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Research Papers

Development and Analysis of a Novel Parallel Manipulator Used in Four-Dimensional Radiotherapy

[+] Author and Article Information
Henry Arenbeck

Boll Automation GmbH,
Industriestraße 6,
Kleinwallstadt 63839, Germany
e-mail: H.Arenbeck@bollautomation.de

Isabel Prause

Department of Mechanism Theory and Dynamics
of Machines,
RWTH Aachen University,
Kackertstraße 16-18,
Aachen 52072, Germany
e-mail: prause@igm.rwth-aachen.de

Dirk Abel

Institute of Automatic Control,
RWTH Aachen University,
Steinbachstr. 54,
Aachen 52074, Germany
e-mail: D.Abel@irt.rwth-aachen.de

Burkhard Corves

Department of Mechanism Theory and
Dynamics of Machines,
RWTH Aachen University,
Kackertstraße 16-18,
Aachen 52072, Germany
e-mail: corves@igm.rwth-aachen.de

1Corresponding author.

Manuscript received July 28, 2016; final manuscript received January 15, 2017; published online March 20, 2017. Assoc. Editor: Marcia K. O'Malley.

J. Mechanisms Robotics 9(3), 031006 (Mar 20, 2017) (10 pages) Paper No: JMR-16-1216; doi: 10.1115/1.4035990 History: Received July 28, 2016; Revised January 15, 2017

Radiotherapy (RT) enables a selective destruction of tumor cells, although the treatment area is limited to the irradiated volume. Any RT technique comes along with multiple sources of error, which can lead to a deviation of the dose that is applied to the patient. Phantoms—structures that replicate a human and include measurement technology to assess the applied dosage—are used to make such errors observable. Past RT-technologies assumed static tumors. Correspondingly, most existing phantoms comprise only static components. Nowadays, RT is at a transition stage toward techniques which explicitly account for physiological motion. These techniques require phantoms generating such motion. Consequentially, a demand for new kinds of manipulators, which operate with a RT-phantom, has come up and will further increase in the future. Key demands of such manipulators are among others, the generation of full rigid body motion, high acceleration, high stiffness, compactness, little weight, and easy portability. Another indispensable feature is the spatial separation of mechatronic components and phantom structure to ensure human equivalency of the latter. In this work, a new kind of parallel kinematic manipulator (PKM), which is tailored to the requirements of RT-phantom technology, is presented. The PKM consists of low cost standardized mechanical components and sets the target structures, which are located inside a human-equivalent area, into translational and rotational motion in three degrees-of-freedom (DOFs). Only a part of the end-effector is located within the human-equivalent area. All the remaining parts of the PKM are located outside that area. Two versions of the manipulator are presented in detail: their kinematics are derived and their kinetostatic properties are compared. This includes a workspace analysis and the analysis of the transmission behavior in general, meaning the influence of the most important design parameters on the performance. It can be shown that practical differences of both kinematics are negligible, while the modified version provides significant mechanical advantages. In conclusion, a first special purpose manipulator for application in the evolving field of RT-phantom technology is presented. The PKM, which employs a novel kinematic structure, provides higher suitability for its purpose than any other robotic system employed so far for the same purpose.

