Pulmonary magnetic resonance-guided online adaptive radiotherapy of locally advanced: the PUMA trial.

BACKGROUND: Patients with locally-advanced non-small-cell lung cancer (LA-NSCLC) are often ineligible for surgery, so that definitive chemoradiotherapy (CRT) represents the treatment of choice. Nevertheless, long-term tumor control is often not achieved. Intensification of radiotherapy (RT) to improve locoregional tumor control is limited by the detrimental effect of higher radiation exposure of thoracic organs-at-risk (OAR). This narrow therapeutic ratio may be expanded by exploiting the advantages of magnetic resonance (MR) linear accelerators, mainly the online adaptation of the treatment plan to the current anatomy based on daily acquired MR images. However, MR-guidance is both labor-intensive and increases treatment times, which raises the question of its clinical feasibility to treat LA-NSCLC. Therefore, the PUMA trial was designed as a prospective, multicenter phase I trial to demonstrate the clinical feasibility of MR-guided online adaptive RT in LA-NSCLC. METHODS: Thirty patients with LA-NSCLC in stage III A-C will be accrued at three German university hospitals to receive MR-guided online adaptive RT at two different MR-linac systems (MRIdian Linac®, View Ray Inc. and Elekta Unity®, Elekta AB) with concurrent chemotherapy. Conventionally fractioned RT with isotoxic dose escalation up to 70 Gy is applied. Online plan adaptation is performed once weekly or in case of major anatomical changes. Patients are followed-up by thoracic CT- and MR-imaging for 24 months after treatment. The primary endpoint is twofold: (1) successfully completed online adapted fractions, (2) on-table time. Main secondary endpoints include adaptation frequency, toxicity, local tumor control, progression-free and overall survival. DISCUSSION: PUMA aims to demonstrate the clinical feasibility of MR-guided online adaptive RT of LA-NSCLC. If successful, PUMA will be followed by a clinical phase II trial that further investigates the clinical benefits of this approach. Moreover, PUMA is part of a large multidisciplinary project to develop MR-guidance techniques. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05237453 .

Statistical breathing curve sampling to quantify interplay effects of moving lung tumors in a 4D Monte Carlo dose calculation framework.

PURPOSE: The interplay between respiratory tumor motion and dose application by intensity modulated radiotherapy (IMRT) techniques can potentially lead to undesirable and non-intuitive deviations from the planned dose distribution. We developed a 4D Monte Carlo (MC) dose recalculation framework featuring statistical breathing curve sampling, to precisely simulate the dose distribution for moving target volumes aiming at a comprehensive assessment of interplay effects. METHODS: We implemented a dose accumulation tool that enables dose recalculations of arbitrary breathing curves including the actual breathing curve of the patient. This MC dose recalculation framework is based on linac log-files, facilitating a high temporal resolution up to 0.1 s. By statistical analysis of 128 different breathing curves, interplay susceptibility of different treatment parameters was evaluated for an exemplary patient case. To facilitate prospective clinical application in the treatment planning stage, in which patient breathing curves or linac log-files are not available, we derived a log-file free version with breathing curves generated by a random walk approach. Interplay was quantified by standard deviations σ in D5%, D50% and D95%. RESULTS: Interplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy (σD95% up to 1.3 %) showing a decrease with higher fraction doses and an increase with higher MU rates. Interplay effects for conformal treatment techniques were negligible (σ<0.1%). The log-file free version and the random walk generated breathing curves yielded similar results (deviations in σ< 0.1 %) and can be used as substitutes for interplay assessment. CONCLUSION: It is feasible to combine statistically sampled breathing curves with MC dose calculations. The universality of the presented framework allows comprehensive assessment of interplay effects in retrospective and prospective clinically relevant scenarios.

A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation.

