Purpose:Intensity modulated radiation therapy always requires compromises between PTV coverage and organs at risk (OAR) sparing. We previously developed metrics that correlate doses to OAR to specific patients’ morphology using stochastic frontier analysis (SFA). Here, we aim to examine the validity of this approach using a large set of realistically simulated dosimetric and geometric data.Methods:SFA describes a set of treatment plans as an asymmetric distribution with respect to a frontier defining optimal plans. Eighty head and neck IMRT plans were used to establish a metric predicting the mean dose to parotids as a function of simple geometric parameters. A database of 140 parotids was used as a basis distribution to simulate physically plausible data of geometry and dose. Distributions comprising between 20 and 5000 were simulated and the SFA was applied to obtain new frontiers, which were compared to the original frontier.Results:It was possible to simulate distributions consistent with the original dataset. Below 160 organs, the SFA could not always describe distributions as asymmetric: a few cases showed a Gaussian or half‐Gaussian distribution. In order to converge to a stable solution, the number of organs in a distribution must ideally be above 100, but in many cases stable parameters could be achieved with as low as 60 samples of organ data. Mean RMS value of the error of new frontiers was significantly reduced when additional organs are used.Conclusion:The number of organs in a distribution showed to have an impact on the effectiveness of the model. It is always possible to obtain a frontier, but if the number of organs in the distribution is small (< 160), it may not represent de lowest dose achievable. These results will be used to determine number of cases necessary to adapt the model to other organs.

2nd ESTRO Forum 2013 S317 26.5.forhypophysis.For PTV54 and PTV60 we found 51.5 and 58.9 gEUD values with LP based initial point, compared to 51.7 and 57.9. Conclusions:The results indicate that the approach of using linear programming is an effective way to easily obtain a good plan and to improve gEUD based optimization.

Purpose: Assess the impact of respiratory motion on three‐dimensional conformal radiation therapy (3DCRT) treatment planning and IMRT treatment planning with 4DCT datasets. Methods: A clinical 3DCRT treatment plan made on clinical primary dataset (free‐breathing 3DCT) was the starting point of this planning analysis. GTV contours were manually reproduced and adapted to account for anatomy changes on each 4DCT phases. For comparison, an IMRT plan was created with the primary dataset using the same contours. The 3DCRT and IMRT plans were copied and recalculated on each phase datasets, keeping all respective beams parameters and monitor units the same. Dosimetric parameters were extracted for each phases of all plans.Results: The lung case presented is a tumor clinging to the diaphragm, chosen for its unusual position and large amplitude of movement among the pool of patients available. Considering PTV coverage for the 3DCRT plans, expiration phases are closer to the primary plan than the inspiration phases. PTV coverage for inspiration phases is best represented by the 4DCT average dataset whereas the primary dataset is better suited to represent the expiration phases. The phase‐calculated IMRT plans also showed expiration phases PTVs coverage is closer to the primary plan than for inspiration phases. In this case, the average dataset is better suited than the primary dataset to describe the shape of the DVH dose drop‐ off for the 4DCT phases. The results obtained showed that a difference of up to 12% in PTV coverage for a 3DCRT and 17% for an IMRT plan can be observed when using breathing phase anatomy to calculate a plan made on the primary dataset Conclusions: Anatomy changes caused by breathing cannot be neglected because of their influence on dosimetric parameters. Our results indicate that the choice of a plan dataset may have an impact on treatment accuracy and robustness.

