Monte Carlo as a four-dimensional radiotherapy treatment-planning tool to account for respiratory motion

Validation of 4D Monte Carlo dose calculations using a programmable deformable lung phantom

PURPOSE

To validate the accuracy of 4D Monte Carlo (4DMC) simulations to calculate dose deliveries to a deforming anatomy in the presence of realistic respiratory motion traces. A previously developed deformable lung phantom comprising an elastic tumor was modified to enable programming of arbitrary motion profiles. 4D simulations of the dose delivered to the phantom were compared with the measurements.

METHODS

The deformable lung phantom moving with irregular breathing patterns was irradiated using static and VMAT beam deliveries. Using the RADPOS 4D dosimetry system, point doses were measured inside and outside the tumor. Dose profiles were acquired using films along the motion path of the tumor (S-I). In addition to dose measurements, RADPOS was used to record the motion of the tumor during dose deliveries. Dose measurements were then compared against 4DMC simulations with EGSnrc/4DdefDOSXYZnrc using the recorded tumor motion.

RESULTS

The agreements between dose profiles from measurements and simulations were determined to be within 2%/2 mm. Point dose agreements were within 2σ of experimental and/or positional/dose reading uncertainties. 4DMC simulations were shown to accurately predict the sensitivity of delivered dose to the starting phase of breathing motions. We have demonstrated that our 4DMC method, combined with RADPOS, can accurately simulate realistic dose deliveries to a deforming anatomy moving with realistic breathing traces. This 4DMC tool has the potential to be used as a quality assurance tool to verify treatments involving respiratory motion. Adaptive treatment delivery is another area that may benefit from the potential of this 4DMC tool.

4D Monte Carlo dose calculations for pre-treatment quality assurance of VMAT SBRT: a phantom-based feasibility study

Volumetric arc therapy (VMAT) for lung stereotactic body radiotherapy (SBRT) is challenging due to both breathing-induced motion and the dynamic components of the linear accelerator. In this study, a 4D Monte Carlo (4DMC) dose calculation method for VMAT SBRT is proposed and the feasibility of the method is evaluated. A rigidly-moving lung phantom was imaged using four dimensional computed tomography (4DCT). VMAT SBRT plans were generated on the average intensity projection dataset using the internal target volume (ITV) strategy (ITV-plan) and a single phase to simulate a dynamic treatment-couch tracking technique (TRACKING-plan). 4DMC simulations were performed and compared to 3D Monte Carlo (3DMC) and 3D- and 4D- calculations in the treatment planning system using the adaptive convolution (AC) algorithm. Dose metrics calculated for the ITV-plan showed an overestimation with 3D adaptive convolution (3DAC) for D[Formula: see text] (GTV) by 3.5% and by 2.0% for 3DMC, both compared to 4DMC. The TRACKING-plan D[Formula: see text] (GTV) calculated with the 3DAC method overestimated by 2.0% compared with 4DMC. Deviations between the calculation methods for D _mean (Lung) and D[Formula: see text] (PTV) were minimal. For both plans, measurements were taken with EBT3 film inside the phantom tumour. EBT3 film profiles showed good agreement with 4DMC for the TRACKING-plan giving a gamma pass rate of 97.2% for 3%/3 mm global and for 3DAC compared with measured, 95.8%. Whereas for the ITV-plan, the 3D profiles varied from film in the ITV periphery region with a pass rates of 50% and 48.6% for 3DAC and 3DMC, respectively. 4DMC agreed more closely to measurements for this plan with a pass rate of 95.8%. We have proposed an accurate method to perform 4D dose calculations for pre-treatment quality assurance of VMAT SBRT. The method was compared to experimental measurements and for both plans, 4DMC dose agreed with measurements more closely than other evaluated dose calculation methods. This study has demonstrated the feasibility of this 4DMC method.

Clinical implementations of 4D pencil beam scanned particle therapy: Report on the 4D treatment planning workshop 2016 and 2017

In 2016 and 2017, the 8th and 9th 4D treatment planning workshop took place in Groningen (the Netherlands) and Vienna (Austria), respectively. This annual workshop brings together international experts to discuss research, advances in clinical implementation as well as problems and challenges in 4D treatment planning, mainly in spot scanned proton therapy. In the last two years several aspects like treatment planning, beam delivery, Monte Carlo simulations, motion modeling and monitoring, QA phantoms as well as 4D imaging were thoroughly discussed. This report provides an overview of discussed topics, recent findings and literature review from the last two years. Its main focus is to highlight translation of 4D research into clinical practice and to discuss remaining challenges and pitfalls that still need to be addressed and to be overcome.

Inverse-planned deliverable 4D-IMRT for lung SBRT

PURPOSE

We present a particle swarm optimization (PSO)-based technique to create deliverable four-dimensional (4D = 3D + time) intensity-modulated radiation therapy (IMRT) plans for lung stereotactic body radiotherapy (SBRT). The 4D planning concept uses respiratory motion as an additional degree of freedom to achieve further sparing of organs at risk (OARs). The 4D-IMRT plan involves the delivery of an order of magnitude more IMRT apertures (~15,000-20,000), with potentially large interaperture variations in the delivered fluence, compared to conventional (i.e., 3D) IMRT. In order to deliver the 4D plan in an efficient manner, we present an optimization-based aperture sequencing technique.

