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Zusammenfassung Vorgestellt wird eine Strategie zur Adaption der Dosis an strahlenresistente hypoxische Tumoren (Dose Painting). Hierzu wurden 15 HNO-Patienten vor Beginn einer 70-Gy-Strahlentherapie mit 18F-FDG und mit dynamischem 18F-FMISO PET untersucht. Nach ca. 20 Gy wurde ein weiterer dyn. 18F-FMISO Scan durchgefuhrt. Die voxelbasierten 18F-FMISO-Daten wurden mit einem kinetischen Modell ausgewertet, das die Berechnung lokaler Gewebeparameter fur Hypoxie und Perfusion ermoglicht. Eine statistische Auswertung ergab, dass nur eine Kombination aus beiden Parametern eine signifikante Stratifizierung hinsichtlich des Therapieerfolgs zulasst. Eine Ubersetzung der Bildgebungsdaten in geeignete Dosisverschreibungen kann nur uber ein TCP-Modell, das die funktionellen Parameter berucksichtigt, erreicht werden. Ein solches Modell wurde mit den Nachsorgedaten der 15 Patienten kalibriert. Somit ist eine Berechnung von lokal variierenden Dosiseskalationsfaktoren moglich, die dann zur Planung eines Hypoxie Dose Paintings verwendet werden konnen. Eine Planungsstudie zeigte, dass Dose Painting ohne eine hohere Belastung der Risikoorgane moglich ist.

With respect to the demands of adaptive and 4D-radiotherapy applications, an algorithm is proposed for a fully automatic, multimodality deformable registration that follows the concept of translational relocation of regularly distributed image subvolumes governed by local anatomical features. Thereby, the problem of global deformable registration is broken down to multiple independent local registration steps which allows for straightforward parallelization of the algorithm. In a subsequent step, possible local misregistrations are corrected for by minimization of the elastic energy of the displacement field under consideration of image information. The final displacement field results from interpolation of the subvolume shift vectors. The algorithm can employ as a similarity measure both the correlation coefficient and mutual information. The latter allows the application to intermodality deformable registration problems. The typical calculation time on a modern multiprocessor PC is well below 1 min, which facilitates almost-interactive, "online" usage. CT-to-MRI and CT-to-cone-beam-CT registrations of head-and-neck data sets are presented, as well as inhale-to-exhale registrations of lung CT data sets. For quantitative evaluation of registration accuracy, a virtual thorax phantom was developed; additionally, a landmark-based evaluation on four lung respiratory-correlated CT data sets was performed. This consistently resulted in average registration residuals on the order of the voxel size or less (3D-residuals approximately 1-2 mm). Summarizing, the presented algorithm allows an accurate multimodality deformable registration with calculation times well below 1 min, and thus bears promise as a versatile basic tool in adaptive and 4D-radiotherapy applications.

Purpose: The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. Methods and Materials: PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as 'eigenmodes,' which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. Results: Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe {approx}94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses ({approx}40-45 Gy) andmore » volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. Conclusions: PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches.« less

The purpose of this work was the development of a probabilistic planning method with biological cost functions that does not require the definition of margins. Geometrical uncertainties were integrated in tumor control probability (TCP) and normal tissue complication probability (NTCP) objective functions for inverse planning. For efficiency reasons random errors were included by blurring the dose distribution and systematic errors by shifting structures with respect to the dose. Treatment plans were made for 19 prostate patients following four inverse strategies: Conformal with homogeneous dose to the planning target volume (PTV), a simultaneous integrated boost using a second PTV, optimization using TCP and NTCP functions together with a PTV, and probabilistic TCP and NTCP optimization for the clinical target volume without PTV. The resulting plans were evaluated by independent Monte Carlo simulation of many possible treatment histories including geometrical uncertainties. The results showed that the probabilistic optimization technique reduced the rectal wall volume receiving high dose, while at the same time increasing the dose to the clinical target volume. Without sacrificing the expected local control rate, the expected rectum toxicity could be reduced by 50% relative to the boost technique. The improvement over the conformal technique was larger yet. The margin based biological technique led to toxicity in between the boost and probabilistic techniques, but its control rates were very variable and relatively low. During evaluations, the sensitivity of the local control probability to variations in biological parameters appeared similar for all four strategies. The sensitivity to variations of the geometrical error distributions was strongest for the probabilistic technique. It is concluded that probabilistic optimization based on tumor control probability and normal tissue complication probability is feasible. It results in robust prostate treatment plans with an improved balance between local control and rectum toxicity, compared to conventional techniques.

A dedicated, efficient Monte Carlo (MC) accelerator head model for intensity modulated stereotactic radiosurgery treatment planning is needed to afford a highly accurate simulation of tiny IMRT fields. A virtual source model (VSM) of a mini multi-leaf collimator (MLC) (the Elekta Beam Modulator (EBM)) is presented, allowing efficient generation of particles even for small fields. The VSM of the EBM is based on a previously published virtual photon energy fluence model (VEF) (Fippel et al 2003 Med. Phys. 30 301) commissioned with large field measurements in air and in water. The original commissioning procedure of the VEF, based on large field measurements only, leads to inaccuracies for small fields. In order to improve the VSM, it was necessary to change the VEF model by developing (1) a method to determine the primary photon source diameter, relevant for output factor calculations, (2) a model of the influence of the flattening filter on the secondary photon spectrum and (3) a more realistic primary photon spectrum. The VSM model is used to generate the source phase space data above the mini-MLC. Later the particles are transmitted through the mini-MLC by a passive filter function which significantly speeds up the time of generation of the phase space data after the mini-MLC, used for calculation of the dose distribution in the patient. The improved VSM model was commissioned for 6 and 15 MV beams. The results of MC simulation are in very good agreement with measurements. Less than 2% of local difference between the MC simulation and the diamond detector measurement of the output factors in water was achieved. The X, Y and Z profiles measured in water with an ion chamber (V = 0.125 cm(3)) and a diamond detector were used to validate the models. An overall agreement of 2%/2 mm for high dose regions and 3%/2 mm in low dose regions between measurement and MC simulation for field sizes from 0.8 x 0.8 cm(2) to 16 x 21 cm(2) was achieved. An IMRT plan film verification was performed for two cases: 6 MV head&neck and 15 MV prostate. The simulation is in agreement with film measurements within 2%/2 mm in the high dose regions (> or = 0.1 Gy = 5% D(max)) and 5%/2 mm in low dose regions (

