected to increase as paradigms for radiation delivery evolve to address underlying biology and adapt to radiation responses. This paper reviews the integration of imaging and radiation oncology, and discusses challenges and opportunities for improving the practice of radiation oncology with imaging.

A simple respiratory indicator for irradiation during voluntary breath holding: a one-touch device without electronic materials

PURPOSE

To evaluate the use, structural principles, operation, and acquired reproducibility of a respiratory monitoring device to be used for voluntary patient breath holding.

MATERIALS AND METHODS

Evaluation was performed of a respiratory monitoring device that enables determination of the respiratory level in a patient by measuring the movement of two contacts on the abdomen and chest wall. Neither metallic nor electronic materials are used in the mechanics for this device. The initial study group comprised 21 consecutive patients (15 men, six women; mean age, 75 years; range, 56-92 years) with lung or abdominal tumors who underwent examination with the device and computed tomography (CT) for three-dimensional reproducibility of lung base position during voluntary breath holding with or without use of the device.

RESULTS

One patient with mild dementia was excluded; in most of the remaining 20 patients, high reproducibility of the breath-holding position was achieved in a short time with the device. In these 20 patients who were able to adapt to use of the device, three-dimensional mean maximum differences in lung base position during three random voluntary breath holds were 2.0 mm along the cranial-caudal axis, 1.5 mm along the anterior-posterior axis, and 1.2 mm along the right-left axis. The differences in all axes were significantly smaller with use of the respiratory monitoring device than without the device.

CONCLUSION

The device demonstrates satisfactory reproducibility of voluntary patient breath holding easily and inexpensively and may offer a convenient device for easy use during irradiation with voluntary breath-holding conditions that require a small internal margin.

Four-dimensional intensity-modulated radiation therapy planning for dynamic tracking using a direct aperture deformation (DAD) method

PURPOSE

Planning for the delivery of intensity-modulated radiation therapy (IMRT) to a moving target, referred to as four-dimensional (4D) IMRT planning, is a crucial step for achieving the treatment objectives for sites that move during treatment delivery. The authors proposed a simplistic method that accounts for both rigid and nonrigid respiration-induced target motion based on 4D computed tomography (4DCT) data sets.

METHODS

A set of MLC apertures and weights was first optimized on a reference phase of a 4DCT data set. At each beam angle, the apertures were morphed from the reference phase to each of the remaining phases according to the relative shape changes in the beam's eye view of the target. Three different planning schemes were evaluated for two lung cases and one pancreas patient: (1) Individually optimizing each breathing phase; (2) optimizing the reference phase and shifting the optimized apertures to other breathing phases based on a rigid-body image registration; and (3) optimizing the reference phase and deforming the optimized apertures to the other phases based on the deformation and translation of target contours. Planning results using scheme 1 serves as the "gold standard" for plan quality assessment; scheme 2 is the method previously proposed in the literature; and scheme 3 is the method the authors proposed in this article. The optimization results were compared between the three schemes for all three cases.

RESULTS

The proposed scheme 3 is comparable to scheme 1 in plan quality, and provides improved target coverage and conformity with similar normal tissue dose compared with scheme 2.

CONCLUSIONS

Direct aperture deformation method for 4D IMRT planning improves upon methods that only consider rigid-body motion and achieves a plan quality close to that optimized for each of the phases.

Respiratory organ motion and dosimetric impact on breast and nodal irradiation

PURPOSE

To examine the respiratory motion for target and normal structures during whole breast and nodal irradiation and the resulting dosimetric impact.

METHODS AND MATERIALS

Four-dimensional CT data sets of 18 patients with early-stage breast cancer were analyzed retrospectively. A three-dimensional conformal dosimetric plan designed to irradiate the breast was generated on the basis of CT images at 20% respiratory phase (reference phase). The reference plans were copied to other respiratory phases at 0% (end of inspiration) and 50% (end of expiration) to simulate the effects of breathing motion on whole breast irradiation. Dose-volume histograms, equivalent uniform dose, and normal tissue complication probability were evaluated and compared.

RESULTS

Organ motion of up to 8.8mm was observed during free breathing. A large lung centroid movement was typically associated with a large shift of other organs. The variation of planning target volume coverage during a free breathing cycle is generally within 1%-5% (17 of 18 patients) compared with the reference plan. However, up to 28% of V(45) variation for the internal mammary nodes was observed. Interphase mean dose variations of 2.2%, 1.2%, and 1.4% were observed for planning target volume, ipsilateral lung, and heart, respectively. Dose variations for the axillary nodes and brachial plexus were minimal.

CONCLUSIONS

The doses delivered to the target and normal structures are different from the planned dose based on the reference phase. During normal breathing, the dosimetric impact of respiratory motion is clinically insignificant with the exception of internal mammary nodes. However, noticeable degradation in dosimetric plan quality may be expected for the patients with large respiratory motion.