METHOD

A graphic processing unit (GPU)-enabled PSO-based inverse planning engine, developed and integrated with a research version of the Eclipse (Varian, Palo Alto, CA) treatment planning system (TPS), was employed to create 4D-IMRT plans as follows. Four-dimensional computed tomography scans (4DCTs) and beam configurations from clinical treatment plans of seven lung cancer patients were retrospectively collected, and in each case, the PSO engine iteratively adjusted aperture monitor unit (MU) weights for all beam apertures across all respiratory phases to optimize OAR dose sparing while maintaining planning target volume (PTV) coverage. We calculated the transition times from each aperture to all other apertures for each beam, taking into account the maximum leaf velocity of the multileaf collimator (MLC), and developed a mixed integer optimization technique for aperture sequencing. The goal of sequencing was to maximize delivery efficiency (i.e., minimize the time required to deliver the dose map) by accounting for leaf velocity, aperture MUs, and duration of each respiratory phase. The efficiency of the proposed delivery method was compared with that of a greedy algorithm which chose only from neighboring apertures for the subsequent steps in the sequence.

RESULTS

4D-IMRT-optimized plans achieved PTV coverage comparable to clinical plans while improving OAR sparing by an average of 39.7% for D max heart, 20.5% for D max esophagus, 25.6% for D max spinal cord, and 2.1% for V 13 lung (with D max standing for maximum dose and V 13 standing for volume receiving ≥ 13 Gy). Our mixed integer optimization-based aperture sequencing enabled the delivery to be performed in fewer cycles compared to the greedy method. This reduction was 89 ± 79 cycles corresponding to an improvement of 15.94 ± 8.01%, when considering respiratory cycle duration of 4 s, and 55 ± 33 cycles corresponding to an improvement of 15.14 ± 4.45%, when considering respiratory cycle duration of 6 s.

CONCLUSION

PSO-based 4D-IMRT represents an attractive technique to further improve OAR sparing in lung SBRT. Efficient delivery of a large number of sparse apertures (control points) introduces a challenge in 4D-IMRT treatment planning and delivery. Through judicious optimization of the aperture sequence across all phases, such delivery can be performed on a clinically feasible time scale.

Effects of magnetic field orientation and strength on the treatment planning of nonsmall cell lung cancer

PURPOSE

Magnetic resonance image-guided radiotherapy (MRgRT) has the potential to increase the accuracy of radiation treatment delivery. Several research groups have developed hybrid MRgRT devices differing by radiation source used and magnetic field orientation and strength. In this work, we investigate the impact of different magnetic field orientations and strengths on the treatment planning of nonsmall cell lung cancer patients (NSCLC).

METHODS

A framework using the in-house developed treatment planning system matRad and the EGSnrc Monte Carlo code system was introduced to perform Monte Carlo-based treatment planning in the presence of a magnetic field. A specialized spectrum-based source model for the beam qualities of 6 MV and cobalt-60 was applied. Optimized plans for stereotactic body radiation therapy (SBRT) and intensity-modulated radiation therapy (IMRT) were generated for four NSCLC patients in the presence of different magnetic field orientations and strengths which are applied in hybrid MRgRT devices currently under development or in clinical use.

RESULTS

SBRT and IMRT treatment planning could be performed with consistent plan quality for all magnetic field setups. Only minor effects on the treatment planning outcome were found in the case of magnetic fields orientated perpendicular to the beam direction. Compared to the perpendicular magnetic field orientation, the inline orientation showed the capability to reduce the dose to lung while maintaining equal target coverage. Particularly for tumors with a central position in lung, a distinct dose reduction was obtained which led to a maximum reduction of mean lung dose by 18.5% (0.5 Gy), when applying a 1 T inline magnetic field.

CONCLUSION

All plans generated in this work obtained dose metrics within clinical constraints according to RTOG guidelines. When considering conventional dose metrics, no detrimental effects due to the magnetic fields were observed on the dose to the tumor or to organs at risk. An evaluation of the effects on skin dose was not ascertainable due to the simplified specification of the source model used. By accounting for the magnetic field during treatment planning, a dose reduction in lung could be achieved for inline-oriented magnetic fields. An inline orientation of the magnetic field therefore showed a potential benefit when treating NSCLC with MRgRT.

Monte Carlo modeling of ultrasound probes for image guided radiotherapy

PURPOSE

To build Monte Carlo (MC) models of two ultrasound (US) probes and to quantify the effect of beam attenuation due to the US probes for radiation therapy delivered under real-time US image guidance.

METHODS

MC models of two Philips US probes, an X6-1 matrix-array transducer and a C5-2 curved-array transducer, were built based on their megavoltage (MV) CT images acquired in a Tomotherapy machine with a 3.5 MV beam in the EGSnrc, BEAMnrc, and DOSXYZnrc codes. Mass densities in the probes were assigned based on an electron density calibration phantom consisting of cylinders with mass densities between 0.2 and 8.0 g/cm(3). Beam attenuation due to the US probes in horizontal (for both probes) and vertical (for the X6-1 probe) orientation was measured in a solid water phantom for 6 and 15 MV (15 × 15) cm(2) beams with a 2D ionization chamber array and radiographic films at 5 cm depth. The MC models of the US probes were validated by comparison of the measured dose distributions and dose distributions predicted by MC. Attenuation of depth dose in the (15 × 15) cm(2) beams and small circular beams due to the presence of the probes was assessed by means of MC simulations.