Purpose: To implement and evaluate a functional mean dose‐based objective in a well‐established IMRT system, using lung perfusion images and direct machine parameter optimization (DMPO). Methods: Nineteen patients underwent SPECT perfusion imaging prior to treatment. In this retrospective study, plans were generated using Pinnacleˈ DMPO (Philips Healthcare, Andover, MA) with the aim of minimizing either the mean lung dose (MLD) or the lung functional mean dose (FMD). A seven equidistant beam configuration was used in all plans. Two levels of dose were prescribed: 50 Gy to the PTV1 (clinical target volume with margins) and 66 Gy to the PTV2 (gross tumor volume with margins). The MLD or FMD objective was decreased by steps of 1 Gy until dose to target volumes or organs at risk was deemed unacceptable. Plans were compared in terms of dose‐volume and dose‐function parameters. Statistical significance was assessed with a Wilcoxon matched pairs test. Results: While keeping PTV coverage similar (volumes receiving 93% of the prescribed dose were all over 98%), differences in MLD between both types of plans for a given patient ranged from –1.0 to +1.5 Gy (p = 0.2050), while FMD decreased significantly with a range of –2.1 to 0.0 Gy (p = 0.0003). The net improvement (FMD difference − MLD difference) ranged between −2.2 and 0.0 Gy. Dose to other organs at risk were similar and below widely‐ accepted tolerances. Conclusions: The use of SPECT perfusion images in conjunction with DMPO allowed a significant decrease of FMD while keeping dose to other structures at an acceptable level. Functionality‐aware dose redistribution could prove useful for dose escalation to improve tumor control with similar or lower lung complication probabilities. The approach can also be easily ported to arc therapy treatment planning using SmartArc.This work is supported by the Natural Sciences and Engineering Research Council of Canada and by a research agreement with Philips Healthcare.

Purpose: Collect statistics on respiratory induces internal motion to improve population based margin definition of target volumes and organs at risks and to determine the feasibility of screening patients that would most benefits from a 4DCT exam. Methods: Motion of relevant internal and external region of interest was evaluated on 4DCT datasets of 16 patients in an open study. Patients were selected based on tumour location. For a given 4DCT dataset, motion was characterized for each of 10 phases of the breathing cycle. Trace differences between two methods of respiratory signal acquisition were also evaluated. Results: Motion in the superior‐inferior (SI) direction, unlike other directions, showed a uniform motion trend between different structures. External markers have an opposed phase motion compared to internal structures. Diaphragm usually showed the largest averaged magnitude of motion (1.55±0.50 cm) with a wide range of amplitude. As can be expected, gastro‐intestinal tumors (0.88±0.27 cm) are in average less mobile than lung tumors (1.18±0.90 cm). Respiratory signal acquisition systems used for this study produced very similar traces regarding baseline variation and peak shape. Conclusion: Population‐based specific organs motion will be used for personalized treatment planning (e.g. delineation of margins, contours). Most structures have a similar shaped motion (i.e. no phase mismatch) and amplitude in the SI direction, except for external markers. Abdomen AP motion is a promising external indicator of internal motion magnitude.

Target accuracy in treatment delivery for prostate cancer still remains a challenging issue among the radiotherapy community. IGRT with Cone Beam CT gives a solution for daily control of target volumes and offers repositioning option. We aim to present an original study using CBCT images in different correction strategies for treatment replanification. For each fraction (fx) of a prostate treatment of 76Gy (n = 38 fx), daily kV CBCT dataset was used for: (1) patient repositioning based on prostate soft tissue manual match; (2) generating an optimized 7-beam IMRT plan which was also calculated on every subsequent fx. This allows building a pool of plans containing a large number of anatomical geometries in terms of bladder and rectum fillings and their relative positions. Three strategies were elaborated: (1) the "classical strategy", a non-correction strategy where the patient is entirely treated with the initial CT-based plan; (2) the "optimal strategy", an online strategy where the patient is treated with the daily optimized CBCT-based plan; (3) "Continuous Offline Replanning" (COR) strategy, uses a pool of calculated offline plans from previous fx CBCT sets. A total of 741, n (n-1)/2, plans were calculated. The most sensitive criterion of choice was the one related to the PTV dose coverage V(95%), directly linked with the rectum filling. Dose coverage was excellent in the "optimal strategy" with an average of 99.95% for the 38 fx. With the classical strategy, for 14/38 fx, it ranged from 94.83% to 100%. In the COR strategy, it ranged from 95.31% to 100% for 35/38 fx which represents a significant treatment enhancement compared with the classical strategy. We also studied the day-to-day cumulative average PTV volume receiving 95% of the prescribed dose (target ≥95%). This goal was achieved for the optimal strategy, obtained after only 4 fractions for the COR strategy and lost at the second fraction for the classical strategy. Results for critical organs, particularly the rectum were consistent. We found that a subset of 8 plans from the pool would be enough to achieve good treatment quality for the 38 fx, with 6/8 of those plans chosen from the 1st and 2nd treatment week. An unusual rectum geometry on the initial CT planning could explain the poor target coverage for strategy (1). This geometry, different in deformation and rotation of the prostate, did not reoccur often thereafter, but led to a systematic error that could not be corrected for with an IGRT technique only. This study opens a new approach of treating patient with an offline strategy never tested before. The COR strategy with daily CBCT images offers dose adaptation to volume with a minimum effort on the current clinical workflow and recommended quality control protocol.