Purpose: To develop a model for reoxygenation dynamic and its relationship to local control after radiotherapy (RT), based on repeated dynamic [ 18 F]-fluoromisonidazole (FMISO) positron emission tomography (PET) examinations in head-and-neck cancer patients. Methods and Materials: Ten head-and-neck cancer patients were examined with dynamic FMISO PET before RT with 70 Gy and after approximately 20 Gy. Two of these patients had two additional dynamic FMISO scans during treatment. Local recurrence was assessed by computed tomography–based follow-up 8–24 months after RT. Tumor-specific values for the level of FMISO retention R and the vascular perfusion efficiency P were determined with a kinetic compartment model. Results: Individual R – P scattergrams before and during therapy were analyzed, and significant therapy-induced changes in the characteristic R – P patterns were observed. A tumor control probability model was derived that involves the tissue parameters R and P and estimates the time to reoxygenation. On the basis of this model, a malignancy value M was introduced and calibrated by a fit to the observed outcome data. Reoxygenation is reflected by the model as a progression to less-malignant tumor types ( i.e. , smaller values of M ). In 4 of 6 patients with severe hypoxia, M had decreased after 20 Gy, whereas 2 patients showed increasing M . Four patients showed no hypoxia in the pretreatment scan. Conclusion: A tumor control probability model was developed based on repeated FMISO PET scans during RT. The model combines the local perfusion efficiency and the degree of hypoxia to estimate reoxygenation time. It constitutes a key for hypoxia image-guided dose escalation in RT.

Purpose: To investigate the feasibility of different hypoxia dose painting strategies in head-and-neck radiotherapy; the potential benefit was limited by the stipulation of isotoxicity with respect to the conventional intensity-modulated radiotherapy (IMRT) treatment. Methods and Materials: Thirteen head-and-neck cancer patients were included into the planning study. For each patient, three different treatment plans were created: a conventional IMRT plan, an additional uniform dose escalation (uniDE) of 10% to the fluorodeoxyglucose (FDG)-positive volume, and a plan in which dose painting by numbers (DPBN) was implemented. Dose painting by numbers was realized according to a map of dose-escalation factors calculated from dynamic [ 18 F]-fluoromisonidazole (FMISO) positron emission tomography data. Results: Both dose-escalation approaches were shown to be feasible under the constraint of limiting normal tissue doses to the level of conventional IMRT. For DPBN, the prescriptions could be fulfilled in larger regions of the target than for uniDE. Fluorodeoxyglucose-positive volumes had sizes up to 94 cm 3 . In contrast, regions receiving comparable dose levels with DPBN presented volumes in the range of 0–2.7 cm 3 . Overtreatment of the target was observed with uniDE in most of the cases, whereas some regions did not receive the required dose to overcome hypoxia-induced radiation insensitivity. Tumor control probability increased from 55.9% with conventional IMRT to 57.7% for the uniDE method in the patient group. For DPBN, a potential increase in tumor control probability from 55.9% to 70.2% was determined. Therefore, DPBN seems to result in higher benefits for the patients. Conclusion: Dose painting by numbers delivers the dose more effectively than an additional uniform boost to the FDG-positive area. If hypoxia could be adequately quantified with a simple imaging technique like FMISO positron emission tomography, DPBN in head-and-neck cancer could substantially increase tumor control.

Purpose Accurate modelling of rectal complications based on DVH data is necessary to allow safe dose escalation in radiotherapy of prostate cancer. We applied different EUD- and dose-volume based NTCP models to rectal wall DVHs and follow-up data of 319 prostate cancer patients in order to identify the dosimetric factors most predictive for grade 2 or higher rectal bleeding.

Purpose: Irradiation of adjuvant lymph nodes in high-risk prostate cancer was shown to be associated with improved rates of biochemical nonevidence of disease in the Radiation Therapy Oncology Group trial (RTOG 94-13). To account for the highly individual lymphatic drainage pattern we tested an intensity-modulated radiation therapy (IMRT) approach based on the determination of pelvic sentinel lymph nodes (SN). Methods and Materials: Patients with a risk of more than 15% lymph node involvement were included. For treatment planning, SN localizations were included into the pelvic clinical target volume. Dose prescriptions were 50.4 Gy to the adjuvant area and 70.0 Gy to the prostate. All treatment plans were generated using equivalent uniform dose (EUD)-based optimization algorithms and Monte Carlo dose calculations and compared with 3D conventional plans. Results: A total of 25 patients were treated and 142 SN were detectable (mean: n = 5.7; range, 0–13). Most SN were found in the external iliac (35%), the internal iliac (18.3%), and the iliac commune (11.3%) regions. Using a standard CT-based planning target volume, relevant SN would have been missed in 19 of 25 patients, mostly in the presacral/perirectal area (22 SN in 12 patients). The comparison of conventional 3D plans with the respective IMRT plans revealed a clear superiority of the IMRT plans. No gastrointestinal or genitourinary acute toxicity Grade 3 or 4 (RTOG criteria) occurred. Conclusions: Distributions of SN are highly variable. Data for SN derived from single photon emission computed tomography are easily integrated into an IMRT-based treatment strategy. By using SN data the probability of a geographic miss is reduced. The use of IMRT allows sparing of normal tissue irradiation.

