Review Special Issues

Image-guided prostate biopsy robots: A review


  • Received: 06 April 2023 Revised: 11 June 2023 Accepted: 03 July 2023 Published: 17 July 2023
  • At present, the incidence of prostate cancer (PCa) in men is increasing year by year. So, the early diagnosis of PCa is of great significance. Transrectal ultrasonography (TRUS)-guided biopsy is a common method for diagnosing PCa. The biopsy process is performed manually by urologists but the diagnostic rate is only 20%–30% and its reliability and accuracy can no longer meet clinical needs. The image-guided prostate biopsy robot has the advantages of a high degree of automation, does not rely on the skills and experience of operators, reduces the work intensity and operation time of urologists and so on. Capable of delivering biopsy needles to pre-defined biopsy locations with minimal needle placement errors, it makes up for the shortcomings of traditional free-hand biopsy and improves the reliability and accuracy of biopsy. The integration of medical imaging technology and the robotic system is an important means for accurate tumor location, biopsy puncture path planning and visualization. This paper mainly reviews image-guided prostate biopsy robots. According to the existing literature, guidance modalities are divided into magnetic resonance imaging (MRI), ultrasound (US) and fusion image. First, the robot structure research by different guided methods is the main line and the actuators and material research of these guided modalities is the auxiliary line to introduce and compare. Second, the robot image-guided localization technology is discussed. Finally, the image-guided prostate biopsy robot is summarized and suggestions for future development are provided.

    Citation: Yongde Zhang, Qihang Yuan, Hafiz Muhammad Muzzammil, Guoqiang Gao, Yong Xu. Image-guided prostate biopsy robots: A review[J]. Mathematical Biosciences and Engineering, 2023, 20(8): 15135-15166. doi: 10.3934/mbe.2023678

    Related Papers:

  • At present, the incidence of prostate cancer (PCa) in men is increasing year by year. So, the early diagnosis of PCa is of great significance. Transrectal ultrasonography (TRUS)-guided biopsy is a common method for diagnosing PCa. The biopsy process is performed manually by urologists but the diagnostic rate is only 20%–30% and its reliability and accuracy can no longer meet clinical needs. The image-guided prostate biopsy robot has the advantages of a high degree of automation, does not rely on the skills and experience of operators, reduces the work intensity and operation time of urologists and so on. Capable of delivering biopsy needles to pre-defined biopsy locations with minimal needle placement errors, it makes up for the shortcomings of traditional free-hand biopsy and improves the reliability and accuracy of biopsy. The integration of medical imaging technology and the robotic system is an important means for accurate tumor location, biopsy puncture path planning and visualization. This paper mainly reviews image-guided prostate biopsy robots. According to the existing literature, guidance modalities are divided into magnetic resonance imaging (MRI), ultrasound (US) and fusion image. First, the robot structure research by different guided methods is the main line and the actuators and material research of these guided modalities is the auxiliary line to introduce and compare. Second, the robot image-guided localization technology is discussed. Finally, the image-guided prostate biopsy robot is summarized and suggestions for future development are provided.



    加载中


    [1] Y. Wu, H. Chen, G. Jiang, Z. Mo, D. Ye, M. Wang, et al., Genome-wide association study (GWAS) of germline copy number variations (CNVs) reveal genetic risks of prostate cancer in Chinese population, J. Cancer, 9 (2018), 923–928. https://doi.org/10.7150/jca.22802 doi: 10.7150/jca.22802
    [2] M. Matuszczak, J. A. Schalken, M. J. C. Salagierski, Prostate cancer liquid biopsy biomarkers' clinical utility in diagnosis and prognosis, Cancers, 13 (2021), 3373. https://doi.org/10.3390/cancers13133373 doi: 10.3390/cancers13133373
    [3] J. Xiang, H. Yan, J. Li, X. Wang, H. Chen, X. Zheng, Transperineal versus transrectal prostate biopsy in the diagnosis of prostate cancer: a systematic review and meta-analysis, World J. Surg. Oncol., 17 (2019), 1–11. https://doi.org/10.1186/s12957-019-1573-0 doi: 10.1186/s12957-019-1573-0
    [4] X. Dai, Y. Zhang, J. Jiang, B. Li, Image‐guided robots for low dose rate prostate brachytherapy: Perspectives on safety in design and use, Int. J. Med. Rob. Comput. Assisted Surg., 17 (2021), e2239. https://doi.org/10.1002/rcs.2239 doi: 10.1002/rcs.2239
    [5] P. Mohan, H. Ho, J. Yuen, W. S. Ng, W. S. Cheng, A 3D computer simulation to study the efficacy of transperineal versus transrectal biopsy of the prostate, Int. J. Comput. Assisted Radiol. Surg., 1 (2007), 351–360. https://doi.org/10.1007/s11548-007-0069-5 doi: 10.1007/s11548-007-0069-5
