- Email: [email protected]
CT-based virtual simulation for external beam radiation therapy
International Congress Series 1230 (2001) 492 – 499
CT-based virtual simulation for external beam radiation therapy G. Karangelisa,*, N. Zambogloub a
Medical Imaging and Cognitive Computing, Fraunhofer Institute-IGD, Rundeturmstrasse 12, 64283 Darmstadt, Germany b Strahlenklinik, Klinikum Offenbach, Offenbach, Germany
Abstract Radiotherapy treatment simulation is an essential part of the cancer treatment using external beam radiotherapy. For several years, the responsible device to perform this process was the simulator, a medical device with the same geometry and capable to perform the same movements with the treatment machine (Linear Accelerator or LINAC). Simulator differs from the LINAC to the low energy it uses, diagnostic X-rays, instead of high-energy treatment rays. Unlikely for a clinic to obtain a real Simulator is a high investment in terms of money, space and personnel. The alternative here can be a Virtual Simulator (VS) or CT-Simulator. CT-Simulators are software that use the patient’s digital data, mainly coming from computed tomography (CT) scanner, instead of the real patient to perform the simulation process. D 2001 Elsevier Science B.V. All rights reserved. Keywords: Radiation therapy; CT simulation; Conformal therapy
1. Introduction A very common technique used in oncology clinics for treating patients with cancer is the external beam radiotherapy. An important step in this process is the simulation of the treatment. The simulation is performed on a medical device called Simulator, which has exactly the same geometry and can perform the same movements with the treatment machine (Linear Accelerator or LINAC), but uses low energy, diagnostic X-rays, instead of high-energy treatment rays. The real Simulator can provide only 2D fluoroscopy
*
Corresponding author. Tel.: +49-6151-155-522. E-mail address: [email protected] (G. Karangelis).
0531-5131/01/$ – see front matter D 2001 Elsevier Science B.V. All rights reserved. PII: S 0 5 3 1 - 5 1 3 1 ( 0 1 ) 0 0 0 6 4 - 4
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
493
images, for verification and documentation purposes. Unlikely for a clinic to obtain a real Simulator is a high investment in terms of money, space and personnel. The alternative here can be a Virtual Simulator (VS) or CT-Simulator. CT-Simulators belong to the most significant technological advances in radiation oncology in the past 20 years. Sherouse [1] first proposed the concept, often called CT-Sim, to distinguish it from Sim-CT, where a simulator is modified for CT use; by late 1990s, several designs and clinical assessments of CT virtual simulators have been reported [1 –6]. In general, CT-Simulators are software that use the patient’s digital data, mainly coming from computed tomography scanner, instead of the real patient to perform the simulation process. The advantages of CT-based virtual simulation are well known and include the fact that target volumes, critical organs and structures can be effectively defined and displayed in multiple image planes (axial, coronal, sagittal or oblique). In CTSimulators, it is possible to display more information on the same screen. These are usually the beam’s eye-view (BEV), where the Digital Reconstructed Radiograph (DRR) is visualised, the room’s eye-view (REV), which includes a model of the simulation or treatment machine and the observer’s eye-view (OEV), where the surface of the patient is displayed. To protect healthy structures, one can draw manual blocks on the BEV or use the automatic multileaf collimator (MLC) adaptation techniques. Furthermore, in virtual simulation, one can examine larger parts of the patient’s volume than on the conventional simulator, especially on the DRR due to the larger field of view of the CT slices. Current developed systems suffer from several drawbacks, like the requirement of expensive and dedicated hardware platform, the low speed and user interaction performance, the lack of compatibility and communication with various peripheral devices in the clinical environment, such as CT scanners and treatment planning systems (TPS). In this work, we have developed graphical simulation and volume visualization techniques to compose a new high-performance CT-based virtual simulation system, which runs on any low cost widely available PC hardware.