Monte Carlo (MC) simulations in positron emission tomography (PET) play an important role in detector modeling and algorithm testing. Nowadays, these simulation are also increasingly used for scatter correction during reconstruction. This can be done ideally by using MC simulations to calculate the system matrix including scatter (full matrix approach). Another approach to incorporate MC simulations into the reconstruction is using a MC based projector and attenuation based back-projector, avoiding the storage of the matrix (dual matrix (DM) approach). It appears desirable to compare these two methods for PET and investigate the reconstruction accuracy in the light of MC noise. For this purpose a method to estimate the error introduced by the matrix, the sinogram or the projector based on repeated simulations with different MC seeds is introduced. Simulations of a single ring scanner (due to storage limitations) were performed.

Analytical dose computation algorithms like pencil beam algorithms (PB) are presently used for clinical treatment planning in intensity-modulated proton therapy. PB offer fast computation times, but are based on substantial approximations. Monte Carlo algorithms (MC) offer better accuracy, but are slower. We present a comparison of optimized treatment plans for six patients computed either with PB or MC. Both PB and MC are used during optimization, plus MC is used to recompute PB results. PB is used with different accuracy settings that define the coarseness of approximation. We evaluate the errors of PB optimized treatment plans via comparison with MC optimized plans (convergence errors) and MC recomputed plans (systematic errors) occurring for different accuracy settings of the PB. The level of lateral heterogeneities, being one of the main sources of inaccuracies of the PB, is quantified by a formula. In geometries with high levels of lateral heterogeneities, the shortcomings of PB are most obvious. For these geometries, simple PB lead to clinically significant differences and more accurate PB settings have to be used to diminish the error. The most accurate PB settings lead however to longer computing times by approximately a factor of 2 to 4 compared to PB with simple settings. Although the errors can be diminished, they cannot be fully eliminated even with sophisticated PB. Further gain in accuracy can therefore only be reached with MC in optimization. The use of MC in optimization is technically feasible, the computing times are however about 25 to 50 times longer compared to PB with most accurate settings.

For beamlet-based IMRT optimization, fast and less accurate dose computation algorithms are frequently used, while more accurate algorithms are needed to recompute the final dose for verification. In order to speed up the optimization process and ensure close proximity between dose in optimization and verification, proper consideration of dose gradients and tissue inhomogeneity effects should be ensured at every stage of the optimization. Due to their speed, pencil beam algorithms are often used for precalculation of beamlet dose distributions in IMRT treatment planning systems. However, accounting for tissue heterogeneities with these models requires the use of approximate rescaling methods. Recently, a finite size pencil beam (fsPB) algorithm, based on a simple and small set of data, was proposed which was specifically designed for the purpose of dose pre-computation in beamlet-based IMRT. The present work describes the incorporation of 3D density corrections, based on Monte Carlo simulations in heterogeneous phantoms, into this method improving the algorithm accuracy in inhomogeneous geometries while keeping its original speed and simplicity of commissioning. The algorithm affords the full accuracy of 3D density corrections at every stage of the optimization, hence providing the means for density related fluence modulation like penumbra shaping at field edges.

PURPOSE: The impact of multileaf collimator (MLC) design and IMRT technique on plan quality and delivery improvements for head-and-neck and meningioma patients is compared in a planning study.MATERIAL AND METHODS: Ten previously treated patients (5 head-and-neck, 5 meningioma) were re-planned for step-and-shoot IMRT (ssIMRT), sliding window IMRT (dMLC) and VMAT using the MLCi2 without (-) and with (+) interdigitation and the Agility-MLC attached to an Elekta 6MV linac. This results in nine plans per patient. Consistent patient individual optimization parameters are used. Plans are generated using the research tool Hyperion V2.4 (equivalent to Elekta Monaco 3.2) with hard constraints for critical structures and objectives for target structures. For VMAT plans, the improved segment shape optimization is used. Critical structures are evaluated based on QUANTEC criteria. PTV coverage is compared by EUD, Dmean, homogeneity and conformity. Additionally, MU/plan, treatment times and number of segments are evaluated.RESULTS: As constrained optimization is used, all plans fulfill the hard constraints. Doses to critical structures do not differ more than 1 Gy between the nine generated plans for each patient. Only larynx, parotids and eyes differ up to 1.5 Gy (Dmean or Dmax) or 7% (volume-constraint) due to (1) increased scatter, (2) not avoiding structures when using the full range of gantry rotation and (3) improved leaf sequencing with advanced segment shape optimization for VMAT plans. EUD, Dmean, homogeneity and conformity are improved using the Agility-MLC. However, PTV coverage is more affected by technique. MU increase with the use of dMLC and VMAT, while the MU are reduced by using the Agility-MLC. Fastest treatments are always achieved using Agility-MLC, especially in combination with VMAT.CONCLUSION: Fastest treatments with the best PTV coverage are found for VMAT plans with Agility-MLC, achieving the same sparing of healthy tissue compared to the other combinations of ssIMRT, dMLC and VMAT with either MLCi2(-/+) or Agility.

Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed.

Monte Carlo (MC) simulations in positron emission tomography (PET) play an important role in detector modeling and algorithm testing. Whereas the simulations are widely used in a forward projection manner to accomplish this task, ideally they should be included into the reconstruction process itself. It is therefore desirable to investigate the convergence properties and the propagation of MC noise of these kinds of reconstruction algorithms. MC simulations were integrated into the maximum likelihood expectation maximization (ML-EM) algorithm in two different ways. In the full matrix approach the system matrix was calculated by running MC simulations, including scatter. This matrix was used in both the projector and the backprojector. In the dual matrix (DM) approach, MC simulations were used to incorporate scatter in the projector, whereas the backprojector only comprised attenuation. Repeated reconstructions with different MC seeds allowed a statistical analysis of the error at each iteration step and made it possible to investigate separately the propagation of the MC noise that was introduced by the sinogram, by the projector, and by the matrix. Both approaches resulted in similar images, but the DM approach with unmatched projector and backprojector yielded a faster initial convergence when compared to the ideal full matrixmore » approach. The analysis of the noise sources for the modeled single ring scanner in full matrix reconstruction showed that the noise introduced by the matrix became comparable to the noise introduced by the sinogram when using a matrix that was simulated with 10 000 emissions/voxel.« less

