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Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the gate/geant4Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with gate/geant4 for various geometries show deviations within 2%-1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 107 primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: The aim of this study was to validate a gradient-based segmentation method for GTV delineation on FDG-PET in NSCLC through surgical specimen, in comparison with threshold-based approaches and CT. Materials and methods: Ten patients with stage I–II NSCLC were prospectively enrolled. Before lobectomy, all patients underwent contrast enhanced CT and gated FDG-PET. Next, the surgical specimen was removed, inflated with gelatin, frozen and sliced. The digitized slices were used to reconstruct the 3D macroscopic specimen. GTVs were manually delineated on the macroscopic specimen and on CT images. GTVs were automatically segmented on PET images using a gradient-based method, a source to background ratio method and fixed threshold values at 40% and 50% of SUVmax. All images were finally registered. Analyses of raw volumes and logarithmic differences between GTVs and GTVmacro were performed on all patients and on a subgroup excluding the poorly defined tumors. A matching analysis between the different GTVs was also conducted using Dice’s similarity index. Results: Considering all patients, both lung and mediastinal windowed CT overestimated the macroscopy, while FDG-PET provided closer values. Among various PET segmentation methods, the gradient-based technique best estimated the true tumor volume. When analysis was restricted to well defined tumors without lung fibrosis or atelectasis, the mediastinal windowed CT accurately assessed the macroscopic specimen. Finally, the matching analysis did not reveal significant difference between the different imaging modalities. Conclusions: FDG-PET improved the GTV definition in NSCLC including when the primary tumor was surrounded by modifications of the lung parenchyma. In this context, the gradient-based method outperformed the threshold-based ones in terms of accuracy and robustness. In other cases, the conventional mediastinal windowed CT remained appropriate. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Helical tomotherapy is a modality of radiation treatment delivery which is equipped with an on-board imaging device (MVCT) allowing for daily patient set-up verification and correction in the medial–lateral (m–l), cranial–caudal (c–c), anterior–posterior (a–p) and transversal angular (roll) directions. In this study, we measured set-up deviations and evaluated different MVCT protocols for brain and head and neck (H&N) cancer patients. Materials and methods: The daily set-up errors of 75 H&N cancer patients immobilized with 5-point fixation thermoplastic masks and 30 brain cancer patients immobilized with 3-point fixation thermoplastic masks were detected by matching the MVCT with the treatment planning CT images. This co-registration procedure was accomplished automatically by the system’s software (automatic deviations), then corrected manually by the radiation therapists (total deviations). Systematic and random errors were analyzed on a patient and a population basis. Moreover, 2 MVCT protocols were retrospectively evaluated; MVCTs were either acquired during the first five fractions (FFFs) or on alternate week (ALT). Systematic deviations were calculated based upon prior “MVCT” fractions and applied during the “non-MVCT” fractions. The resulting residual deviations were then analyzed. Results: The total systematic (and random) deviations reached 1.7mm (1.4mm), 1.6mm (1.5mm), 1.5mm (1.5mm) and 0.6° (0.6°) for H&N cancer patients and reached 1.6mm (0.9mm), 1.7mm (1.1mm), 1.1mm (0.8mm) and 0.9° (0.6°) for brain cancer patients in the m–l, c–c, a–p and roll directions, respectively. A t-test detected small but statistically significant differences between the automatic and total deviations. Both MVCT protocols gave rise to similar residual deviations. However, for H&N cancer patients the ALT protocol resulted in smaller residual deviations and CTV-PTV margins, particularly in the a–p direction. Conclusion: The total systematic and random deviations were comparable to the previously published data. No clinical difference exists between the automatic and total deviations. Both MVCT protocols were similar. But, for H&N cancer patients, the ALT protocol gave rise to smaller residual deviations and therefore is the correct formula to adopt in order to reduce the frequency of pre-treatment MVCTs. [Copyright &y& Elsevier]

