The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Christopher J Moore - One of the best experts on this subject based on the ideXlab platform.
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a method to combine target volume data from 3d and 4d planned thoracic radiotherapy patient cohorts for machine learning applications
Radiotherapy and Oncology, 2017Co-Authors: Corinne Johnson, Gareth J Price, Christopher J Moore, Jonathan Khalifa, Corinne Faivrefinn, Andre Dekker, Marcel Van HerkAbstract:Abstract Background and purpose The gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV). We present and validate a method to synthesise GTV data from the iGTV, allowing the combination of 3D and 4D planned patient cohorts for modelling. Material and methods Expert Delineations in 40 non-small cell lung cancer patients were used to develop linear fit and erosion methods to synthesise the GTV volume and shape. Quality was assessed using Dice Similarity Coefficients (DSC) and closest point measurements; by calculating dosimetric features; and by assessing the quality of random forest models built on patient populations with and without synthetic GTVs. Results Volume estimates were within the magnitudes of inter-observer Delineation variability. Shape comparisons produced mean DSCs of 0.8817 and 0.8584 for upper and lower lobe cases, respectively. A model trained on combined true and synthetic data performed significantly better than models trained on GTV alone, or combined GTV and iGTV data. Conclusions Accurate synthesis of GTV size from the iGTV permits the combination of lung cancer patient cohorts, facilitating machine learning applications in thoracic radiotherapy.
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early clinical evaluation of a novel three dimensional structure Delineation software tool sculpter for radiotherapy treatment planning
British Journal of Radiology, 2008Co-Authors: Catherine Mcbain, Gareth J Price, Christopher J Moore, Matthew M L Green, J Sykes, Aminah Amer, Vincent Khoo, P B PriceAbstract:Modern radiotherapy treatment planning (RTP) necessitates increased Delineation of target volumes and organs at risk. Conventional manual Delineation is a laborious, time-consuming and subjective process. It is prone to inconsistency and variability, but has the potential to be improved using automated segmentation algorithms. We carried out a pilot clinical evaluation of SCULPTER (Structure Creation Using Limited Point Topology Evidence in Radiotherapy) - a novel prototype software tool designed to improve structure Delineation for RTP. Anonymized MR and CT image datasets from patients who underwent radiotherapy for bladder or prostate cancer were studied. An experienced radiation oncologist used manual and SCULPTER-assisted methods to create clinically acceptable organ Delineations. SCULPTER was also tested by four other RTP professionals. Resulting contours were compared by qualitative inspection and quantitatively by using the volumes of the structures delineated and the time taken for completion. The SCULPTER tool was easy to apply to both MR and CT images and diverse anatomical sites. SCULPTER Delineations closely reproduced manual contours with no significant volume differences detected, but SCULPTER Delineations were significantly quicker (p<0.05) in most cases. In conclusion, clinical application of SCULPTER resulted in rapid and simple organ Delineations with equivalent accuracy to manual methods, demonstrating proof-of-principle of the SCULPTER system and supporting its potential utility in RTP.
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a method to calculate coverage probability from uncertainties in radiotherapy via a statistical shape model
Physics in Medicine and Biology, 2007Co-Authors: Gareth J Price, Christopher J MooreAbstract:In this paper we describe a technique that may be used to model the geometric uncertainties that accrue during the radiotherapy process. Using data from in-treatment cone beam CT scans, we simultaneously analyse non-uniform observer Delineation variability and organ motion together with patient set-up errors via the creation of a point distribution model (PDM). We introduce a novel method of generating a coverage probability matrix, that may be used to determine treatment margins and calculate uncertainties in dose, from this statistical shape model. The technique does not assume rigid body motion and can extrapolate shape variability in a statistically meaningful manner. In order to construct the PDM, we generate corresponding surface points over a set of Delineations. Correspondences are established at a set of points in parameter space on spherically parameterized and canonical aligned outlines. The method is demonstrated using rectal Delineations from serially acquired in-treatment cone beam CT image volumes of a prostate patient (44 image volumes total), each delineated by a minimum of two observers (maximum six). Two PDMs are constructed, one with set-up errors included and one without. We test the normality assumptions of the PDMs and find the distributions to be Gaussian in nature. The rectal PDM variability is in general agreement with data in the literature. The two resultant coverage probability matrices show differences as expected.