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References

Kutcher, G. J. , Coia, L. , Gillin, M. , Hanson, W. F. , Leibel, S. , Morton, R. J. , Palta, J. R. , Purdy, J. A. , Reinstein, L. E. , Svensson, G. K. , Weller, M. , and Wingfield, L. , 1994, “ Comprehensive QA for Radiation Oncology: Report of AAPM Radiation Therapy Committee Task Group 40,” Med. Phys., 21(4), pp. 581–618. [CrossRef] [PubMed]
Smith, W. L. , and Becker, N. , 2009, “ Time Delays and Margins in Gated Radiotherapy,” J. Appl. Clin. Med. Phys., 10(3), pp. 140–154. [CrossRef]
Alasti, H. , Cho, Y.-B. , Vandermeer, A. D. , Abbas, A. , Norrlinger, B. , Shubbar, S. , and Bezjak, A. , 2006, “ A Novel Four-Dimensional Radiotherapy Method for Lung Cancer: Imaging, Treatment Planning and Delivery,” Phys. Med. Biol., 51(12), pp. 3251–3267. [CrossRef] [PubMed]
Vinogradskiy, Y. Y. , Balter, P. , Followill, D. S. , Alvarez, P. E. , White, R. A. , and Starkschall, G. , 2009, “ Verification of Four-Dimensional Photon Dose Calculations,” Med. Phys., 36(8), pp. 3438–3447. [CrossRef] [PubMed]
Mutaf, Y. D. , Antolak, J. A. , and Brinkmann, D. H. , 2007, “ The Impact of Temporal Inaccuracies on 4DCT Image Quality,” Med. Phys., 34(5), pp. 1615–1622. [CrossRef] [PubMed]
Darwesh, R. M. , Clay, D. , Hay, P. D. , Kalirai, C. , Rassoulian, H. , Pitiot, A. , and Perkins, A. C. , 2013, “ A Three Dimensional Drive System for Use With Fillable Emission Phantoms for SPECT and PET Imaging,” Phys. Med., 29(6), pp. 695–700. [CrossRef] [PubMed]
Ceberg, S. , Karlsson, A. , Gustavsson, H. , Wittgren, L. , and Bäck, S. Å. J. , 2008, “ Verification of Dynamic Radiotherapy: The Potential for 3D Dosimetry Under Respiratory-Like Motion Using Polymer Gel,” Phys. Med. Biol., 53(20), pp. N387–N396. [CrossRef] [PubMed]
Dunn, L. , Kron, T. , Taylor, M. L. , Callahan, J. , and Franich, R. D. , 2012, “ A Phantom for Testing of 4D-CT for Radiotherapy of Small Lesions,” Med. Phys., 39(9), pp. 5372–5383. [CrossRef] [PubMed]
Tacke, M. B. , Nill, S. , Krauß, A. , and Oelfke, U. , 2010, “ Real-Time Tumor Tracking: Automatic Compensation of Target Motion Using the Siemens 160 MLC,” Med. Phys., 37(2), pp. 753–761. [CrossRef] [PubMed]
Malinowski, K. T. , Noel, C. , Lu, W. , Lechleiter, K. , Hubenschmidt, J. , Low, D. A. , and Parikh, P. , 2007, “ Development of the 4D Phantom for Patient-Specific, End-to-End Radiation Therapy QA,” Proc. SPIE, 6510, pp. 1–9.
Nakayama, H. , Mizowaki, T. , Narita, Y. , Kawada, N. , Takahashi, K. , Mihara, K. , and Hiraoka, M. , 2008, “ Development of a Three-Dimensionally Movable Phantom System for Dosimetric Verifications,” Med. Phys., 35(5), pp. 1643–1650. [CrossRef] [PubMed]
Serban, M. , Heath, E. , Stroian, G. , Collins, D. L. , and Seuntjens, J. , 2008, “ A Deformable Phantom for 4D Radiotherapy Verification: Design and Image Registration Evaluation,” Med. Phys., 35(3), pp. 1094–1102. [CrossRef] [PubMed]
Stanley, N. , Glide-Hurst, C. , Kim, J. , Adams, J. , Li, S. , Wen, N. , Chetty, I. J. , and Zhong, H. , 2013, “ Using Patient-Specific Phantoms to Evaluate Deformable Image Registration Algorithms for Adaptive Radiation Therapy,” J. Appl. Clin. Med. Phys., 14(6), pp. 177–194. [CrossRef]
Szegedi, M. , Rassiah-Szegedi, P. , Fullerton, G. , Wang, B. , and Salter, B. , 2010, “ A Proto-Type Design of a Real-Tissue Phantom for the Validation of Deformation Algorithms and 4D Dose Calculations,” Phys. Med. Biol., 55(13), pp. 3685–3699. [CrossRef] [PubMed]
Biederer, J. , and Heller, M. , 2003, “ Artificial Thorax for MR Imaging Studies in Porcine Heart-Lung Preparations,” Radiology, 226(1), pp. 250–255. [CrossRef] [PubMed]
Yun, J. , Yip, E. , Wachowicz, K. , Rathee, S. , Mackenzie, M. , Robinson, D. , and Fallone, B. G. , 2012, “ Evaluation of a Lung Tumor Autocontouring Algorithm for Intrafractional Tumor Tracking Using Low-Field MRI: A Phantom Study,” Med. Phys., 39(3), pp. 1481–1494. [CrossRef] [PubMed]
