Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT-to-CBCT deformable registration for "dose of the day" calculations

The suitability of common metrics for assessing parotid and larynx autosegmentation accuracy

Contouring structures in the head and neck is time‐consuming, and automatic segmentation is an important part of an adaptive radiotherapy workflow. Geometric accuracy of automatic segmentation algorithms has been widely reported, but there is no consensus as to which metrics provide clinically meaningful results. This study investigated whether geometric accuracy (as quantified by several commonly used metrics) was associated with dosimetric differences for the parotid and larynx, comparing automatically generated contours against manually drawn ground truth contours. This enabled the suitability of different commonly used metrics to be assessed for measuring automatic segmentation accuracy of the parotid and larynx. Parotid and larynx structures for 10 head and neck patients were outlined by five clinicians to create ground truth structures. An automatic segmentation algorithm was used to create automatically generated normal structures, which were then used to create volumetric‐modulated arc therapy plans. The mean doses to the automatically generated structures were compared with those of the corresponding ground truth structures, and the relative difference in mean dose was calculated for each structure. It was found that this difference did not correlate with the geometric accuracy provided by several metrics, notably the Dice similarity coefficient, which is a commonly used measure of spatial overlap. Surface‐based metrics provided stronger correlation and are, therefore, more suitable for assessing automatic segmentation of the parotid and larynx.

PACS number(s): 87.57.nm, 87.55.D, 87.55.Qr

Adaptive Radiotherapy for Head Neck Cancer

Changes in patient anatomy may occur either from a tumour volume, position or function of a specific organ at risk, or target volume, weight loss or a reduction in postoperative oedema, and may vary between patients. Adaptive radiotherapy aims to correct morphological variations by realizing one or more plans during the treatment course. Imaging is used to detect these variations, thereby deciding on a potential replanning. At present, adaptive radiotherapy for head neck cancer (HNC) mainly deals with treatment response, such as weight loss or tumor shrinkage. Therefore a properly timed repeat CT scan during treatment is a suitable basis for plan adaptation to account for treatment response.

Analysis of Dosimetric Impacts of Cone Beam Computed Tomography-Based Volumetric Modulated Arc Therapy Planning

OBJECTIVE

To quantify the Hounsfield unit (HU) variations between computed tomography (CT) and cone beam CT (CBCT) and study its impact on volumetric modulated arc therapy (VMAT) plans.

METHODS

HU number variations in CT and CBCT images were evaluated using the Catphan-504 phantom, and changes in seven different materials within the phantom (air, polymethylpentene, low-density polyethylene, polystyrene, acrylic, Delrin, and Teflon) were studied. The HU variations in half-fan and full-fan modes of CBCT were evaluated. The effect of variations in the shape of the body cross sections was assessed by reducing the body of the Catphan by 0.5 cm and 1.0 cm. CBCT-based VMAT plans in 27 patients (10 prostate, 10 brain, and 7 head and neck (HN)) were compared with corresponding CT-based plans. The dosimetric variations were assessed referring to different points on the dose volume histogram (D_5%, D_50%, and D_95% for PTVs and D_1%, D_max, and D_mean for organs at risk). The relative percentage of difference (ΔD (%)) between CT- and CBCT-based VMAT plans were examined on these points. To evaluate the dosimetric accuracy, dose distributions were compared using Omnipro-I'mRT software. The VMAT plans were evaluated based on 3 mm-3%, 2 mm-2%, and 1 mm-1% gamma criteria.

RESULTS

The HU difference in CT and CBCT was highest for air, Delrin, and Teflon, whereas the difference was less than 20 HU for the other materials. The dose volume histograms of both CT- and CBCT-based plans were in excellent agreement in both phantom and patients, except in HN cases where the difference was 7%. The average 3 mm-3% gamma pass points in brain, prostate, and HN patients were 97 ± 0.2%, 96 ± 0.06%, and 93.3 ± 1.1%, respectively. The gamma pass rates reduced to 88.8 ± 0.06%, 91 ± 0.04%, and 79 ± 6% in 2 mm-2%, and further declined to 76.6 ± 0.09%, 75.2 ± 0.5%, and 60 ± 6% using the stringent 1 mm-1% gamma criteria for brain, prostate, and HN cases, respectively.

