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SUMMARYThe objective of this study was to determine how clinicians make use of the modern multiplex PCR assays (MPAs) to manage patients hospitalized for community-acquired pneumonia (CAP). We studied the use of MPAs in 1648 patients hospitalized for CAP over a 3-year period at the moment of the setup of the new PCR assay. We observed that the use of MPAs for the identification of multiple respiratory pathogens marks a radical change in the investigation of CAP etiology. Surprisingly, the contribution of MPAs to the medical decision-making process varies drastically according to the units of care.

Objectifs Des outils de detection rapide des bacteries et des virus impliques dans les infections pulmonaires ont ete developpes pour pallier les difficultes rencontrees au cours de la pandemie grippale a virus A(H1N1)pdm2009. L’absence de diagnostic avait rendu difficiles la mise en place de mesures preventives et l’utilisation ciblee des antiviraux. Depuis les techniques de PCR multiplex qui ciblent 15 a 20 pathogenes sur un prelevement unique se sont etablies dans la routine. Les objectifs de ce travail etaient d’evaluer l’utilisation de la PCR multiplex comme outil diagnostique des pneumopathies aigues communautaires (PAC) et de tester un outil PMSI de mesure d’impact medical et economique de son utilisation. Methodes Les patients avec PAC hospitalises en pneumologie et en reanimation polyvalente au CHRU de Tours ont ete selectionnes a partir d’un algorithme PMSI sur trois hivers (semaine 38 a semaine 18 de l’annee suivante) : avant l’utilisation de la PCR multiplex (2008–2009), en utilisation hebdomadaire (2010–2011) et en routine quotidienne (2011–2012). Un retour aux dossiers sur un echantillon aleatoire de 570 patients a permis la validation de l’algorithme PMSI. Un recueil de variables d’interet (duree de sejour, duree d’antibiotherapie, prescription d’antiviraux, nombre et type de prelevements a visee microbiologique, ventilation mecanique, ECMO) a ete mene pour mesurer l’impact de l’utilisation de cette innovation sur la prise en charge et evaluer l’impact economique (estimation des couts). Resultats Il y avait 1349 patients hospitalises pour PAC sur la periode. Les parametres de performance du PMSI etaient : sensibilite 94 %, specificite 85 %, valeur predictive positive 83 %, valeur predictive negative 95 %. En 2010–2011, 27 % [IC95 % 25,6–27,6 %] des PAC hospitalisees avaient beneficie d’une PCR, dont 18,2 % [IC95 % 17,5–19 %] en pneumologie et 37,2 % [IC95 % 35,7–38,8 %] en reanimation, et 33,5 % [IC95 % 32,2–34,9 %] en 2012–2013, dont 13,0 %[IC95 % 12,5–18,4 %] en pneumologie et 66,9 % [IC 95 % 64,3–69,8 %] en reanimation. En 2010–2011, 58 % des PCR etaient positives et 67 % en 2011–2012. Les analyses de l’impact medico-economiques sont en cours. Conclusion La PCR multiplex n’est pas un outil diagnostique systematique de patients hospitalises pour PAC, y compris pour les PAC severes.

To compare the dosimetric and geometric properties of a commercial x-ray based image-guided small animal irradiation system, installed at three institutions and to establish a complete and broadly accessible commissioning procedure.The system consists of a 225 kVp x-ray tube with fixed field size collimators ranging from 1 to 44 mm equivalent diameter. The x-ray tube is mounted opposite a flat-panel imaging detector, on a C-arm gantry with 360° coplanar rotation. Each institution performed a full commissioning of their system, including half-value layer, absolute dosimetry, relative dosimetry (profiles, percent depth dose, and relative output factors), and characterization of the system geometry and mechanical flex of the x-ray tube and detector. Dosimetric measurements were made using Farmer-type ionization chambers, small volume air and liquid ionization chambers, and radiochromic film. The results between the three institutions were compared.At 225 kVp, with 0.3 mm Cu added filtration, the first half value layer ranged from 0.9 to 1.0 mm Cu. The dose-rate in-air for a 40 × 40 mm(2) field size, at a source-to-axis distance of 30 cm, ranged from 3.5 to 3.9 Gy/min between the three institutions. For field sizes between 2.5 mm diameter and 40 × 40 mm(2), the differences between percent depth dose curves up to depths of 3.5 cm were between 1% and 4% on average, with the maximum difference being 7%. The profiles agreed very well for fields5 mm diameter. The relative output factors differed by up to 6% for fields larger than 10 mm diameter, but differed by up to 49% for fields ≤5 mm diameter. The mechanical characteristics of the system (source-to-axis and source-to-detector distances) were consistent between all three institutions. There were substantial differences in the flex of each system.With the exception of the half-value layer, and mechanical properties, there were significant differences between the dosimetric and geometric properties of the three systems. This underscores the need for careful commissioning of each individual system for use in radiobiological experiments.