Gareth J Price - One of the best experts on this subject based on the ideXlab platform.
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a method to combine target volume data from 3d and 4d planned thoracic radiotherapy patient cohorts for machine learning applications
Radiotherapy and Oncology, 2017Co-Authors: Corinne Johnson, Gareth J Price, Christopher J Moore, Jonathan Khalifa, Corinne Faivrefinn, Andre Dekker, Marcel Van HerkAbstract:Abstract Background and purpose The gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV). We present and validate a method to synthesise GTV data from the iGTV, allowing the combination of 3D and 4D planned patient cohorts for modelling. Material and methods Expert Delineations in 40 non-small cell lung cancer patients were used to develop linear fit and erosion methods to synthesise the GTV volume and shape. Quality was assessed using Dice Similarity Coefficients (DSC) and closest point measurements; by calculating dosimetric features; and by assessing the quality of random forest models built on patient populations with and without synthetic GTVs. Results Volume estimates were within the magnitudes of inter-observer Delineation variability. Shape comparisons produced mean DSCs of 0.8817 and 0.8584 for upper and lower lobe cases, respectively. A model trained on combined true and synthetic data performed significantly better than models trained on GTV alone, or combined GTV and iGTV data. Conclusions Accurate synthesis of GTV size from the iGTV permits the combination of lung cancer patient cohorts, facilitating machine learning applications in thoracic radiotherapy.
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early clinical evaluation of a novel three dimensional structure Delineation software tool sculpter for radiotherapy treatment planning
British Journal of Radiology, 2008Co-Authors: Catherine Mcbain, Gareth J Price, Christopher J Moore, Matthew M L Green, J Sykes, Aminah Amer, Vincent Khoo, P B PriceAbstract:Modern radiotherapy treatment planning (RTP) necessitates increased Delineation of target volumes and organs at risk. Conventional manual Delineation is a laborious, time-consuming and subjective process. It is prone to inconsistency and variability, but has the potential to be improved using automated segmentation algorithms. We carried out a pilot clinical evaluation of SCULPTER (Structure Creation Using Limited Point Topology Evidence in Radiotherapy) - a novel prototype software tool designed to improve structure Delineation for RTP. Anonymized MR and CT image datasets from patients who underwent radiotherapy for bladder or prostate cancer were studied. An experienced radiation oncologist used manual and SCULPTER-assisted methods to create clinically acceptable organ Delineations. SCULPTER was also tested by four other RTP professionals. Resulting contours were compared by qualitative inspection and quantitatively by using the volumes of the structures delineated and the time taken for completion. The SCULPTER tool was easy to apply to both MR and CT images and diverse anatomical sites. SCULPTER Delineations closely reproduced manual contours with no significant volume differences detected, but SCULPTER Delineations were significantly quicker (p<0.05) in most cases. In conclusion, clinical application of SCULPTER resulted in rapid and simple organ Delineations with equivalent accuracy to manual methods, demonstrating proof-of-principle of the SCULPTER system and supporting its potential utility in RTP.
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a method to calculate coverage probability from uncertainties in radiotherapy via a statistical shape model
Physics in Medicine and Biology, 2007Co-Authors: Gareth J Price, Christopher J MooreAbstract:In this paper we describe a technique that may be used to model the geometric uncertainties that accrue during the radiotherapy process. Using data from in-treatment cone beam CT scans, we simultaneously analyse non-uniform observer Delineation variability and organ motion together with patient set-up errors via the creation of a point distribution model (PDM). We introduce a novel method of generating a coverage probability matrix, that may be used to determine treatment margins and calculate uncertainties in dose, from this statistical shape model. The technique does not assume rigid body motion and can extrapolate shape variability in a statistically meaningful manner. In order to construct the PDM, we generate corresponding surface points over a set of Delineations. Correspondences are established at a set of points in parameter space on spherically parameterized and canonical aligned outlines. The method is demonstrated using rectal Delineations from serially acquired in-treatment cone beam CT image volumes of a prostate patient (44 image volumes total), each delineated by a minimum of two observers (maximum six). Two PDMs are constructed, one with set-up errors included and one without. We test the normality assumptions of the PDMs and find the distributions to be Gaussian in nature. The rectal PDM variability is in general agreement with data in the literature. The two resultant coverage probability matrices show differences as expected.
