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  • Germany  (10)
  • IMRT  (6)
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  • 1
    Keywords: IRRADIATION ; radiotherapy ; Germany ; LUNG ; THERAPY ; ALGORITHM ; CT ; imaging ; INFORMATION ; SYSTEM ; SYSTEMS ; EXPOSURE ; TISSUE ; computed tomography ; validation ; NUCLEAR-MEDICINE ; TIME ; PATIENT ; COMPLEX ; MARKER ; SIGNAL ; PERFORMANCE ; MARKERS ; REGION ; REGISTRATION ; LOCALIZATION ; COMPUTED-TOMOGRAPHY ; MOTION ; nuclear medicine ; GATED RADIOTHERAPY ; IMRT ; ORDER ; radiology ; RE ; THERAPIES ; breathing cycle ; methods ; NUCLEAR ; technique ; MUTUAL INFORMATION ; RESPIRATORY MOTION ; phantom ; ENGLAND ; PREDICT ; MAXIMIZATION ; tumor motion ; MEDICINE ; X-RAY ; particle therapy ; LIMITS ; POSITION ; CONE-BEAM CT ; LUNG-TUMORS
    Abstract: Respiratory motion limits the potential of modern high-precision radiotherapy techniques such as IMRT and particle therapy. Due to the uncertainty of tumour localization, the ability of achieving dose conformation often cannot be exploited sufficiently, especially in the case of lung tumours. Various methods have been proposed to track the position of tumours using external signals, e. g. with the help of a respiratory belt or by observing external markers. Retrospectively gated time-resolved x-ray computed tomography (4D CT) studies prior to therapy can be used to register the external signals with the tumour motion. However, during treatment the actual motion of internal structures may be different. Direct control of tissue motion by online imaging during treatment promises more precise information. On the other hand, it is more complex, since a larger amount of data must be processed in order to determine the motion. Three major questions arise from this issue. Firstly, can the motion that has occurred be precisely determined in the images? Secondly, how large must, respectively how small can, the observed region be chosen to get a reliable signal? Finally, is it possible to predict the proximate tumour location within sufficiently short acquisition times to make this information available for gating irradiation? Based on multiple studies on a porcine lung phantom, we have tried to examine these questions carefully. We found a basic characteristic of the breathing cycle in images using the image similarity method normalized mutual information. Moreover, we examined the performance of the calculations and proposed an image-based gating technique. In this paper, we present the results and validation performed with a real patient data set. This allows for the conclusion that it is possible to build up a gating system based on image data, solely, or ( at least in avoidance of an exceeding exposure dose) to verify gates proposed by the various external systems
    Type of Publication: Journal article published
    PubMed ID: 18495978
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  • 2
    Keywords: CT ; REGISTRATION ; INTENSITY-MODULATED RADIOTHERAPY ; FAILURE ; IMRT ; head and neck cancer ; DELINEATION ; IGRT ; QUANTITATIVE PERTECHNETATE SCINTIGRAPHY ; SALIVARY-GLAND FUNCTION ; Adaptive RT ; STAGE NASOPHARYNGEAL CARCINOMA ; TARGET VOLUME
    Abstract: PURPOSE: To present an approach to fast, interfractional adaptive RT in intensity-modulated radiation therapy (IMRT) of head and neck tumors in clinical routine. Ensuring adequate patient position throughout treatment proves challenging in high-precision RT despite elaborate immobilization. Because of weight loss, treatment plans must be adapted to account for requiring supportive therapy incl. feeding tube or parenteral nutrition without treatment breaks. METHODS AND MATERIALS: In-room CT position checks are used to create adapted IMRT treatment plans by stereotactic correlation to the initial setup, and volumes are adapted to the new geometry. New IMRT treatment plans are prospectively created on the basis of position control scans using the initial optimization parameters in KonRad without requiring complete reoptimization and thus facilitating quick replanning in daily routine. Patients treated for squamous cell head and neck cancer (SCCHN) in 2006-2007 were evaluated as to necessity/number of replannings, weight loss, dose, and plan parameters. RESULTS: Seventy-two patients with SCCHN received IMRT to the primary site and lymph nodes (median dose 70.4 Gy). All patients received concomitant chemotherapy requiring supportive therapy by feeding tube or parenteral nutrition. Median weight loss was 7.8 kg, median volume loss was approximately 7%. Fifteen of 72 patients required adaptation of their treatment plans at least once. Target coverage was improved by up to 10.7% (median dose). The increase of dose to spared parotid without replanning was 11.7%. Replanning including outlining and optimization was feasible within 2 hours for each patient, and treatment could be continued without any interruptions. CONCLUSION: To preserve high-quality dose application, treatment plans must be adapted to anatomical changes. Replanning based on position control scans therefore presents a practical approach in clinical routine. In the absence of clinically usable online correction methods, this approach allows significant improvement of target volume coverage and continuous parotid sparing without treatment delays.