The potential for detrimental incidents and the ever increasing complexity of patient treatments emphasize the need for accurate dosimetric verification in radiotherapy. For this reason, all curative treatments are verified, either pretreatment or in vivo, by electronic portal imaging device (EPID) dosimetry in the Radiation Oncology Department of The Netherlands Cancer Institute-Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands. Since the clinical introduction of the method in January 2005 until August 2009, treatment plans of 4337 patients have been verified. Among these plans, 17 serious errors were detected that led to intervention. Due to their origin, nine of these errors would not have been detected with pretreatment verification. The method is illustrated in detail by the case of a plan transfer error detected in a 5 x 5 Gy intensity-modulated radiotherapy (IMRT) rectum treatment. The EPID reconstructed dose at the isocenter was 6.3% below the planned value. Investigation of the plan transfer chain revealed that due to a network transfer error, the plan was corrupted. 3D analysis of the acquired EPID data revealed serious underdosage of the planning target volume: On average 11.6%, locally up to 20%. This report shows the importance of in vivo (EPID) dosimetry for all treatment plans as well as the ability of the method to assess the dosimetric impact of deviations found.

International audience

International audience

Respiratory motion causes artifacts in cone-beam (CB) CT images acquired on slow rotating scanners integrated with linear accelerators. Respiration-correlated CBCT has been proposed to correct for the respiratory motion but only a subset of the CB projections is used to reconstruct each frame of the 4D CBCT image and, therefore, adequate image quality requires long acquisition times. In this article, the authors develop an on-the-fly solution to estimate and compensate for the respiratory motion in the reconstruction of a 3D CBCT image from all the CB projections. An a priori motion model of the patient respiratory cycle is estimated from the 4D planning CT. During the acquisition, the model is correlated with the respiration using a respiratory signal extracted from the CB projections. The estimated motion is next compensated for in an optimized reconstruction algorithm. The motion compensated for is forced to be null on average over the acquisition time to ensure that the compensation results in a CBCT image which describes the mean position of each organ, even if the a priori motion model is inaccurate. Results were assessed on simulated, phantom, and patient data. In all experiments, blur was visually reduced by motion-compensated CBCT. Simulations showed robustness to inaccuracies of the motion model observed on patient data such as amplitude variations, phase shifts, and setup errors, thus proving the efficiency of the compensation using an a priori motion model. Noise and view-aliasing artifacts were lower on motion-compensated CBCT images with 1 min scan than on respiration-correlated CBCT images with 4 min scan. Finally, on-the-fly motion estimation and motion-compensated reconstruction were within the acquisition time of the CB projections and the CBCT image available a few seconds after the end of the acquisition. In conclusion, the authors developed and implemented a method for correcting the respiratory motion during the treatment fractions which can replace respiration-correlated CBCT for improving image quality while decreasing acquisition time