2. Implementation Our CT-Simulator, EXOMIO, can run on any low-cost PC system under Windows NT or Windows2000 operating system. The main part of the software is a 3D visualization system of medical volume data that has been developed over several years in FraunhoferIGD [7]. Due to the system design, no special graphic card is needed and unlimited amount of volume data, in our case, CT, can be imported into the system. This is an important issue since CT-Simulators must be able to handle large data sets, from 40 up to 150 slices, in order to produce high-quality rendering mages. The data used in this work have been acquired with a Siemens Somatom Plus-4 CT scanner, but the system can connect via network directly to any CT scanner that support DICOM-3 communication protocol. EXOMIO can display the imported volume data as original 2D CT scans, as orthogonal or oblique reconstructed planes. The implemented 3D-reconstruction pipeline uses perspective projection to reconstruct the BEV image and parallel projection for the OEV. Both views support transparent reconstruction modes like maximum intensity
494
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
Fig. 1. The EXOMIO user interfaces.
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
495
projection (MIP) [8] and X-ray [9] and surface reconstruction mode using iso-value, gradient [10] and semitransparent shading (see Fig. 1(a) and (b)).
Fig. 2. Protecting normal structures using manual blocks and MLC.
496
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
Using EXOMIO, the simulation process is performed with the following working steps. Collect patient’s CT data including the attached on the patient’s skin aluminum markers. Transfer CT data to CT-Simulator. The physician must detect the slice location with the aluminum markers and define the reference point for the specific plan. This step guaranties the reproduction of the correct patient position through the treatment process. Then, the physician defines the tumor volume and the organs at risk. Afterwards, she/he will place the necessary fields so as to cover the tumor volume (see Fig. 2). The simulation plan is transferred via DICOM server to the TPS for dose calculation and final treatment plan optimization. Verify patient position using portal imaging, on the LINAC before irradiation. Perform treatment on the treatment machine (Linear Accelerator or LINAC). The above working steps can vary among clinics or among treatment cases. In any case, the concept is that a CT-Simulator must be compatible with several devices and applications in an oncology clinic. EXOMIO provides the following communication capabilities for data exchange:
Communication with the CT scanner for the acquisition of the CT volume data. This is fulfilled using DICOM-3 server. Connectivity to TPSs via DICOM server for the exchange of the simulation plan, organ structures and dose volume. Use of the internal Ethernet network to export the DRR images in DICOM or standard image formats like BMP, to the portal-imaging device. This connectivity is essential for the patient position verification during treatment. Transfer of the block shape for each field to the block-cutting machine through the internal Ethernet network. EXOMIO can export the coordinates of the projected field edges on the patient’s skin, to the laser skin-marking device for external field verification. In this case, we make again use of the internal Ethernet network.
3. Results 3.1. System accuracy On the real Simulator, system inaccuracies are coming mainly from the mechanical components. Baltas et al. [11] on a report about quality assurance of the real Simulators found that for different simulator components, the following errors might occur:
Table movements might have an error up to ± 2mm. Irradiation field size and light field at the level of iso-center might have an error up to ± 3.0 mm. Iso-center sphere size for static angle rotation of gantry, collimator or table might have an error up to ± 2.5 mm.
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
497
On the other hand, the VS system accuracy and the rendering image quality dependents on the CT data resolution especially in the longitudinal (Z-axis) direction, where the slice thickness can vary from 1 to 10 mm. In most of our cases, we use equidistant slices with thickness between 3 and 5 mm and the total number of slices according to the patient case were between 40 and 120 slices. A cubic phantom of size 120 120 mm was initially used to exam the accuracy of EXOMIO. Inside the phantom spheres of diameter 2 mm are placed in constant distance. The phantom was scanned using 1-mm slice thickness. The total number of produced slices was 120, in square CT matrices of 512 512 pixels. The recorded system error concerning the table translation is at ± 1 mm. The beam size and the projected light field size matched completely. No iso-center sphere effect occurred during component rotation. The interactive landmark registration routine might have the error of the slice thickness. The algorithms automatic SSD settings, the automatic translation of the beam iso-center to the PTV’s center of gravity has an error of voxel size. The accuracy of the routines automatic field and block adaptation on the PTV is related to the resolution of the BEV image. In most cases, the BEV image has the size of 256 256 up to 400 400. The higher the image resolution, the smaller the error of these routines. In this case, we give a tolerance of ± 2 mm. 3.2. Clinical trials The system is installed in the clinic of Offenbach since September 2000. So far, more than 300 patients have gone through virtual and real simulation, so as to compare the two systems. For 80 patient cases, we performed time measurements on the real Simulator and on EXOMIO. Table 1 illustrates that average simulation time for the 80 patients is 31 min. The clinical persons involved in the process are the medical – technical assistance (MTA) and the physician. It is interesting to notice that the physician spends most of his/her time on documenting the patient case. Table 2 illustrates the average time when performing the CT-simulation using EXOMIO. In this case, the simulation time is the half of the time needed with the real simulator. The patient is
Table 1 Average time needed to perform simulation with the real simulator Person
Process
Mean time (min)
Patient MTA
Simulation Positioning Fluoroscopy Develop X-ray Patient marking
31 2.9 5.0 4.1 3.8 15.8
Documentation Fluoroscopy
15.5 5.0 20.5
Total time Physician Total time
498
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
Table 2 Average time needed to perform simulation with EXOMIO Person
Process
Mean time (min)
Patient Physician
CT scan Structure definition Field placement Documentation
12.8 6.5 3.0 3.0 12.5
Total time
involved only during the CT data acquisition and the physician spends the whole time on preparing the patient’s plan.