CONCLUSION

Based on the results of this study, it is our belief that CBCT images can be used as a tool for evaluating the dosimetric variation in patient VMAT plans.

Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction

Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI = 58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI = 69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC = 0.58, q-value = 0.33), while the differentiation was significant with other textures (AUC = 0.71-0.73, p < 0.009). Among the deformable algorithms, fast-demons (AUC = 0.68-0.70, q-value < 0.03) and fast-free-form (AUC = 0.69-0.74, q-value < 0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC = 0.72-0.78, q-value < 0.01). Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, fast-demons, fast-free-form, and rigid algorithms should be applied with care due to their inferior performance compared to other algorithms.

Comparison of CT number calibration techniques for CBCT-based dose calculation

PURPOSE

The aim of this work was to compare and validate various computed tomography (CT) number calibration techniques with respect to cone beam CT (CBCT) dose calculation accuracy.

METHODS

CBCT dose calculation accuracy was assessed for pelvic, lung, and head and neck (H&N) treatment sites for two approaches: (1) physics-based scatter correction methods (CBCTr); (2) density override approaches including assigning water density to the entire CBCT (W), assignment of either water or bone density (WB), and assignment of either water or lung density (WL). Methods for CBCT density assignment within a commercially available treatment planning system (RSauto), where CBCT voxels are binned into six density levels, were assessed and validated. Dose-difference maps and dose-volume statistics were used to compare the CBCT dose distributions with the ground truth of a planning CT acquired the same day as the CBCT.

RESULTS

For pelvic cases, all CTN calibration methods resulted in average dose-volume deviations below 1.5 %. RSauto provided larger than average errors for pelvic treatments for patients with large amounts of adipose tissue. For H&N cases, all CTN calibration methods resulted in average dose-volume differences below 1.0 % with CBCTr (0.5 %) and RSauto (0.6 %) performing best. For lung cases, WL and RSauto methods generated dose distributions most similar to the ground truth.

CONCLUSION

The RSauto density override approach is an attractive option for CTN adjustments for a variety of anatomical sites. RSauto methods were validated, resulting in dose calculations that were consistent with those calculated on diagnostic-quality CT images, for CBCT images acquired of the lung, for patients receiving pelvic RT in cases without excess adipose tissue, and for H&N cases.

Cone Beam Computed Tomography: The Challenges and Strategies in Its Application for Dose Accumulation

Online image guidance using cone beam computed tomography (CBCT) has greatly improved the geometric precision of radiotherapy. Changes in anatomy are common during a course of fractionated treatment, resulting in dose deviation from the planned distribution. There is increased interest in performing dose accumulation to compute the actual delivered dose and to adapt the treatment when necessary. This can be achieved by delineating the volume of interest and by generating "dose of the day" through dose computation on the CBCT. However, the image quality and the accuracy of the CT number of CBCT are deemed to be inferior to fan beam CT, which increases the uncertainty associated in this process. A review of literature was conducted to assess the reliability of and to examine strategies for overcoming the challenges in using CBCT for volume delineation and dose computation. The review demonstrates that the uncertainty varies across body sites, and different strategies have been recommended to generate comparable results to images from CT simulators. This facilitates a better understanding of the potential and the limitation of using CBCT for dose accumulation.

A three-dimensional head-and-neck phantom for validation of multimodality deformable image registration for adaptive radiotherapy

PURPOSE

To develop a three-dimensional (3D) deformable head-and-neck (H&N) phantom with realistic tissue contrast for both kilovoltage (kV) and megavoltage (MV) imaging modalities and use it to objectively evaluate deformable image registration (DIR) algorithms.

METHODS

The phantom represents H&N patient anatomy. It is constructed from thermoplastic, which becomes pliable in boiling water, and hardened epoxy resin. Using a system of additives, the Hounsfield unit (HU) values of these materials were tuned to mimic anatomy for both kV and MV imaging. The phantom opens along a sagittal midsection to reveal radiotransparent markers, which were used to characterize the phantom deformation. The deformed and undeformed phantoms were scanned with kV and MV imaging modalities. Additionally, a calibration curve was created to change the HUs of the MV scans to be similar to kV HUs, (MC). The extracted ground-truth deformation was then compared to the results of two commercially available DIR algorithms, from Velocity Medical Solutions and mim software.