    [6] D. Batura, G. G. Rao, The national burden of infections after prostate biopsy in England and Wales: a wake-up call for better prevention, J. Antimicrob. Chemother., 68 (2013), 247–249. https://doi.org/10.1093/jac/dks401 doi: 10.1093/jac/dks401
    [7] P. Emiliozzi, A. Corsetti, B. Tassi, G. Federico, M. Martini, V. Pansadoro, Best approach for prostate cancer detection: a prospective study on transperineal versus transrectal six-core prostate biopsy, Urology, 61 (2003), 961–966. https://doi.org/10.1016/S0090-4295(02)02551-7 doi: 10.1016/S0090-4295(02)02551-7
    [8] K. K. Hodge, J. E. McNeal, M. K. Terris, T. A. Stamey, Random systematic versus directed ultrasound guided transrectal core biopsies of the prostate, J. Urol., 142 (1989), 71–74. https://doi.org/10.1016/S0022-5347(17)38664-0 doi: 10.1016/S0022-5347(17)38664-0
    [9] P. Tucan, F. Craciun, C. Vaida, B. Gherman, D. Pisla, C. Radu, et al., Development of a control system for an innovative parallel robot used in prostate biopsy, in 2017 21st International Conference on Control Systems and Computer Science (CSCS), IEEE, (2017), 76–83. https://doi.org/10.1109/CSCS.2017.17
    [10] A. Rovetta, R. Sala, Execution of robot-assisted biopsies within the clinical context, J. Image Guided Surg., 1 (1995), 280–287. https://doi.org/10.1002/(SICI)1522-712X(1995)1:5<280::AID-IGS4>3.0.CO;2-6 doi: 10.1002/(SICI)1522-712X(1995)1:5<280::AID-IGS4>3.0.CO;2-6
    [11] L. Phee, J. Yuen, D. Xiao, C. F. Chan, H. HO, C. H. Thng, et al., Ultrasound guided robotic biopsy of the prostate, Int. J. Humanoid Rob., 3 (2006), 463–483. https://doi.org/10.1142/S0219843606000850 doi: 10.1142/S0219843606000850
    [12] K. A. Roehl, J. A. V. Antenor, W. J. Catalona, Serial biopsy results in prostate cancer screening study, J. Urol., 167 (2002), 2435–2439. https://doi.org/10.1016/S0022-5347(05)64999-3 doi: 10.1016/S0022-5347(05)64999-3
    [13] M. K. Terris, E. M. Wallen, T. A. Stamey, Comparison of mid-lobe versus lateral systematic sextant biopsies in the detection of prostate cancer, Urol. Int., 59 (1997), 239–242. https://doi.org/10.1159/000283071 doi: 10.1159/000283071
    [14] D. W. Keetch, J. M. McMurtry, D. S. Smith, G. L. Andriole, W. J. Catalona, et al., Prostate specific antigen density versus prostate specific antigen slope as predictors of prostate cancer in men with initially negative prostatic biopsies, J. Urol., 156 (1996), 428–431. https://doi.org/10.1016/S0022-5347(01)65868-3 doi: 10.1016/S0022-5347(01)65868-3
    [15] M. K. Terris, J. E. McNeal, F. S Freiha, T. A. Stamey, Efficacy of transrectal ultrasound-guided seminal vesicle biopsies in the detection of seminal vesicle invasion by prostate cancer, J. Urol., 149 (1993), 1035–1039. https://doi.org/10.1016/S0022-5347(17)36290-0 doi: 10.1016/S0022-5347(17)36290-0
    [16] J. C. Presti, Prostate cancer: Assessment of risk using digital rectal examination, tumor grade, prostate-specific antigen, and systematic biopsy, Radiol. Clin. N. Am., 38 (2000), 49–58. https://doi.org/10.1016/S0033-8389(05)70149-4
    [17] I. H. A. E. Ahmed, H. G. E. Mohamed Ali Hassan, M. E. G. Abo ElMaaty, S. E. M. E. E. Metwally, Role of MRI in diagnosis of prostate cancer and correlation of results with transrectal ultrasound guided biopsy "TRUS", Egypt. J. Radiol. Nucl. Med., 53 (2022), 1–13. https://doi.org/10.1186/s43055-022-00755-7 doi: 10.1186/s43055-022-00755-7
    [18] P. Blumenfeld, N. Hata, S. DiMaio, K. Zou, S. Haker, G, Fichtinger, et al., Transperineal prostate biopsy under magnetic resonance image guidance: a needle placement accuracy study, J. Magn. Reson. Imaging, 26 (2007), 688–694. https://doi.org/10.1002/jmri.21067 doi: 10.1002/jmri.21067
    [19] K. M. Chan, J. M. Gleadle, M. O'Callaghan, K. Vasilev, M. MacGregor, Prostate cancer detection: A systematic review of urinary biosensors, Prostate Cancer Prostatic Dis., 25 (2022), 39–46. https://doi.org/10.1038/s41391-021-00480-8 doi: 10.1038/s41391-021-00480-8
    [20] A. Afshar-Oromieh, U. Haberkorn, H. P. Schlemmer, M. Fenchel, M. Eder, M. Eisenhut, et al., Comparison of PET/CT and PET/MRI hybrid systems using a 68Ga-labelled PSMA ligand for the diagnosis of recurrent prostate cancer: initial experience, Eur. J. Nucl. Med. Mol. Imaging, 41 (2014), 887–897. https://doi.org/10.1007/s00259-013-2660-z
    [21] S. Shoji, S. Hiraiwa, T. Ogawa, M. Kawakami, M. Nakano, K. Hashida, et al., Accuracy of real-time magnetic resonance imaging-transrectal ultrasound fusion image-guided transperineal target biopsy with needle tracking with a mechanical position-encoded stepper in detecting significant prostate cancer in biopsy-naive men, Int. J. Urol., 24 (2017), 288–294. https://doi.org/10.1111/iju.13306 doi: 10.1111/iju.13306