Treatment planning using direct machine parameter optimization (DMPO) typically starts with coplanar beam orientations. SPECT perfusion imaging may also be included in the optimization process to provide better avoidance of well-perfused lung. An appropriate choice of angles may therefore be required to deposit dose in less functional lung tissue. In this study of four lung cancer cases (A to D), we compared two types of plans produced by DMPO, using either five coplanar equidistant beams or a set of couch and gantry angles optimized by an anatomy-based aperture inverse planning system (ABAIPS). For each patient, two planning target volumes (PTVs) were defined, with prescriptions of respectively 50 and 66 Gy. Using the ABAIPS, angle optimization was conducted. For cases A to C, non-coplanar configurations were obtained, while for case D the resulting beams were coplanar. Both equidistant and ABAIPS-optimized configurations were set as initial conditions for DMPO. All plans had similar coverage, with more than 99% of PTVs receiving 95% of their prescription dose. Lung dose-volume parameters below 20 Gy were improved for cases A to C by an optimal choice of angles. Perfusion-weighted dose-volume parameters show a larger decrease in the same dose region. Mean dose and mean perfusion-weighted dose also decreased. For case D, no improvement was seen. Non-coplanar configurations help improve lung sparing and should not be systematically excluded. SPECT information and angle optimization appear to be useful tools for a patient-based treatment plan optimization using aperture-based IMRT. This may lead to a less toxic dose escalation.

To describe side effects after reirradiation (re-RT) of the thoracic chest wall, and to study associated predictive factors for severe toxicity in order to provide insight into chest wall re-RT tolerance. Between 1987 and 2007, a retrospective review of our experience identified 345 overlap regions in 257 patients who underwent re-RT of the thoracic chest wall. The biologically effective dose (BED) was calculated for acute toxicity with an α/β ratio of 10 and late toxicity with an α/β ratio of 3. Toxicities were graded and grouped into categories: severe, mild, and no toxicity until last follow-up. Cox stepwise regression analysis was used to determine factors associated with severe toxicity. Breast cancer was the predominant histology at initial RT (78%) and re-RT (75%), followed by lung cancer and lymphoma. The total median dose was 45 Gy (±11 Gy) at initial irradiation (RT) and was 30 Gy (±12 Gy) at re-RT. Of the 345 regions, 92% were the result of one re-treatment, 7% of two re-treatments (3 consecutive courses) and 0.3% of 3 re-treatments (4 consecutive courses). Of the 257 patients, 74% had one overlap region, 20% had 2, 6% had 3, and 1% had 4 regions of overlap. The median cumulative dose to the overlap region was 78 Gy (±27 Gy3). The median interval to re-RT was 42 months (±88 months) for regions re-treated once. Median follow-up from re-RT for all regions was 10 months (±29 months). Acute and late severe toxicity occurred in 9 and 11 overlap regions, respectively, all within 60 months of follow-up. Moreover, severe toxicity only occurred in regions with a cumulative BED3 of 139 Gy3 or more. No Grade 4 or 5 toxicity was reported. On multivariate analysis, shorter interval between initial treatment and re-RT (p = 0.01) and cumulative BED10 (p < 0.0001) were the most important factors for severe acute toxicity. Factors retained for late severe toxicity were presence of comorbidity (p = 0.0006), number of overlap regions per patient (p < 0.0001) and cumulative BED3 (p < 0.0001). Chest wall re-RT resulted in acceptable toxicity. Re-RT may be given with less concern in patients with fewer predictors. Late severe toxicity seems less probable if the cumulative biologically effective dose is ≤139 Gy3.