RESULTS

The 3.5 MV CT number to mass density calibration curve was found to be linear with R(2) > 0.99. The maximum mass densities in the X6-1 and C5-2 probes were found to be 4.8 and 5.2 g/cm(3), respectively. Dose profile differences between MC simulations and measurements of less than 3% for US probes in horizontal orientation were found, with the exception of the penumbra region. The largest 6% dose difference was observed in dose profiles of the X6-1 probe placed in vertical orientation, which was attributed to inadequate modeling of the probe cable. Gamma analysis of the simulated and measured doses showed that over 96% of measurement points passed the 3%/3 mm criteria for both probes placed in horizontal orientation and for the X6-1 probe in vertical orientation. The X6-1 probe in vertical orientation caused the highest attenuation of the 6 and 15 MV beams, which at 10 cm depth accounted for 33% and 43% decrease compared to the respective (15 × 15) cm(2) open fields. The C5-2 probe in horizontal orientation, on the other hand, caused a dose increase of 10% and 53% for the 6 and 15 MV beams, respectively, in the buildup region at 0.5 cm depth. For the X6-1 probe in vertical orientation, the dose at 5 cm depth for the 3-cm diameter 6 MV and 5-cm diameter 15 MV beams was attenuated compared to the corresponding open fields to a greater degree by 65% and 43%, respectively.

CONCLUSIONS

MC models of two US probes used for real-time image guidance during radiotherapy have been built. Due to the high beam attenuation of the US probes, the authors generally recommend avoiding delivery of treatment beams that intersect the probe. However, the presented MC models can be effectively integrated into US-guided radiotherapy treatment planning in cases for which beam avoidance is not practical due to anatomy geometry.

Improving radiotherapy planning, delivery accuracy, and normal tissue sparing using cutting edge technologies

In the United States, more than half of all new invasive cancers diagnosed are non-small cell lung cancer, with a significant number of these cases presenting at locally advanced stages, resulting in about one-third of all cancer deaths. While the advent of stereotactic ablative radiation therapy (SABR, also known as stereotactic body radiotherapy, or SBRT) for early-staged patients has improved local tumor control to >90%, survival results for locally advanced stage lung cancer remain grim. Significant challenges exist in lung cancer radiation therapy including tumor motion, accurate dose calculation in low density media, limiting dose to nearby organs at risk, and changing anatomy over the treatment course. However, many recent technological advancements have been introduced that can meet these challenges, including four-dimensional computed tomography (4DCT) and volumetric cone-beam computed tomography (CBCT) to enable more accurate target definition and precise tumor localization during radiation, respectively. In addition, advances in dose calculation algorithms have allowed for more accurate dosimetry in heterogeneous media, and intensity modulated and arc delivery techniques can help spare organs at risk. New delivery approaches, such as tumor tracking and gating, offer additional potential for further reducing target margins. Image-guided adaptive radiation therapy (IGART) introduces the potential for individualized plan adaptation based on imaging feedback, including bulky residual disease, tumor progression, and physiological changes that occur during the treatment course. This review provides an overview of the current state of the art technology for lung cancer volume definition, treatment planning, localization, and treatment plan adaptation.

A mass-conserving 4D XCAT phantom for dose calculation and accumulation

PURPOSE

The XCAT phantom is a realistic 4D digital torso phantom that is widely used in imaging and therapy research. However, lung mass is not conserved between respiratory phases of the phantom, making detailed dosimetric simulations and dose accumulation unphysical. A framework is developed to correct this issue by enforcing local mass conservation in the XCAT lung. Dose calculations are performed to assess the implications of neglecting mass conservation, and to demonstrate an application of the phantom to calculate the accumulated delivered dose in an irregularly breathing patient.

METHODS

A displacement vector field (DVF) between each respiratory state and a reference image is generated from the XCAT motion model and its divergence is calculated and used to correct the lung density. A series of phantoms with regular and irregular breathing (based on patient data) are generated and modified to conserve mass. Monte Carlo methods are used to simulate conventional and SBRT treatment delivery. The calculated dose is deformed and accumulated using the DVF. Results from the mass-conserving and original XCAT are compared. A 4DCT is simulated for the irregularly breathing patient, and a 4DCT-based dose estimate is compared with the accumulated delivered dose.

RESULTS

The presented framework successfully conserves mass in the XCAT lung. The spatial distribution of the lung dose was qualitatively changed by the use of a mass conservation in the XCAT; however, the corresponding DVH did not change significantly. The comparison of the delivered dose with the 4DCT-based prediction shows similar lung metric results, however dose differences of 10% can be seen in some spatial regions.

CONCLUSIONS

The XCAT phantom has been successfully modified so that it conserves lung mass during respiration, enabling it to be used as a tool to perform dose accumulation studies in the lung without relying on deformable image registration. Neglecting mass conservation can result in erroneous spatial distributions of the dose in the lung. Using this tool to simulate patient treatments reveals differences between the planned dose and the calculated delivered dose for the full treatment. The software is freely available from the authors.

Multigating, a 4D optimized beam tracking in scanned ion beam therapy

The treatment of moving tumors with a scanned ion beam is challenging due to interplay effects and changing beam range. We propose multigating, as a method for 4D-treatment optimization and delivery. In 3D beam tracking, tracking vectors are added during delivery to beam spot positions based on the detected motion phase. This has the disadvantage of dose errors in case of complex motion patterns and an uncertain out-of-target dose distribution. In multigating, the motion phase for each beam spot is predefined, which allows to add the tracking vector prior to beam weight optimization on all motion phases. The synchronization of delivery and target motion is assured by fast gating. The feasibility of the delivery was shown in a film experiment and required only minor software modification to the treatment planning system. In a treatment planning study in 4 lung cancer patients, target coverage could be restored to the level of a static reference plan by multigating (V95 > 99%) but not by standard beam tracking (V95 < 95%). The conformity of the multigating plans was only slightly lower than those of the static plan, with a conformity number of 72.0% (median, range 64.6–76.6%) compared to 75.8% (70.8–81.5%) in spite of target motion of up to 22 mm. In conclusion, we showed the technical feasibility of multigating, a 4D-optimization and delivery method using scanned beams that allows for conformal and homogeneous dose delivery to moving targets also in case of complex motion.