    [22] S. Shoji, Magnetic resonance imaging-transrectal ultrasound fusion image-guided prostate biopsy: current status of the cancer detection and the prospects of tailor-made medicine of the prostate cancer, Investig. Clin. Urol., 60 (2019), 4–13. https://doi.org/10.4111/icu.2019.60.1.4 doi: 10.4111/icu.2019.60.1.4
    [23] C. J. Das, A. Razik, A. Netaji, S. Verma, Prostate MRI-TRUS fusion biopsy: A review of the state of the art procedure, Abdom. Radiol., 45 (2020), 2176–2183. https://doi.org/10.1007/s00261-019-02391-8 doi: 10.1007/s00261-019-02391-8
    [24] J. Hanske, Y. Risse, F. Roghmann, D. Pucheril, S. Berg, K. H. Tully, et al., Comparison of prostate cancer detection rates in patients undergoing MRI/TRUS fusion prostate biopsy with two different software-based systems, Prostate, 82 (2022), 227–234. https://doi.org/10.1002/pros.24264 doi: 10.1002/pros.24264
    [25] J. Zhang, A. Zhu, D. Sun, S. Guo, H. Zhang, S. Liu, et al., Is targeted magnetic resonance imaging/transrectal ultrasound fusion prostate biopsy enough for the detection of prostate cancer in patients with PI-RADS > = 3: Results of a prospective, randomized clinical trial, J. Cancer Res. Ther., 16 (2020), 1698–1702. https://doi.org/10.4103/jcrt.JCRT_1495_20 doi: 10.4103/jcrt.JCRT_1495_20
    [26] L. Wang, Y. Zhang, S. Zuo, Y. Xu, A review of the research progress of interventional medical equipment and methods for prostate cancer, Int. J. Med. Rob. Comput. Assisted Surg., 17 (2021), e2303. https://doi.org/10.1002/rcs.2303 doi: 10.1002/rcs.2303
    [27] X. Zhang, H. Du, M. Lu, Y. Zhang, Breast intervention surgery robot under image navigation: A review, Adv. Mech. Eng., 13 (2021). https://doi.org/10.1177/16878140211028113
    [28] J. Tokuda, S. E. Song, G. S. Fischer, I. I. Iordachita, R. Seifabadi, N. B. Cho, et al., Preclinical evaluation of an MRI-compatible pneumatic robot for angulated needle placement in transperineal prostate interventions, Int. J. Comput. Assisted Radiol. Surg., 7 (2012), 949–957. https://doi.org/10.1007/s11548-012-0750-1 doi: 10.1007/s11548-012-0750-1
    [29] J. Tokuda, G. S. Fischer, C. Csoma, S. P. DiMaio, D. G. Gobbi, G. Fichtinger, et al., Software strategy for robotic transperineal prostate therapy in closed-bore MRI, in 2008 11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2008), Springer, (2008), 701–709. https://doi.org/10.1007/978-3-540-85990-1_84
    [30] A. J. Krafft, P. Zamecnik, F. Maier, A. de Oliveira, P. Hallscheidt, H. P. Schlemmer, et al., Passive marker tracking via phase-only cross correlation (POCC) for MR-guided needle interventions: Initial in vivo experience, Physica Med., 29 (2013), 607–614. https://doi.org/10.1016/j.ejmp.2012.09.002 doi: 10.1016/j.ejmp.2012.09.002
    [31] R. Seifabadi, S. E. Song, A. Krieger, N. Cho, J. Tokuda, G. Fichtinger, et al., Robotic system for MRI-guided prostate biopsy: Feasibility of teleoperated needle insertion and ex vivo phantom study, Int. J. Comput. Assisted Radiol. Surg., 7 (2012), 181–190. https://doi.org/10.1007/s11548-011-0598-9
    [32] A. Krieger, I. Iordachita, S. E. Song, N. B. Cho, P. Guion, G. Fichtinger, et al., Development and preliminary evaluation of an actuated MRI-compatible robotic device for MRI-guided prostate intervention, in 2010 IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2010), 1066–1073. https://doi.org/10.1109/ROBOT.2010.5509727
    [33] K. Y. Kim, M. Li, B. Gonenc, W. Shang, S. Eslami, I. L. Iordachita, Design of an MRI-compatible modularized needle driver for In-bore MRI-guided prostate interventions, in 2015 15th International Conference on Control, Automation and Systems (ICCAS), IEEE, (2015), 1520–1525. https://doi.org/10.1109/ICCAS.2015.7364595
    [34] N. A. Patel, G. Li, W. Shang, M. Wartenberg, T. Heffter, E. C. Burdette, et al., System integration and preliminary clinical evaluation of a robotic system for MRI-guided transperineal prostate biopsy, J. Med. Rob. Res., 4 (2019), 1950001. https://doi.org/10.1142/S2424905X19500016 doi: 10.1142/S2424905X19500016
    [35] G. Fichtinger, A. Krieger, R. C. Susil, A. Tanacs, L. L. Whitcomb, E. Atalar, Transrectal prostate biopsy inside closed MRI scanner with remote actuation, under real-time image guidance, in 5th International Conference on Medical Image Computing and Computer-assisted Intervention, Springer, (2002), 91–98. https://doi.org/10.1007/3-540-45786-0_12
    [36] A. Krieger, R. C. Susil, C. Ménard, J. A. Coleman, G. Fichtinger, E. Atalar, et al., Design of a novel MRI compatible manipulator for image guided prostate interventions, IEEE Trans. Biomed. Eng., 52 (2005), 306–313. https://doi.org/10.1109/TBME.2004.840497 doi: 10.1109/TBME.2004.840497
    [37] E. Balogh, A. Deguet, R. C. Susil, A. Krieger, A. Viswanathan, C. Menard, et al., Visualization, planning, and monitoring software for MRI-guided prostate intervention robot, in 7th International Conference on Medical Image Computing and Computer-assisted Intervention (MICCAI 2004), Springer, (2004), 73–80. https://doi.org/10.1007/978-3-540-30136-3_10