4. Discussion In this work, we introduce a CT-based virtual simulation system that involves highend visualization techniques and provides flexibility in communication with other systems and devices in the clinical environment. The system serves to optimize and accelerate the external beam simulation process. Main advantages of the VS against the real Simulator are:
The absence of the patient thought the simulation process since their electronic data are used for the simulation. CT-Simulation avoids the often experienced bottlenecks in patient workload flow within a department of radiation oncology. Reduced time needed to prepare the simulation plan about 50%. Reduced effort and personnel. Low investment in money and space for the clinic department. Low maintenance costs.
Furthermore, a CT-Simulator provides 3D imaging tools, including the entire patient anatomy. These features are not supported from any real Simulator. In addition, it provides higher accuracy on beam configuration and block contour drawing (see Fig. 2). The only significant advantage of the classical simulator is the ability to use fluoroscopy in order to assess the movement of tumor and organs in relation to the field geometry. This advantage still has to be overcome with CT-Simulation.
References [1] G. Sherouse, C. Mosher, K. Novins, J. Rosemann, E.L. Chaney, Virtual simulation: concept and implementation, Proceedings of 9th International Conference of the Use of Computers in Radiation Therapy (ICCR), North-Holland, Scheveningen, The Netherlands, 1987, pp. 433 – 436. [2] J. Rosenman, S. Sailer, G. Sherouse, E.L. Chaney, J.E. Tepper, Virtual simulation: initial clinical results, Int. J. Radiat. Oncol., Biol. Phys. 20 (1991) 843 – 851. [3] G. Sherouse, E.L. Chaney, The portable virtual simulator, Int. J. Radiat. Oncol., Biol. Phys. 21 (1991) 475 – 482.
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
499
[4] J.M. Michalski, J.A. Purdy, W. Harms, J.W. Matthews, The CT-simulation 3D treatment planning process, Front. Radiat. Ther. Oncol. 29 (1996) 43 – 56. [5] J.A. Purdy, 3D radiation treatment planning: a new era, Front Radiat. Ther. Oncol. 29 (1996) 1 – 16. [6] J. Conway, M.H. Robinson, CT virtual simulation, Br. J. Radiol. 70 (1997) 106 – 118. [7] G. Sakas, Interactive volume rendering of large fields, Visual Computer 9 (8) (1993) 425 – 438. [8] G. Sakas, M. Grimm, A. Savopoulos, Optimised maximum intensity projection (MIP), Rendering Techniques ’95, Springer, 1995, pp. 51 – 63. [9] W. Cai, Transfer functions in DRR volume rendering, CARS ’99, Paris, France, June 23 – 26, 1999. [10] M. Levoy, Display of surface from volume data, IEEE CG&A 8 (5) (1988). [11] D. Baltas, K. Mueller-Sievers, B. Kober, Preliminary results of a intercomparison of quality control referring to therapy simulators, ESTRO, Second Biennial Meeting on Physics in Clinical Radiotherapy, Prague, 1993.