lower lobe lung tumors move with amplitudes of up to 2 cm due to respiration. To reduce respiration imaging artifacts in planning CT scans, 4D imaging techniques are used. Currently, we use a single (midventilation) frame of the 4D data set for clinical delineation of structures and radiotherapy planning. A single frame, however, often contains artifacts due to breathing irregularities, and is noisier than a conventional CT scan since the exposure per frame is lower. Moreover, the tumor may be displaced from the mean tumor position due to hysteresis. The aim of this work is to develop a framework for the acquisition of a good quality scan representing all scanned anatomy in the mean position by averaging transformed (deformed) CT frames, i.e., canceling out motion. A nonrigid registration method is necessary since motion varies over the lung.4D and inspiration breath-hold (BH) CT scans were acquired for 13 patients. An iterative multiscale motion estimation technique was applied to the 4D CT scan, similar to optical flow but using image phase (gray-value transitions from bright to dark and vice versa) instead. From the (4D) deformation vector field (DVF) derived, the local mean position in the respiratory cycle was computed and the 4D DVF was modified to deform all structures of the original 4D CT scan to this mean position. A 3D midposition (MidP) CT scan was then obtained by (arithmetic or median) averaging of the deformed 4D CT scan. Image registration accuracy, tumor shape deviation with respect to the BH CT scan, and noise were determined to evaluate the image fidelity of the MidP CT scan and the performance of the technique.Accuracy of the used deformable image registration method was comparable to established automated locally rigid registration and to manual landmark registration (average difference to both methods0.5 mm for all directions) for the tumor region. From visual assessment, the registration was good for the clearly visible features (e.g., tumor and diaphragm). The shape of the tumor, with respect to that of the BH CT scan, was better represented by the MidP reconstructions than any of the 4D CT frames (including MidV; reduction of "shape differences" was 66%). The MidP scans contained about one-third the noise of individual 4D CT scan frames.We implemented an accurate method to estimate the motion of structures in a 4D CT scan. Subsequently, a novel method to create a midposition CT scan (time-weighted average of the anatomy) for treatment planning with reduced noise and artifacts was introduced. Tumor shape and position in the MidP CT scan represents that of the BH CT scan better than MidV CT scan and, therefore, was found to be appropriate for treatment planning.

Purpose: Conventional radiotherapy planning uses simplified DVH-derived metrics (e.g. D99, D95) as surrogates for tumor control probability when evaluating plan quality. While this has the advantage of providing an easily derived predictor variable, such metrics fail to consider critical aspects of the underlying radiobiology. Counter to observed radiobiological effects, there is a prevailing assumption of tumor subvolume independence. We tested this by introducing a parameter to capture departures from independence using a modified metric, termed the “generalized tumor dose” (gTD). Methods: For given dose distributions, cell survival was derived from a comprehensive biological model (Jeong, 2013 Phys. Med. Biol.). The gTD metric applied a generalized mean term, q, to subvolume survival values, with this term optimized according to its predictive power over the NSCLS cohort (N=316). Patients were treated 1.8–2.2 Gy/Fx in 28–39 Fxs (n=50), or 2.75 Gy/Fx in 24 fractions (n=266). Results were compared to other metrics according binary outcome and actuarial survival prediction. Results: Fitting model parameters to combined cohort data using log-likelihood and actuarial methods, we derived an optimized generalized mean parameter q of −1.14 (95% confidence interval upper bound=0.08). Patient-specific gTD values derived using this value showed superior performance to other clinical metrics. For gTD, normalized log-likelihood=−0.471, AUC=0.634, and R^2=0.066, versus normalized log-likelihood=−0.508/−0.504, AUC=0.473/0.462, and R^2=0.0011/0.0014 for D99/D95. Furthermore, when q wasn’t incorporated into the model (q=1, implicitly), AUC decreased to 0.622, normalized log-likelihood to −0.501 and R^2 to 0.0144. Conclusion: Negative q values suggest areas of highest dose play a greater role in determining outcome than expected based only on TCP.The biological origin of this effect could be of several potential causes, including bystander effects, genomic intra-tumor heterogeneity, or tumor shrinkage. Accounting for these interactions, the gTD metric provides superior accuracy as a predictor of outcome.

Objectifs Des outils de detection rapide des bacteries et des virus impliques dans les infections pulmonaires ont ete developpes pour pallier les difficultes rencontrees au cours de la pandemie grippale a virus A(H1N1)pdm2009. L’absence de diagnostic avait rendu tres difficiles la mise en place de mesures preventives et l’utilisation ciblee des antiviraux. Depuis les techniques de PCR multiplex qui ciblent 15 a 20 pathogenes sur un prelevement unique se sont etablies dans la routine. Les objectifs de ce travail etaient de faire une evaluation precoce de l’impact medical et economique de l’utilisation de la PCR multiplex dans la prise en charge des pneumopathies aigues communautaires (PAC). Methodes Les patients avec PAC hospitalises en pneumologie, en reanimation medicale au CHRU de Tours ont ete selectionnes a partir d’un algorithme PMSI sur trois hivers : – avant l’utilisation de la PCR multiplex (2008–2009); – en utilisation hebdomadaire (2010–2011); – en routine quotidienne (2011–2012). Un retour aux dossiers sur un echantillon aleatoire de 570 patients a permis la validation de l’algorithme PMSI. Un recueil de variables d’interet (duree de sejour, duree d’antibiotherapie…) a ete mene pour mesurer l’impact de l’utilisation de cette innovation sur la prise en charge et evaluer l’impact economique (estimation des couts). Resultats Les parametres de performance du PMSI etaient : sensibilite 94 %, specificite 85 %, valeur predictive positive 83 %, valeur predictive negative 95 % ; 22 % des PAC hospitalisees en 2010–2011 avaient beneficie d’une PCR, dont 15 % en pneumologie et 31 % en reanimation, et 28 % en 2012–2013, dont 16 % en pneumologie et 56 % en reanimation. En 2010–2011, 58 % des PCR etaient positives et 67 % en 2011–2012. Les analyses de l’impact medico-economiques sont en cours. Conclusion Le premier constat est que le recours a la PCR multiplex n’est pas systematique face a une PAC hospitalisee, meme en periode hivernale.