BACKGROUND: We describe and evaluate a deep network algorithm which automatically contours organs at risk in the thorax and pelvis on computed tomography (CT) images for radiation treatment planning. METHODS: The algorithm identifies the region of interest (ROI) automatically by detecting anatomical landmarks around the specific organs using a deep reinforcement learning technique. The segmentation is restricted to this ROI and performed by a deep image-to-image network (DI2IN) based on a convolutional encoder-decoder architecture combined with multi-level feature concatenation. The algorithm is commercially available in the medical products "syngo.via RT Image Suite VB50" and "AI-Rad Companion Organs RT VA20" (Siemens Healthineers). For evaluation, thoracic CT images of 237 patients and pelvic CT images of 102 patients were manually contoured following the Radiation Therapy Oncology Group (RTOG) guidelines and compared to the DI2IN results using metrics for volume, overlap and distance, e.g., Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD95). The contours were also compared visually slice by slice. RESULTS: We observed high correlations between automatic and manual contours. The best results were obtained for the lungs (DSC 0.97, HD95 2.7 mm/2.9 mm for left/right lung), followed by heart (DSC 0.92, HD95 4.4 mm), bladder (DSC 0.88, HD95 6.7 mm) and rectum (DSC 0.79, HD95 10.8 mm). Visual inspection showed excellent agreements with some exceptions for heart and rectum. CONCLUSIONS: The DI2IN algorithm automatically generated contours for organs at risk close to those by a human expert, making the contouring step in radiation treatment planning simpler and faster. Few cases still required manual corrections, mainly for heart and rectum.

Dosimetric Impact of the Positional Imaging Frequency for Hypofractionated Prostate Radiotherapy - A Voxel-by-Voxel Analysis.

BACKGROUND: To investigate deviations between planned and applied treatment doses for hypofractionated prostate radiotherapy and to quantify dosimetric accuracy in dependence of the image guidance frequency. METHODS: Daily diagnostic in-room CTs were carried out in 10 patients in treatment position as image guidance for hypofractionated prostate radiotherapy. Fraction doses were mapped to the planning CTs and recalculated, and applied doses were accumulated voxel-wise using deformable registration. Non-daily imaging schedules were simulated by deriving position correction vectors from individual scans and used to rigidly register the following scans until the next repositioning before dose recalculation and accumulation. Planned and applied doses were compared regarding dose-volume indices and TCP and NTCP values in dependence of the imaging and repositioning frequency. RESULTS: Daily image-guided repositioning was associated with only negligible deviations of analyzed dose-volume parameters and conformity/homogeneity indices for the prostate, bladder and rectum. Average CTV T did not significantly deviate from the plan values, and rectum NTCPs were highly comparable, while bladder NTCPs were reduced. For non-daily image-guided repositioning, there were significant deviations in the high-dose range from the planned values. Similarly, CTV dose conformity and homogeneity were reduced. While TCPs and rectal NTCPs did not significantly deteriorate for non-daily repositioning, bladder NTCPs appeared falsely diminished in dependence of the imaging frequency. CONCLUSION: Using voxel-by-voxel dose accumulation, we showed for the first time that daily image-guided repositioning resulted in only negligible dosimetric deviations for hypofractionated prostate radiotherapy. Regarding dosimetric aberrations for non-daily imaging, daily imaging is required to adequately deliver treatment.

Real-time 4DMRI-based internal target volume definition for moving lung tumors.