The present study evaluated a hull-volume definition strategy for the planning organ at risk volume (PRV) for the rectum in the planning of radiotherapy of prostate cancer. The bounding volumes of rectum contours of 1 to 5 CT scans were compared on the basis of the rectum coverage probabilities for 5 patients. In addition, IMRT treatment plans were optimized using the rectum hull PRV5 of 5 CTs and each of the conventional rectum contours PRV1. The plans were compared on the basis of the organ doses caused by the individual organ motion. PRV5 allowed to cover the rectum with a probability of nearly 90% (PRV1 67%). Rectal wall dose showed a great variability for PRV1, while planned and treatment dose agreed well for PRV5 due to the improved geometric information which resulted in a better rectal sparing. In conclusion, the rectum hull-volume PRV5 is a well suited PRV for planning of IMRT dose distributions allowing dose escalation as well as rectal sparing.

Background and purpose To evaluate an optimization approach where coverage probabilities are incorporated into the optimization of intensity modulated radiotherapy (IMRT) to overcome the problem of margin definition in the case of overlapping planning target volume and organs at risk. Patients and methods IMRT plans were generated for three optimization approaches: based on a planning CT plus margin (A), on prostate and rectum contours from five pre-treatment CT plus margin (B), and on coverage probabilities (C). For approach (C), the probability of organ occupation was computed for each voxel from five pre-treatment CTs and the population distribution of systematic setup error and it was used as local weight in the costfunctions. Monte Carlo simulations of treatment courses were used to compute the probability distribution of prostate and rectal wall equivalent uniform dose (EUD). Results Treatment simulations showed best and most robust results for prostate and rectal wall EUD within the population for (C). For (A) the rectal wall EUD was on average about 1.5 Gy greater than in (C), while the prostate EUD was lower than those from (C) for most of the patients for (B) (especially for those with great organ motion). Conclusions The incorporation of coverage probabilities as local weights allows for dose escalation as well as improved rectal sparing and results in a safer and more robust IMRT treatment.

Background and purpose To evaluate the performance of ten different treatment-planning systems when intensity modulated (IMRT) plans are designed for breast treatments that include the irradiation of the internal mammary chain. Patients and methods A dataset of five patients (CT images and volumes of interest) was distributed to design IMRT plans on the ten systems. To minimise biases, the same geometry and clinical planning aims were imposed on the individual plans. Results were analysed in terms of dose distributions and dose volume histograms. Results and conclusions For target coverage, the volume receiving more than 95% of the prescribed dose ranged from 77% (OTP) to 91% (Eclipse and Pinnacle), the volume receiving more than 107% ranged from 3.3% (Hyperion) to 23.2% (OTP). The mean dose to ipsilateral lung ranged from 13 Gy (Eclipse) to 18 Gy (OTP). The volume of the contralateral breast receiving more than 10 Gy ranged from 3% (Pinnacle) to 26% (Precise). The volume of heart receiving more than 20 Gy ranged from 7% (Eclipse) to 47% (Precise), the maximum significant dose to heart ranged from ∼27 Gy (XiO) to ∼49 Gy (Precise). The maximum significant dose to healthy tissue ranged from ∼51 Gy (Eclipse) to ∼62 Gy (OTP). It was also possible to show that the treatment geometry proposed here enables to minimise contralateral breast irradiation while keeping minimal ipsilateral lung (or heart) involvement and satisfactory target coverage.

Dose optimization for intensity modulated radiotherapy (IMRT) using small field elements (beamlets) requires the computation of a large number of very small, often only virtual fields of typically a few mm to 1 cm in size. The primary requirements for a suitable dose computation algorithm are (1) speed and (2) proper consideration of the penumbra of the fields which are composed of these beamlets. Here, a finite size pencil beam (fsPB) algorithm is proposed which was specifically designed for the purpose of beamlet-based IMRT. The algorithm employs an analytical function for the cross-profiles of the beamlets which is based on the assumption of self-consistency, i.e. the requirement that an arbitrary superposition of abutting beamlets should add up to a homogeneous field. The depth dependence is stored in tables derived from Monte Carlo computed dose distributions. It is demonstrated that the algorithm produces accurately the output factors and cross-profiles of typical multi-leaf-shaped segments. Due to the accurate penumbra model, the dose distribution features physically feasible gradients at any stage of the iterative optimization, which eliminates the problem of large discrepancies in normal tissue dose due to misaligned gradients between optimized and recomputed treatment plans.

Geometric uncertainties arise during treatment planning and treatment and mean that dose-dependent parameters such as EUD are random variables with a patient specific probability distribution. Treatment planning with highly conformal treatment techniques such as intensity modulated radiation therapy requires new evaluation tools which allow us to estimate this influence of geometrical uncertainties on the probable treatment dose for a planned dose distribution. Monte Carlo simulations of treatment courses with recalculation of the dose according to the daily geometric errors are a gold standard for such an evaluation. Distribution histograms which show the relative frequency of a treatment quality parameter in the treatment simulations can be used to evaluate the potential risks and chances of a planned dose distribution. As treatment simulations with dose recalculation are very time consuming for sufficient statistical accuracy, it is proposed to do treatment simulations in the dose parameter space where the result is mainly determined by the systematic and random component of the geometrical uncertainties. Comparison of the parameter space simulation method with the gold standard for prostate cases and a head and neck case shows good agreement as long as the number of fractions is high enough and the influence of tissue inhomogeneities and surface curvature on the dose is small.