Beside insulinoma, alternative causes of hyperinsulinaemic hypoglycaemia include the rare autoimmune syndrome related to spontaneous autoantibodies either to insulin or to insulin receptor. We describe a case of hypoglycaemia with high insulinemia in which insulinoma could not be evidenced. Surprisingly, we found in the patient's serum both insulin autoantibodies and insulin receptor autoantibodies. Available data eventually supported the predominant role of insulin autoantibodies rather than insulin receptor autoantibodies in the mechanism of hypoglycaemia of this patient. Insulin antibodies were present in high titre. Most of the insulin in serum was bound to the insulin antibodies and free insulin was slightly increased. HLA typing displayed DR4 haplotype, known to be strongly linked to the insulin autoimmune syndrome. The patient's serum was able to inhibit insulin binding to its receptor in a cultured cell line overexpressing insulin receptors both in experiments with native serum and with serum depleted from insulin antibodies. However, we could not demonstrate that the insulin receptor antibodies had insulin mimicking effect. We have no obvious explanation for the presence of these two antibodies in the same patient. Possible hypotheses might involve an idiotype-anti-idiotype mechanism or a poly-autoimmune disease.

This study was carried out to determine the stability of the response of amorphous silicon (a-Si)-flat panel imagers for dosimetry applications. Measurements of the imager's response under reference conditions were performed on a regular basis for four detectors of the same manufacturer. We found that the ambient temperature influenced the dark-field, while the gain of the imager signal was unaffected. Therefore, temperature fluctuations were corrected for by applying a "dynamic" darkfield correction. This correction method also removed the influence of a small, irreversible increase of the dark-field current, which was equal to 0.5% of the dynamic range of the imager per year and was probably caused by mild radiation damage to the a-Si array. By applying a dynamic dark-field correction, excellent stability of the response over the entire panel of all imagers of 0.5% (1 SD) was obtained over an observation period up to 23 months. However, two imagers had to be replaced after several months. For one imager, an image segment stopped functioning, while the image quality of the other imager degraded significantly. We conclude that the tested a-Si EPIDs have a very stable response and are therefore well suited for dosimetry. We recommend, however, applying quality assurance tests dedicated to both imaging and dosimetry.

Purpose:Modelingtumourcontrol probability (TCP) in breast conserving therapy (BCT) with the classic Webb‐Nahum radiotherapymodel cannot explain the outcomes of treatments without radiotherapy (65% TCP at 10 years) from the Fifth Cycle data of the Early Breast Cancer Trialists' Collaborative Group (EBCTCG). The TCP model was extended to solve this inconsistency. Methods: We proposed a statistical model originating from the Webb‐Nahum model, but also considered tumour cell quantity as a heterogeneous variable and introduced a new heterogeneity factor: indolent‐cell fraction (ICF). With assumed Beta distribution, this ICF factor describes the proportion of tumour cells remaining after primary surgery which do not cause local recurrence even if radiotherapy is omitted. The residual microscopic tumour cell quantity was estimated using detailed digital analysis of the microscopic slides from breast‐cancer resection specimens (60 patients, 1818 slides). The ICF factor together with an approximation of radiosensitivity was estimated using Shor‐Zhurbenko optimization to fit data from the EORTC boost‐vs‐no‐boost trial to the new model. Uncertainties were incorporated using bootstrapping. The analysis was performed separately for younger (age = 50 years) and older patients. Finally, the radiotherapydose‐TCP responses of two groups were compared. Results: The estimated number of residual microscopic tumour cells after surgery was significantly larger in younger patients (9.1e7) than in older patients (1.6e7, P