PURPOSE: In photon radiotherapy, respiratory-induced target motion can be accounted for by internal target volumes (ITV) or mid-ventilation target volumes (midV) defined on the basis of four-dimensional computed tomography (4D-CT). Intrinsic limitations of these approaches can result in target volumes that are not representative for the gross tumor volume (GTV) motion over the course of treatment. To address these limitations, we propose a novel patient-specific ITV definition method based on real-time 4D magnetic resonance imaging (rt-4DMRI). METHODS: Three lung cancer patients underwent weekly rt-4DMRI scans. A total of 24 datasets were included in this retrospective study. The GTV was contoured on breath-hold MR images and propagated to all rt-4DMRI images by deformable image registration. Different targets were created for the first (reference) imaging sessions: ITVs encompassing all GTV positions over the complete (ITV 80 s ) or partial acquisition time ( ITV 10 s ), ITVs including only voxels with a GTV probability-of-presence (POP) of at least 5% ( ITV 5 % ) or 10% ( ITV 10 % ), and the mid-ventilation GTV position. Reference planning target volumes ( PTV r ) were created by adding margins around the ITVs and midV target volumes. The geometrical overlap of the PTV r with ITV n 5 % from the six to eight subsequent imaging sessions on days n was quantified in terms of the Dice similarity coefficient (DSC), sensitivity [SE: ( PTV r ∩ ITV n 5 % )/ ITV n 5 % ] and precision [PRE: ( PTV r ∩ ITV n 5 % )/ PTV r ] as surrogates for target coverage and normal tissue sparing. RESULTS: Patient-specific analysis yielded a high variance of the overlap values of PTV r 10 s , when different periods within the reference imaging session were sampled. The mid-ventilation-based PTVs were smaller than the ITV-based PTVs. While the SE was high for patients with small breathing pattern variations, changes of the median breathing amplitudes in different imaging sessions led to inferior SE values for the mid-ventilation PTV for one patient. In contrast, PTV r 5 % and PTV r 10 % showed higher SE values with a higher robustness against interfractional changes, at the cost of larger target volumes. CONCLUSIONS: The results indicate that rt-4DMRI could be valuable for the definition of target volumes based on the GTV POP to achieve a higher robustness against interfractional changes than feasible with today's 4D-CT-based target definition concepts.

Towards optimal stopping in radiation therapy.

A typical fractionated radiotherapy (RT) course is a long and arduous process, demanding significant financial, physical, and mental commitments from patients. Each additional session of RT significantly increases the physical and psychological burden on patients and leads to higher radiation exposure in organs-at-risk (OAR), while, in some cases, the therapeutic benefits might not be high enough to justify the risks. Today, through technological advancements in molecular biology, imaging, and genetics more information is gathered about individual patient response before, during, and after the treatment. we highlight some of the ways that mathematical tools can help assess treatment efficacy on the fly, adapt the treatment plan based on individual biological response, and optimally stop the treatment, if necessary. We term this "Optimal Stopping in RT (OSRT)", after a similar concept in the fields of dynamic programming and Markov decision processes. In short, OSRT can dynamically determine "whether, when and how" to stop the treatment to improve therapeutic ratios.

Feasibility of 4DCBCT-based proton dose calculation: An ex vivo porcine lung phantom study.

Inter-fractional variations of breathing pattern and patient anatomy introduce dose uncertainties in proton therapy. One approach to monitor these variations is to utilize the cone-beam computed tomography (CT, CBCT) scans routinely taken for patient positioning, reconstruct them as 4DCBCTs, and generate 'virtual CTs' (vCTs), combining the accurate CT numbers of the diagnostic 4DCT and the geometry of the daily 4DCBCT by using deformable image registration (DIR). In this study different algorithms for 4DCBCT reconstruction and DIR were evaluated. For this purpose, CBCT scans of a moving ex vivo porcine lung phantom with 663 and 2350 projections respectively were acquired, accompanied by an additional 4DCT as reference. The CBCT projections were sorted in 10 phase bins with the Amsterdam-shroud method and reconstructed phase-by-phase using first a FDK reconstruction from the Reconstruction Toolkit (RTK) and again an iterative reconstruction algorithm implemented in the Gadgetron Toolkit. The resulting 4DCBCTs were corrected by DIR of the corresponding 4DCT phases, using both a morphons algorithm from REGGUI and a b-spline deformation from Plastimatch. The resulting 4DvCTs were compared to the 4DCT by visual inspection and by calculating water equivalent thickness (WET) maps from the phantom's surface to the distal edge of a target from various angles. The optimized procedure was successfully repeated with mismatched input phases and on a clinical patient dataset. Proton treatment plans were simulated on the 4DvCTs and the dose distributions compared to the reference based on the 4DCT via gamma pass rate analysis. A combination of iterative reconstruction and morphons DIR yielded the most accurate 4DvCTs, with median WET differences under 2mm and 3%/3mm gamma pass rates per phase between 89% and 99%. These results suggest that image correction of iteratively reconstructed 4DCBCTs with a morphons DIR of the planning CT may yield sufficiently accurate 4DvCTs for daily time resolved proton dose calculations.