CT-based virtual simulation for external beam radiation therapy G. Karangelisa,*, N. Zambogloub a
Medical Imaging and Cognitive Computing, Fraunhofer Institute-IGD, Rundeturmstrasse 12, 64283 Darmstadt, Germany b Strahlenklinik, Klinikum Offenbach, Offenbach, Germany
Abstract Radiotherapy treatment simulation is an essential part of the cancer treatment using external beam radiotherapy. For several years, the responsible device to perform this process was the simulator, a medical device with the same geometry and capable to perform the same movements with the treatment machine (Linear Accelerator or LINAC). Simulator differs from the LINAC to the low energy it uses, diagnostic X-rays, instead of high-energy treatment rays. Unlikely for a clinic to obtain a real Simulator is a high investment in terms of money, space and personnel. The alternative here can be a Virtual Simulator (VS) or CT-Simulator. CT-Simulators are software that use the patient’s digital data, mainly coming from computed tomography (CT) scanner, instead of the real patient to perform the simulation process. D 2001 Elsevier Science B.V. All rights reserved. Keywords: Radiation therapy; CT simulation; Conformal therapy
1. Introduction A very common technique used in oncology clinics for treating patients with cancer is the external beam radiotherapy. An important step in this process is the simulation of the treatment. The simulation is performed on a medical device called Simulator, which has exactly the same geometry and can perform the same movements with the treatment machine (Linear Accelerator or LINAC), but uses low energy, diagnostic X-rays, instead of high-energy treatment rays. The real Simulator can provide only 2D fluoroscopy
*
Corresponding author. Tel.: +49-6151-155-522. E-mail address: [email protected] (G. Karangelis).
0531-5131/01/$ – see front matter D 2001 Elsevier Science B.V. All rights reserved. PII: S 0 5 3 1 - 5 1 3 1 ( 0 1 ) 0 0 0 6 4 - 4
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
493
images, for verification and documentation purposes. Unlikely for a clinic to obtain a real Simulator is a high investment in terms of money, space and personnel. The alternative here can be a Virtual Simulator (VS) or CT-Simulator. CT-Simulators belong to the most significant technological advances in radiation oncology in the past 20 years. Sherouse [1] first proposed the concept, often called CT-Sim, to distinguish it from Sim-CT, where a simulator is modified for CT use; by late 1990s, several designs and clinical assessments of CT virtual simulators have been reported [1 –6]. In general, CT-Simulators are software that use the patient’s digital data, mainly coming from computed tomography scanner, instead of the real patient to perform the simulation process. The advantages of CT-based virtual simulation are well known and include the fact that target volumes, critical organs and structures can be effectively defined and displayed in multiple image planes (axial, coronal, sagittal or oblique). In CTSimulators, it is possible to display more information on the same screen. These are usually the beam’s eye-view (BEV), where the Digital Reconstructed Radiograph (DRR) is visualised, the room’s eye-view (REV), which includes a model of the simulation or treatment machine and the observer’s eye-view (OEV), where the surface of the patient is displayed. To protect healthy structures, one can draw manual blocks on the BEV or use the automatic multileaf collimator (MLC) adaptation techniques. Furthermore, in virtual simulation, one can examine larger parts of the patient’s volume than on the conventional simulator, especially on the DRR due to the larger field of view of the CT slices. Current developed systems suffer from several drawbacks, like the requirement of expensive and dedicated hardware platform, the low speed and user interaction performance, the lack of compatibility and communication with various peripheral devices in the clinical environment, such as CT scanners and treatment planning systems (TPS). In this work, we have developed graphical simulation and volume visualization techniques to compose a new high-performance CT-based virtual simulation system, which runs on any low cost widely available PC hardware.