RESULTS

The phantom produced a 3D deformation, representing neck flexion, with a magnitude of up to 8 mm and was able to represent tissue HUs for both kV and MV imaging modalities. The two tested deformation algorithms yielded vastly different results. For kV-kV registration, mim produced mean and maximum errors of 1.8 and 11.5 mm, respectively. These same numbers for Velocity were 2.4 and 7.1 mm, respectively. For MV-MV, kV-MV, and kV-MC Velocity produced similar mean and maximum error values. mim, however, produced gross errors for all three of these scenarios, with maximum errors ranging from 33.4 to 41.6 mm.

CONCLUSIONS

The application of DIR across different imaging modalities is particularly difficult, due to differences in tissue HUs and the presence of imaging artifacts. For this reason, DIR algorithms must be validated specifically for this purpose. The developed H&N phantom is an effective tool for this purpose.

Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm

PURPOSE

The aims of this work were to evaluate the performance of several deformable image registration (DIR) algorithms implemented in our in-house software (NiftyReg) and the uncertainties inherent to using different algorithms for dose warping.

METHODS

The authors describe a DIR based adaptive radiotherapy workflow, using CT and cone-beam CT (CBCT) imaging. The transformations that mapped the anatomy between the two time points were obtained using four different DIR approaches available in NiftyReg. These included a standard unidirectional algorithm and more sophisticated bidirectional ones that encourage or ensure inverse consistency. The forward (CT-to-CBCT) deformation vector fields (DVFs) were used to propagate the CT Hounsfield units and structures to the daily geometry for "dose of the day" calculations, while the backward (CBCT-to-CT) DVFs were used to remap the dose of the day onto the planning CT (pCT). Data from five head and neck patients were used to evaluate the performance of each implementation based on geometrical matching, physical properties of the DVFs, and similarity between warped dose distributions. Geometrical matching was verified in terms of dice similarity coefficient (DSC), distance transform, false positives, and false negatives. The physical properties of the DVFs were assessed calculating the harmonic energy, determinant of the Jacobian, and inverse consistency error of the transformations. Dose distributions were displayed on the pCT dose space and compared using dose difference (DD), distance to dose difference, and dose volume histograms.

RESULTS

All the DIR algorithms gave similar results in terms of geometrical matching, with an average DSC of 0.85 ± 0.08, but the underlying properties of the DVFs varied in terms of smoothness and inverse consistency. When comparing the doses warped by different algorithms, we found a root mean square DD of 1.9% ± 0.8% of the prescribed dose (pD) and that an average of 9% ± 4% of voxels within the treated volume failed a 2%pD DD-test (DD2%-pp). Larger DD2%-pp was found within the high dose gradient (21% ± 6%) and regions where the CBCT quality was poorer (28% ± 9%). The differences when estimating the mean and maximum dose delivered to organs-at-risk were up to 2.0%pD and 2.8%pD, respectively.

CONCLUSIONS

The authors evaluated several DIR algorithms for CT-to-CBCT registrations. In spite of all methods resulting in comparable geometrical matching, the choice of DIR implementation leads to uncertainties in dose warped, particularly in regions of high gradient and/or poor imaging quality.

A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation

BACKGROUND

Although altered protocols that challenge conventional radiation fractionation have been tested in prospective clinical trials, we still have limited understanding of how to select the most appropriate fractionation schedule for individual patients. Currently, the prescription of definitive radiotherapy is based on the primary site and stage, without regard to patient-specific tumor or host factors that may influence outcome. We hypothesize that the proportion of radiosensitive proliferating cells is dependent on the saturation of the tumor carrying capacity. This may serve as a prognostic factor for personalized radiotherapy (RT) fractionation.

METHODS

We introduce a proliferation saturation index (PSI), which is defined as the ratio of tumor volume to the host-influenced tumor carrying capacity. Carrying capacity is as a conceptual measure of the maximum volume that can be supported by the current tumor environment including oxygen and nutrient availability, immune surveillance and acidity. PSI is estimated from two temporally separated routine pre-radiotherapy computed tomography scans and a deterministic logistic tumor growth model. We introduce the patient-specific pre-treatment PSI into a model of tumor growth and radiotherapy response, and fit the model to retrospective data of four non-small cell lung cancer patients treated exclusively with standard fractionation. We then simulate both a clinical trial hyperfractionation protocol and daily fractionations, with equal biologically effective dose, to compare tumor volume reduction as a function of pretreatment PSI.