Abstract: Background and purpose: Weight loss, tumor shrinkage, and tissue edema induce substantial modification of patient’s anatomy during head and neck (HN) radiotherapy (RT) or chemo-radiotherapy. These modifications may impact on the dose distribution to both target volumes (TVs) and organs at risk (OARs). Adaptive radiotherapy (ART) where patients are re-imaged and re-planned several times during the treatment is a possible strategy to improve treatment delivery. It however requires the use of specific deformable registration (DR) algorithms that requires proper validation on a clinical material. Materials and methods: Twelve voxel-based DR strategies were compared with a dataset of 5 patients imaged with computed tomography (CT) before and once during RT (on average after a mean dose of 36.8Gy): level-set (LS), level-set implemented in multi-resolution (LSMR), Demons’ algorithm implemented in multi-resolution (DMR), DMR followed by LS (DMR-LS), fast free-form deformable registration via calculus of variations (F3CV) and F3CV followed by LS (F3CV-LS). The use of an edge-preserving denoising filter called “local M-smoothers” applied to the registered images and combined to all the aforesaid strategies was also tested (fLS, fLSMR, fDMR, fDMR-LS, fF3CV, fF3CV-LS). All these strategies were compared to a rigid registration based on mutual information (MI, fMI). Chronological and anti-chronological registrations were also studied. The various DR strategies were evaluated using a volume-based criterion (i.e. Dice similarity index, DSI) and a voxel-intensity criterion (i.e. correlation coefficient, CC) on a total of 18 different manually contoured volumes. Results: For the DSI analysis, the best three strategies were DMR, fDMR-LS, and fDMR, with the median values of 0.86, 0.85 and 0.85, respectively; corresponding inter-quartile range (IQR) reached 9.6%, 10% and 10.2%. For the CC analysis, the best three strategies were fDMR-LS, DMR-LS and DMR with the median values of 0.97, 0.96 and 0.94, respectively; corresponding IQR reached 11%, 9% and 15%. Concerning the time-sequence analysis, the anti-chronological registration (all deformable strategies pooled) showed a better median DSI value (0.84 vs 0.83, p <0.001) and IQR (11.2% vs 12.4%). For CC, the anti-chronological registration (all deformable strategies pooled) had a slightly lower median value (0.91 vs 0.912, p <0.001) but a better IQR (16.4% vs 21%). Conclusions: The use of fDMR-LS is a good registration strategy for HN-ART as it is the best compromise in terms of median and IQR for both DSI and CC. Even though less robust in terms of CC, DMR is a good alternative. None of the time-sequence appears superior. [Copyright &y& Elsevier]

Abstract: Numerous methods or algorithms have been designed to solve the problem of nonlinear dimensionality reduction (NLDR). However, very few among them are able to embed efficiently ‘circular’ manifolds like cylinders or tori, which have one or more essential loops. This paper presents a simple and fast procedure that can tear or cut those manifolds, i.e. break their essential loops, in order to make their embedding in a low-dimensional space easier. The key idea is the following: starting from the available data points, the tearing procedure represents the underlying manifold by a graph and then builds a maximum subgraph with no loops anymore. Because it works with a graph, the procedure can preprocess data for all NLDR techniques that uses the same representation. Recent techniques using geodesic distances (Isomap, geodesic Sammon''s mapping, geodesic CCA, etc.) or -ary neighborhoods (LLE, hLLE, Laplacian eigenmaps) fall in that category. After describing the tearing procedure in details, the paper comments a few experimental results. [Copyright &y& Elsevier]

Dimension reduction techniques are widely used for the analysis and visualization of complex sets of data. This paper compares two recently published methods for nonlinear projection: Isomap and Curvilinear Distance Analysis (CDA). Contrarily to the traditional linear PCA, these methods work like multidimensional scaling, by reproducing in the projection space the pairwise distances measured in the data space. However, they differ from the classical linear MDS by the metrics they use and by the way they build the mapping (algebraic or neural). While Isomap relies directly on the traditional MDS, CDA is based on a nonlinear variant of MDS, called Curvilinear Component Analysis (CCA). Although Isomap and CDA share the same metric, the comparison highlights their respective strengths and weaknesses. [Copyright &y& Elsevier]