Purpose: To compare two methods to generate treatment plans for intensity-modulated radiotherapy(IMRT) of prostate cancer, delivered in a step-and-shoot mode. The first method uses fluence optimization (inverse planning) followed by conversion of the fluence weight map into a limited number of segments. In the second method, segments are manually assigned using a class solution (forward planning), followed by computeroptimization of the segment weights. Methods: Treatment plans for IMRT, utilizing a simultaneous integrated boost, were created. Plans comprise a five-field technique to deliver 78 Gy to the prostate plus seminal vesicles. Five patients were evaluated. Optimization objectives of both planning approaches concerned dose coverage of the target volumes and the dose distribution in the rectal wall. The two methods were evaluated by comparing dose distributions, the complexity of the resulting plan and the time expenditure to generate and to deliver the plan. Results: For both planning approaches 99% of the target volumes received 95% of the prescribed dose, which complies with our planning objectives. Inverse planning resulted in more conformal dose distributions than forward planning (conformity index: 1.37 versus 1.51). Inverse planning reduced the dose to the rectal wall compared to a manually designed plan, albeit to a small extent. The theoretical probability of severe rectal proctitis and/or stenosis was reduced on average by 1.9% with inverse planning. Maximal sparing of the rectal wall was achieved with inverse planning for a patient whose target volume was partly wrapped around the rectum. The number of segments generated with inverse planning ranged between 33 and 52, and between 9 and 13 segments for manually created segments. Conclusion:Dose coverage of the planning target volumes is adequate for both approaches of planning. Inverse planning results in slightly better dose distributions with respect to the rectal wall compared to manual planning, at the cost of an increase of the number of segments by a factor of 3.

A method for the quantitative four-dimensional (4D) evaluation of discrete dose data based on gradient-dependent local acceptance thresholds is presented. The method takes into account the local dose gradients of a reference distribution for critical appraisal of misalignment and collimation errors. These contribute to the maximum tolerable dose error at each evaluation point to which the local dose differences between comparison and reference data are compared. As shown, the presented concept is analogous to the gamma-concept of Low et al (1998a Med. Phys. 25 656-61) if extended to (3+1) dimensions. The pointwise dose comparisons of the reformulated concept are easier to perform and speed up the evaluation process considerably, especially for fine-grid evaluations of 3D dose distributions. The occurrences of false negative indications due to the discrete nature of the data are reduced with the method. The presented method was applied to film-measured, clinical data and compared with gamma-evaluations. 4D and 3D evaluations were performed. Comparisons prove that 4D evaluations have to be given priority, especially if complex treatment situations are verified, e.g., non-coplanar beam configurations.

Image guided radiotherapy has the potential to improve both tumour control and normal tissue sparing by including temporal patient specific geometry information into the adaptive planning process. In this study we present a practical method of image guided adaptive inverse planning based on computed tomography (CT) and portal image feedback during the treatment course. The method is based on a general description of the radiotherapy optimization problem subject to dynamic geometrical variations of the patient/organs. We will demonstrate the feasibility of off-line image feedback into the inverse planning process with the example of three prostate cancer patients. CT and portal images acquired during the early course of the treatment are used to predict the geometrical variation distribution of a patient and to re-optimize the treatment plan accordingly. We will study the convergence of the optimization problem with respect to the number of image measurements and adaptive feedback loops.

An algorithm for the optimization of the direction of intensity-modulated beams is presented. Although the global optimum dose distribution cannot be predicted, usually a large number of equivalent beam configurations exists. This degeneracy facilitates beam direction optimization (BDO) through a number of possible approximations and because the target set of good beam configurations is very large. Usually, the target volume is accessible through a finite number of paths of little resistance, which are defined by the properties of the objective function and the global optimum dose distribution. Since these paths can be occupied by a finite number of beams, it is reasonable to assume that a minimum number of beams for a configuration that is degenerate to the global optimum exists. Efficiency of the BDO will be characterized by detecting this degeneracy threshold. Beam configurations are altered by adding and deleting beams. A fast exhaustive (up to 3500 non-coplanar orientations) search finds beam directions that improve a configuration. Redundant beams of a configuration can be identified by a fast criterion based on second-order derivative information of the objective function. This offers a fast means of iteratively substituting redundant beams from a configuration. Inferior stationary states can be evaded by adding more beams than the desired number to the current configuration, followed by the subsequent cancellation of superfluous beams. The significance of BDO is examined in a coplanar and a non-coplanar test case. The existence of a threshold number for the minimum configuration and its dependence on the complexity of the problem are shown. BDO outperforms manual configurations and equispaced coplanar beam arrangements in both example cases.

Amorphous silicon electronic portal imaging devices (a-Si EPIDs) allow fast acquisition of high resolution portal images (PI). A visualization of organ movement for adaptive image-guided radiotherapy (IGRT) can be reached by implantation and automatic detection of fiducial markers. A method of automatic detection has been developed for fiducial spherical tungsten markers on PIs, acquired with an a-Si flat-panel imager. The detection method consists of a 2D Mexican hat filter (MHF), whose parameters are tuned to the particular marker signal. The high selectivity of this filter allows a reliable and precise detection of tungsten markers down to a diameter of 1.5 mm. The presented method allows fast, automatic and unsupervised detection of markers. Inevitably, the detection is hampered by image background (bone structures, etc) and noise. A detection success rate higher than 95% was reached, analysing PIs of patients with markers fixed on their skin. Furthermore, this approach to automatic marker detection can also be generalized to elliptic MHFs for the detection of cylindrical markers. The accuracy and detection probability of this method may allow accurate and fast online localization of the considered organ.

In general, the deposition of a given target dose requires a longer radiation time for intensity-modulated photon beams (IMBs) than for unmodulated beams. Hence, the routine use of intensity-modulated radiotherapy (IMRT) has repercussions both on the exposure of the patient to scatter and institutional radiation safety. A rule of thumb is presented to assess the maximum prolongation of radiation time for a case class in an idealized setting using static superimposed field segments. The method considers only the degree to which risk structures have to be blocked to meet specified dose restrictions.