Marielle E.p. Philippens - One of the best experts on this subject based on the ideXlab platform.
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Evaluation of diffusion weighted imaging for tumor Delineation in head-and-neck radiotherapy by comparison with automatically segmented 18F-fluorodeoxyglucose positron emission tomography
Elsevier, 2018Co-Authors: Tim Schakel, Boris Peltenburg, Jan-willem Dankbaar, Carlos E. Cardenas, Michalis Aristophanous, Chris H.j. Terhaard, Johannes M. Hoogduin, Marielle E.p. PhilippensAbstract:Background and purpose: Diffusion weighted (DW) MRI may facilitate target volume Delineation for head-and-neck (HN) radiation treatment planning. In this study we assessed the use of a dedicated, geometrically accurate, DW-MRI sequence for target volume Delineation. The Delineations were compared with semi-automatic segmentations on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images and evaluated for interobserver variation. Methods and materials: Fifteen HN cancer patients underwent both DW-MRI and FDG-PET for RT treatment planning. Target Delineation on DW-MRI was performed by three observers, while for PET a semi-automatic segmentation was performed using a Gaussian mixture model. For interobserver variation and intermodality variation, volumes, overlap metrics and Hausdorff distances were calculated from the Delineations. Results: The median volumes delineated by the three observers on DW-MRI were 10.8, 10.5 and 9.0 cm3 respectively, and was larger than the median PET volume (8.0 cm3). The median conformity index of DW-MRI for interobserver variation was 0.73 (range 0.38–0.80). Compared to PET, the Delineations on DW-MRI by the three observers showed a median dice similarity coefficient of 0.71, 0.69 and 0.72 respectively. The mean Hausdorff distance was small with median (range) distances between PET and DW-MRI of 2.3 (1.5–6.8), 2.5 (1.6–6.9) and 2.0 (1.35–7.6) mm respectively. Over all patients, the median 95th percentile distances were 6.0 (3.0–13.4), 6.6 (4.0–24.0) and 5.3 (3.4–26.0) mm. Conclusion: Using a dedicated DW-MRI sequence, target volumes could be defined with good interobserver agreement and a good overlap with PET. Target volume Delineation using DW-MRI is promising in head-and-neck radiotherapy, combined with other modalities, it can lead to more precise target volume Delineation. Keywords: Radiotherapy, Head and neck, Target volume Delineation, Diffusion MRI, PE
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Verification of HE-based CTV in laryngeal and hypopharyngeal cancer using pan-cytokeratin
Elsevier, 2018Co-Authors: Hans Ligtenberg, Chris H.j. Terhaard, Cornelis P J Raaijmakers, Stefan M. Willems, Lilian N. Ruiter, Elise Anne Jager, Marielle E.p. PhilippensAbstract:Background: For accurate target definition, we determined margins for the clinical target volume (CTV) for laryngeal and hypopharyngeal cancer in computed tomography (CT, 4.3 mm), magnetic resonance imaging (MR, 6.1 mm) and fluorodeoxyglucose (FDG)-positron emission tomography (PET, 5.2 mm). Previously, we used Hematoxylin-eosin (HE) stained whole-mount sections of total laryngectomy specimens as gold standard to define CTV margins. In the present study, we verified the HE-based tumor Delineation with staining for pan-cytokeratin, specific for squamous cell carcinoma. Methods: Twenty-seven patients with a T3/T4 laryngeal hypopharyngeal tumor were included. From each patient, a total laryngectomy specimen was obtained. Four subsequent 3-mm thick slices containing tumor were selected of which 4-µm thick whole-mount sections were obtained and stained with HE and for pan-cytokeratin CK-AE1/3. Tumors were microscopically delineated on both sections by an experienced head-and-neck pathologist. Tumor Delineations were compared using the conformity index (CI) and the distance between both contours. Results: The CI between HE-based and CK-AE1/3-based tumor Delineations was 0.87. The maximum and 95th percentile (p95) extent of the HE-based tumor Delineations from the CK-AE1/3-based tumor Delineations were 1.7 mm and 0.7 mm, respectively. The maximum and p95 extent of the CK-AE1/3-based tumor Delineations from the HE-based tumor Delineations was 1.9 mm and 0.8 mm, respectively. Conclusions: Histopathological assessment of tumor outline on standard HE-stained sections is comparable to microscopic tumor extent based on squamous cell specific pan-cytokeratin staining. Therefore, CTV margins based on HE based tumor contour will be adequate. Keywords: Head and neck, Squamous cell carcinoma, Histopathology, Pan-cytokeratin, Target definition, H