RESULTS

With tumor doubling time and radiosensitivity assumed constant across patients, a patient-specific pretreatment PSI is sufficient to fit individual patient response data (R(2) = 0.98). PSI varies greatly between patients (coefficient of variation >128 %) and correlates inversely with radiotherapy response. For this study, our simulations suggest that only patients with intermediate PSI (0.45-0.9) are likely to truly benefit from hyperfractionation. For up to 20 % uncertainties in tumor growth rate, radiosensitivity, and noise in radiological data, the absolute estimation error of pretreatment PSI is <10 % for more than 75 % of patients.

CONCLUSIONS

Routine radiological images can be used to calculate individual PSI, which may serve as a prognostic factor for radiation response. This provides a new paradigm and rationale to select personalized RT dose-fractionation.

Comparing cone-beam CT intensity correction methods for dose recalculation in adaptive intensity-modulated photon and proton therapy for head and neck cancer

BACKGROUND

Adaptive intensity-modulated photon and proton radiotherapy (IMRT and IMPT) of head and neck (H&N) cancer requires frequent three-dimensional (3D) dose calculation. We compared two approaches for dose recalculation on the basis of intensity-corrected cone-beam (CB) x-ray computed tomography (CT) images.

MATERIAL AND METHODS

For nine H&N tumor patients, virtual CTs (vCT) were generated by deformable image registration of the planning CT (pCT) to the CBCT. The second intensity correction approach used population-based lookup tables for scaling CBCT intensities to the pCT HU range (CBCTLUT). IMRT and IMPT plans were generated with a commercial treatment planning system. Dose recalculations on vCT and CBCTLUT were analyzed using a (3%, 3 mm) gamma-index analysis and comparison of normal tissue and tumor dose/volume parameters. A replanning CT (rpCT) acquired within three days of the CBCT served as reference. Single field uniform dose (SFUD) proton plans were created and recalculated on vCT and CBCTLUT for proton range comparison.

RESULTS

Dose/volume parameters showed minor differences between rpCT, vCT and CBCTLUT in IMRT, but clinically relevant deviations between CBCTLUT and rpCT in the spinal cord for IMPT. Gamma-index pass-rates were found increased for vCT with respect to CBCTLUT in IMPT (by up to 21 percentage points) and IMRT (by up to 9 percentage points) for most cases. The SFUD-based proton range assessment showed improved agreement of vCT and rpCT, with 88-99% of the depth dose profiles in beam's eye view agreeing within 3 mm. For CBCTLUT, only 80-94% of the profiles fulfilled this criterion.

CONCLUSION

vCT and CBCTLUT are suitable options for dose recalculation in adaptive IMRT. In the scope of IMPT, the vCT approach is preferable.

Validation of a deformable image registration technique for cone beam CT-based dose verification

PURPOSE

As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (dir) for prostate treatments.

METHODS

A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformed CT. The registration quality was assessed as the ability of the dir method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it's suitability to be used for dose calculation. plastimatch, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder.

RESULTS

The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field lengths decreased from 10.1 to 2.5 mm when CBCT was calibrated prior to registration. The results showed no dependence on the level of bladder filling. In comparison with the dose calculated on the primary deformed CT, differences in mean dose averaged over all organs were 0.2% and 3.9% for dose calculated on the secondary deformed CT with and without CBCT calibration, respectively, and 0.5% for dose calculated directly on the calibrated CBCT, for the full-bladder scenario. Gamma analysis for the distance to agreement of 2 mm and 2% of prescribed dose indicated a pass rate of 100% for both cases involving calibrated CBCT and on average 86% without CBCT calibration.

CONCLUSIONS

Using deformable registration on the planning CT images to evaluate the IMRT dose based on daily CBCTs was found feasible. The proposed method will provide an accurate dose distribution using planning CT and pretreatment CBCT data, avoiding the additional uncertainties introduced by CBCT inhomogeneity and artifacts. This is a necessary initial step toward future image-guided adaptive radiotherapy of the prostate.