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.

Advances in 4D radiation therapy for managing respiration: part II - 4D treatment planning

The development of 4D CT imaging technology made possible the creation of patient models that are reflective of respiration-induced anatomical changes by adding a temporal dimension to the conventional 3D, spatial-only, patient description. This had opened a new venue for treatment planning and radiation delivery, aimed at creating a comprehensive 4D radiation therapy process for moving targets. Unlike other breathing motion compensation strategies (e.g. breath-hold and gating techniques), 4D radiotherapy assumes treatment delivery over the entire respiratory cycle - an added bonus for both patient comfort and treatment time efficiency. The time-dependent positional and volumetric information holds the promise for optimal, highly conformal, radiotherapy for targets experiencing movements caused by respiration, with potentially elevated dose prescriptions and therefore higher cure rates, while avoiding the uninvolved nearby structures. In this paper, the current state of the 4D treatment planning is reviewed, from theory to the established practical routine. While the fundamental principles of 4D radiotherapy are well defined, the development of a complete, robust and clinically feasible process still remains a challenge, imposed by limitations in the available treatment planning and radiation delivery systems.

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.

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).

[From image-guided radiotherapy to dose-guided radiotherapy]

PURPOSE

In case of tumour displacement, image-guided radiotherapy (IGRT) based on the use of cone beam CT (tomographie conique) allows replacing the tumour under the accelerator by rigid registration. Anatomical deformations require however replanning, involving an estimation of the cumulative dose, session after session. This is the objective of this study.

PATIENTS AND METHODS

Two examples of arc-intensity modulated radiotherapy are presented: a case of prostate cancer (total dose=80 Gy) with tomographie conique (daily prostate registration) and one head and neck cancer (70 Gy). For the head and neck cancer, the patient had a weekly scanner allowing a dose distribution calculation. The cumulative dose was calculated per voxel on the planning CT after deformation of the dose distribution (with trilinear interpolation) following the transformation given by a non-rigid registration step (Demons registration method) from: either the tomographie conique (prostate), or the weekly CT. The cumulative dose was eventually compared with the planned dose.

RESULTS

In cases of prostate irradiation, the "cumulative" dose corresponded to the planned dose to the prostate. At the last week of irradiation, it was above the planned dose for the rectum and bladder. The volume of rectal wall receiving more than 50 Gy (V50) was 20% at the planning and 26% at the end of treatment, increasing the risk of rectal toxicity (NTCP) of 14%. For the bladder wall, V50 were 73% and 82%, respectively. In head and neck, the "cumulative" dose to the parotid exceeded the planned dose (mean dose increasing from 46 Gy to 54 Gy) from the 5th week of irradiation on, suggesting the need for replanning within the first 5 weeks of radiotherapy.

CONCLUSION

The deformable registration estimates the cumulative dose delivered in the different anatomical structures. Validation on digital and physical phantoms is however required before clinical evaluation.

Comparison of IGRT registration strategies for optimal coverage of primary lung tumors and involved nodes based on multiple four-dimensional CT scans obtained throughout the radiotherapy course

PURPOSE

To investigate the impact of primary tumor and involved lymph node (LN) geometry (centroid, shape, volume) on internal target volume (ITV) throughout treatment for locally advanced non-small cell lung cancer using weekly four-dimensional computed tomography (4DCT).

METHODS AND MATERIALS

Eleven patients with advanced non-small cell lung cancer were treated using image-guided radiotherapy with acquisition of weekly 10-Phase 4DCTs (n = 51). Initial ITV was based on planning 4DCT. Master-ITV incorporated target geometry across the entire treatment (all 4DCTs). Geographic miss was defined as the % Master-ITV positioned outside of the initial planning ITV after registration is complete. Registration strategies considered were bony (B), primary tumor soft tissue alone (T), and registration based on primary tumor and involved LNs (T_LN).

RESULTS

The % geographic miss for the primary tumor, mediastinal, and hilar lymph nodes based on each registration strategy were (1) B: 30%, 30%, 30%; (2) T: 21%, 40%, 36%; and (3) T_LN: 26%, 26%, 27%. Mean geographic expansions to encompass 100% of the primary tumor and involved LNs were 1.2 ± 0.7 cm and 0.8 ± 0.3 cm, respectively, for B and T_LN. Primary and involved LN expansions were 0.7 ± 0.5 cm and 1.1 ± 0.5 cm for T.

CONCLUSION

T is best for solitary targets. When treatments include primary tumor and LNs, B and T_LN provide more comprehensive geographic coverage. We have identified high % geographic miss when considering multiple registration strategies. The dosimetric implications are the subject of future study.

Estimation of three-dimensional intrinsic dosimetric uncertainties resulting from using deformable image registration for dose mapping

PURPOSE

This article presents a general procedural framework to assess the point-by-point precision in mapped dose associated with the intrinsic uncertainty of a deformable image registration (DIR) for any arbitrary patient.