    [38] A. Krieger, I. I. Iordachita, P. Guion, A. K. Singh, A. Kaushal, C. Menard, et al., An MRI-compatible robotic system with hybrid tracking for MRI-guided prostate intervention, IEEE Trans. Biomed. Eng., 58 (2011), 3049–3060. https://doi.org/10.1109/TBME.2011.2134096 doi: 10.1109/TBME.2011.2134096
    [39] A. Krieger, S. E. Song, N. B. Cho, I. I. Iordachita, P. Guion, G. Fichtinger, et al., Development and evaluation of an actuated MRI-compatible robotic system for MRI-guided prostate intervention, IEEE/ASME Trans. Mechatron., 18 (2011), 273–284. https://doi.org/10.1109/TMECH.2011.2163523 doi: 10.1109/TMECH.2011.2163523
    [40] J. Bohren, I. Iordachita, L. L. Whitcomb, Design requirements and feasibility study for a 3-DOF MRI-compatible robotic device for MRI-guided prostate intervention, in 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2012), 677–682. https://doi.org/10.1109/ICRA.2012.6225260
    [41] H. Elhawary, A. Zivanovic, M. Rea, B. L. Davies, C. Besant, D. McRobbie, et al., A modular approach to MRI-compatible robotics, IEEE Eng. Med. Biol. Mag., 27 (2008), 35–41. https://doi.org/10.1109/EMB.2007.910260 doi: 10.1109/EMB.2007.910260
    [42] M. Rea, D. McRobbie, H. Elhawary, Z. T. H. Tse, M. Lamperth, I. Young, System for 3-D real-time tracking of MRI-compatible devices by image processing, IEEE/ASME Trans. Mechatron., 13 (2008), 379–382. https://doi.org/10.1109/TMECH.2008.924132 doi: 10.1109/TMECH.2008.924132
    [43] H. Elhawary, Z. T. H. Tse, M. Rea, A. Zivanovic, B. L. Davies, C. Besant, et al., Robotic system for transrectal biopsy of the prostate: real-time guidance under MRI, IEEE Eng. Med. Biol. Mag., 29 (2010), 78–86. https://doi.org/10.1109/MEMB.2009.935709 doi: 10.1109/MEMB.2009.935709
    [44] A. A. Goldenberg, J. Trachtenberg, W. Kucharczyk, Y. Yi, M. Haider, L. Ma, et al., Robotic system for closed-bore MRI-guided prostatic interventions, IEEE/ASME Trans. Mechatron., 13 (2008), 374–379. https://doi.org/10.1109/TMECH.2008.924122 doi: 10.1109/TMECH.2008.924122
    [45] A. A. Goldenberg, J. Trachtenberg, Y. Yi, R. Weersink, M. S. Sussman, M. Haider, et al., Robot-assisted MRI-guided prostatic interventions, Robotica, 28 (2010), 215–234. https://doi.org/10.1017/S026357470999066X doi: 10.1017/S026357470999066X
    [46] G. S. Fischer, I. Iordachita, C. Csoma, J. Tokuda, S. P. DiMaio, C. M. Tempany, et al., MRI-compatible pneumatic robot for transperineal prostate needle placement, IEEE/ASME Trans. Mechatron., 13 (2008), 295–305. https://doi.org/10.1109/TMECH.2008.924044 doi: 10.1109/TMECH.2008.924044
    [47] J. Tokuda, G. S. Fischer, S. P. DiMaio, D. G. Gobbi, C. Csoma, P. W. Mewes, et al., Integrated navigation and control software system for MRI-guided robotic prostate interventions, Comput. Med. Imaging Graphics, 34 (2010), 3–8. https://doi.org/10.1016/j.compmedimag.2009.07.004 doi: 10.1016/j.compmedimag.2009.07.004
    [48] G. S. Fischer, I. Iordachita, C. Csoma, J. Tokuda, P. W. Mewes, Pneumatically operated MRI-compatible needle placement robot for prostate interventions, in 2008 IEEE International Conference on Robotics and Automation, IEEE, (2008), 2489–2495. https://doi.org/10.1109/ROBOT.2008.4543587
    [49] M. G. Schouten, J. Ansems, W. K. J. Renema, D. Bosboom, T. W. J. Scheenen, J. J. Futterer, The accuracy and safety aspects of a novel robotic needle guide manipulator to perform transrectal prostate biopsies, Med. Phys., 37 (2010), 4744–4750. https://doi.org/10.1118/1.3475945 doi: 10.1118/1.3475945
    [50] D. Yakar, M. G. Schouten, D. G. H. Bosboom, J. O. Barentsz, T. W. J. Scheenen, J. J. Fuetterer, Feasibility of a pneumatically actuated MR-compatible robot for transrectal prostate biopsy guidance, Radiology, 260 (2011), 241–247. https://doi.org/10.1148/radiol.11101106 doi: 10.1148/radiol.11101106
    [51] M. G. Schouten, J. G. R. Bomers, D. Yakar, H. Huisman, E. Rothgang, D. Bosboom, et al., Evaluation of a robotic technique for transrectal MRI-guided prostate biopsies, Eur. Radiol., 22 (2012), 476–483. https://doi.org/10.1007/s00330-011-2259-3 doi: 10.1007/s00330-011-2259-3
    [52] S. E. Song, N. B. Cho, G. Fischer, N. Hata, C. Tempany, G. Fichtinger, et al., Development of a pneumatic robot for MRI-guided transperineal prostate biopsy and brachytherapy: New approaches, in 2010 IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2010), 2580–2585. https://doi.org/10.1109/ROBOT.2010.5509710
    [53] S. E. Song, N. Cho, J. Tokuda, N. Hata, C. Tempany, G. Fichtinger, et al., Preliminary evaluation of a MRI-compatible modular robotic system for MRI-guided prostate interventions, in 2010 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, IEEE, (2010), 796–801. https://doi.org/10.1002/jmri.21259