Dose-guided patient positioning in proton radiotherapy using multicriteria-optimization.

Proton radiotherapy (PT) requires accurate target alignment before each treatment fraction, ideally utilizing 3D in-room X-ray computed tomography (CT) imaging. Typically, the optimal patient position is determined based on anatomical landmarks or implanted markers. In the presence of non-rigid anatomical changes, however, the planning scenario cannot be exactly reproduced and positioning should rather aim at finding the optimal position in terms of the actually applied dose. In this work, dose-guided patient alignment, implemented as multicriterial optimization (MCO) problem, was investigated in the scope of intensity-modulated and double-scattered PT (IMPT and DSPT) for the first time. A method for automatically determining the optimal patient position with respect to pre-defined clinical goals was implemented. Linear dose interpolation was used to access a continuous space of potential patient shifts. Fourteen head and neck (H&N) and eight prostate cancer patients with up to five repeated CTs were included. Dose interpolation accuracy was evaluated and the potential dosimetric advantages of dose-guided over bony-anatomy-based patient alignment investigated by comparison of clinically relevant target and organ-at-risk (OAR) dose-volume histogram (DVH) parameters. Dose interpolation was found sufficiently accurate with average pass-rates of 90% and 99% for an exemplary H&N and prostate patient, respectively, using a 2% dose-difference criterion. Compared to bony-anatomy-based alignment, the main impact of automated MCO-based dose-guided positioning was a reduced dose to the serial OARs (spinal cord and brain stem) for the H&N cohort. For the prostate cohort, under-dosage of the target structures could be efficiently diminished. Limitations of dose-guided positioning were mainly found in reducing target over-dosage due to weight loss for H&N patients, which might require adaptation of the treatment plan. Since labor-intense online quality-assurance is not required for dose-guided patient positioning, it might, nevertheless, be considered an interesting alternative to full online re-planning for initially mitigating the effects of anatomical changes.

Multi-criterial patient positioning based on dose recalculation on scatter-corrected CBCT images.

BACKGROUND AND PURPOSE: Our aim was to evaluate the feasibility and potential advantages of dose guided patient positioning based on dose recalculation on scatter corrected cone beam computed tomography (CBCT) image data. MATERIAL AND METHODS: A scatter correction approach has been employed to enable dose calculations on CBCT images. A recently proposed tool for interactive multicriterial dose-guided patient positioning which uses interpolation between pre-calculated sample doses has been utilized. The workflow was retrospectively evaluated for two head and neck patients with a total of 39 CBCTs. Dose-volume histogram (DVH) parameters were compared to rigid image registration based isocenter corrections (clinical scenario). RESULTS: The accuracy of the dose interpolation was found sufficient, facilitating the implementation of dose guided patient positioning. Compared to the clinical scenario, the mean dose to the parotid glands could be improved for 2 out of 5 fractions for the first patient while other parameters were preserved. For the second patient, the mean coverage over all fractions of the high dose PTV could be improved by 4%. For this patient, coverage improvements had to be traded against organ at risk (OAR) doses within their clinical tolerance limits. CONCLUSIONS: Dose guided patient positioning using in-room CBCT data is feasible and offers increased control over target coverage and doses to OARs.

Application of single- and dual-energy CT brain tissue segmentation to PET monitoring of proton therapy.