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validated guidelines for tumor Delineation on magnetic resonance imaging for laryngeal and hypopharyngeal cancer
Acta Oncologica, 2016Co-Authors: E A Jager, Frank A. Pameijer, Marielle E.p. Philippens, J Caldasmagalhaes, N Kasperts, Stefan M. Willems, T Schakel, H Ligtenberg, C Terhaard, Cornelis P J RaaijmakersAbstract:AbstractBackground: Validation of magnetic resonance imaging (MRI) and development of guidelines for the Delineation of the gross tumor volume (GTV) is of utmost importance to benefit from the visibility of anatomical details on MR images and to achieve an accurate GTV Delineation. In the ideal situation, the GTV Delineation corresponds to the histopathologically determined ‘true tumor volume’. Consequently, we developed guidelines for GTV Delineation of laryngeal and hypopharyngeal tumors on MRI and determined the accuracy of the resulting Delineation of the tumor outline on histopathology as gold standard.Material and methods: Twenty-seven patients with T3 or T4 laryngeal/hypopharyngeal cancer underwent a MRI scan before laryngectomy. Hematoxylin and eosin sections were obtained from surgical specimens and tumor was delineated by one pathologist. GTV was delineated on MR images by three independent observers in two sessions. The first session (del1) was performed according to clinical practice. In the s...
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inter observer agreement of mri based tumor Delineation for preoperative radiotherapy boost in locally advanced rectal cancer
Radiotherapy and Oncology, 2016Co-Authors: J P M Burbach, Marielle E.p. Philippens, J J E Kleijnen, O Reerink, E Seravalli, T Schakel, Bram Van Asselen, B W Raaymakers, Marco Van Vulpen, Martijn IntvenAbstract:Abstract Background While surgery remains the cornerstone of rectal cancer treatment, organ-preservation is upcoming. Therefore, neo-adjuvant treatment should be optimized. By escalating doses, response can be increased. To limit toxicity of boost, accurate gross tumor volume (GTV) definition is required. MRI, especially undeformed fast spin echo diffusion-weighted MRI (DWI), looks promising for Delineation. However, inconsistencies between observers should be quantified before clinical implementation. We aim to find which MRI sequence (T2w, DWI or combination) is optimal and clinically useful for GTV definition by evaluating inter-observer agreement. Methods Locally advanced rectal cancer patients (tumors b =800s/mm 2 ). Three independent observers delineated T2w, DWI and combination (Combi) after training-set. Volumes, conformity index (CI), and maximum Hausdorff distance (HD) were calculated between any observer-pair per patient per modality. Results Twenty-four consecutive patients were included. One patient had cT2 (4.2%), 19 cT3 (79.1%) and 4 cT4 (16.7%), with 2 clinical node negative (8.3%), 4 cN1 (16.7%), and 18 cN2 (75.0%) on MRI. From 24 patients, 70 sequences were available (24x T2, 23x DWI, and 23x Combi). Between observers, no significant volume differences were observed per modality. T2 showed significantly largest volumes compared to DWI (mean difference 19.85ml, SD 17.42, p p p >0.61). Average HD was largest on T2 (18.60mm, max 31.40mm, min 9.20mm). Discussion Delineation on DWI resulted in Delineation of the smallest volumes with similar consistency and mean distances, but with slightly lower Hausdorff distances compared to T2 and Combi. However, with lack of a gold standard it remains difficult to establish if Delineations also represent true tumor. Study strengths were DWI adaptation to exclude geometrical distortions and training-set. DWI shows great potential for Delineation purposes as long as sufficient experience exists and geometrical distortions are eliminated.