Long-term stability of the Hounsfield unit to electron density calibration curve in cone-beam computed tomography images for adaptive radiotherapy treatment planning

Aim

To use cone-beam computed tomography (CBCT) images for treatment planning, the Hounsfield unit (HU)-electron density (ED) calibration table for CBCT should be stable. The purpose of this study was to verify the stability of the HU values for the CBCT system over 1 year and to evaluate the effects of variation in HU-ED calibration curves on dose calculation.

Materials and Methods

A tissue characterisation phantom was scanned with the field of view (FOV) of size S (FOV-S) and FOV of size M (FOV-M) using the CBCT system once a month for 1 year. A single field treatment plan was constructed on digital phantom images to validate the dose distribution using mean HU-ED calibration curves and possible variations.

Results

HU values for each material rod over the observation period varied with trend. The HU value of the cortical bone rod decreased by about 100 HU for the FOV-S and by about 300 HU for the FOV-M. Possible variation in the HU-ED calibration curves produced a ≤17·9% dose difference in the dose maximum in the treatment plan.

Conclusions

The CBCT system should be calibrated periodically for consistent dose calculation.

Registration by interactive inverse simulation: application for adaptive radiotherapy

PURPOSE

This paper introduces a new methodology for semi-automatic registration of anatomical structure deformations. The contribution is to use an interactive inverse simulation of physics-based deformable model, computed in real time.

METHODS

The method relies on nonlinear finite element method (FEM) within a constraint-based framework. Given a set of few registered points provided by the user, a real-time optimization adapts the boundary conditions and(/or) some parameters of the FEM in order to obtain the adequate geometrical deformations. To dramatically fasten the process, the method relies on a projection of the model in the space of the optimization variables. In this reduced space, a quadratic programming problem is formulated and solved very quickly. The method is validated with numerical examples for retrieving some unknown parameters such as the Young's modulus and some pressures on the boundaries of the model.

RESULTS

The approach is employed in the context of radiotherapy of the neck where weight loss during the 7 weeks of the therapy modifies the volume of the anatomical structures and induces large deformations. Indeed, sensitive structures such as the parotid glands may cross the target volume due to these deformations which leads to adverse effects for the patient. We thus apply the approach for the registration of the parotid glands during the radiotherapy of the head and neck cancer.

CONCLUSIONS

The results show how the method could be used in a clinical routine and be employed in the planning in order to limit the radiations of these glands.

Phantom based evaluation of CT to CBCT image registration for proton therapy dose recalculation

The ability to perform dose recalculation on the anatomy of the day is important in the context of adaptive proton therapy. The objective of this study was to investigate the use of deformable image registration (DIR) and cone beam CT (CBCT) imaging to generate the daily stopping power distribution of the patient. We investigated the deformation of the planning CT scan (pCT) onto daily CBCT images to generate a virtual CT (vCT) using a deformable phantom designed for the head and neck (H & N) region. The phantom was imaged at a planning CT scanner in planning configuration, yielding a pCT and in deformed, treatment day configuration, yielding a reference CT (refCT). The treatment day configuration was additionally scanned at a CBCT scanner. A Morphons DIR algorithm was used to generate a vCT. The accuracy of the vCT was evaluated by comparison to the refCT in terms of corresponding features as identified by an adaptive scale invariant feature transform (aSIFT) algorithm. Additionally, the vCT CT numbers were compared to those of the refCT using both profiles and regions of interest and the volumes and overlap (DICE coefficients) of various phantom structures were compared. The water equivalent thickness (WET) of the vCT, refCT and pCT were also compared to evaluate proton range differences. Proton dose distributions from the same initial fluence were calculated on the refCT, vCT and pCT and compared in terms of proton range. The method was tested on a clinical dataset using a replanning CT scan acquired close in time to a CBCT scan as reference using the WET evaluation. Results from the aSIFT investigation suggest a deformation accuracy of 2-3 mm. The use of the Morphon algorithm did not distort CT number intensity in uniform regions and WET differences between vCT and refCT were of the order of 2% of the proton range. This result was confirmed by proton dose calculations. The patient results were consistent with phantom observations. In conclusion, our phantom study suggests the vCT approach is adequate for proton dose recalculation on the basis of CBCT imaging.