• MANIV is a safe breathing-constraining technique that is well-tolerated by patients. • The volume-controlled mode reduces inter-session variation in tumour motion amplitude and stabilizes the respiratory rate, which may facilitate tracking strategies. • The shallow-controlled mode reduces the tumour motion amplitude while ensuring regular, rapid, and shallow breathing that may benefit margin strategies. • The slow-controlled mode repeats short end-inspiratory plateaus (>15 s), well tolerated by patients and potentially useful for gated delivery. Current motion mitigation strategies, like margins, gating, and tracking, deal with geometrical uncertainties in the tumour position, induced by breathing during radiotherapy (RT). However, they often overlook motion variability in amplitude, respiratory rate, or baseline position, when breathing spontaneously. Consequently, this may negatively affect the delivered dose conformality in comparison to the plan. We previously demonstrated on volunteers that 3 different modes of mechanically-assisted and non-invasive ventilation (MANIV) may reduce variability in breathing motion. The volume-controlled mode (VC) constraints the amplitude and respiratory rate (RR) in physiologic condition. The shallow-controlled mode (SH), derived from VC, increases the RR and decreases amplitude. The slow-controlled mode (SL) induces repeated breath holds with constrained ventilation pressure. In this study, we compared these mechanical ventilation modes to spontaneous breathing or breath hold and assessed their tolerance and effects on internal tumour motion in patients receiving RT. The VC and SH modes were evaluated in ten patients with lung or liver cancers (cohort A). The SL mode was evaluated in 12 left breast cancer patients (cohort B). After a training and simulation session, the patients underwent 2 MRI sessions to analyze the internal motion of breast and tumour. MANIV was well tolerated, without any adverse events or oxymetric changes, even in patients with respiratory comorbidities. In cohort A, when compared to spontaneous breathing (SP), VC reduced significantly inter-session variations of the tumour motion amplitude (p = 0.01), as well as intra- and inter-session variations of the RR (p < 0.05). As to SH, the RR increased, while its variations within and across sessions decreased when compared to SP (p < 0.001). SH reduced the median amplitude of the tumour motion by 6.1 mm or 38.2% (p ≤ 0.01) compared to VC. In cohort B, breast position stability over the end-inspiratory plateaus obtained spontaneously or with SL remained similar. Median duration of the plateaus in SL was 16.6 s. MANIV is a safe and well tolerated ventilation technique for patients receiving radiotherapy. MANIV could thus make current motion mitigation strategies less critical and more robust. Clinical implementation might be considered, provided the ventilation mode is carefully selected with respect to the treatment indication and patient individualities. [ABSTRACT FROM AUTHOR]

Abstract: Background and purpose: The planning process in radiotherapy (RT) typically involves the acquisition of a unique set of CT images – and eventually of functional images – which is used for delineation of target volumes (TV) and organs at risk (OAR) and for dose calculation. Restricting the delineation and dose calculation solely on pre-treatment images is an oversimplification as it is only a snapshot of the patient’s anatomy. The objectives of the present study were (1) to assess the consequences of anatomic modification in dose distribution for both TVs and OARs; (2) to assess the potential benefit of adaptive strategies using Helical Tomotherapy (HT); and (3) to compare CT-based and FDG-PET-based adaptive planning strategies. Materials and methods: Ten patients with H&N SCC were imaged before and during concomitant chemo-RT using CT and FDG-PET acquisition after a mean dose of 14.2, 24.5, 35.0 and 44.9Gy. Simultaneous integrated boost IMRT planning was performed using HT. We compared (1) the planned dose distribution, (2) the delivered dose distributions that took into account impact of anatomical modifications on dose distribution, (3) the adaptive dose distributions after replanning to take into account the anatomic modifications and the anatomic or functional GTV shrinkage. Results: There was an increase between the planned and the delivered high dose volumes, which correlated with the slope of the GTV shrinkage. The adaptive high dose volumes were significantly smaller than the delivered ones. The difference between the adaptive and the delivered high dose volume also correlated with the slope of the GTV shrinkage. For both parotid glands combined, the delivered D mean showed a statistical trend for an increase of 4.4% compared to the planned D mean. For the ipsilateral parotid glands, there was a correlation between the D mean gain and the slope of the GTV shrinkage when an adaptive planning was used. For the oral cavity, the adaptive D mean was 10% smaller than the delivered ones. For the PRV around the spinal cord, there was an increase of about 4.5% between the delivered and the planned D 2%. The adaptive planning translated into a decrease in D 2% of 7.2%. The differences between the delivered and planned D 2% and between the adaptive and the delivered D 2% were correlated with the slope of the GTV shrinkage. For the CTVproph and PTVproph coverage, adaptive strategy induced a better dose conformation. No significant difference was observed in the various figures of merit between PET-based plan and CT-based isodose distributions. Conclusions: The dose distribution that is actually delivered to patients significantly differs from what was planned because of anatomic modifications. Adaptive multi-modality IMRT is feasible in H&N tumors and could compensate and improve dose distribution. Some useful surrogate criteria or “flags” are, however, needed to identify patients who might benefit from an adaptive strategy. The optimal adaptive strategy still needs to be defined and prospective studies will have to be conducted to address the safety and the clinical impact of such approaches on patient outcome. [Copyright &y& Elsevier]