The purpose of this work was to evaluate the ability of single and dual energy computed tomography (SECT, DECT) to estimate tissue composition and density for usage in Monte Carlo (MC) simulations of irradiation induced ß + activity distributions. This was done to assess the impact on positron emission tomography (PET) range verification in proton therapy. A DECT-based brain tissue segmentation method was developed for white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). The elemental composition of reference tissues was assigned to closest CT numbers in DECT space (DECTdist). The method was also applied to SECT data (SECTdist). In a validation experiment, the proton irradiation induced PET activity of three brain equivalent solutions (BES) was compared to simulations based on different tissue segmentations. Five patients scanned with a dual source DECT scanner were analyzed to compare the different segmentation methods. A single magnetic resonance (MR) scan was used for comparison with an established segmentation toolkit. Additionally, one patient with SECT and post-treatment PET scans was investigated. For BES, DECTdist and SECTdist reduced differences to the reference simulation by up to 62% when compared to the conventional stoichiometric segmentation (SECTSchneider). In comparison to MR brain segmentation, Dice similarity coefficients for WM, GM and CSF were 0.61, 0.67 and 0.66 for DECTdist and 0.54, 0.41 and 0.66 for SECTdist. MC simulations of PET treatment verification in patients showed important differences between DECTdist/SECTdist and SECTSchneider for patients with large CSF areas within the treatment field but not in WM and GM. Differences could be misinterpreted as PET derived range shifts of up to 4 mm. DECTdist and SECTdist yielded comparable activity distributions, and comparison of SECTdist to a measured patient PET scan showed improved agreement when compared to SECTSchneider. The agreement between predicted and measured PET activity distributions was improved by employing a brain specific segmentation applicable to both DECT and SECT data.

A novel method for interactive multi-objective dose-guided patient positioning.

In intensity-modulated radiation therapy (IMRT), 3D in-room imaging data is typically utilized for accurate patient alignment on the basis of anatomical landmarks. In the presence of non-rigid anatomical changes, it is often not obvious which patient position is most suitable. Thus, dose-guided patient alignment is an interesting approach to use available in-room imaging data for up-to-date dose calculation, aimed at finding the position that yields the optimal dose distribution. This contribution presents the first implementation of dose-guided patient alignment as multi-criteria optimization problem. User-defined clinical objectives are employed for setting up a multi-objective problem. Using pre-calculated dose distributions at a limited number of patient shifts and dose interpolation, a continuous space of Pareto-efficient patient shifts becomes accessible. Pareto sliders facilitate interactive browsing of the possible shifts with real-time dose display to the user. Dose interpolation accuracy is validated and the potential of multi-objective dose-guided positioning demonstrated for three head and neck (H&N) and three prostate cancer patients. Dose-guided positioning is compared to replanning for all cases. A delineated replanning CT served as surrogate for in-room imaging data. Dose interpolation accuracy was high. Using a [Formula: see text] dose difference criterion, a median pass-rate of 95.7% for H&N and 99.6% for prostate cases was determined in a comparison to exact dose calculations. For all patients, dose-guided positioning allowed to find a clinically preferable dose distribution compared to bony anatomy based alignment. For all H&N cases, mean dose to the spared parotid glands was below [Formula: see text] (up to [Formula: see text] with bony alignment) and clinical target volume (CTV) [Formula: see text] above 99.1% (compared to 95.1%). For all prostate patients, CTV [Formula: see text] was above 98.9% (compared to 88.5%) and [Formula: see text] to the rectum below [Formula: see text] (compared to 56.1%). Replanning yielded improved results for the H&N cases. For the prostate cases, differences to dose-guided positioning were minor.

Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT.

PURPOSE: This work aims at investigating intensity corrected cone-beam x-ray computed tomography (CBCT) images for accurate dose calculation in adaptive intensity modulated proton therapy (IMPT) for prostate and head and neck (H&N) cancer. A deformable image registration (DIR)-based method and a scatter correction approach using the image data obtained from DIR as prior are characterized and compared on the basis of the same clinical patient cohort for the first time. METHODS: Planning CT (pCT) and daily CBCT data (reconstructed images and measured projections) of four H&N and four prostate cancer patients have been considered in this study. A previously validated Morphons algorithm was used for DIR of the planning CT to the current CBCT image, yielding a so-called virtual CT (vCT). For the first time, this approach was translated from H&N to prostate cancer cases in the scope of proton therapy. The warped pCT images were also used as prior for scatter correction of the CBCT projections for both tumor sites. Single field uniform dose and IMPT (only for H&N cases) treatment plans have been generated with a research version of a commercial planning system. Dose calculations on vCT and scatter corrected CBCT (CBCTcor) were compared by means of the proton range and a gamma-index analysis. For the H&N cases, an additional diagnostic replanning CT (rpCT) acquired within three days of the CBCT served as additional reference. For the prostate patients, a comprehensive contour comparison of CBCT and vCT, using a trained physician's delineation, was performed. RESULTS: A high agreement of vCT and CBCTcor was found in terms of the proton range and gamma-index analysis. For all patients and indications between 95% and 100% of the proton dose profiles in beam's eye view showed a range agreement of better than 3 mm. The pass rate in a (2%,2 mm) gamma-comparison was between 96% and 100%. For H&N patients, an equivalent agreement of vCT and CBCTcor to the reference rpCT was observed. However, for the prostate cases, an insufficient accuracy of the vCT contours retrieved from DIR was found, while the CBCTcor contours showed very high agreement to the contours delineated on the raw CBCT. CONCLUSIONS: For H&N patients, no considerable differences of vCT and CBCTcor were found. For prostate cases, despite the high dosimetric agreement, the DIR yields incorrect contours, probably due to the more pronounced anatomical changes in the abdomen and the reduced soft-tissue contrast in the CBCT. Using the vCT as prior, these inaccuracies can be overcome and images suitable for accurate delineation and dose calculation in CBCT-based adaptive IMPT can be retrieved from scatter correction of the CBCT projections.