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pathologic validation of a model based on diffusion weighted imaging and dynamic contrast enhanced magnetic resonance imaging for tumor Delineation in the prostate peripheral zone
International Journal of Radiation Oncology Biology Physics, 2012Co-Authors: Greetje Groenendaal, Marielle E.p. Philippens, Alie Borren, Maaike R Moman, Evelyn M Monninkhof, Paul J Van Diest, Marco Van Vulpen, Uulke A Van Der HeideAbstract:Purpose For focal boost strategies in the prostate, the robustness of magnetic resonance imaging—based tumor Delineations needs to be improved. To this end we developed a statistical model that predicts tumor presence on a voxel level (2.5×2.5×2.5 mm3) inside the peripheral zone. Furthermore, we show how this model can be used to derive a valuable input for radiotherapy treatment planning. Methods and Materials The model was created on 87 radiotherapy patients. For the validation of the voxelwise performance of the model, an independent group of 12 prostatectomy patients was used. After model validation, the model was stratified to create three different risk levels for tumor presence: gross tumor volume (GTV), high-risk clinical target volume (CTV), and low-risk CTV. Results The model gave an area under the receiver operating characteristic curve of 0.70 for the prediction of tumor presence in the prostatectomy group. When the registration error between magnetic resonance images and pathologic Delineation was taken into account, the area under the curve further improved to 0.89. We propose that model outcome values with a high positive predictive value can be used to define the GTV. Model outcome values with a high negative predictive value can be used to define low-risk CTV regions. The intermediate outcome values can be used to define a high-risk CTV. Conclusions We developed a logistic regression with a high diagnostic performance for voxelwise prediction of tumor presence. The model output can be used to define different risk levels for tumor presence, which in turn could serve as an input for dose planning. In this way the robustness of tumor Delineations for focal boost therapy can be greatly improved.
R Steenbakkers - One of the best experts on this subject based on the ideXlab platform.
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decreased 3d observer variation with matched ct mri for target Delineation in nasopharynx cancer
Radiation Oncology, 2010Co-Authors: Coen R N Rasch, R Steenbakkers, Joop C Duppen, Avraham Eisbruch, Frank Paulsen, Frank A. Pameijer, Isabelle Fitton, Peter J C M Nowak, Johannes H A M Kaanders, Marcel Van HerkAbstract:Purpose: To determine the variation in target Delineation of nasopharyngeal carcinoma and the impact of measures to minimize this variation. Materials and methods: For ten nasopharyngeal cancer patients, ten observers each delineated the Clinical Target Volume (CTV) and the CTV elective. After 3D analysis of the delineated volumes, a second Delineation was performed. This implied improved Delineation instructions, a combined Delineation on CT and co-registered MRI, forced use of sagittal reconstructions, and an on-line anatomical atlas. Results: Both for the CTV and the CTV elective Delineations, the 3D SD decreased from Phase 1 to Phase 2, from 4.4 to 3.3 mm for the CTV and from 5.9 to 4.9 mm for the elective. There was an increase agreement, where the observers intended to delineate the same structure, from 36 to 64 surface % (p = 0.003) for the CTV and from 17 to 59% (p = 0.004) for the elective. The largest variations were at the caudal border of the Delineations but these were smaller when an observer utilized the sagittal window. Hence, the use of sagittal side windows was enforced in the second phase and resulted in a decreased standard deviation for this area from 7.7 to 3.3 mm (p = 0.001) for the CTV and 7.9 to 5.6 mm (p = 0.03) for the CTV elective. Discussion: Attempts to decrease the variation need to be tailored to the specific causes of the variation. Use of Delineation instructions multimodality imaging, the use of sagittal windows and an on-line atlas result in a higher agreement on the intended target.