Abstract: Purpose: Anatomic changes occur during radiation therapy (RT) for head and neck (H&N) tumors. This study aims at quantifying the volumetric and positional changes of gross tumor volumes (GTV), clinical target volumes (CTV), and organs at risk (OAR). Anatomic (CT) and functional (FDG-PET) imaging were used for the delineation of the GTVs. Materials and methods: Ten patients with H&N tumors treated by chemo-RT were used. Contrast-enhanced CT and FDG-PET were acquired prior and during RT following delivery of mean doses of 14.2, 24.5, 35.0, and 44.9Gy. CT-based GTVs were manually delineated, and PET-based GTVs were segmented using a gradient-based segmentation method. Pre-treatment prophylactic dose CTVs were manually delineated on the pre-treatment CT using consistent and reproducible guidelines. Per-treatment prophylactic CTVs were obtained with an automatic re-contouring method based on deformable registration. For the therapeutic dose CTVs, a 5mm margin was applied around the corresponding GTVs. OARs such as the parotid glands and the submandibular glands were manually delineated on the pre-treatment CT. OARs on the per-treatment CT were automatically delineated using the method used for prophylactic CTVs. The mean slopes of the relative change in volume over time and the mean displacements of the center of mass after 44.9Gy were calculated for each volume. Results: Regarding volumetric changes, CT-based and PET-based primary tumor GTVs decreased at a mean rate of 3.2% and 3.9%/treatment day (td), respectively; nodal GTVs decreased at a mean rate of 2.2%/td. This led to a corresponding decrease of the CT-based and PET-based therapeutic CTVs by 2.4% and 2.5%/td, respectively. CT- and PET-based prophylactic tumor CTVs decreased by an average of 0.7% and 0.5%/td, respectively. No difference in volume shrinkage was observed between CT- and PET-based volumes. The ipsilateral and contralateral parotid glands showed a mean decrease of 0.9% and 1.0%/td, respectively. The ipsilateral and contralateral submandibular glands shrank at a mean rate of 1.5% and 1.3%/td, respectively. Regarding positional changes, CT-based GTVs showed a lateral shift of 1.3mm, PET-based GTVs a posterior shift of 3.4mm and the nodal GTVs a medial shift of 1.0mm, translating into parallel shifts of the therapeutic CTVs. The ipsilateral prophylactic nodal CTV shifted medially by 1.8mm. The ipsilateral parotid gland shifted medially by 3.4mm. The ipsilateral submandibular gland showed a medial shift of 1.7mm and a superior shift of 2.7mm. The contralateral submandibular gland only showed a superior shift of 1.7mm. Conclusions: Volumetric and positional changes in TVs and OARs were observed during concomitant chemo-RT suggesting that adaptive strategies, where patients are re-imaged and possibly re-planned during treatment, are worth evaluating. [Copyright &y& Elsevier]