Background Chromosomal rearrangements in the receptor tyrosine kinase (RTK) ROS1 define a new molecular subset of NSCLC. ALK inhibitors can inhibit ROS1 kinase activity in cell lines. We examined the efficacy and safety of crizotinib, a small molecule inhibitor of two other RTKs, MET and ALK, in patients with advanced, ROS1-rearranged NSCLC. Methods Patients with advanced NSCLC harboring ROS1 rearrangement, as determined using a break-apart FISH assay, were recruited into an expansion cohort of the original phase 1 study of crizotinib. Patients were treated with crizotinib at the standard oral dose of 250 mg BID. The objective response rate (ORR) was determined based on RECIST v1.0. The disease control rate (DCR; stable disease [SD] + partial response [PR] + complete response [CR]) was evaluated at weeks 8 and 16. Results At the time of data cut-off on April 19, 2012, 15 patients with ROS1 NSCLC had received crizotinib and 14 were evaluable for response. The median age was 54 years (range 31–72). Fourteen patients were never-smokers and all had adenocarcinoma histology. All patients were confirmed negative for ALK rearrangement. The median number of prior treatments was 1 (range 0–6). The first ROS1 patient received crizotinib on October 19, 2010. To date, the ORR is 57% (8/14; 95% CI 28.9–82.3), with 7 PR and 1 CR. There were 4 SD, one of which was unconfirmed as PR at the time of data cut-off. The DCR at 8 weeks was 79% (11/14). Median duration of treatment was 25.7 weeks (range 0.1 + to 65.3 + ), and 12 patients continue on study. The pharmacokinetics, antitumor activity and safety profile of crizotinib in this group of patients were similar to those observed in patients with ALK-positive NSCLC. Conclusions Crizotinib is associated with clinically significant antitumor activity in patients with ROS1 NSCLC. Similar to ALK, ROS1 rearrangement defines another unique molecular subset of NSCLC patients for whom crizotinib therapy may be highly effective. Importantly, this study represents the first clinical investigation of ROS1 as a driver mutation and therapeutic target in cancer. Disclosure S.I. Ou: Advisory role: Pfizer, Genentech. Compensated Honoraria: Pfizer, Genentech, Lilly. Myself Research funding: Pfizer. Myself (institution). D.R. Camidge: Advisory role: Pfizer. Myself. Honoraria: Pfizer. Myself. L. Tye: Employment: Pfizer. Clinician. Myself. Stock Ownership; Pfizer. Myself. K. Wilner: Emplyement: Pfizer. Senior Director. Myself. Compensated. Stock ownership: Pfizer. Myself. M. Varella-Garcia: Honoraria: Abbott Molecular. Myself. funding for the trial provided by NIH - yes. A.T. Shaw: Advisory role: Pfizer, Ariad, Chugai, Novartis, Daiichi-sankyo. Myself. Compensated Research funding: Astra Zeneca, Novartis. Myself. All other authors have declared no conflicts of interest.

The demands for precision of modern radiation therapy approaches (IMRT,SBRT) require a comprehensive understanding of the application of Image‐GuidedRadiation Therapy(IGRT) systems and their utilization. Modern IGRT systems provide unprecedented visualization of anatomy over the recent state‐of‐the art (MV portal imaging), with modern image guidance hardware (kV X‐Ray, in‐room CT, emerging external and internal imaging systems). They furthermore integrate advanced image registration methods as well as integrated couch control systems. While significantly empowering precision therapy, IGRT comes at a cost. Not only does the IGRT equipment require specific attention for commissioning and quality assurance, in many instances the physicists will need to re‐learn or acquire new knowledge about imaging‐specific issues. In all cases, a significant change to the operational procedures of the department will occur, and both extensive staff training, as well as implementation of new policies, procedures, and workflow models for treatment, will be necessary. The relationship between information gathered at simulation, tradeoffs made during treatment planning, and plan sensitivities will influence the use of image guidance, and uncertainties in imaging at the treatment unit may require re‐consideration of margins and planning strategies. This course will help guide a physicist through the process of initiating an IGRT program. The overall concept of implementing IGRT from a departmental perspective will be briefly overviewed. A detailed discussion of IGR T technologies and the details of their commissioning and quality assurance needs will be provided. The development of IGRT strategies, policies, training, and process quality control will be described. Learning Objectives: 1. Understand the technical and procedural components involved in initiating an IGRT program 2. Understand the costs and benefits of various levels of IGRT use 3. Understand the needs for quality assurance tied to IGRT implementation 4. Understand the relationships between IGRT and decisions made in simulation and treatment planning Gain sufficient knowledge to proactively plan new IGRT utilization paradigms in the clinic