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reduction of observer variation using matched ct pet for lung cancer Delineation a three dimensional analysis
International Journal of Radiation Oncology Biology Physics, 2006Co-Authors: R Steenbakkers, Kirsten E I Deurloo, A L J Uitterhoeve, Patrick T R Rodrigus, Gijsbert W P M Kramer, Lambert Zijp, Joop C Duppen, Isabelle Fitton, Emile F I Comans, Johan BussinkAbstract:PURPOSE: Target Delineation using only CT information introduces large geometric uncertainties in radiotherapy for lung cancer. Therefore, a reduction of the Delineation variability is needed. The impact of including a matched CT scan with 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) and adaptation of the Delineation protocol and software on target Delineation in lung cancer was evaluated in an extensive multi-institutional setting and compared with the Delineations using CT only. METHODS AND MATERIALS: The study was separated into two phases. For the first phase, 11 radiation oncologists (observers) delineated the gross tumor volume (GTV), including the pathologic lymph nodes of 22 lung cancer patients (Stages I-IIIB) on CT only. For the second phase (1 year later), the same radiation oncologists delineated the GTV of the same 22 patients on a matched CT-FDG-PET scan using an adapted Delineation protocol and software (according to the results of the first phase). All delineated volumes were analyzed in detail. The observer variation was computed in three dimensions by measuring the distance between the median GTV surface and each individual GTV. The variation in distance of all radiation oncologists was expressed as a standard deviation. The observer variation was evaluated for anatomic regions (lung, mediastinum, chest wall, atelectasis, and lymph nodes) and interpretation regions (agreement and disagreement; i.e., >80% vs. 0. For all anatomic regions, the interpretation differences among the radiation oncologists were reduced. The amount of disagreement was 45% and 18% for the first and second phase, respectively. Furthermore, the mean Delineation time (12 vs. 16 min, p<0.001) and mean number of corrections (25 vs. 39, p<0.001) were reduced in the second phase compared with the first phase. CONCLUSION: For high-precision radiotherapy, the Delineation of lung target volumes using only CT introduces too great a variability among radiation oncologists. Implementing matched CT-FDG-PET and adapted Delineation protocol and software reduced observer variation in lung cancer Delineation significantly with respect to CT only. However, the remaining observer variation was still large compared with other geometric uncertainties (setup variation and organ motion).
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observer variation in target volume Delineation of lung cancer related to radiation oncologist computer interaction a big brother evaluation
Radiotherapy and Oncology, 2005Co-Authors: R Steenbakkers, Kirsten E I Deurloo, A L J Uitterhoeve, Patrick T R Rodrigus, Gijsbert W P M Kramer, Lambert Zijp, Joop C Duppen, Isabelle Fitton, Johan Bussink, Katrien De JaegerAbstract:BACKGROUND AND PURPOSE: To evaluate the process of target volume Delineation in lung cancer for optimization of imaging, Delineation protocol and Delineation software. PATIENTS AND METHODS: Eleven radiation oncologists (observers) from five different institutions delineated the Gross Tumor Volume (GTV) including positive lymph nodes of 22 lung cancer patients (stages I-IIIB) on CT only. All radiation oncologist-computer interactions were recorded with a tool called 'Big Brother'. For each radiation oncologist and patient the following issues were analyzed: Delineation time, number of delineated points and corrections, zoom levels, level and window (L/W) settings, CT slice changes, use of side windows (coronal and sagittal) and software button use. RESULTS: The mean Delineation time per GTV was 16 min (SD 10 min). The mean Delineation time for lymph node positive patients was on average 3 min larger (P = 0.02) than for lymph node negative patients. Many corrections (55%) were due to L/W change (e.g. delineating in mediastinum L/W and then correcting in lung L/W). For the lymph node region, a relatively large number of corrections was found (3.7 corr/cm2), indicating that it was difficult to delineate lymph nodes. For the tumor-atelectasis region, a relative small number of