The 'clinical target distribution' (CTD) has recently been introduced as a promising alternative to the binary clinical target volume (CTV). However, a comprehensive study that considers the CTD, together with geometric treatment uncertainties, was lacking. Because the CTD is inherently a probabilistic concept, this study proposes a fully probabilistic approach that integrates the CTD directly in a robust treatment planning framework. First, the CTD is derived from a reported microscopic tumor infiltration model such that it explicitly features the probability of tumor cell presence in its target definition. Second, two probabilistic robust optimization methods are proposed that evaluate CTD coverage under uncertainty. The first method minimizes the expected-value (EV) over the uncertainty scenarios and the second method minimizes the sum of the expected value and standard deviation (EV-SD), thereby penalizing the spread of the objectives from the mean. Both EV and EV-SD methods introduce the CTD in the objective function by using weighting factors that represent the probability of tumor presence. The probabilistic methods are compared to a conventional worst-case approach that uses the CTV in a worst-case optimization algorithm. To evaluate the treatment plans, a scenario-based evaluation strategy is implemented that combines the effects of microscopic tumor infiltrations with the other geometric uncertainties. The methods are tested for five lung tumor patients, treated with intensity-modulated proton therapy. The results indicate that for the studied patient cases, the probabilistic methods favor the reduction of the esophagus dose but compensate by increasing the high-dose region in a low conflicting organ such as the lung. These results show that a fully probabilistic approach has the potential to obtain clinical benefits when tumor infiltration uncertainties are taken into account directly in the treatment planning process. [ABSTRACT FROM AUTHOR]

Purpose: Robust optimization is becoming the gold standard for generating robust plans against various kinds of treatment uncertainties. Today, most robust optimization strategies use a pragmatic set of treatment scenarios (the so‐called uncertainty set) consisting of combinations of maximum errors, of each considered uncertainty source (such as tumor motion, setup and image‐conversion errors). This approach presents two key issues. First, a subset of considered scenarios is unnecessarily improbable which could potentially compromise the plan quality. Second, the resulting large uncertainty set leads to long plan computation times, which limits the potential for robust optimization as a standard clinical tool. In order to address these issues, a method is introduced which is able to preselect a limited set of relevant treatment error scenarios. Methods: Uncertainties due to systematic setup errors, image‐conversion errors and respiratory tumor motion are considered. A four‐dimensional (4D)‐equiprobability hypersurface is defined, which takes into account the joint probabilities of the above‐mentioned uncertainty sources. Only scenarios that lie on the predefined 4D hypersurface are considered, guaranteeing statistical consistency of the uncertainty set. In this regard, twelve scenarios are selected that cover maximum spatial displacements of the tumor during breathing. Subsequently, additional scenarios are considered (sampled from the aforementioned 4D hypersurface) in order to cover any estimated residual range errors. Two different scenario‐selection procedures were tested: (a) the maximum displacements (MD) method that only considers twelve scaled maximum displacement scenarios and (b) maximum displacements and residual range (MDR) method which, in addition to the scaled maximum displacement scenarios, considers additional maximum range uncertainty scenarios. The methods were tested for five lung cancer patients by performing comprehensive Monte Carlo robustness evaluations. Results: A plan computation time gain of 78% is achieved by applying the MD method, whilst obtaining a target robustness of D95 larger than 95% of the prescribed dose, for the worst‐case scenario. Additionally, the MD method has the potential to be fully automatic which makes it a promising candidate for fast automatic planning workflows. The MDR method produced plans with excellent target robustness (D99 larger than 95% of the prescribed dose, even for the worst‐case scenario), whilst still obtaining a significant plan computation time gain of 57%. Conclusions: Two scenario‐selection procedures were developed which achieved significant reduction of plan computation time and memory consumption, without compromising plan quality or robustness. [ABSTRACT FROM AUTHOR]