On the basis of two clinical cases, we present fluence-modulated radiotherapy with a sequencer integrated into the optimization of our treatment-planning software HYPERION. In each case, we achieved simple relations for the dependence of the total number of segments on the complexity of the sequencing, as well as for the dependence of the dose-distribution quality on the number of segments. For both clinical cases, it was possible to obtain treatment plans that complied with the clinical demands on dose distribution and number of segments. Also, compared to the widespread concept of equidistant steps, our method of sequencing with fluence steps of variable size led to a significant reduction of the number of segments, while maintaining the quality of the dose distribution. Our findings substantiate the value of the integration of the sequencer into the optimization for the clinical efficiency of IMRT.

To compare intensity-modulated treatment plans of patients with head and neck cancer generated by forward and inverse planning. Ten intensity-modulated treatment plans, planned and treated with a step&shoot technique using a forward planning approach, were retrospectively re-planned with an inverse planning algorithm. For this purpose, two strategies were applied. First, inverse planning was performed with the same beam directions as forward planning. In addition, nine equidistant, coplanar incidences were used. The main objective of the optimisation process was the sparing of the parotid glands beside an adequate treatment of the planning target volume (PTV). Inverse planning was performed both with pencil beam and Monte Carlo dose computation to investigate the influence of dose computation on the result of the optimisation. In most cases, both inverse planning strategies managed to improve the treatment plans distinctly due to a better target coverage, a better sparing of the parotid glands or both. A reduction of the mean dose by 3-11Gy for at least one of the parotid glands could be achieved for most of the patients. For three patients, inverse planning allowed to spare a parotid gland that had to be sacrificed by forward planning. Inverse planning increased the number of segments compared to forward planning by a factor of about 3; from 9-15 to 27-46. No significant differences for PTV and parotid glands between both inverse planning approaches were found. Also, the use of Monte Carlo instead of pencil beam dose computation did not influence the results significantly. The results demonstrate the potential of inverse planning to improve intensity-modulated treatment plans for head and neck cases compared to forward planning while retaining clinical utility in terms of treatment time and quality assurance

One approach to the computation of photon IMRT treatment plans is the formulation of an optimization problem with an objective function that derives from an objective density. An investigation of the second-order properties of such an objective function in a neighborhood of the minimizer opens an intuitive access to many traits of this approach. A general finding is that only a small subset of the parameter space has nonzero curvature, while the objective function is entirely flat in a neighborhood of the minimizer in most directions. The dimension of the subspace of vanishing curvature serves as a measure for the degeneracy of the solution. This finding is important both for algorithm design and evaluation of the mathematical model of clinical intuition, expressed by the objective function. The structure of the subspace of great curvature is found to be imposed on the problem by conflicts between objectives of target and critical structures. These conflicts and their corresponding modes of resolution form a common trait between all reasonable treatment plans of a given case. The high degree of degeneracy makes the use of a conjugate gradient optimization algorithm particularly favorable since the number of iterations to convergence is equivalent to the number of different eigenvalues of the curvature tensor and is hence independent from the number of optimization parameters. A high level of degeneracy of the fluence profiles implies that it should be possible to stipulate further delivery-related conditions without causing severe deterioration of the dose distribution.

The present paper introduces a concept for the description of treatment objectives of IMRT which emphasizes the assurance of an acceptable dose distribution in risk organs. A number of DVH manipulation tools are available to take into account both the volume effects of normal tissue and the influence of dose fractionation. The optimization of the dose distribution strictly obeys the prescribed risks of complications, as well as the limits of dose homogeneity in the target volume. The application of IMRT is made more efficient by limiting the modulation of the fluence profiles. The use of this algorithm could simplify IMRT in a way that a larger number of patients can profit from this type of treatment.

PURPOSE: This study compared normal tissue complication probability (NTCP) modeling of chronic gastrointestinal toxicities following prostate cancer treatment for 2 treatment modalities. Possible factors causing discrepancies in optimal NTCP model parameters between 3-dimensional conformal radiation therapy (3D-CRT) and intensity modulated RT (IMRT) were analyzed and discussed, including the impact of patient characteristics, image guidance, toxicity scoring bias, and NTCP model limitations.METHODS AND MATERIALS: Rectal wall dose-volume histograms of 1115 patients treated for prostate cancer under an adaptive radiation therapy protocol were used to model gastrointestinal toxicity grade ≥2 (according to Common Terminology Criteria for Adverse Events). A total of 457 patients were treated with 3D-CRT and 658 with IMRT. 3D-CRT patients were matched to IMRT patients based on various patient characteristics, using a propensity score-based algorithm. Parameters of the Lyman equivalent uniform dose and cut-off dose logistic regression NTCP models were estimated for the 2 matched treatment modalities and the combined group.RESULTS: After they were matched, the 3D-CRT and IMRT groups contained 275 and 550 patients with a large discrepancy of 28.7% versus 7.8% toxicities, respectively (PCONCLUSIONS: Our analysis did not reveal a single definitive cause for discrepancies of model parameters between 3D-CRT and IMRT. Patient characteristics and bias in toxicity scoring, as well as image guidance alone, are unlikely causes of the large discrepancy of toxicities. Whether the cause was inherent to the specific NTCP models used in this study needs to be verified by future investigations. Because IMRT is increasingly used clinically, it is important that appropriate NTCP model parameters are determined for this treatment modality.

A step and shoot sequencer was developed that can be integrated into an IMRT optimization algorithm. The method uses non-uniform fluence steps and is adopted to the constraints of an MLC. It consists of a clustering, a smoothing and a segmentation routine. The performance of the algorithm is demonstrated for eight mathematical profiles of differing complexity and two optimized profiles of a clinical prostate case. The results in terms of stability, flexibility, speed and conformity fulfil the criteria for the integration into the optimization concept. The performance of the clustering routine is compared with another previously published one (Bortfeld et al 1994 Int. J. Radiat. Oncol. Biol. Ph.vs. 28 723-30) and yields slightly better results in terms of mean and maximum deviation between the optimized and the clustered protile. We discuss the specific attributes of the algorithm concerning its integration into the optimization concept.