METHODS

Dose uncertainty is obtained via a three-step process. In the first step, for each voxel in an imaging pair, a cluster of points is obtained by an iterative DIR procedure. In the second step, the dispersion of the points due to the imprecision of the DIR method is used to compute the spatial uncertainty. Two different ways to quantify the spatial uncertainty are presented in this work. Method A consists of a one-dimensional analysis of the modules of the position vectors, whereas method B performs a more detailed 3D analysis of the coordinates of the points. In the third step, the resulting spatial uncertainty estimates are used in combination with the mapped dose distribution to compute the point-by-point dose standard deviation. The process is demonstrated to estimate the dose uncertainty induced by mapping a 62.6 Gy dose delivered on maximum exhale to maximum inhale of a ten-phase four-dimensional lung CT.

RESULTS

For the demonstration lung image pair, the standard deviation of inconsistency vectors is found to be up to 9.2 mm with a mean sigma of 1.3 mm. This uncertainty results in a maximum estimated dose uncertainty of 29.65 Gy if method A is used and 21.81 Gy for method B. The calculated volume with dose uncertainty above 10.00 Gy is 602 cm3 for method A and 1422 cm3 for method B.

CONCLUSIONS

This procedure represents a useful tool to evaluate the precision of a mapped dose distribution due to the intrinsic DIR uncertainty in a patient. The procedure is flexible, allowing incorporation of alternative intrinsic error models.

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.

Four-dimensional dosimetry validation and study in lung radiotherapy using deformable image registration and Monte Carlo techniques

Thoracic cancer treatment presents dosimetric difficulties due to respiratory motion and lung inhomogeneity. Monte Carlo and deformable image registration techniques have been proposed to be used in four-dimensional (4D) dose calculations to overcome the difficulties. This study validates the 4D Monte Carlo dosimetry with measurement, compares 4D dosimetry of different tumor sizes and tumor motion ranges, and demonstrates differences of dose-volume histograms (DVH) with the number of respiratory phases that are included in 4D dosimetry. BEAMnrc was used in dose calculations while an optical flow algorithm was used in deformable image registration and dose mapping. Calculated and measured doses of a moving phantom agreed within 3% at the center of the moving gross tumor volumes (GTV). 4D CT image sets of lung cancer cases were used in the analysis of 4D dosimetry. For a small tumor (12.5 cm³) with motion range of 1.5 cm, reduced tumor volume coverage was observed in the 4D dose with a beam margin of 1 cm. For large tumors and tumors with small motion range (around 1 cm), the 4D dosimetry did not differ appreciably from the static plans. The dose-volume histogram (DVH) analysis shows that the inclusion of only extreme respiratory phases in 4D dosimetry is a reasonable approximation of all-phase inclusion for lung cancer cases similar to the ones studied, which reduces the calculation in 4D dosimetry.

Real-time tumor tracking: automatic compensation of target motion using the Siemens 160 MLC

PURPOSE

Advanced high quality radiation therapy techniques such as IMRT require an accurate delivery of precisely modulated radiation fields to the target volume. Interfractional and intrafractional motion of the patient's anatomy, however, may considerably deteriorate the accuracy of the delivered dose to the planned dose distributions. In order to compensate for these potential errors, a dynamic real-time capable MLC control system was designed.

METHODS

The newly developed adaptive MLC control system contains specialized algorithms which are capable of continuous optimization and correction of the aperture of the MLC according to the motion of the target volume during the dose delivery. The algorithms calculate the new leaf positions based on target information provided online to the system. The algorithms were implemented in a dynamic target tracking control system designed for a Siemens 160 MLC. To assess the quality of the new target tracking system in terms of dosimetric accuracy, experiments with various types of motion patterns using different phantom setups were performed. The phantoms were equipped with radiochromic films placed between solid water slabs. Dosimetric results of exemplary deliveries to moving targets with and without dynamic MLC tracking applied were compared in terms of the gamma criterion to the reference dose delivered to a static phantom.

RESULTS

Our measurements indicated that dose errors for clinically relevant two-dimensional target motion can be compensated by the new control system during the dose delivery of open fields. For a clinical IMRT dose distribution, the gamma success rate was increased from 19% to 77% using the new tracking system. Similar improvements were achieved for the delivery of a complete IMRT treatment fraction to a moving lung phantom. However, dosimetric accuracy was limited by the system's latency of 400 ms and the finite leaf width of 5 mm in the isocenter plane.

CONCLUSIONS

Different experimental setups representing different target tracking scenarios proved that the tracking concept, the new algorithms and the dynamic control system make it possible to effectively compensate for dose errors due to target motion in real-time. These early results indicate that the method is suited to increasing the accuracy and the quality of the treatment delivery for the irradiation of moving tumors.

Extension of the NCAT phantom for the investigation of intra-fraction respiratory motion in IMRT using 4D Monte Carlo