Feasibility of automated proton therapy plan adaptation for head and neck tumors using cone beam CT images.

BACKGROUND: Intensity modulated proton therapy (IMPT) of head and neck (H&N) tumors may benefit from plan adaptation to correct for the dose perturbations caused by weight loss and tumor volume changes observed in these patients. As cone beam CT (CBCT) is increasingly considered in proton therapy, it may be possible to use available CBCT images following intensity correction for plan adaptation. This is the first study exploring IMPT plan adaptation on CBCT images corrected and delineated by deformable image registration of the planning CT (pCT) to the CBCT, yielding a virtual CT (vCT). METHODS: A Morphons algorithm was used to deform the pCTs and corresponding delineations of 9 H&N cancer patients to a weekly CBCT acquired within ±3 days of a control replanning CT scan (rpCT). The IMPT treatment plans were adapted using the vCT and the adapted and original plans were recalculated on the rpCT for dose/volume parameter evaluation of the impact of adaptation. RESULTS: On the rpCT, the adapted plans were equivalent to the original plans in terms of target volumes D 95 and V 95, but showed a significant reduction of D 2 in these volumes. OAR doses were mostly equivalent or reduced. In particular, the adapted plans did not reduce parotid gland D mean, but the dose to the optical system. For three patients the spinal cord or brain stem received higher, though well below tolerance, maximum dose. Subsequent tightening of the treatment planning constraints for these OARs on new vCT-adapted plans did not degrade target coverage and yielded pCT equivalent plans on the vCT. CONCLUSIONS: An offline automated procedure to generate an adapted IMPT plan on CBCT images was developed and investigated. When evaluating the adapted plan on a control rpCT we observed reduced D 2 in target volumes as major improvement. OAR sparing was only partially improved by the procedure. Despite potential limitations in the accuracy of the vCT approach, an improved quality of the adapted plans could be achieved.

Comparison of proton therapy treatment planning for head tumors with a pencil beam algorithm on dual and single energy CT images.