Breast radiotherapy has undergone significant innovation in the past 10 years and the frequency of image‐guidedradiation therapy(IGRT) is increasing. This session will review clinical indications for breast radiotherapy (RT) and conventional RT methods. Ongoing clinical innovations in breast RT techniques will then be highlighted (e.g., partial breast irradiation, IMRT and VMAT for irradiation of the internal mammary chain). Finally, the emerging role of IGRT will be discussed with its application to improving setup reproducibility and designing appropriate target margins. The IGRT methods will include surface imaging although the focus will remain on more widely‐available IGRT systems such as CBCT and kV imaging. a.Brief clinical review of RT as a function of breast cancer stage according to RTOG guidelines b.Dosimetric advances in breast RT, including IMRT and VMAT for nodal irradiation and partial breast irradiation for early‐stage cancer c.The role of IGRT for setup reproducibility and margin design d. IGRT for adaptive RT in cases of seroma reduction. Learning Objectives: 1. Review the clinical targets for breast RT as a function of cancer stage 2. Learn about innovative uses of advanced radiotherapy techniques for breast treatment 3. Highlight the emerging role of IGRT to guide planning and treatment. Jan‐Jakob Sonke's research is sponsored by Elekta Corporation.

Purpose: To elucidate our approach of 3D in vivo dose verification of VMAT and to present the clinical results since its introduction in 2009. Methods: An EPID‐based method using a back‐projection algorithm is clinically applied for 3D in vivo dose verification of the delivery of VMAT plans, created using the SmartArc module of Pinnacle. Single‐arc treatment is applied for VMAT of prostate cancer, while two arcs are used for most other VMAT treatments (head‐and‐neck, lung‐SBRT, and brain‐SRS). EPID ‘movies’ are acquired during VMAT delivery on Elekta linacs using in‐house developed software. Our routine clinical procedure is to perform 3D in vivo dose verification of the first three fractions. The comparison of the EPID‐reconstructed and planned dose distributions is done by a 3D γ‐evaluation method, based on 3%/3mm γ‐criteria. Since August 2011 dose‐reconstruction and γ‐evaluation software runs automatically. Results: The analysis of the results of about 4000 VMAT arcs (February 2012) showed that γ‐evaluation data are comparable to the values found previously for 2D IMRT verification. The average difference between measured and predicted isocenter dose was (−0.2±3.7)%. More than 90% of the in vivo VMAT analyses were directly approved (no interaction of any kind needed); the remaining required further inspection by a clinical physicist. The limitations of the model and anatomical changes of the patient, confirmed by cone‐ beam CT scans, were the main reasons for the observed deviations. Examples will be given of differences between (in vivo) measured and planned dose distributions that were not observed during phantom measurements. Using the automatical software, a dosimetry report is available for inspection within minutes after treatment delivery without any manual intervention. Conclusions:EPIDdosimetry is a simple and accurate tool for 3D in vivo dose verification of VMAT delivery. It is faster than pre‐ treatment verification and provides clinically more relevant information.