    Type of Publication: Journal article published
    PubMed ID: 21310549
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  • 3
    Keywords: radiotherapy ; COMBINATION ; Germany ; MODEL ; MODELS ; PROSTATE ; THERAPY ; CT ; IMAGES ; imaging ; INFORMATION ; meningioma ; radiation ; PATIENT ; tumour ; MRI ; treatment ; EXPERIENCE ; RADIATION-THERAPY ; PROSTATE-CANCER ; US ; SAFETY ; treatment planning ; PET ; nuclear medicine ; dynamic MRI ; GLIOMAS ; MAPS ; INTEGRATION ; STANDARD ; SOFTWARE ; radiation therapy ; BREAST-TUMORS ; MRSI ; MUTUAL INFORMATION ; parameter map
    Abstract: Planning of radiotherapy is often difficult due to restrictions on morphological images. New imaging techniques enable the integration of biological information into treatment planning and help to improve the detection of vital and aggressive tumour areas. This might improve clinical outcome. However, nowadays morphological data sets are still the gold standard in the planning of radiotherapy. In this paper, we introduce an in-house software platform enabling us to combine images from different imaging modalities yielding biological and morphological information in a workflow driven approach. This is demonstrated for the combination of morphological CT, MRI, functional DCE-MRI and PET data. Data of patients with a tumour of the prostate and with a meningioma were examined with DCE-MRI by applying pharmacokinetic two-compartment models for post-processing. The results were compared with the clinical plans for radiation therapy. Generated parameter maps give additional information about tumour spread, which can be incorporated in the definition of safety margins
    Type of Publication: Journal article published
    PubMed ID: 16177540
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  • 4
    Keywords: CANCER ; radiotherapy ; tumor ; COMBINATION ; Germany ; LUNG ; PROSTATE ; ALGORITHM ; CT ; imaging ; INFORMATION ; lung cancer ; LUNG-CANCER ; MASK ; TISSUE ; TIME ; PATIENT ; COMPLEX ; COMPLEXES ; CONTRAST ; treatment ; TARGET ; ACQUISITION ; EXPERIENCE ; VECTOR ; NUMBER ; prostate cancer ; PROSTATE-CANCER ; REGISTRATION ; BEAM ; DELIVERY ; HEAD ; CANCER-PATIENTS ; MULTILEAF COLLIMATOR ; treatment planning ; BODY ; CANCER PATIENTS ; LINEAR-ACCELERATOR ; RECONSTRUCTION ; IMRT ; PATIENT FIXATION ; IMPLEMENTATION ; INCREASE ; chordoma ; LEVEL ; methods ; fractionated stereotactic radiotherapy ; technique ; MUTUAL INFORMATION ; cancer research ; cone beam CT ; LANDMARK ; INCREASES ; CLINICAL IMPLEMENTATION ; ACCELERATOR ; WORKLOAD
    Abstract: ABSTRACT: BACKGROUND: The purpose of the study was the clinical implementation of a kV cone beam CT (CBCT) for setup correction in radiotherapy. PATIENTS AND METHODS: For evaluation of the setup correction workflow, six tumor patients (lung cancer, sacral chordoma, head-and-neck and paraspinal tumor, and two prostate cancer patients) were selected. All patients were treated with fractionated stereotactic radiotherapy, five of them with intensity modulated radiotherapy (IMRT). For patient fixation, a scotch cast body frame or a vacuum pillow, each in combination with a scotch cast head mask, were used. The imaging equipment, consisting of an x-ray tube and a flat panel imager (FPI), was attached to a Siemens linear accelerator according to the in-line approach, i.e. with the imaging beam mounted opposite to the treatment beam sharing the same isocenter. For dose delivery, the treatment beam has to traverse the FPI which is mounted in the accessory tray below the multi-leaf collimator. For each patient, a predefined number of imaging projections over a range of at least 200 degrees were acquired. The fast reconstruction of the 3D-CBCT dataset was done with an implementation of the Feldkamp-David-Kress (FDK) algorithm. For the registration of the treatment planning CT with the acquired CBCT, an automatic mutual information matcher and manual matching was used. RESULTS AND DISCUSSION: Bony landmarks were easily detected and the table shifts for correction of setup deviations could be automatically calculated in all cases. The image quality was sufficient for a visual comparison of the desired target point with the isocenter visible on the CBCT. Soft tissue contrast was