    [54] S. E. Song, N. Hata, I. Iordachita, G. Fichtinger, C. Tempany, J. Tokuda, A workspace‐orientated needle‐guiding robot for 3T MRI‐guided transperineal prostate intervention: evaluation of in‐bore workspace and MRI compatibility, Int. J. Med. Rob. Comput. Assisted Surg., 9 (2013), 67–74. https://doi.org/10.1002/rcs.1430 doi: 10.1002/rcs.1430
    [55] R. Seifabadi, I. Iordachita, G. Fichtinger, Design of a teleoperated needle steering system for MRI-guided prostate interventions, in 2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), IEEE, (2012), 793–798. https://doi.org/10.1109/BioRob.2012.6290862
    [56] R. Seifabadi, F. Aalamifar, I. Iordachita, G. Fichtinger, Toward teleoperated needle steering under continuous MRI guidance for prostate percutaneous interventions, Int. J. Med. Rob. Comput. Assisted Surg., 12 (2016), 355–369. https://doi.org/10.1002/rcs.1692 doi: 10.1002/rcs.1692
    [57] H. Su, D. C. Cardona, W. J. Shang, A. Camilo, G. A. Cole, D. C. Rucker, et al., A MRI-guided concentric tube continuum robot with piezoelectric actuation: A feasibility study, in 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2012), 1939–1945. https://doi.org/10.1109/ICRA.2012.6224550
    [58] W. Shang, S. Hao, L. Gang, C. Furlong, G. S. Fischer, A fabry-perot interferometry based MRI-Compatible miniature uniaxial force sensor for percutaneous needle placement, IEEE Sens. J., (2013), 57–60. https://doi.org/10.1109/ICSENS.2013.6688137
    [59] G. Li, H. Su, W. Shang, J. Tokuda, N. Hata, C. M. Tempany, et al., A fully actuated robotic assistant for MRI-guided prostate biopsy and brachytherapy, in Conference on Medical Imaging-image-guided Procedures, Robotic Interventions, and Modeling, SPIE, (2013), 867117. https://doi.org/10.1117/12.2007669
    [60] S. Eslami, G. S. Fischer, S. E. Song, J. Tokuda, N. Hata, C. M. Tempany, et al., Towards clinically optimized MRI-guided surgical manipulator for minimally invasive prostate percutaneous interventions: constructive design, in 2013 IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2013), 1228–1233. https://doi.org/10.1109/ICRA.2013.6630728
    [61] S. Eslami, W. Shang, G. Li, N. Patel, G. S. Fischer, J. Tokuda, et al., In‐bore prostate transperineal interventions with an MRI‐guided parallel manipulator: System development and preliminary evaluation, Int. J. Med. Rob. Comput. Assisted Surg., 12 (2016), 199–213. https://doi.org/10.1002/rcs.1671 doi: 10.1002/rcs.1671
    [62] M. Li, B. Gonenc, K. Kim, W. Shang, I. Iordachita, Development of an MRI-compatible needle driver for in-bore prostate biopsy, in International Conference on Advanced Robotics (ICAR), IEEE, (2015), 130–136. https://doi.org/10.1109/ICAR.2015.7251445
    [63] Y. Wang, S. Kim, E. C. Burdette, P. Kazanzides, I. Iordachita, Robotic system with multiplex power transmission for MRI-guided percutaneous interventions, in 2016 38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, (2016), 5228–5232. https://doi.org/10.1109/EMBC.2016.7591906
    [64] D. Stoianovici, C. Kim, G. Srimathveeravalli, P. Sebrecht, D. Petrisor, J. Coleman, et al., MRI-safe robot for endorectal prostate biopsy, IEEE/ASME Trans. Mechatron., 19 (2013), 1289–1299. https://doi.org/10.1109/TMECH.2013.2279775 doi: 10.1109/TMECH.2013.2279775
    [65] D. Stoianovici, C. Jun, S. Lim, P. Li, D. Petrisor, S. Fricke, et al., Multi-imager compatible, MR safe, remote center of motion needle-guide robot, IEEE Trans. Biomed. Eng., 65 (2017), 165–177. https://doi.org/10.1109/TBME.2017.2697766 doi: 10.1109/TBME.2017.2697766
    [66] L. Chen, T. Paetz, V. Dicken, S. Krass, J. A. Issawi, D. Ojdanic, et al., Design of a dedicated five degree-of-freedom magnetic resonance imaging compatible robot for image guided prostate biopsy, J. Med. Devices, 9 (2015), 015002. https://doi.org/10.1115/1.4029506 doi: 10.1115/1.4029506
    [67] D. Stoianovici, C. Kim, D. Petrisor, C. Jun, S. Lim, M. W. Ball, et al., MR safe robot, FDA clearance, safety and feasibility of prostate biopsy clinical trial, IEEE/ASME Trans. Mechatron., 22 (2016), 115–126. https://doi.org/10.1109/TMECH.2016.2618362 doi: 10.1109/TMECH.2016.2618362
    [68] M. W. Ball, A. E. Ross, K. Ghabili, C. Kim, C. Jun, D. Petrisor, et al., Safety and feasibility of direct magnetic resonance imaging-guided transperineal prostate biopsy using a novel magnetic resonance imaging-safe robotic device, Urology, 109 (2017), 216–221. https://doi.org/10.1016/j.urology.2017.07.010 doi: 10.1016/j.urology.2017.07.010
    [69] A. M. Aleong, T. Looi, K. V. Luo, Z. Zou, A. Waspe, S. Singh, et al., Preliminary study of a modular MR-compatible robot for image-guided insertion of multiple needles, Front. Oncol., 12 (2022), 829369. https://doi.org/10.3389/fonc.2022.829369 doi: 10.3389/fonc.2022.829369
    [70] P. Biswas, H. Dehghani, S. Sikander, S. E. Song, Kinematic and mechanical modelling of a novel 4-DOF robotic needle guide for MRI-guided prostate intervention, Biomed. Eng. Adv., 4 (2022), 100036. https://doi.org/10.1016/j.bea.2022.100036 doi: 10.1016/j.bea.2022.100036