Acquisition and processing of multimodality image data are now fundamental parts of patient management in radiation therapy.Image data are acquired and analyzed to aid diagnosis and staging, to guide treatment planning and delivery and to help monitor the patient during and after therapy. Most radiotherapy departments have dedicated CT scanners, some with 4D capabilities. Many departments also have or are contemplating dedicated MR and PET/CT scanners. More imaging devices are also appearing in the treatment room, with in‐room, on‐board and integrated imaging devices becoming commonplace. The availability of hybrid MR scanner/treatment units is not far off. Naturally, each imaging modality provides both benefits and challenges towards supporting and improving the radiotherapy process. In order to leverage the information in the various imaging studies, effective processing tools are needed to extract useful information and to combine and present it in a way that promotes a clear and efficient workflow. There are several classes of these tools including image enhancement, visualization, segmentation, registration and quantification. These tools may be used individually or in combination at many points in the radiotherapy process with the overall goal to create a more accurate and complete model of the patient so that an effective course of therapy can be devised and carried out. This course will provide an overview of the different imaging modalities and procedures used in radiotherapy and highlight the benefits and challenges of each. The details of the various image processing tools used to extract, combine and analyze the information from the various imaging studies will also be presented. Finally, the effective use of these tools at each step of the radiotherapy process will be described and elucidated using several clinical examples. Educational Objectives: 1. Understand the basic principles for the different imaging modalities used in radiation therapy. 2. Understand the mechanics of the different classes of image processing tools using in radiotherapy. 3. Understand how different image data and processing tools are used to support and improve the radiotherapy process.

7015 Background: Published lung SBRT outcomes/dose response data for inoperable NSCLC come from small phase I-II studies or larger datasets not requiring image-guided radiotherapy (IGRT) or volumet...

Acquisition, processing and analysis of medical image data are now fundamental parts of patient management in radiation therapy.Image data are used to aid diagnosis and staging, to guide treatment planning and delivery and to help monitor the patient during and after therapy. Most radiotherapy departments have dedicated CT scanners, some with 4D capabilities. Many departments also have or are contemplating dedicated MR and PET/CT scanners. More imaging devices are also appearing in the treatment room, with in‐room, on‐board and integrated imaging devices becoming commonplace. The availability of hybrid MR scanner/treatment units is not far off. Naturally, each imaging modality provides both benefits and challenges towards supporting and improving the radiotherapy process. In order to leverage the information in the various imaging studies, effective processing tools are needed to extract useful information and to combine and present it in a way that promotes a clear and efficient workflow. There are several classes of these tools including image enhancement, visualization, segmentation, registration and quantification. These tools may be used individually or in combination at many points in the radiotherapy process with the overall goal to create a more complete and accurate model of the patient so that an effective course of therapy can be devised and carried out. This course provides an overview of the different imaging modalities and procedures used in radiotherapy and highlights the benefits and challenges of each. A detailed description of the various image processing tools used to extract, combine and analyze the information from different imaging studies is also presented. Finally, the effective use of these tools at each step of the radiotherapy process is described and elucidated using numerous clinical examples. Learning Objectives: 1. Act 1 Understand the benefits and challenges of the various imaging modalities used in radiation therapy. 2. Act 2 Understand the mechanics of the different classes of image processing tools using in radiotherapy. 3. Act 3 Understand how image processing tools are used to support and improve the radiotherapy process.

Purpose: Four‐dimensional (4D) imaging techniques can be used to obtain (respiration) artifact‐free CTimages of the thorax. However, its use in radiotherapy is limited since clinical treatment planning systems are currently not able to use the full 4D data. The purpose of this study was to reconstruct a representative single 3D CT scan from the 4D data set (with tumor closest to the mean position) for use in radiotherapy planning of lungtumors to enable reduction of treatment error margins. Method and Materials: After acquisition of the 4D CT scan (10 frames), the tumor is manually segmented (roughly) in the first frame and automatically (gray‐value) registered to the tumor in the subsequent frames. This gives the motion of the tumor during the respiratory cycle in 3D. Subsequently, from the cranio‐caudal (CC) tumor motion curve, the mean tumor position and its corresponding mid‐ventilation (MV) time‐percentage are calculated. The CT scan for planning is reconstructed at this time‐percentage. As indication of the merit of this concept, its effect on margins from CTV to PTV and on the PTV volume was calculated covering respiratory motion, respiratory baseline variation and setup errors (systematic and random). Results: Based on 13 patients, the worst tumor position accuracy (with respect to the mean tumor position) in the mid‐ventilation CT scan occurred in the anterior‐posterior direction: −0.7±0.8 mm (due to hysteresis). For these patients, the errors in conventional free‐breathing CT were estimated to be 0±3.4 mm (CC) and 0±1.4 mm (AP). The mid‐ventilation concept resulted in margin reduction up to 45% and a PTV volume reduction up to 35%. Conclusion: The mid‐ventilation concept, based on tumor motion, is a simple method to obtain an artifact‐free CT scan with smaller systematic errors compared to conventional CT scans. Significant reduction of the PTV volume can be achieved.