Purpose: To implement SPECT-based plan optimization in an anatomy-based aperture inverse planning system (IPS) for the avoidance of functional pulmonary regions for cases of lung cancer. Method and Materials: The IPS allows simultaneous optimization of beam orientations and weights from apertures defined by an anatomy-based segmentation. SPECT perfusion information has been integrated in the dose-volume-based cost function of the inverse planning system through a voxel-by-voxel linear spatial modulation of the importance factors (IFs) according to local perfusion score. For two cases of lung cancer, plans have been generated by the IPS using four non-coplanar incidences (gantry and couch angles optimized) using a purely anatomical approach and the SPECT-based approach. Planning target volume (PTV) coverage and lung avoidance (both volumetric and functional) have been compared. Results: Maximum dose to PTV is usually increased when increasing importance of functional lung regions in the optimization, creating boost regions. For the first case, the functional volume of lung receiving 20 Gy (F20) decreases from 28.4% to 22.0% while the mean lung perfused dose (MpLD) decreases from 16.5 Gy to 13.7 Gy. For the second case, the F20 does not vary (26.5%) and the MpLD decreases from 17.4 Gy to 16.6 Gy. All plans produced are simpler than typical IMRT plans, with few segments (5 or 10) and few monitor units (range 285–375) used. Conclusions: The system allows generation of simple aperture-based IMRT plans with the addition of functional lung sparing when considering SPECT-based information. However, the extent of the benefit is patient-dependant and varies according to the perfusion pattern and proximity of other critical structures to the PTV. Boost regions created by the redistribution of dose might prove useful in the context of dose escalation in lung irradiation.

In the case of non-small cell lung cancer, doses typically prescribed (60-66 Gy) are not sufficient to ensure a satisfactory tumor control probability. Dose escalation needs to be realized, but dose to organs at risk (OARs) must be kept under widely accepted clinical thresholds. Also, lung functionality is not homogeneously distributed over all the volume: single-photon emission computed tomography (SPECT) allows spatial characterization of perfusion, open the way to the design of treatments plans that could preferentially avoid highly-functional lung. In this study, three cases of lung cancer were retrospectively used to assess the capacity of an anatomy-based aperture inverse planning system to realize dose escalation while limiting dose to perfused lung. Plans were generated for four-beam non-coplanar configurations, mixing 6 and 23 MV photon beams. All dose calculations were performed using Pinnacle3 superposition/convolution algorithm. An increasing dose was prescribed to a subvolume of the initial planning target volume. Levels of escalation achieved for the three cases studied were 81 Gy, 111 Gy and 66 Gy to the subvolume. Escalation was limited in two cases by the dose to the esophagus and in the other case by the presence of overdosages near beam entry ports. Calculation of dose-volume parameters for OARs shows that they respect clinical thresholds. Plans generated by the system are less complex than plans generated in beamlet-based IMRT, because of the use of few, large segments. The approach used in this study allows important dose escalation, potentially improving treatment outcome.

Purpose: To investigate the possibility of performing IMRT in head and neck treatment sites with less segments and monitor units (MU). Materials and Methods: Six pharyngeal cases (n = 6) were analysed and four cases (n = 4), in the sinonasal region. For each one, an IMRT plan was first realized using a commercial software (P3 IMRT, Pinnacle3 — IMFAST segmentation algorithm). These patients had to receive 32 fractions of simultaneous integrated boost external beam radiotherapy at 1.8 and 2.15 Gy/fraction, respectively to the low and high risk planning target volumes (PTV1 and PTV2). Then, an‐in‐house inverse planning system, called Ballista, based on predetermined segments, was used to realize comparable plans. Its segments are generated with the subtraction of the projection of the OARs with the PTV (planning target volume). Results: For the pharyngeal Ballista plans, the average volume of the PTV that received at least 100% of the prescribed dose (V100) was 85.0±4.5% for the first prescription (PTV1) and the V100 for the second prescription (PTV2 — simultaneous integrated boost —) was 78.5±10.9%. With Pinnacle3,the V100 value was 86.6±4.8% and 81.5±12.4% respectively for PTV1 and PTV2 (see figure 2a and 2b). On average, Ballista plans have required 932±124 MU and 52±10 segments compared to 1238±230 MU and 117±7 segments for Pinnacle3. For the sinonasal Ballista plans, the average V100 obtained was 80.0±3.1%. With Pinnacle3, the V100 gave 75.7±2.7%. Ballista plans have required an average of 406±54 MU and 22±1 segments compared to 697±133 MU and 99±14 segments for beamlet‐based IMRT. Conclusion: In step‐and‐shoot head and neck IMRT, an anatomy‐based MLC optimization system can achieve similar dosimetric plans comparable to traditional beamlet‐based IMRT with less number of segments and MU.