2. Implementation Our CT-Simulator, EXOMIO, can run on any low-cost PC system under Windows NT or Windows2000 operating system. The main part of the software is a 3D visualization system of medical volume data that has been developed over several years in FraunhoferIGD [7]. Due to the system design, no special graphic card is needed and unlimited amount of volume data, in our case, CT, can be imported into the system. This is an important issue since CT-Simulators must be able to handle large data sets, from 40 up to 150 slices, in order to produce high-quality rendering mages. The data used in this work have been acquired with a Siemens Somatom Plus-4 CT scanner, but the system can connect via network directly to any CT scanner that support DICOM-3 communication protocol. EXOMIO can display the imported volume data as original 2D CT scans, as orthogonal or oblique reconstructed planes. The implemented 3D-reconstruction pipeline uses perspective projection to reconstruct the BEV image and parallel projection for the OEV. Both views support transparent reconstruction modes like maximum intensity
494
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
Fig. 1. The EXOMIO user interfaces.
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
495
projection (MIP) [8] and X-ray [9] and surface reconstruction mode using iso-value, gradient [10] and semitransparent shading (see Fig. 1(a) and (b)).
Fig. 2. Protecting normal structures using manual blocks and MLC.
496
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
Using EXOMIO, the simulation process is performed with the following working steps. Collect patient’s CT data including the attached on the patient’s skin aluminum markers. Transfer CT data to CT-Simulator. The physician must detect the slice location with the aluminum markers and define the reference point for the specific plan. This step guaranties the reproduction of the correct patient position through the treatment process. Then, the physician defines the tumor volume and the organs at risk. Afterwards, she/he will place the necessary fields so as to cover the tumor volume (see Fig. 2). The simulation plan is transferred via DICOM server to the TPS for dose calculation and final treatment plan optimization. Verify patient position using portal imaging, on the LINAC before irradiation. Perform treatment on the treatment machine (Linear Accelerator or LINAC). The above working steps can vary among clinics or among treatment cases. In any case, the concept is that a CT-Simulator must be compatible with several devices and applications in an oncology clinic. EXOMIO provides the following communication capabilities for data exchange:
Communication with the CT scanner for the acquisition of the CT volume data. This is fulfilled using DICOM-3 server. Connectivity to TPSs via DICOM server for the exchange of the simulation plan, organ structures and dose volume. Use of the internal Ethernet network to export the DRR images in DICOM or standard image formats like BMP, to the portal-imaging device. This connectivity is essential for the patient position verification during treatment. Transfer of the block shape for each field to the block-cutting machine through the internal Ethernet network. EXOMIO can export the coordinates of the projected field edges on the patient’s skin, to the laser skin-marking device for external field verification. In this case, we make again use of the internal Ethernet network.
3. Results 3.1. System accuracy On the real Simulator, system inaccuracies are coming mainly from the mechanical components. Baltas et al. [11] on a report about quality assurance of the real Simulators found that for different simulator components, the following errors might occur:
Table movements might have an error up to ± 2mm. Irradiation field size and light field at the level of iso-center might have an error up to ± 3.0 mm. Iso-center sphere size for static angle rotation of gantry, collimator or table might have an error up to ± 2.5 mm.
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
497
On the other hand, the VS system accuracy and the rendering image quality dependents on the CT data resolution especially in the longitudinal (Z-axis) direction, where the slice thickness can vary from 1 to 10 mm. In most of our cases, we use equidistant slices with thickness between 3 and 5 mm and the total number of slices according to the patient case were between 40 and 120 slices. A cubic phantom of size 120 120 mm was initially used to exam the accuracy of EXOMIO. Inside the phantom spheres of diameter 2 mm are placed in constant distance. The phantom was scanned using 1-mm slice thickness. The total number of produced slices was 120, in square CT matrices of 512 512 pixels. The recorded system error concerning the table translation is at ± 1 mm. The beam size and the projected light field size matched completely. No iso-center sphere effect occurred during component rotation. The interactive landmark registration routine might have the error of the slice thickness. The algorithms automatic SSD settings, the automatic translation of the beam iso-center to the PTV’s center of gravity has an error of voxel size. The accuracy of the routines automatic field and block adaptation on the PTV is related to the resolution of the BEV image. In most cases, the BEV image has the size of 256 256 up to 400 400. The higher the image resolution, the smaller the error of these routines. In this case, we give a tolerance of ± 2 mm. 3.2. Clinical trials The system is installed in the clinic of Offenbach since September 2000. So far, more than 300 patients have gone through virtual and real simulation, so as to compare the two systems. For 80 patient cases, we performed time measurements on the real Simulator and on EXOMIO. Table 1 illustrates that average simulation time for the 80 patients is 31 min. The clinical persons involved in the process are the medical – technical assistance (MTA) and the physician. It is interesting to notice that the physician spends most of his/her time on documenting the patient case. Table 2 illustrates the average time when performing the CT-simulation using EXOMIO. In this case, the simulation time is the half of the time needed with the real simulator. The patient is
Table 1 Average time needed to perform simulation with the real simulator Person
Process
Mean time (min)
Patient MTA
Simulation Positioning Fluoroscopy Develop X-ray Patient marking
31 2.9 5.0 4.1 3.8 15.8
Documentation Fluoroscopy
15.5 5.0 20.5
Total time Physician Total time
498
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
Table 2 Average time needed to perform simulation with EXOMIO Person
Process
Mean time (min)
Patient Physician
CT scan Structure definition Field placement Documentation
12.8 6.5 3.0 3.0 12.5
Total time
involved only during the CT data acquisition and the physician spends the whole time on preparing the patient’s plan.