A method which combines the accuracy of Monte Carlo dose calculation with a finite size pencil-beam based intensity modulation optimization is presented. The pencil-beam algorithm is employed to compute the fluence element updates for a converging sequence of Monte Carlo dose distributions. The combination is shown to improve results over the pencil-beam based optimization in a lung tumour case and a head and neck case. Inhomogeneity effects like a broader penumbra and dose build-up regions can be compensated for by intensity modulation.

A method to smooth intensity-modulated photon beams is presented which can be applied in conjunction with any optimization algorithm. The method employs an additional soft constraint to minimize the area of the surface defined by the photon fluence.

Most algorithms for numerical multifractal analysis rely on some evaluation of related scaling laws. We present a self-consistent way to obtain from a partition sum ${S}_{q}(l)$ the spectrum of singularities $f(\ensuremath{\alpha})$ and its confidence intervals. With this tool we gain insights into the intricacies of fixed-size algorithms and propose consequent improvements. We give a numerical analysis of the H\'enon attractor which displays theoretical predictions of a phase transition.

Acta Oncologica can this year celebrate its 50 years jubilee as the leading Scandinavian journal in oncology. As a part of this celebration the 11th Acta Oncologica Symposium was held in Aarhus, Denmark, on June 11 – 13, 2013. The symposium was dedicated to aspects of Biology-Guided Adaptive Radiotherapy (BiGART). The 172 participants of the meeting included physicians, physicists, radiobiologists and other scientists with an active interest in this specifi c area. The format included invited presentations, proffered papers and discussion rounds. More than 100 abstracts were submitted to the conference. Acta Oncologica has sponsored scientifi c symposia since 1989. The aim of this activity has been to focus on oncological issues of emerging interest, preferably with a multi-disciplinary or multi-professional approach. The current series of Acta Oncologica meetings with focus on radiotherapy (RT) have encompassed stereotactic body RT (SBRT) [1], image-guided RT (IGRT) [2,3], adaptive RT (BiGART) [4] and particle RT [5]. Other topics have over the years included sentinel lymph node biopsy in breast cancer, prostate cancer, normal tissue morbidity, breast cancer, and rehabilitation. The goal of BiGART is adaptation of RT in time and space based on biological and anatomical features, maximizing the therapeutic ratio for each individual patient. Key topics for the BiGART2013 conference included

Item does not contain fulltext Abstract Background. Assessing hypoxia with oxygen probes provides a sparse sampling of tumor volumes only, bearing a risk of missing hypoxic regions. Full coverage is achieved with positron emission tomography (PET) using the tracer (18)F-fluoromisonidazole (FMISO). In this study, the correlation between different FMISO PET imaging parameters and the median voxel PO2 (medianPO2) was analyzed. A measure of the median PO2 characterizes the microenvironment in consistency with probe measurements. Material and methods. Tissue oxygenations and FMISO diffusion-retention dynamics were simulated. Transport of FMISO and O2 molecules into and out of tissue was modeled by vessel maps derived from histology of head-and-neck squamous cell cancer xenograft tumor lines. Parameter sets were evaluated for 300 distinct 2 x 2 mm(2) vessel configurations, including medianPO2 and two FMISO PET parameters: FH denotes the sub-regional signal four hours post injection (pi) and FH/P denotes the ratio between FH and the time-averaged signal 0-15 min pi. Correlations between O2 and FMISO parameters were evaluated. A receiver operating characteristics (ROC) analysis was performed, regarding the accuracy of FH and FH/P in identifying voxels with medianPO2 < 2.5 mmHg. Results. In hypoxic sub-regions, the correlation between FH and medianPO2 is low (R(2) = 0.37), while the correlation between FH/P and median PO2 is high (R(2) = 0.99). The ROC analysis showed that hypoxic regions can be identified using FH/P with a higher diagnostic accuracy (YI = sensitivity+ specificity-1 = 1.0), than using FH alone (YI = 0.83). Both FMISO parameters are moderately effective in identifying hypoxia on the microscopic length scale (YI = 0.63 and 0.60). Conclusions. A combination of two FMISO PET scans acquired 0-15 min and four hours pi may yield an accurate measure of the medianPO2 in a voxel (FH/P). This measure is comparable to averaged oxygen probe measurements and has the advantage of covering the entire tumor volume. Therefore, it may improve the prediction of radiotherapy outcome and facilitate individualized dose prescriptions.

The oxidized Fe4S4 ferredoxin from the hyperthermophilic bacterium Thermotoga maritima has been investigated by one- and two-dimensional NMR in order to characterize its hyperfine-shifted resonances originating from the cysteinyl cluster ligands and to assign its resonances in the diamagnetic shift range. The chemical shift and relaxation time pattern of the hyperfine-shifted signals is very similar to other oxidized Fe4S4 ferredoxins. A tentative sequence-specific assignment of these resonances according to a general pattern of chemical shift of cysteine protons versus sequence position of cluster ligand is presented. Furthermore, sequence-specific assignments for 85% of the amino acid residues that were obtained without any guidance by known X-ray structures of ferredoxins are given. They reveal the formation of at least two elements of secondary structure by the polypeptide chain of T. maritima ferredoxin: an alpha-helix comprising residues C43-D49 and a double-stranded antiparallel beta-sheet consisting of the N- and C-terminal parts of the protein. This folding pattern is very similar to that of the crystallographically characterized ferredoxin from the mesophile Desulfovibrio gigas [Kissinger, C.R., Sieker, L.C., Adman E.T. & Jensen, L.H. (1991) J. Mol. Biol. 219, 693-715] and therefore suggesting different mechanisms of stabilization for T. maritima ferredoxin and the ferredoxin from the hyperthermophilic archaeon Pyrococcus furiosus that was recently investigated by NMR [Teng, Q., Zhou, Z.H., Smith, E.T., Busse, S. C., Howard, J.B., Adams M.W.W. & La Mar, G.N. (1994) Biochemistry 33, 6316-6326].