PURPOSE: Dual energy CT (DECT) has recently been proposed as an improvement over single energy CT (SECT) for stopping power ratio (SPR) estimation for proton therapy treatment planning (TP), thereby potentially reducing range uncertainties. Published literature investigated phantoms. This study aims at performing proton therapy TP on SECT and DECT head images of the same patients and at evaluating whether the reported improved DECT SPR accuracy translates into clinically relevant range shifts in clinical head treatment scenarios. METHODS: Two phantoms were scanned at a last generation dual source DECT scanner at 90 and 150 kVp with Sn filtration. The first phantom (Gammex phantom) was used to calibrate the scanner in terms of SPR while the second served as evaluation (CIRS phantom). DECT images of five head trauma patients were used as surrogate cancer patient images for TP of proton therapy. Pencil beam algorithm based TP was performed on SECT and DECT images and the dose distributions corresponding to the optimized proton plans were calculated using a Monte Carlo (MC) simulation platform using the same patient geometry for both plans obtained from conversion of the 150 kVp images. Range shifts between the MC dose distributions from SECT and DECT plans were assessed using 2D range maps. RESULTS: SPR root mean square errors (RMSEs) for the inserts of the Gammex phantom were 1.9%, 1.8%, and 1.2% for SECT phantom calibration (SECTphantom), SECT stoichiometric calibration (SECTstoichiometric), and DECT calibration, respectively. For the CIRS phantom, these were 3.6%, 1.6%, and 1.0%. When investigating patient anatomy, group median range differences of up to -1.4% were observed for head cases when comparing SECTstoichiometric with DECT. For this calibration the 25th and 75th percentiles varied from -2% to 0% across the five patients. The group median was found to be limited to 0.5% when using SECTphantom and the 25th and 75th percentiles varied from -1% to 2%. CONCLUSIONS: Proton therapy TP using a pencil beam algorithm and DECT images was performed for the first time. Given that the DECT accuracy as evaluated by two phantoms was 1.2% and 1.0% RMSE, it is questionable whether the range differences reported here are significant.

Long-term results in malignant pleural mesothelioma treated with neoadjuvant chemotherapy, extrapleural pneumonectomy and intensity-modulated radiotherapy.

INTRODUCTION: We investigated the clinical outcome and the toxicity of trimodal therapy of malignant pleural mesothelioma (MPM) treated with neoadjuvant chemotherapy, extrapleural pneumonectomy (EPP) and adjuvant intensity-modulated radiotherapy (IMRT). METHODS: Chemotherapy regimens included Cisplatin/Pemetrexed, Carboplatin/Pemetrexed and Cisplatin/Gemcitabine, followed by EPP. 62 patients completed the adjuvant radiotherapy. IMRT was carried out in two techniques, either step&shoot or helical tomotherapy. Median target dose was 48 Gy to 54 Gy. Toxicity was scored with the Common Terminology Criteria (CTC) for Adverse Events. We used Kaplan-Meier method to estimate actuarial rate of locoregional control (LRC), distant control (DC) and overall survival (OS), measured from the date of surgery. Rates were compared using the logrank test. For multivariate analysis the Cox proportional hazard model was used. RESULTS: The median OS, LRC and DC times were 20.4, 31.4 and 21.4 months. The 1-, 2-, 3-year OS rates were 63, 42, 28 %, the LRC rates were 81, 60, 40 %, and the DC rates were 62, 48, 41 %. We observed no CTC grade 4 or grade 5 toxicity. Step&shoot and helical tomotherapy were equivalent both in dosimetric characteristics and clinical outcome. Biphasic tumor histology was associated with worse clinical outcome compared to epitheloid histology. CONCLUSIONS: Mature clinical results of trimodal treatment for MPM were presented. They indicate that hemithoracic radiotherapy after EPP can be safely administered by either step&shoot IMRT and tomotherapy. However, the optimal prospective patient selection for this aggressive trimodal therapy approach remains unclear. This study can serve as a benchmark for current and future therapy concepts for MPM.

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.

Combined use of (18)F-FDG and (18)F-FMISO in unresectable non-small cell lung cancer patients planned for radiotherapy: a dynamic PET/CT study.