4. Discussion In this work, we introduce a CT-based virtual simulation system that involves highend visualization techniques and provides flexibility in communication with other systems and devices in the clinical environment. The system serves to optimize and accelerate the external beam simulation process. Main advantages of the VS against the real Simulator are:
The absence of the patient thought the simulation process since their electronic data are used for the simulation. CT-Simulation avoids the often experienced bottlenecks in patient workload flow within a department of radiation oncology. Reduced time needed to prepare the simulation plan about 50%. Reduced effort and personnel. Low investment in money and space for the clinic department. Low maintenance costs.
Furthermore, a CT-Simulator provides 3D imaging tools, including the entire patient anatomy. These features are not supported from any real Simulator. In addition, it provides higher accuracy on beam configuration and block contour drawing (see Fig. 2). The only significant advantage of the classical simulator is the ability to use fluoroscopy in order to assess the movement of tumor and organs in relation to the field geometry. This advantage still has to be overcome with CT-Simulation.
References [1] G. Sherouse, C. Mosher, K. Novins, J. Rosemann, E.L. Chaney, Virtual simulation: concept and implementation, Proceedings of 9th International Conference of the Use of Computers in Radiation Therapy (ICCR), North-Holland, Scheveningen, The Netherlands, 1987, pp. 433 – 436. [2] J. Rosenman, S. Sailer, G. Sherouse, E.L. Chaney, J.E. Tepper, Virtual simulation: initial clinical results, Int. J. Radiat. Oncol., Biol. Phys. 20 (1991) 843 – 851. [3] G. Sherouse, E.L. Chaney, The portable virtual simulator, Int. J. Radiat. Oncol., Biol. Phys. 21 (1991) 475 – 482.
G. Karangelis, N. Zamboglou / International Congress Series 1230 (2001) 492–499
499
[4] J.M. Michalski, J.A. Purdy, W. Harms, J.W. Matthews, The CT-simulation 3D treatment planning process, Front. Radiat. Ther. Oncol. 29 (1996) 43 – 56. [5] J.A. Purdy, 3D radiation treatment planning: a new era, Front Radiat. Ther. Oncol. 29 (1996) 1 – 16. [6] J. Conway, M.H. Robinson, CT virtual simulation, Br. J. Radiol. 70 (1997) 106 – 118. [7] G. Sakas, Interactive volume rendering of large fields, Visual Computer 9 (8) (1993) 425 – 438. [8] G. Sakas, M. Grimm, A. Savopoulos, Optimised maximum intensity projection (MIP), Rendering Techniques ’95, Springer, 1995, pp. 51 – 63. [9] W. Cai, Transfer functions in DRR volume rendering, CARS ’99, Paris, France, June 23 – 26, 1999. [10] M. Levoy, Display of surface from volume data, IEEE CG&A 8 (5) (1988). [11] D. Baltas, K. Mueller-Sievers, B. Kober, Preliminary results of a intercomparison of quality control referring to therapy simulators, ESTRO, Second Biennial Meeting on Physics in Clinical Radiotherapy, Prague, 1993.