problematic for the prostate of an obese patient, but good in the lung tumor case. The detected maximum setup deviation was 3 mm for patients fixated with the body frame, and 6 mm for patients positioned in the vacuum pillow. Using an action level of 2 mm translational error, a target point correction was carried out in 4 cases. The additional workload of the described workflow compared to a normal treatment fraction led to an extra time of about 10-12 minutes, which can be further reduced by streamlining the different steps. CONCLUSION: The cone beam CT attached to a LINAC allows the acquisition of a CT scan of the patient in treatment position directly before treatment. Its image quality is sufficient for determining target point correction vectors. With the presented workflow, a target point correction within a clinically reasonable time frame is possible. This increases the treatment precision, and potentially the complex patient fixation techniques will become dispensable
    Type of Publication: Journal article published
    PubMed ID: 16723023
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  • 5
    Keywords: IRRADIATION ; radiotherapy ; tumor ; Germany ; THERAPY ; TOXICITY ; CT ; imaging ; INFORMATION ; SYSTEM ; TOOL ; VOLUME ; RISK ; TUMORS ; PATIENT ; MARKER ; REDUCTION ; CONTRAST ; MR ; MRI ; treatment ; TRIAL ; RADIATION-THERAPY ; STEREOTACTIC RADIOSURGERY ; MELANOMA ; SAFETY ; treatment planning ; RECONSTRUCTION ; ultrasound ; proton therapy ; INTEGRATION ; uveal melanoma ; SIZE ; GAMMA-KNIFE ; GEOMETRY ; EYE ; BEAM RADIOTHERAPY ; BRACHYTHERAPY ; CHOROIDAL MELANOMA ; EYEPLAN ; INTRAOCULAR TUMORS ; OCTOPUS ; SURFACE COIL
    Abstract: Background and Purpose: Proton therapy for uveal melanoma provides high-conformal dose application to the target volume and, thus, an optimal saving of the organs at risk nearby. Treatment planning is done with the model-based treatment-planning system EYEPLAN. Tumor reconstruction is based only on a fundus composite, which often leads to an overestimation of the clinical target volume (CTV). The purpose was to exploit MRI on trial in a proton therapy-planning system by using the novel image-based treatment-planning system OCTOPUS. Patients and Methods: Ten patients with uveal melanomas received both a high-resolution planning CT and MRI of the eye. MR examinations were made with an eye coil. EYEPLAN requires eye geometry data for modeling, and tantalum marker clips for submillimeter positioning and additional information from ultrasound and 3-D imaging. By contrast, OCTOPUS provides the full integration of 3-D imaging (e.g., CT, MRI). CTVs were delineated in each slice. For all patients, CTVs (EYEPLAN vs. OCTOPUS) were compared intraindividually. Results: OCTOPUS planning led to a mean reduction of the target volume by a factor of 1.7 (T1-weighted [T1w]) and 2.2 (T2w) without compromising safety. The corresponding field size could be scaled down on average by a factor of 1.2 (T1w) and 1.4 (T2w), respectively. Conclusion: Compared with the conventional EYEPLAN, MRI-based treatment planning of ocular tumors with OCTOPUS could be a powerful tool for reducing the CTV and, consequently, the treatment volume and the field size. This might be translated into a better patient compliance during treatment and a decreased late toxicity
    Type of Publication: Journal article published
    PubMed ID: 16826358
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  • 6
    Keywords: ONCOLOGY ; radiology ; IMRT ; nuclear medicine ; imaging ; SYSTEM ; NEW-YORK ; NUCLEAR-MEDICINE ; PROSTATE ; interactive ; MEDICINE ; USA ; NUCLEAR
    Type of Publication: Meeting abstract published
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  • 7
    Keywords: MEDICINE ; NUCLEAR ; SCANNER ; radiology ; ONCOLOGY ; nuclear medicine ; TUMORS ; NUCLEAR-MEDICINE ; PATIENT ; tumor ; imaging ; CT ; Germany ; evaluation
    Type of Publication: Meeting abstract published
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  • 8
    Keywords: NUCLEAR ; MEDICINE ; GUIDED RADIOTHERAPY ; radiotherapy ; tumor ; Germany ; imaging ; PATIENT ; NUCLEAR-MEDICINE ; ONCOLOGY ; radiology ; nuclear medicine
    Type of Publication: Meeting abstract published