    [71] K. Y. Kim, H. S. Woo, J. H. Cho, Y. K. Lee, Development of a two DOF needle driver for CT-guided needle insertion-type interventional robotic system, in 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), IEEE, (2017), 470–475. https://doi.org/10.1109/ROMAN.2017.8172344
    [72] D. Stoianovici, A. Patriciu, D. Petrisor, D. Mazilu, L. Kavoussi, A new type of motor: pneumatic step motor, IEEE/ASME Trans. Mechatron., 12 (2007), 98–106. https://doi.org/10.1109/TMECH.2006.886258 doi: 10.1109/TMECH.2006.886258
    [73] E. Mendoza, J. P. Whitney, A testbed for haptic and magnetic resonance imaging-guided percutaneous needle biopsy, IEEE Rob. Autom. Lett., 4 (2019), 3177–3183. https://doi.org/10.1109/LRA.2019.2925558 doi: 10.1109/LRA.2019.2925558
    [74] Y. Wang, H. Su, K. Harrington, G. S. Fischer, Sliding mode control of piezoelectric valve regulated pneumatic actuator for MRI-compatible robotic intervention, in ASME Dynamic Systems and Control Conference, ASME, (2010), 23–28. https://doi.org/10.1115/DSCC2010-4203
    [75] K. Tadakuma, L. M. DeVita, J. S. Plante, Y. Shaoze, S. Dubowsky, The experimental study of a precision parallel manipulator with binary actuation: With application to MRI cancer treatment, in 2018 IEEE International Conference on Robotics and Automation, IEEE, (2008), 2503–2508. https://doi.org/10.1109/ROBOT.2008.4543589
    [76] J. S. Plante, K. Tadakuma, L. M. DeVita, D. F. Kacher, J. R. Roebuck, S. P. DiMaio, et al., An MRI-compatible needle manipulator concept based on elastically averaged dielectric elastomer actuators for prostate cancer treatment: An accuracy and MR-compatibility evaluation in phantoms, J. Med. Devices, 3 (2009). https://doi.org/10.1115/1.3191729
    [77] S. Proulx, P. Chouinard, J. P. L. Bigue, J. S. Plante, Design of a binary needle manipulator using elastically averaged air muscles for prostate cancer treatments, in ASME International Design Engineering Technical Conferences, ASME, (2009), 123–132. https://doi.org/10.1115/DETC2009-86480
    [78] S. Proulx, G. Miron, A. Girard, J. S. Plante, Experimental validation of an elastically averaged binary manipulator for MRI-guided prostate cancer interventions, in ASME International Design Engineering Technical Conferences, ASME, (2010), 409–418. https://doi.org/10.1115/DETC2010-28235
    [79] S. Proulx, J. S. Plante, Design and experimental assessment of an elastically averaged binary manipulator using pneumatic air muscles for magnetic resonance imaging guided prostate interventions, J. Mech. Des., 133 (2011). https://doi.org/10.1115/1.4004983
    [80] G. Miron, A, Girard, J. S. Plante, M. Lepage, Design and manufacturing of embedded pneumatic actuators for an MRI-Compatible prostate cancer binary manipulator, in ASME International Design Engineering Technical Conferences, ASME, (2012), 1133–1142. https://doi.org/10.1115/DETC2012-71380
    [81] G. Miron, A. Girard, J. S. Plante, M. Lepage, Design and manufacturing of embedded air-muscles for a magnetic resonance imaging compatible prostate cancer binary manipulator, J. Mech. Des., 135 (2013). https://doi.org/10.1115/1.4007932
    [82] R. Gassert, A. Yamamoto, D. Chapuis, L. Dovat, H. Bleuler, E. Burdet, Actuation methods for applications in MR environments, Concepts Magn. Reson. Part B, 29 (2006), 191–209. https://doi.org/10.1002/cmr.b.20070
    [83] H. Su, G. A. Cole, G. S. Fischer, High-field MRI-compatible needle placement robots for prostate interventions: pneumatic and piezoelectric approaches, J. Mech. Des., 26 (2012), 21–32.
    [84] E. Hempel, H. Fischer, L. Gumb, T. Hohn, H. Krause, U. Voges, et al., An MRI-compatible surgical robot for precise radiological interventions, Comput. Aided Surg., 8 (2003), 180–191. https://doi.org/10.3109/10929080309146052 doi: 10.3109/10929080309146052
    [85] H. Su, A. Camilo, G. A. Cole, N. Hata, C. M. Tempany, G. S. Fischer, High-field MRI-compatible needle placement robot for prostate interventions, Mech. Des., 163 (2011), 623–629. https://doi.org/10.3233/978-1-60750-706-2-623 doi: 10.3233/978-1-60750-706-2-623
    [86] J. D. Velazco-Garcia, N. V. Navkar, S. Balakrishnan, J. Abinahed, A. Al-Ansari, G. Younes, et al., Preliminary evaluation of robotic transrectal biopsy system on an interventional planning software, in 19th Annual IEEE International Conference on Bioinformatics and Bioengineering (BIBE), IEEE, (2019), 357–362. https://doi.org/10.1109/BIBE.2019.00070
    [87] P. C. Mozer, A. W. Partin, D. Stoianovici, Robotic image-guided needle interventions of the prostate, Urology, 11 (2009), 7–15.
    [88] L. Phee, X. Di, J. Yuen, C. F. Chan, H. Ho, C. H. Thng, et al., Ultrasound guided robotic system for transperineal biopsy of the prostate, in IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2005), 1315–1320.