Aim of this study was to evaluate and compare, by means of dynamic and static PET/CT, the distribution patterns and pharmacokinetics of fluorine-18 fluorodeoxyglucose ((18)F-FDG) and of fluorine-18-fluoromisonidazole ((18)F-FMISO) in non-small cell lung cancer (NSCLC) patients scheduled for intensity modulated radiation therapy (IMRT). Thirteen patients suffering from inoperable stage III NSCLC underwent PET/CTs with (18)F-FDG and (18)F-FMISO for tumor metabolism and hypoxia assessment accordingly. Evaluation of PET/CT studies was based on visual analysis, semi-quantitative (SUV) calculations and absolute quantitative estimations, after application of a two-tissue compartment model and a non-compartmental approach. (18)F-FDG PET/CT revealed all thirteen primary lung tumors as sites of increased (18)F-FDG uptake. Six patients demonstrated also in total 43 (18)F-FDG avid metastases; these patients were excluded from radiotherapy. (18)F-MISO PET/CT demonstrated 12/13 primary lung tumors with faint tracer uptake. Only one tumor was clearly (18)F-FMISO avid, (SUVaverage = 3.4, SUVmax = 5.0). Mean values for (18)F-FDG, as derived from dPET/CT data, were SUVaverage = 8.9, SUVmax = 15.1, K1 = 0.23, k2 = 0.53, k3 = 0.17, k4 = 0.02, influx = 0.05 and fractal dimension (FD) = 1.25 for the primary tumors. The respective values for (18)F-FMISO were SUVaverage = 1.4, SUVmax = 2.2, K1 = 0.26, k2 = 0.56, k3 = 0.06, k4 = 0.06, influx = 0.02 and FD = 1.14. No statistically significant correlation was observed between the two tracers. (18)F-FDG PET/CT changed therapy management in six patients, by excluding them from planned IMRT. (18)F-FMISO PET/CT revealed absence of significant tracer uptake in the majority of the (18)F-FDG avid NSCLCs. Lack of correlation between the two tracers' kinetics indicates that they reflect different molecular mechanisms and implies the discordance between increased glycolysis and hypoxia in the malignancy.

Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation.

PURPOSE: Intensity modulated proton therapy (IMPT) of head and neck (H&N) cancer patients may be improved by plan adaptation. The decision to adapt the treatment plan based on a dose recalculation on the current anatomy requires a diagnostic quality computed tomography (CT) scan of the patient. As gantry-mounted cone beam CT (CBCT) scanners are currently being offered by vendors, they may offer daily or weekly updates of patient anatomy. CBCT image quality may not be sufficient for accurate proton dose calculation and it is likely necessary to perform CBCT CT number correction. In this work, the authors investigated deformable image registration (DIR) of the planning CT (pCT) to the CBCT to generate a virtual CT (vCT) to be used for proton dose recalculation. METHODS: Datasets of six H&N cancer patients undergoing photon intensity modulated radiation therapy were used in this study to validate the vCT approach. Each dataset contained a CBCT acquired within 3 days of a replanning CT (rpCT), in addition to a pCT. The pCT and rpCT were delineated by a physician. A Morphons algorithm was employed in this work to perform DIR of the pCT to CBCT following a rigid registration of the two images. The contours from the pCT were deformed using the vector field resulting from DIR to yield a contoured vCT. The DIR accuracy was evaluated with a scale invariant feature transform (SIFT) algorithm comparing automatically identified matching features between vCT and CBCT. The rpCT was used as reference for evaluation of the vCT. The vCT and rpCT CT numbers were converted to stopping power ratio and the water equivalent thickness (WET) was calculated. IMPT dose distributions from treatment plans optimized on the pCT were recalculated with a Monte Carlo algorithm on the rpCT and vCT for comparison in terms of gamma index, dose volume histogram (DVH) statistics as well as proton range. The DIR generated contours on the vCT were compared to physician-drawn contours on the rpCT. RESULTS: The DIR accuracy was better than 1.4 mm according to the SIFT evaluation. The mean WET differences between vCT (pCT) and rpCT were below 1 mm (2.6 mm). The amount of voxels passing 3%/3 mm gamma criteria were above 95% for the vCT vs rpCT. When using the rpCT contour set to derive DVH statistics from dose distributions calculated on the rpCT and vCT the differences, expressed in terms of 30 fractions of 2 Gy, were within [-4, 2 Gy] for parotid glands (D(mean)), spinal cord (D(2%)), brainstem (D(2%)), and CTV (D(95%)). When using DIR generated contours for the vCT, those differences ranged within [-8, 11 Gy]. CONCLUSIONS: In this work, the authors generated CBCT based stopping power distributions using DIR of the pCT to a CBCT scan. DIR accuracy was below 1.4 mm as evaluated by the SIFT algorithm. Dose distributions calculated on the vCT agreed well to those calculated on the rpCT when using gamma index evaluation as well as DVH statistics based on the same contours. The use of DIR generated contours introduced variability in DVH statistics.