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  • 9
    Keywords: radiotherapy ; Germany ; THERAPY ; ALGORITHM ; CT ; IMAGES ; imaging ; SYSTEM ; SYSTEMS ; ACCURACY ; SIMULATION ; MRI ; MAGNETIC-RESONANCE ; magnetic resonance imaging ; REGION ; Jun ; HEAD ; COMPUTED-TOMOGRAPHY ; SPATIAL DISTORTION ; DEVICES ; 2D ; RE ; SIZE ; MR-IMAGES
    Abstract: For the application of magnetic resonance imaging (MRI) in precision radiotherapy, image distortions must be reduced to a minimum to maintain geometrical accuracy. Recently, two-dimensional (2D) and three-dimensional (3D) algorithms for MRI-device-specific distortion corrections were developed by the manufacturers of MRI devices. A previously developed phantom (Karger C P et al 2003 Phys. Med. Biol. 48 211 - 21) was used to quantify and assess the size of geometrical image distortions before and after application of the 2D and 3D correction algorithm in the head region. Four different types of MRI devices with different gradient systems were measured. For comparison, measurements were also performed with two computed tomography (CT) devices. Mean distortions of up to 4.6 +/- 1.4 mm (maximum: 5.8 mm) were found prior to the correction. After the correction, the mean distortions were well below 2.0 mm in most cases. Distortions in the CT images were below or equal to 1.0 mm on average. Generally, the 3D algorithm produced comparable or better results than the 2D algorithm. The remaining distortions after the correction appear to be acceptable for fractionated radiotherapy
    Type of Publication: Journal article published
    PubMed ID: 16757858
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  • 10
    Keywords: radiotherapy ; Germany ; THERAPY ; ALGORITHM ; CT ; DIAGNOSIS ; IMAGES ; TOOL ; RISK ; RESOLUTION ; validation ; radiation ; TIME ; PATIENT ; IMPACT ; DOMAIN ; treatment ; FREQUENCY ; FREQUENCIES ; RADIATION-THERAPY ; REGISTRATION ; treatment planning ; THIN-PLATE SPLINES ; rectum ; DEFORMATIONS ; elastic registration ; correlation ; MUTUAL INFORMATION ; NONRIGID REGISTRATION ; SET ; COEFFICIENTS ; LANDMARK ; elastic image registration ; adaptive radiotherapy ; BRAIN SHIFT ; CORRELATION-COEFFICIENT ; DEFORMABLE IMAGE REGISTRATION ; MAXIMIZATION
    Abstract: Image registration has many medical applications in diagnosis, therapy planning and therapy. Especially for time-adaptive radiotherapy, an efficient and accurate elastic registration of images acquired for treatment planning, and at the time of the actual treatment, is highly desirable. Therefore, we developed a fully automatic and fast block matching algorithm which identifies a set of anatomical landmarks in a 3D CT dataset and relocates them in another CT dataset by maximization of local correlation coefficients in the frequency domain. To transform the complete dataset, a smooth interpolation between the landmarks is calculated by modified thin-plate splines with local impact. The concept of the algorithm allows separate processing of image discontinuities like temporally changing air cavities in the intestinal track or rectum. The result is a fully transformed 3D planning dataset (planning CT as well as delineations of tumour and organs at risk) to a verification CT, allowing evaluation and, if necessary, changes of the treatment plan based on the current patient anatomy without time-consuming manual re-contouring. Typically the total calculation time is less than 5min, which allows the use of the registration tool between acquiring the verification images and delivering the dose fraction for online corrections. We present verifications of the algorithm for five different patient datasets with different tumour locations ( prostate, paraspinal and head-and-neck) by comparing the results with manually selected landmarks, visual assessment and consistency testing. It turns out that the mean error of the registration is better than the voxel resolution (2 x 2 x 3 mm(3)). In conclusion, we present an algorithm for fully automatic elastic image registration that is precise and fast enough for online corrections in an adaptive fractionated radiation treatment course
    Type of Publication: Journal article published
    PubMed ID: 16985271
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