The purpose of this work was to create a computational platform for studying motion in intensity modulated radiotherapy (IMRT). Specifically, the non-uniform rational B-spline (NURB) cardiac and torso (NCAT) phantom was modified for use in a four-dimensional Monte Carlo (4D-MC) simulation system to investigate the effect of respiratory-induced intra-fraction organ motion on IMRT dose distributions as a function of diaphragm motion, lesion size and lung density. Treatment plans for four clinical scenarios were designed: diaphragm peak-to-peak amplitude of 1 cm and 3 cm, and two lesion sizes--2 cm and 4 cm diameter placed in the lower lobe of the right lung. Lung density was changed for each phase using a conservation of mass calculation. Further, a new heterogeneous lung model was implemented and tested. Each lesion had an internal target volume (ITV) subsequently expanded by 15 mm isotropically to give the planning target volume (PTV). The PTV was prescribed to receive 72 Gy in 40 fractions. The MLC leaf sequence defined by the planning system for each patient was exported and used as input into the MC system. MC simulations using the dose planning method (DPM) code together with deformable image registration based on the NCAT deformation field were used to find a composite dose distribution for each phantom. These composite distributions were subsequently analyzed using information from the dose volume histograms (DVH). Lesion motion amplitude has the largest effect on the dose distribution. Tumor size was found to have a smaller effect and can be mitigated by ensuring the planning constraints are optimized for the tumor size. The use of a dynamic or heterogeneous lung density model over a respiratory cycle does not appear to be an important factor with a <or=0.6% change in the mean dose received by the ITV, PTV and right lung. The heterogeneous model increases the realism of the NCAT phantom and may provide more accurate simulations in radiation therapy investigations that use the phantom. This work further evaluates the NCAT phantom for use as a tool in radiation therapy research in addition to its extensive use in diagnostic imaging and nuclear medicine research. Our results indicate that the NCAT phantom, combined with 4D-MC simulations, is a useful tool in radiation therapy investigations and may allow the study of relative effects in many clinically relevant situations.

Monte Carlo dose mapping on deforming anatomy

This paper proposes a Monte Carlo-based energy and mass congruent mapping (EMCM) method to calculate the dose on deforming anatomy. Different from dose interpolation methods, EMCM separately maps each voxel's deposited energy and mass from a source image to a reference image with a displacement vector field (DVF) generated by deformable image registration (DIR). EMCM was compared with other dose mapping methods: energy-based dose interpolation (EBDI) and trilinear dose interpolation (TDI). These methods were implemented in EGSnrc/DOSXYZnrc, validated using a numerical deformable phantom and compared for clinical CT images. On the numerical phantom with an analytically invertible deformation map, EMCM mapped the dose exactly the same as its analytic solution, while EBDI and TDI had average dose errors of 2.5% and 6.0%. For a lung patient's IMRT treatment plan, EBDI and TDI differed from EMCM by 1.96% and 7.3% in the lung patient's entire dose region, respectively. As a 4D Monte Carlo dose calculation technique, EMCM is accurate and its speed is comparable to 3D Monte Carlo simulation. This method may serve as a valuable tool for accurate dose accumulation as well as for 4D dosimetry QA.

Design and testing of a simulation framework for dosimetric motion studies integrating an anthropomorphic computational phantom into four-dimensional Monte Carlo

We have designed a simulation framework for motion studies in radiation therapy by integrating the anthropomorphic NCAT phantom into a 4D Monte Carlo dose calculation engine based on DPM. Representing an artifact-free environment, the system can be used to identify class solutions as a function of geometric and dosimetric parameters. A pilot dynamic conformal study for three lesions ( approximately 2.0 cm) in the right lung was performed (70 Gy prescription dose). Tumor motion changed as a function of tumor location, according to the anthropomorphic deformable motion model. Conformal plans were simulated with 0 to 2 cm margin for the aperture, with additional 0.5 cm for beam penumbra. The dosimetric effects of intensity modulated radiotherapy (IMRT) vs. conformal treatments were compared in a static case. Results show that the Monte Carlo simulation framework can model tumor tracking in deformable anatomy with high accuracy, providing absolute doses for IMRT and conformal radiation therapy. A target underdosage of up to 3.67 Gy (lower lung) was highlighted in the composite dose distribution mapped at exhale. Such effects depend on tumor location and treatment margin and are affected by lung deformation and ribcage motion. In summary, the complexity in the irradiation of moving targets has been reduced to a controlled simulation environment, where several treatment options can be accurately modeled and quantified The implemented tools will be utilized for extensive motion study in lung/liver irradiation.

4D-Imaging of the lung: reproducibility of lesion size and displacement on helical CT, MRI, and cone beam CT in a ventilated ex vivo system

PURPOSE

Four-dimensional (4D) imaging is a key to motion-adapted radiotherapy of lung tumors. We evaluated in a ventilated ex vivo system how size and displacement of artificial pulmonary nodules are reproduced with helical 4D-CT, 4D-MRI, and linac-integrated cone beam CT (CBCT).

METHODS AND MATERIALS

Four porcine lungs with 18 agarose nodules (mean diameters 1.3-1.9 cm), were ventilated inside a chest phantom at 8/min and subject to 4D-CT (collimation 24 x 1.2 mm, pitch 0.1, slice/increment 24 x 10(2)/1.5/0.8 mm, pitch 0.1, temporal resolution 0.5 s), 4D-MRI (echo-shared dynamic three-dimensional-flash; repetition/echo time 2.13/0.72 ms, voxel size 2.7 x 2.7 x 4.0 mm, temporal resolution 1.4 s) and linac-integrated 4D-CBCT (720 projections, 3-min rotation, temporal resolution approximately 1 s). Static CT without respiration served as control. Three observers recorded lesion size (RECIST-diameters x/y/z) and axial displacement. Interobserver- and interphase-variation coefficients (IO/IP VC) of measurements indicated reproducibility.

RESULTS

Mean x/y/z lesion diameters in cm were equal on static and dynamic CT (1.88/1.87; 1.30/1.39; 1.71/1.73; p > 0.05), but appeared larger on MRI and CBCT (2.06/1.95 [p < 0.05 vs. CT]; 1.47/1.28 [MRI vs. CT/CBCT p < 0.05]; 1.86/1.83 [CT vs. CBCT p < 0.05]). Interobserver-VC for lesion sizes were 2.54-4.47% (CT), 2.29-4.48% (4D-CT); 5.44-6.22% (MRI) and 4.86-6.97% (CBCT). Interphase-VC for lesion sizes ranged from 2.28% (4D-CT) to 10.0% (CBCT). Mean displacement in cm decreased from static CT (1.65) to 4D-CT (1.40), CBCT (1.23) and MRI (1.16).