    [89] H. S. S. Ho, P, Mohan, E. D. Lim, D. L. Li, S. P. Yuen, W. S. Ng, et al., Robotic ultrasound‐guided prostate intervention device: system description and results from phantom studies, Int. J. Med. Rob. Comput. Assisted Surg., 5 (2009), 51–58. https://doi.org/10.1002/rcs.232 doi: 10.1002/rcs.232
    [90] H. Ho, J. S. P. Yuen, P. Mohan, E. W. Lim, C. W. S. Cheng, Robotic transperineal prostate biopsy: Pilot clinical study, Urology, 78 (2011), 1203–1208. https://doi.org/10.1016/j.urology.2011.07.1389 doi: 10.1016/j.urology.2011.07.1389
    [91] Y. Zhang, F. Liu, Y. Yu, Structural design of prostate biopsy robot based on TRIZ theory, J. Med. Devices, 72 (2012), 3176–3181. https://doi.org/10.4028/www.scientific.net/AMR.538-541.3176 doi: 10.4028/www.scientific.net/AMR.538-541.3176
    [92] J. A. Long, N. Hungr, M. Baumann, J. L. Descotes, M. Bolla, J. Y. Giraud, et al., Development of a novel robot for transperineal needle based interventions: Focal therapy, brachytherapy and prostate biopsies, J. Urol., 188 (2012), 1369–1374. https://doi.org/10.1016/j.juro.2012.06.003 doi: 10.1016/j.juro.2012.06.003
    [93] C. Poquet, P. Mozer, G. Morel, M. A. Vitrani, A novel comanipulation device for assisting needle placement in ultrasound guided prostate biopsies, in 2013 IEEE International Conference on Intelligent Robots and Systems (IROS), IEEE, (2013), 4084–4091. https://doi.org/10.1109/IROS.2013.6696941
    [94] C. Poquet, P. Mozer, M. A.Vitrani, G. Morel, An endorectal ultrasound probe comanipulator with hybrid actuation combining brakes and motors, IEEE/ASME Trans. Mechatron., 20 (2015), 186–196. https://doi.org/10.1109/TMECH.2014.2314859 doi: 10.1109/TMECH.2014.2314859
    [95] M. A. Vitrani, J. Troccaz, A. S. Silvent, S. Y. Selmi, J. Sarrazin, D. Reversat, et al., PROSBOT–Model and image controlled prostatic robot, IRBM, 36 (2015). https://doi.org/10.1016/j.irbm.2015.01.012
    [96] M. A. Vitrani, M. Baumann, D. Reversat, G. Morel, A. Moreau-Gaudry, P. Mozer, Prostate biopsies assisted by comanipulated probe-holder: first in man, Int. J. Comput. Assisted Radiol. Surg., 11 (2016), 1153–1161. https://doi.org/10.1007/s11548-016-1399-y doi: 10.1007/s11548-016-1399-y
    [97] S. Lim, C. Jun, D. Chang, D. Petrisor, M. Han, D. Stoianovici, Robotic transrectal ultrasound guided prostate biopsy, IEEE Trans. Biomed. Eng., 66 (2019), 2527–2537. https://doi.org/10.1109/TBME.2019.2891240
    [98] J. Yan, B. Pan, Y. Fu, Ultrasound-guided prostate percutaneous intervention robot system and calibration by informative particle swarm optimization, Front. Mech. Eng., 17 (2022), 3. https://doi.org/10.1007/s11465-021-0659-x doi: 10.1007/s11465-021-0659-x
    [99] C. Thoma, MRI/TRUS fusion outperforms standard and combined biopsy approaches, Nat. Rev. Urol., 12 (2015), 119. https://doi.org/10.1038/nrurol.2015.28 doi: 10.1038/nrurol.2015.28
    [100] T. P. Frye, P. A. Pinto, A. K. George, Optimizing patient population for MP-MRI and fusion biopsy for prostate cancer detection, Curr. Urol. Rep., 16 (2015), 1–7. https://doi.org/10.1007/s11934-015-0521-y doi: 10.1007/s11934-015-0521-y
    [101] D. Pisla, P. Tucan, B. Gherman, N. Crisan, I. Andras, C. Vaida, et al., Development of a parallel robotic system for transperineal biopsy of the prostate, Mech. Sci., 8 (2017), 195–213. https://doi.org/10.5194/ms-8-195-2017 doi: 10.5194/ms-8-195-2017
    [102] P. Tucan, C. Vaida, B. Gherman, F. Craciun, N. Plitea, I. Birlescu, et al., Control system of a medical parallel robot for transperineal prostate biopsy, in 2017 21st International Conference on System Theory, Control and Computing (ICSTCC), IEEE, (2017), 206–211. https://doi.org/10.1109/ICSTCC.2017.8107035
    [103] D. Pisla, D. Ani, C. Vaida, B. Gherman, P. Tucan, N. Plitea, BIO-PROS-2: An innovative parallel robotic structure for transperineal prostate biopsy, in IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), IEEE, (2016), 157–162. https://doi.org/10.1109/AQTR.2016.7501308
    [104] B. Maris, C. Tenga, R. Vicario, L. Palladino, N. Murr, M. De Piccoli, et al., Toward autonomous robotic prostate biopsy: a pilot study, Int. J. Comput. Assisted Radiol. Surg., 16 (2021), 1393–1401. https://doi.org/10.1007/s11548-021-02437-7 doi: 10.1007/s11548-021-02437-7
    [105] W. Wang, B. Pan, Y. Fu, Y. Liu, Development of a transperineal prostate biopsy robot guided by MRI-TRUS image, Int. J. Med. Rob. Comput. Assisted Surg., 17 (2021), e2266. https://doi.org/10.1002/rcs.2266 doi: 10.1002/rcs.2266
    [106] X. Xiao, Y. Wu, Q. Wu, H. Ren, Concurrently bendable and rotatable continuum tubular robot for omnidirectional multi-core transurethral prostate biopsy, Med. Biol. Eng. Comput., 60 (2021), 229–238. https://doi.org/10.1007/s11517-021-02434-7 doi: 10.1007/s11517-021-02434-7
    [107] X. Xiao, C. Li, X. Gu, Y. Yan, Y. Wu, Q. Wu, et al., A tubular dual-roller bending mechanism towards robotic transurethral prostate biopsy, IEEE/ASME Trans. Mechatron., 1 (2020), 99–108. https://doi.org/10.1109/TMECH.2020.3040749 doi: 10.1109/TMECH.2020.3040749
    [108] H. Li, P. Wu, Z. Wang, J. Mao, F. E. Alsaadi, N. Zeng, A generalized framework of feature learning enhanced convolutional neural network for pathology-image-oriented cancer diagnosis, Comput. Biol. Med., 151 (2022), 106265. https://doi.org/10.1016/j.compbiomed.2022.106265 doi: 10.1016/j.compbiomed.2022.106265