Introducing interactive inverse FEM simulation and its application for adaptive radiotherapy

We introduce a new methodology for semi-automatic deformable registration of anatomical structures, using interactive inverse simulations. The method relies on non-linear real-time Finite Element Method (FEM) within a constraint-based framework. Given a set of few registered points provided by the user, a real-time optimization adapts the boundary conditions and(/or) some parameters of the FEM in order to obtain the adequate geometrical deformations. To dramatically fasten the process, the method relies on a projection of the model in the space of the optimization variables. In this reduced space, a quadratic programming problem is formulated and solved very quickly. The method is validated with numerical examples for retrieving Young's modulus and some pressures on the boundaries. Then, we apply the approach for the registration of the parotid glands during the radiotherapy of the head and neck cancer. Radiotherapy treatment induces weight loss that modifies the shape and the positions of these structures and they eventually intersect the target volume. We show how we could adapt the planning to limit the radiation of these glands.

Assessment of the dosimetric accuracies of CATPhan 504 and CIRS 062 using kV-CBCT for performing direct calculations

The dosimetric accuracies of CATPhan 504 and CIRS 062 have been evaluated using the kV-CBCT of Varian TrueBeam linac and Eclipse TPS. The assessment was done using the kV-CBCT as a standalone tool for dosimetric calculations towards Adaptive replanning. Dosimetric calculations were made without altering the HU-ED curves of the planning computed tomography (CT) scanner that is used by the Eclipse TPS. All computations were done using the images and dataset from kV-CBCT while maintaining the HU-ED calibration curve of the planning CT (pCT), assuming pCT was used for the initial treatment plan. Results showed that the CIRS phantom produces doses within ±5% of the CT-based plan while CATPhan 504 produces a variation of ±14% of the CT-based plan.

Challenges of radiotherapy: report on the 4D treatment planning workshop 2013

This report, compiled by experts on the treatment of mobile targets with advanced radiotherapy, summarizes the main conclusions and innovations achieved during the 4D treatment planning workshop 2013. This annual workshop focuses on research aiming to advance 4D radiotherapy treatments, including all critical aspects of time resolved delivery, such as in-room imaging, motion detection, motion managing, beam application, and quality assurance techniques. The report aims to revise achievements in the field and to discuss remaining challenges and potential solutions. As main achievements advances in the development of a standardized 4D phantom and in the area of 4D-treatment plan optimization were identified. Furthermore, it was noticed that MR imaging gains importance and high interest for sequential 4DCT/MR data sets was expressed, which represents a general trend of the field towards data covering a longer time period of motion. A new point of attention was work related to dose reconstructions, which may play a major role in verification of 4D treatment deliveries. The experimental validation of results achieved by 4D treatment planning and the systematic evaluation of different deformable image registration methods especially for inter-modality fusions were identified as major remaining challenges. A challenge that was also suggested as focus for future 4D workshops was the adaptation of image guidance approaches from conventional radiotherapy into particle therapy. Besides summarizing the last workshop, the authors also want to point out new evolving demands and give an outlook on the focus of the next workshop.

Evaluating the therapeutic dose distribution of intensity-modulated radiation therapy for head and neck with cone-beam computed tomography image: a methodological study

An approximate correction method for the CT value-electron density curve of CBCT was established, through comparison and fitting with FBCT images, and applied to evaluate the therapeutic dose of IMRT. The precision of using CBCT for plan calculation was validated by comparing the dose distribution between CBCT- and FBCT-based IMRT plans. Also setup deviations were simulated to evaluate the ability of the CBCT-based calculation for detecting the dose errors caused by positioning deviation. The gamma comparison between CBCT- and FBCT-based dose computations showed that the pass rates of (2%, 2 mm) criteria were better than 97.60 ± 0.83% and 97.74 ± 2.08% in the phantom and 10 NPC cases. When setup deviation was introduced into CBCT-based dose calculation, the gamma pass rate significantly decreased while the volumetric doses of the targets and some normal organs exhibited different changes compared to the original plan. Our results validated the above CT value-electron density correction which reduced the difference between CBCT- and FBCT-based IMRT plan calculation for NPC to less than 2%. Online CBCT-based dose calculation can be used to reflect and evaluate the dose distribution discrepancy caused by setup deviation and structure changes during the treatment, ensuring more effective quality control of IMRT treatment.