CONCLUSIONS

Lesion sizes are exactly reproduced with 4D-CT but overestimated on 4D-MRI and CBCT with a larger variability due to limited temporal and spatial resolution. All 4D-modalities underestimate lesion displacement.

Dose calculation with respiration-averaged CT processed from cine CT without a respiratory surrogate

Dose calculation for thoracic radiotherapy is commonly performed on a free-breathing helical CT despite artifacts caused by respiratory motion. Four-dimensional computed tomography (4D-CT) is one method to incorporate motion information into the treatment planning process. Some centers now use the respiration-averaged CT (RACT), the pixel-by-pixel average of the ten phases of 4D-CT, for dose calculation. This method, while sparing the tedious task of 4D dose calculation, still requires 4D-CT technology. The authors have recently developed a means to reconstruct RACT directly from unsorted cine CT data from which 4D-CT is formed, bypassing the need for a respiratory surrogate. Using RACT from cine CT for dose calculation may be a means to incorporate motion information into dose calculation without performing 4D-CT. The purpose of this study was to determine if RACT from cine CT can be substituted for RACT from 4D-CT for the purposes of dose calculation, and if increasing the cine duration can decrease differences between the dose distributions. Cine CT data and corresponding 4D-CT simulations for 23 patients with at least two breathing cycles per cine duration were retrieved. RACT was generated four ways: First from ten phases of 4D-CT, second, from 1 breathing cycle of images, third, from 1.5 breathing cycles of images, and fourth, from 2 breathing cycles of images. The clinical treatment plan was transferred to each RACT and dose was recalculated. Dose planes were exported at orthogonal planes through the isocenter (coronal, sagittal, and transverse orientations). The resulting dose distributions were compared using the gamma index within the planning target volume (PTV). Failure criteria were set to 2%/1 mm. A follow-up study with 50 additional lung cancer patients was performed to increase sample size. The same dose recalculation and analysis was performed. In the primary patient group, 22 of 23 patients had 100% of points within the PTV pass y criteria. The average maximum and mean y indices were very low (well below 1), indicating good agreement between dose distributions. Increasing the cine duration generally increased the dose agreement. In the follow-up study, 49 of 50 patients had 100% of points within the PTV pass the y criteria. The average maximum and mean y indices were again well below 1, indicating good agreement. Dose calculation on RACT from cine CT is negligibly different from dose calculation on RACT from 4D-CT. Differences can be decreased further by increasing the cine duration of the cine CT scan.

A simplified method of four-dimensional dose accumulation using the mean patient density representation

The purpose of this work was to demonstrate, both in phantom and patient, the feasibility of using an average 4DCT image set (AVG-CT) for 4D cumulative dose estimation. A series of 4DCT numerical phantoms and corresponding AVG-CTs were generated. For full 4D dose summation, static dose was calculated on each phase and cumulative dose was determined by combining each phase's static dose distribution with known tumor displacement. The AVG-CT cumulative dose was calculated similarly, although the same AVG-CT static dose distribution was used for all phases (i.e., tumor displacements). Four lung cancer cases were also evaluated for stereotactic body radiotherapy and conformal treatments; however, deformable image registration of the 4DCTs was used to generate the displacement vector fields (DVFs) describing patient-specific motion. Dose discrepancy between full 4D summation and AVG-CT approach was calculated and compared. For all phantoms, AVG-CT approximation yielded slightly higher cumulative doses compared to full 4D summation, with dose discrepancy increasing with increased tumor excursion. In vivo, using the AVG-CT coupled with deformable registration yielded clinically insignificant differences for all GTV parameters including the minimum, mean, maximum, dose to 99% of target, and dose to 1% of target. Furthermore, analysis of the spinal cord, esophagus, and heart revealed negligible differences in major dosimetric indices and dose coverage between the two dose calculation techniques. Simplifying 4D dose accumulation via the AVG-CT, while fully accounting for tumor deformation due to respiratory motion, has been validated, thereby, introducing the potential to streamline the use of 4D dose calculations in clinical practice, particularly for adaptive planning purposes.

An energy transfer method for 4D Monte Carlo dose calculation

This article presents a new method for four-dimensional Monte Carlo dose calculations which properly addresses dose mapping for deforming anatomy. The method, called the energy transfer method (ETM), separates the particle transport and particle scoring geometries: Particle transport takes place in the typical rectilinear coordinate system of the source image, while energy deposition scoring takes place in a desired reference image via use of deformable image registration. Dose is the energy deposited per unit mass in the reference image. ETM has been implemented into DOSXYZnrc and compared with a conventional dose interpolation method (DIM) on deformable phantoms. For voxels whose contents merge in the deforming phantom, the doses calculated by ETM are exactly the same as an analytical solution, contrasting to the DIM which has an average 1.1% dose discrepancy in the beam direction with a maximum error of 24.9% found in the penumbra of a 6 MV beam. The DIM error observed persists even if voxel subdivision is used. The ETM is computationally efficient and will be useful for 4D dose addition and benchmarking alternative 4D dose addition algorithms.