corrections was found (1.0 corr/cm2), indicating that including or excluding atelectasis into the GTV was a clinical decision. Inappropriate use of L/W settings was frequently found (e.g. 46% of all delineated points in the tumor-lung region were delineated in mediastinum L/W settings). Despite a large observer variation in cranial and caudal direction of 0.72 cm (1 SD), the coronal and sagittal side windows were not used in 45 and 60% of the cases, respectively. For the more difficult cases, observer variation was smaller when the coronal and sagittal side windows were used. CONCLUSIONS: With the 'Big Brother' tool a method was developed to trace the Delineation process. The differences between observers concerning the Delineation style were large. This study led to recommendations on how to improve Delineation accuracy by adapting the Delineation protocol (guidelines for L/W use) and Delineation software (double window with lung and mediastinum L/W settings at the same time, enforced use of coronal and sagittal views) and including FDG-PET information (lymph nodes and atelectasis).
K Verhoeven - One of the best experts on this subject based on the ideXlab platform.
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vessel based Delineation guidelines for the elective lymph node regions in breast cancer radiation therapy procab guidelines
Radiotherapy and Oncology, 2015Co-Authors: K Verhoeven, Caroline Weltens, V Remouchamps, K Mahjoubi, Liv Veldeman, Benoit Lengele, E Hortobagyi, Carine KirkoveAbstract:Objective A national project to improve the quality of breast radiation therapy was started, named PROCAB (PROject on CAncer of the Breast). One of the objectives was to reach a national consensus guideline for the Delineation of the regional lymph node areas in breast radiation therapy. Methods The realization of the new guidelines was a step by step process that started with multiple expert meetings where the existing guidelines were analyzed and the Delineations of the lymph node regions were performed together with a surgeon, specialized in the anatomy of the drainage of the breast. Results The Delineation guidelines are vessel-based. Since the occurrence of pathological lymph nodes is typically around the veins, the cranial and caudal borders of all different nodal regions are based on a 5 mm margin around the veins, except for the parasternal lymph node area. Compared to the existing guidelines there are some major changes. Conclusion With this project a national as well as a European (ESTRO) consensus guideline for the Delineation of the regional lymph node areas in breast RT is reached. The new Delineation atlas is vessel-based and no longer field-based.
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estro consensus guideline on target volume Delineation for elective radiation therapy of early stage breast cancer
Radiotherapy and Oncology, 2015Co-Authors: Birgitte Vrou Offersen, V Remouchamps, Carine Kirkove, L Boersma, Youlia M Kirova, S Hol, M C Aznar, Albert Biete Sola, Jeanphilippe Pignol, K VerhoevenAbstract:Background and purpose Delineation of clinical target volumes (CTVs) is a weak link in radiation therapy (RT), and large inter-observer variation is seen in breast cancer patients. Several guidelines have been proposed, but most result in larger CTVs than based on conventional simulator-based RT. The aim was to develop a Delineation guideline obtained by consensus between a broad European group of radiation oncologists. Material and methods During ESTRO teaching courses on breast cancer, teachers sought consensus on Delineation of CTV through dialogue based on cases. One teacher delineated CTV on CT scans of 2 patients, followed by discussion and adaptation of the Delineation. The consensus established between teachers was sent to other teams working in the same field, both locally and on a national level, for their input. This was followed by developing a broad consensus based on discussions. Results Borders of the CTV encompassing a 5 mm margin around the large veins, running through the regional lymph node levels were agreed, and for the breast/thoracic wall other vessels were pointed out to guide Delineation, with comments on margins for patients with advanced breast cancer. Conclusion The ESTRO consensus on CTV for elective RT of breast cancer, endorsed by a broad base of the radiation oncology community, is presented to improve consistency.