Purpose: Analytical algorithms have a limited accuracy when modeling very heterogeneous tumor sites. This work addresses the performance of a hybrid dose optimizer that combines both Monte Carlo (MC) and pencil beam (PB) dose engines to get the best trade‐off between speed and accuracy for proton therapy plans. Methods: The hybrid algorithm calculates the optimal spot weights (w) by means of an iterative optimization process where the dose at each iteration is computed by using a precomputed dose influence matrix based on the conventional PB plus a correction term c obtained from a MC simulation. Updates of c can be triggered as often as necessary by calling the MC dose engine with the last corrected values of w as input. In order to analyze the performance of the hybrid algorithm against dose calculation errors, it was applied to a simplistic water phantom for which several test cases with different errors were simulated, including proton range uncertainties. Afterwards, the algorithm was used in three clinical cases (prostate, lung, and brain) and benchmarked against full MC‐based optimization. The influence of different stopping criteria in the final results was also investigated. Results: The hybrid algorithm achieved excellent results provided that the estimated range in a homogeneous material is the same for the two dose engines involved, i.e., PB and MC. For the three patient cases, the hybrid plans were clinically equivalent to those obtained with full MC‐based optimization. Only a single update of c was needed in the hybrid algorithm to fulfill the clinical dose constraints, which represents an extra computation time to obtain c that ranged from 1 (brain) to 4 min (lung) with respect to the conventional PB‐based optimization, and an estimated average gain factor of 14 with respect to full MC‐based optimization. Conclusion: The hybrid algorithm provides an improved trade‐off between accuracy and speed. This algorithm can be immediately considered as an option for improving dose calculation accuracy of commercial analytical treatment planning systems, without a significant increase in the computation time (≪5 min) with respect to current PB‐based optimization. [ABSTRACT FROM AUTHOR]

Purpose The IAEA TRS-398 code of practice details the reference conditions for reference dosimetry of proton beams using ionization chambers and the required beam quality correction factors (kQ). Pencil beam scanning ( PBS) systems cannot approximate reference conditions using a single spot. However, dose distributions requested in TRS-398 can be reproduced with PBS using a combination of spots. This study aims to demonstrate, using Monte Carlo ( MC) simulations, that kQ factors computed/measured for broad beams can be used with scanned beams for similar reference dose distributions with no additional significant uncertainty. Methods We consider the Alfonso formalism13 usually employed for nonstandard photon beams. To approach reference conditions similar as IAEA TRS-398 and the associated dose distributions, PBS must combine many pencil beams with range or energy modulation and shaping techniques that differ from those used in passive systems (broad beams). In order to evaluate the impact of these differences on kQ factors, ionization chamber responses are computed with MC (Geant4 9.6) in three different proton beams, with their corresponding quality factors (Q), producing a 10 × 10 cm2 field with a flat dose distribution for (a) a dedicated scanned pencil beam (Qpbs), (b) a hypothetical proton source (Qhyp), and (c) a double-scattering beam (Qds). The tested ionization chamber cavities are a 2 × 2 × 0.2 mm³ air cavity, a Roos-type ionization chamber, and a Farmer-type ionization chamber. Results and Discussion Ranges of Qpbs, Qhyp, and Qds are consistent within 0.4 mm. Flatnesses of dose distributions are better than 0.5%. Calculated [ABSTRACT FROM AUTHOR]

The aim of the study was to show that the presence of a small quantity of konjac glucomannan (KGM) in potato starch suspension increased the stability of carvacrol trapping. For that purpose, several freeze-thaw cycles were used to accelerate the ageing of the product and consequently drastically destabilize the gels, and induce syneresis. The stability of carvacrol trapping was evaluated by the quantification of carvacrol in the syneresis liquid. The stability of the starch gel structure was studied at microscopic and macroscopic scale. The moment of the addition of carvacrol and the presence of KGM both had an effect on the stability of carvacrol trapping and of the structure of the gel. KGM promoted amylose retrogradation but slowed down amylopectin retrogradation. The stability of potato starch gels can be improved by the addition of a small quantity of KGM which showed a ‘cryoprotectant’ behaviour. New method to characterize the micro and macrostructure from SEM images processing has also been proposed. The processing of microscopy images was done using Generalized Fourier Descriptors and allowed the characterization of each sample. The carvacrol addition lowered the physical stability of the gel with larger pores and increased syneresis. On the contrary, the KGM addition increased the size of the pores but prevented the formation of very large pores and reduced syneresis. The most stable system was obtained by the addition of carvacrol at the end of heating, in a konjac glucomannan–potato starch gel. [ABSTRACT FROM AUTHOR]