A linac delivering intensity-modulated radiotherapy (IMRT) can benefit from a flattening filter free (FFF) design which offers higher dose rates and reduced accelerator head scatter than for conventional (flattened) delivery. This reduction in scatter simplifies beam modeling, and combining a Monte Carlo dose engine with a FFF accelerator could potentially increase dose calculation accuracy. The objective of this work was to model a FFF machine using an adapted version of a previously published virtual source model (VSM) for Monte Carlo calculations and to verify its accuracy.An Elekta Synergy linear accelerator operating at 6 MV has been modified to enable irradiation both with and without the flattening filter (FF). The VSM has been incorporated into a commercially available treatment planning system (Monaco™ v 3.1) as VSM 1.6. Dosimetric data were measured to commission the treatment planning system (TPS) and the VSM adapted to account for the lack of angular differential absorption and general beam hardening. The model was then tested using standard water phantom measurements and also by creating IMRT plans for a range of clinical cases.The results show that the VSM implementation handles the FFF beams very well, with an uncertainty between measurement and calculation of1% which is comparable to conventional flattened beams. All IMRT beams passed standard quality assurance tests with95% of all points passing gamma analysis (γ1) using a 3%/3 mm tolerance.The virtual source model for flattened beams was successfully adapted to a flattening filter free beam production. Water phantom and patient specific QA measurements show excellent results, and comparisons of IMRT plans generated in conventional and FFF mode are underway to assess dosimetric uncertainties and possible improvements in dose calculation and delivery.

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Contains fulltext : 97120.pdf (Publisher’s version ) (Closed access) Hypoxia can be assessed non-invasively by positron emission tomography (PET) using radiotracers such as [(18)F]fluoromisonidazole (Fmiso) accumulating in poorly oxygenated cells. Typical features of dynamic Fmiso PET data are high signal variability in the first hour after tracer administration and slow formation of a consistent contrast. The purpose of this study is to investigate whether these characteristics can be explained by the current conception of the underlying microscopic processes and to identify fundamental effects. This is achieved by modelling and simulating tissue oxygenation and tracer dynamics on the microscopic scale. In simulations, vessel structures on histology-derived maps act as sources and sinks for oxygen as well as tracer molecules. Molecular distributions in the extravascular space are determined by reaction-diffusion equations, which are solved numerically using a two-dimensional finite element method. Simulated Fmiso time activity curves (TACs), though not directly comparable to PET TACs, reproduce major characteristics of clinical curves, indicating that the microscopic model and the parameter values are adequate. Evidence for dependence of the early PET signal on the vascular fraction is found. Further, possible effects leading to late contrast formation and potential implications on the quantification of Fmiso PET data are discussed.

An inverse treatment planning system based on fast Monte Carlo (MC) dose calculation is presented. It allows optimisation of intensity modulated dose distributions in 15 to 60 minutes on present day personal computers. If a multi-processor machine is available, parallel simulation of particle histories is also possible, leading to further calculation time reductions. The optimisation process is divided into two stages. The first stage results in fluence profiles based on pencil beam (PB) dose calculation. The second stage starts with MC verification and post-optimisation of the PB dose and fluence distributions.

The aim of the study was to assess the influence of carbogen (95% O2, 5% CO2) or pure oxygen breathing on renal oxygenation measured by blood oxygenation level dependent (BOLD) magnetic resonance imaging at 3.0 T. Seven healthy young volunteers (median age 25, range 23–35 years) participated in the study. A T2*-weighted fat-saturated spoiled gradient-echo sequence was implemented on a 3.0 T whole-body imager (TE/TR = 27.9 ms/49 ms, excitation angle 20°) with an acquisition time of approximately 5.3 s. A total of 100 images were acquired during 22 min. A block design was applied for gas administration: 4 min room air, 4 min carbogen/oxygen, 4 min room air, 4 min carbogen/oxygen and 6 min room air. A compartment model was fitted to the data sets accounting for time-dependent increase/decrease of renal oxygenation as well as baseline changes of the scanner. T2*-weighted images showed good image quality without notable artefacts or distortions. Mean relative signal increase due to carbogen breathing was 2.73% (95% confidence interval: 1.34–5.54) in the right kidney and 3.76% (1.53–9.20) in the left kidney, while oxygen breathing led to a signal enhancement of 3.20% (2.57–3.98) in the right kidney and 3.16% (1.83–5.45) in the left kidney. No statistical difference was found between carbogen and oxygen breathing or between the oxygenation of the right and the left kidney. A significant difference was found in the characteristic time constant for the signal increase with a faster saturation taking place for oxygen breathing. Renal tissue oxygenation is clearly influenced by carbogen or oxygen breathing. The changes can be assessed by T2*-weighted MRI at high field strengths. The effects are in the expected range for the BOLD effect of 3–4% at 3.0 T. The proposed technique might be interesting for the assessment of renal tissue oxygenation and its regulation in patients with kidney diseases. Copyright © 2009 John Wiley & Sons, Ltd.

Treatment plans optimized for intensity modulated proton therapy (IMPT) may be very sensitive to setup errors, range uncertainties and dose calculation errors. To mitigate the adverse effect of range and setup errors, uncertainty can be accounted for in the formulation of the IMPT optimization problem via stochastic or robust programming techniques. Dose calculation accuracy can be improved by applying Monte Carlo algorithms or pencil beam algorithms with sub-pencil beam decomposition. However, the costs for the improved accuracy are larger calculation times, especially in case of Monte Carlo. For two paraspinal cases, we show that dose calculation errors can lead to severe degradation of the dose distribution. We further demonstrate that there is an interrelation between different types of errors: a treatment plan which is made robust against range and setup errors, is typically less sensitive to dose calculation errors as well.