Purpose: An anatomic aperture‐based IMRT optimization program, named Ballista, was recently developed at our institution. Even though studies previously published concluded local minima in full‐IMRT optimization were not problematic, early observations with Ballista revealed their nuisance in the case of simplified IMRT. The purpose of this study was to evaluate the extent of local minima and their impact on the optimization process.Method and Materials: In Ballista beam weights are optimized by a bound‐constrained quasi‐Newton algorithm, which cannot escape local minima, even with a quadratic dose‐based objective function. Therefore, a high number (20 000) of descents were launched with random initial weights to explore the solution space for a varying number of beams. Actual treatment plan DVHs corresponding to different local minima were analyzed, yielding information on the nature of those minima. Results: When only four beam weights were optimized, only a few but very distinctive local minima were found. For a more realistic case of 20 beam weights, the optimization revealed an astonishing number of local minima, almost forming a continuum in the objective function value space. DVH analysis showed local minima generally favor one or more organs‐at‐risk (OARs) while the other objectives, especially those concerning the target volume, are less than optimal compared with the global minimum. Also, all minima lie on the boundary of the solution space. It was found that limiting the initial beam weights to small values eliminates the vast majority of the solution space containing local minima. Conclusion: With Ballista local minima proved to be a major problem. Plans corresponding to different minima differed drastically. In order to give the optimization a “clear shot” at the global minimum, initial beam weights must be limited to small values. This focuses the optimization on improving the target volume objectives since all OARs objectives are initially met.

Purpose: An anatomic aperture‐based IMRT optimization program, named Ballista, was developed at our institution. Even though studies previously published concluded local minima in full‐IMRT optimization were not problematic, early observations with Ballista revealed their nuisance. The purpose of the present study was to evaluate the extent of local minima and their impact on the optimization. Method and Materials: In Ballista beam weights are optimized by quasi‐Newton algorithm, which cannot escape local minima, even with a quadratic dose‐based objective function. Therefore, a large number of descents were launched with random initial weights to explore the solution space for a varying number of beams. Treatment plan DVHs of different local minima were also analyzed. Results: When four beam weights were optimized, only a few but very distinctive local minima were found. For a case of 20 beam weights, the optimization revealed an astonishing number of local minima. DVH analysis showed local minima generally favor one or more organs‐at‐risk (OARs) while the other objectives are less than optimal compared with the global minimum. It was found that limiting the initial beam weights to small values eliminates the majority of the solution space containing local minima. Conclusion: With Ballista local minima proved to be a major problem. Plans corresponding to different minima differed drastically. In order to give the optimization a “clear shot” at the global minimum, initial beam weights must be limited to small values. The optimization thus focuses on improving the target volume objectives since all OARs objectives are initially met.

Septicemic Escherichia coli 4787 (O115: K-: H51: F165) of porcine origin possess gene clusters related to extraintestinal E. coli fimbrial adhesins. This strain produces two fimbriae: F1651 and F1652. F1651 (Prs-like) belongs to the P fimbrial family, encoded by foo operon and F1652 is a F1C-like encoded by fot operon. Data from this study suggest that these two operons are part of two PAIs. PAI I4787 includes a region of 20 kb, which not only harbors the foo operon but also contains a potential P4 integrase gene and is located within the pheU tRNA gene, at 94 min of the E. coli chromosome. PAI II4787 includes a region of over 35 kb, which harbors the fot operon, iroBCDEN gene clusters, as well as part of microcin M genes and nonfunctional mobility genes. PAI II4787 is found between the proA and yagU at 6 min of the E. coli chromosome.