Purpose: Validation of dose escalation through FDG-PET dose painting (DP) for oropharyngeal squamous cell carcinoma (SCC) requires randomized clinical trials with large sample size, potentially involving different treatment planning and delivery systems. As a first step of a joint clinical study of DP, a planning comparison was performed between Tomotherapy HiArt® (HT) and Varian RapidArc® (RA).Methods: The planning study was conducted on five patients with oropharyngeal SCC. Elective and therapeutic CTVs were delineated based on anatomic information, and the respective PTVs (CTVs + 4 mm) were prescribed a dose of 56 (PTV56) and 70 Gy (PTV70). A gradient-based method was used to delineate automatically the external contours of the FDG-PET volume (GTVPET). Variation of the FDG uptake within the GTVPET was linearly converted into a prescription between 70 and 86 Gy. A dilation of the voxel-by-voxel prescription of 2.5 mm was applied to account for geometric errors in dose delivery (PTVPET). The study was divided in two planning phases aiming at maximizing target coverage (phase I) and lowering doses to OAR (phase II). A Quality-Volume Histogram (QVH) assessed conformity with the DP prescription inside the PTVPET.Results: In phase I, for both HT and RA, all plans achieved comparable target coverage for PTV56 and PTV70, respecting the planning objectives. A median value of 99.9 and 97.2% of all voxels in the PTVPET received at least 95% of the prescribed dose for RA and HT, respectively. A median value of 0.0% and 3.7% of the voxels in the PTVPET received 105% or more of prescribed dose for RA and HT, respectively. In phase II, no significant differences were found in OAR sparing. Median treatment times were 13.7 min for HT and 5 min for RA.Conclusions: Both HT and RA can generate similar dose distributions for FDG-PET based dose escalation and dose painting in oropharyngeal SCC patients. [ABSTRACT FROM AUTHOR]

Objective.To develop a methodology for using FDG PET/CT in adaptive dose painting by numbers (DPBN) in head and neck squamous cell carcinoma (HNSCC) patients. Issues related to noise in PET and treatment robustness against geometric errors are addressed. Methods.Five patients with locally advanced HNSCC scheduled for chemo-radiotherapy were imaged with FDG-PET/CT at baseline and 2–3 times during radiotherapy (RT). The GTVPETwas segmented with a gradient-based method. A double median filter reduces the impact of noise in the PET uptake-to-dose conversion. Filtered FDG uptake values were linearly converted into a voxel-by-voxel prescription from 70 (median uptake) to 86 Gy (highest uptake). A PTVPETwas obtained by applying a dilation of 2.5 mm to the entire prescription. Seven iso-uptake thresholds led to seven sub-levels compatible with the Tomotherapy HiArt®Treatment Planning System. Planning aimed to deliver a median dose of 56 Gy and 70 Gy in 35 fractions on the elective and therapeutic PTVs, respectively. Plan quality was assessed with quality volume histogram (QVH). At each time point, plans were generated with a total of 3–4 plans for each patient. Deformable image registration was used for automatic contour propagation and dose summation of the 3 or 4 treatment plans (MIMvista®). Results.GTVPETsegmentations were performed successfully until week 2 of RT but failed in two patients at week 3. QVH analysis showed high conformity for all plans (mean VQ = 0.9593%; mean VQ = 1.053.9%; mean QF 2.2%). Good OAR sparing was achieved while keeping high plan quality. Conclusion.Our results show that adaptive FDG-PET-based escalated dose painting in patients with locally advanced HNSCC is feasible while respecting strict dose constraints to organs at risk. Clinical studies must be conducted to evaluate toxicities and tumor response of such a strategy. [ABSTRACT FROM PUBLISHER]