An overview of Monte Carlo treatment planning for radiotherapy

The implementation of Monte Carlo dose calculation algorithms in clinical radiotherapy treatment planning systems has been anticipated for many years. Despite a continuous increase of interest in Monte Carlo Treatment Planning (MCTP), its introduction into clinical practice has been delayed by the extent of calculation time required. The development of newer and faster MC codes is behind the commercialisation of the first MC-based treatment planning systems. The intended scope of this article is to provide the reader with a compact 'primer' on different approaches to MCTP with particular attention to the latest developments in the field.

A deliverable four-dimensional intensity-modulated radiation therapy-planning method for dynamic multileaf collimator tumor tracking delivery

PURPOSE

To develop a deliverable four-dimensional (4D) intensity-modulated radiation therapy (IMRT) planning method for dynamic multileaf collimator (MLC) tumor tracking delivery.

METHODS AND MATERIALS

The deliverable 4D IMRT planning method involves aligning MLC leaf motion parallel to the major axis of target motion and translating MLC leaf positions by the difference in the target centroid position between respiratory phases of the 4D CT scan. This method ignores nonlinear respiratory motion and deformation. A three-dimensional (3D) optimal method whereby an IMRT plan on each respiratory phase of the 4D CT scan was independently optimized was used for comparison. For 12 lung cancer patient 4D CT scans, individual phase plans and deformable dose-summed 4D plans using the two methods were created and compared.

RESULTS

For each of the individual phase plans, the deliverable method yielded similar isodose distributions and dose-volume histograms. The deliverable and 3D optimal methods yielded statistically equivalent dose-volume metrics for both individual phase plans and 4D plans (p > 0.05 for all metrics compared). The deliverable method was affected by 4D CT artifacts in one case. Both methods were affected by high vector field variations from deformable registration.

CONCLUSIONS

The deliverable method yielded similar dose distributions for each of the individual phase plans and statistically equivalent dosimetric values compared with the 3D optimal method, indicating that the deliverable method is dosimetrically robust to the variations of fractional time spent in respiratory phases on a given 4D CT scan. Nonlinear target motion and deformation did not cause significant dose discrepancies.

Development of a geometry-based respiratory motion-simulating patient model for radiation treatment dosimetry

Temporal and spatial anatomic changes caused by respiration during radiation treatment delivery can lead to discrepancies between prescribed and actual radiation doses. The present paper documents a study to construct a respiratory‐motion‐simulating, four‐dimensional (4D) anatomic and dosimetry model for the study of the dosimetric effects of organ motion for various radiation treatment plans and delivery strategies. The non‐uniform rational B‐splines (NURBS) method has already been used to reconstruct a three‐dimensional (3D) VIP‐Man (“visible photographic man”) model that can reflect the deformation of organs during respiration by using time‐dependent equations to manipulate surface control points. The EGS4 (Electron Gamma Shower, version 4) Monte Carlo code is then used to apply the 4D model to dose simulation. We simulated two radiation therapy delivery scenarios: gating treatment and 4D image‐guided treatment. For each delivery scenario, we developed one conformal plan and one intensity‐modulated radiation therapy plan. A lesion in the left lung was modeled to investigate the effect of respiratory motion on radiation dose distributions. Based on target dose–volume histograms, the importance of using accurate gating to improve the dose distribution is demonstrated. The results also suggest that, during 4D image‐guided treatment delivery, monitoring of the patient's breathing pattern is critical. This study demonstrates the potential of using a “standard” motion‐simulating patient model for 4D treatment planning and motion management.

PACS numbers: 87.53.Bn, 87.53.Kn, 87.53.Tf, 87.53.Wz, 87.57.Gg, 89.80.+h

Respiratory-gated helical computed tomography of lung: reproducibility of small volumes in an ex vivo model

PURPOSE

Motion-adapted radiotherapy with gated irradiation or tracking of tumor positions requires dedicated imaging techniques such as four-dimensional (4D) helical computed tomography (CT) for patient selection and treatment planning. The objective was to evaluate the reproducibility of spatial information for small objects on respiratory-gated 4D helical CT using computer-assisted volumetry of lung nodules in a ventilated ex vivo system.

METHODS AND MATERIALS

Five porcine lungs were inflated inside a chest phantom and prepared with 55 artificial nodules (mean diameter, 8.4 mm +/- 1.8). The lungs were respirated by a flexible diaphragm and scanned with 40-row detector CT (collimation, 24 x 1.2 mm; pitch, 0.1; rotation time, 1 s; slice thickness, 1.5 mm; increment, 0.8 mm). The 4D-CT scans acquired during respiration (eight per minute) and reconstructed at 0-100% inspiration and equivalent static scans were scored for motion-related artifacts (0 or absent to 3 or relevant). The reproducibility of nodule volumetry (three readers) was assessed using the variation coefficient (VC).

RESULTS

The mean volumes from the static and dynamic inspiratory scans were equal (364.9 and 360.8 mm3, respectively, p = 0.24). The static and dynamic end-expiratory volumes were slightly greater (371.9 and 369.7 mm3, respectively, p = 0.019). The VC for volumetry (static) was 3.1%, with no significant difference between 20 apical and 20 caudal nodules (2.6% and 3.5%, p = 0.25). In dynamic scans, the VC was greater (3.9%, p = 0.004; apical and caudal, 2.6% and 4.9%; p = 0.004), with a significant difference between static and dynamic in the 20 caudal nodules (3.5% and 4.9%, p = 0.015). This was consistent with greater motion-related artifacts and image noise at the diaphragm (p <0.05). The VC for interobserver variability was 0.6%.

CONCLUSION

Residual motion-related artifacts had only minimal influence on volumetry of small solid lesions. This indicates a high reproducibility of spatial information for small objects in low pitch helical 4D-CT reconstructions.