Keall, P. J. , Kini, V. R. , Vedam, S. S. , and Mohan, R. , 2001, “ Motion Adaptive X-Ray Therapy: A Feasibility Study,” Phys. Med. Biol., 46(1), pp. 1–10. [CrossRef] [PubMed]
Steidl, P. , Richter, D. , Schuy, C. , Schubert, E. , Haberer, T. , Durante, M. , and Bert, C. , 2012, “ A Breathing Thorax Phantom With Independently Programmable 6D Tumour Motion for Dosimetric Measurements in Radiation Therapy,” Phys. Med. Biol., 57(8), pp. 2235–2250. [CrossRef] [PubMed]
Haas, O. C. L. , Paluszczyszyn, D. , Ruta, M. , and Skworcow, P. , 2011, “ Motion Prediction and Control for Patient Motion Compensation in Radiotherapy,” IFAC Proc. Vols., 18(1), pp. 5985–5990. [CrossRef]
Merlet, J.-P. , 2006, Parallel Robots, 2nd ed., Kluwer Academic Publishers, Boston, MA.
Arenbeck, H. , 2015, Robotische Systeme und Regelungsstrategien für die Radiotherapie bewegter Tumore, 1st ed., Shaker, Aachen, Germany.
Neumann, K. E. , 1988, “ Robot,” U.S. Patent No. 4,732,525 A.
Siciliano, B. , 1999, “ The Tricept Robot: Inverse Kinematics, Manipulability Analysis and Closed-Loop Direct Kinematics Algorithm,” Robotica, 17(4), pp. 437–445. [CrossRef]
Zoppi, M. , Zlatanov, D. , and Gosselin, C. M. , 2005, “ Analytical Kinematics Models and Special Geometries of a Class of 4-DOF Parallel Mechanisms,” IEEE Trans. Rob., 21(6), pp. 1046–1055. [CrossRef]
Gao, F. , and Gruver, W. A. , 1997, “ Performance Evaluation Criteria for Analysis and Design of Robotic Specimens,” 8th International Conference on Advanced Robotics (ICAR), Monterey, CA, July 7–9, pp. 879–884.
Liu, X.-J. , Wang, J. , and Pritschow, G. , 2006, “ Performance Atlases and Optimum Design of Planar 5R Symmetrical Parallel Mechanisms,” Mech. Mach. Theory, 41(2), pp. 119–144. [CrossRef]
Lujan, A. E. , Balter, J. M. , and Ten Haken, R. K. , 2003, “ A Method for Incorporating Organ Motion Due to Breathing Into 3D Dose Calculations in the Liver: Sensitivity to Variations in Motion,” Med. Phys., 30(10), pp. 2643–2649. [CrossRef] [PubMed]

Figures

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Fig. 1

The robot and its main mechanical components (base version)

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Fig. 2

Kinematic structure of the robot (base version)

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Fig. 3

Kinematic structure of the robot (modified version)

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Fig. 4

Reference frames of the phantom robot

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Fig. 5

Workspace with enclosed largest sphere of the selected configuration

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Fig. 6

Reachable workspace volume for different parameter settings

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Fig. 7

Volume of largest sphere within the reachable workspace

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Fig. 8

Maximum actuator torque for each point of the prescribed workspace

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Fig. 9

Maximum actuator velocities for each point of the prescribed workspace

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Fig. 10

Maximum actuator torque within the largest cubes

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Fig. 11

Maximum actuator velocity within the largest cubes

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Fig. 12

Maximum required power within the largest cubes

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Fig. 13

Norm of deviation of the Jacobian matrices for both versions

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Fig. 14

Magnitude of structural rotations for base version

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Fig. 15

Magnitude of structural rotations for modified version

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Fig. 16

Prototype of 4D-phantom

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