Abstract: Purpose: To compare the mid-position (MidP) strategy to the conventional internal target volume (ITV) for lung tumor management in helical TomoTherapy, using 4D Monte Carlo (MC) plan simulations. Materials and methods: For NSCLC patients treated by SBRT (n =8) or SIB-IMRT (n =7), target volumes and OARs were delineated on a contrast-enhanced CT, while 4D-CT was used to generate either ITV or MidP volumes with deformable registrations. PTV margins were added. Conformity indexes, volumetric and dosimetric parameters were compared for both strategies. Dose distributions were also computed using a 4D MC model (TomoPen) to assess how intra-fraction tumor motion affects tumor coverage, with and without interplay effect. Results: PTVs derived from MidP were on average 1.2 times smaller than those from ITV, leading to lower doses to OARs. Planned dose conformity to TVs was similar for both strategies. 4D MC computation showed that ITV ensured adequate TV coverage (D 95 within 1% of clinical requirements), while MidP failed in 3 patients of the SBRT group (D 95 to the TV lowered by 4.35%, 2.16% and 2.61%) due to interplay effect in one case and to breathing motion alone in the others. Conclusions: Compared to the ITV, the MidP significantly reduced PTV and doses to OARs. MidP is safe for helical delivery except for very small tumors (<5cc) with large-amplitude motion (>10mm) where the ITV might remain the most adequate approach. [Copyright &y& Elsevier]

Summary: Intensity-modulated radiation therapy (IMRT) is a conformal irradiation technique that enables steep dose gradients. In head and neck tumours this approach spares parotid-gland function without compromise to treatment efficacy. Anatomical and molecular imaging modalities may be used to tailor treatment by enabling proper selection and delineation of target volumes and organs at risk, which in turn lead to dose prescriptions that take into account the underlying tumour biology (eg, human papillomavirus status). Therefore, adaptations can be made throughout the course of radiotherapy, as required. Planned dose increases to parts of the target volumes may also be used to match the radiosensitivity of tumours (so-called dose-painting), assessed by molecular imaging. For swift implementation of tailored and adaptive IMRT, tools and procedures, such as accurate image acquisition and reconstruction, automatic segmentation of target volumes and organs at risk, non-rigid image and dose registration, and dose summation methods, need to be developed and properly validated. [ABSTRACT FROM AUTHOR]

Abstract: Background and purpose: Adaptive strategies in radiotherapy (RT) require the knowledge of the total dose given to every organ of the body. Because of anatomical changes and setup errors non-rigid registration is necessary to map the different dose fractions to a common reference. This study evaluates practically if the accumulation of all of these registered dose fractions must take radiobiology into account in a classical clinical setting. Materials and methods: Ten patients with head and neck tumors treated by chemo-RT were used. Contrast-enhanced CT scans were acquired prior and during RT following delivery of mean doses of 14.2, 24.5, 35.0 and 44.9Gy and the planned pre-treatment helical tomotherapy sinograms were applied on the per-treatment CTs to create a series of per-treatment dose distributions corresponding to each per-treatment CT image. In order to calculate the cumulative dose distribution, the per-treatment dose maps were non-rigidly deformed by using the deformation map computed by a non-rigid registration. The deformed dose maps were then summed in two ways: one while taking radiobiology into account and one without. These two strategies were compared using clinical surrogates in the target volumes (TV) and in surrounding organs at risk (OAR). Results: The differences between the strategies, while statistically significant (p <0.05), are clinically irrelevant. In the OARs, the mean differences stay in the 0.01–0.07Gy range for the total dose. In the targets, all mean differences stay in the 0.001–0.012Gy range. However, some local high difference spots appear leading to punctual errors as high as 2.5Gy. Conclusion: If using current radiotherapy practices and clinical recommendations based on dose surrogates computed globally on OARs and TVs, one does not need to take radiobiological effects into account while accumulating total dose as these lead to very small differences compared to a simple accumulation technique consisting of a linear sum of the dose fractions. However, care must be taken if other adaptive strategies, based on local rather than global information, are used. [Copyright &y& Elsevier]