    [109] S. Alkhalaf, F. Alturise, A. A. Bahaddad, B. M. E. Elnaim, S. Shabana, S. Abdel-Khalek, et al., Adaptive aquila optimizer with explainable artificial intelligence-enabled cancer diagnosis on medical imaging, Cancers, 15 (2023), 1492. https://doi.org/10.3390/cancers15051492 doi: 10.3390/cancers15051492
    [110] P. Wu, Z. Wang, B. Zheng, H. Li, F. E. Alsaadi, N. Zeng, AGGN: Attention-based glioma grading network with multi-scale feature extraction and multi-modal information fusion, Comput. Biol. Med., 152 (2023), 106457. https://doi.org/10.1016/j.compbiomed.2022.106457 doi: 10.1016/j.compbiomed.2022.106457
    [111] K. S. Pradhan, P. Chawla, R. Tiwari, HRDEL: High ranking deep ensemble learning-based lung cancer diagnosis model, Expert Syst. Appl., 213 (2023), 118956. https://doi.org/10.1016/j.eswa.2022.118956 doi: 10.1016/j.eswa.2022.118956
    [112] H. Li, N. Zeng, P. Wu, K. Clawson, Cov-Net: A computer-aided diagnosis method for recognizing COVID-19 from chest X-ray images via machine vision, Expert Syst. Appl., 207 (2022), 118029. https://doi.org/10.1016/j.eswa.2022.118029 doi: 10.1016/j.eswa.2022.118029
    [113] S. P. Dimaio, S. Pieper, K. Chinzei, N. Hata, S. J. Haker, D. F. Kacher, et al., Robot-assisted needle placement in open MRI: System architecture, integration and validation, Comput. Aided Surg., 12 (2007), 15–24. https://doi.org/10.1080/10929080601168254 doi: 10.1080/10929080601168254
    [114] P. W. Mewes, J. Tokuda, S. P. DiMaio, G. S. Fischer, C. Csoma, D. G. Gobbi, et al., Integrated system for robot-assisted in prostate biopsy in closed MRI scanner, in 2008 IEEE International Conference on Robotics and Automation, IEEE, (2008), 2959–2962. https://doi.org/10.1109/ROBOT.2008.4543659
    [115] N. A. Patel, T. van Katwijk, G. Li, P. Moreira, W. Shang, S. Misra, et al., Closed-loop asymmetric-tip needle steering under continuous intraoperative MRI guidance, in 2015 37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, (2015), 4869–4874. https://doi.org/10.1109/EMBC.2015.7319484
    [116] C. Qin, P. Tu, X. Chen, J. Troccaz, A novel registration-based algorithm for prostate segmentation via the combination of SSM and CNN, Med. Phys., 49 (2022), 5268–5282. https://doi.org/10.1002/mp.15698 doi: 10.1002/mp.15698
    [117] Z. Wang, R. Wu, Y. Xu, Y. Liu, R. Chai, H. Ma, A two-stage CNN method for MRI image segmentation of prostate with lesion, Biomed. Signal Process. Control, 82 (2023), 104610. https://doi.org/10.1016/j.bspc.2023.104610 doi: 10.1016/j.bspc.2023.104610
    [118] Z. Li, J. Fang, R. Qiu, H. Gong, W. Zhang, L. Li, et al., CDA-Net: A contrastive deep adversarial model for prostate cancer segmentation in MRI images, Biomed. Signal Process. Control, 83 (2023), 104622. https://doi.org/10.1016/j.bspc.2023.104622 doi: 10.1016/j.bspc.2023.104622
    [119] D. Xiao, L. Phee, J. Yuen, C. Chan, F. Liu, W. S. Ng, et al., Software design of transperineal prostate needle biopsy robot, in 2005 IEEE International Conference on Control Applications, IEEE, (2015), 13–18. https://doi.org/10.1109/CCA.2005.1507093
    [120] M. Baumann, P. Mozer, V. Daanen, J. Troccaz, Prostate biopsy tracking with deformation estimation, Med. Image Anal., 16 (2012), 562–576. https://doi.org/10.1016/j.media.2011.01.008 doi: 10.1016/j.media.2011.01.008
    [121] M. Abayazid, N. Shahriari, S. Misra, Three-dimensional needle steering towards a localized target in a prostate phantom, in 2014 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), IEEE, (2014), 7–12. https://doi.org/10.1109/BIOROB.2014.6913743
    [122] B. Busam, P. Ruhkamp, S. Virga, B. Lentes, J. Rackerseder, N. Navab, et al., Markerless inside-out tracking for 3d ultrasound compounding, in Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation, Springer, (2018), 56–64. https://doi.org/10.1007/978-3-030-01045-4_7
    [123] T. Peng, J. Zhao, Y. Gu, C. Wang, Y. Wu, X. Cheng, et al., H-ProMed: Ultrasound image segmentation based on the evolutionary neural network and an improved principal curve, Pattern Recognit., 131 (2022), 108890. https://doi.org/10.1016/j.patcog.2022.108890 doi: 10.1016/j.patcog.2022.108890
    [124] X. Xu, T. Sanford, B. Turkbey, S. Xu, B. J. Wood, P. Yan, Shadow-consistent semi-supervised learning for prostate ultrasound segmentation, IEEE Trans. Med. Imaging, 41 (2022), 1331–1345. https://doi.org/10.1109/TMI.2021.3139999 doi: 10.1109/TMI.2021.3139999
    [125] X. Wang, Z. Chang, Q. Zhang, C. Li, F. Miao, G. Gao, Prostate ultrasound image segmentation based on DSU-Net, Biomedicines, 11 (2023), 646. https://doi.org/10.3390/biomedicines11030646 doi: 10.3390/biomedicines11030646
    [126] J. Bi, Y. Zhang, US/MRI guided robotic system for the interventional treatment of prostate, Int. J. Pattern Recognit Artif Intell., 34 (2020), 2059014. https://doi.org/10.1142/S0218001420590144 doi: 10.1142/S0218001420590144
    [127] N. Altini, A. Brunetti, V. P. Napoletano, F. Girardi, E. Allegretti, S. M. Hussain, et al., A fusion biopsy framework for prostate cancer based on deformable superellipses and nnU-Net, Bioengineering, 9 (2022), 343. https://doi.org/10.3390/bioengineering9080343 doi: 10.3390/bioengineering9080343
    [128] P. Kulkarni, S. Sikander, P. Biswas, S. Frawley, S. E. Song, Review of robotic needle guide systems for percutaneous intervention, Ann. Biomed. Eng., 47 (2019), 2489–2513. https://doi.org/10.1007/s10439-019-02319-9 doi: 10.1007/s10439-019-02319-9
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2564) PDF downloads(281) Cited by(3)

Article outline

Figures and Tables

Figures(5)  /  Tables(1)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog