Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data

Navid Shahriari, Wout Heerink, Tim van Katwijk, Edsko E.G. Hekman, Matthijs Oudkerk, Sarthak Misra

    Research output: Contribution to journalArticleAcademicpeer-review

    5 Citations (Scopus)

    Abstract

    Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with the target is difficult and the needle tends to deflect from a straight path. In this work, we present a CT-compatible robotic system, which can both position the needle at the puncture point and also insert and rotate the needle. The robot has a remote-center-of-motion arm which is achieved through a parallel mechanism. A new needle steering scheme is also developed where CT images are fused with electromagnetic (EM) sensor data using an unscented Kalman filter. The data fusion allows us to steer the needle using the real-time EM tracker data. The robot design and the steering scheme are validated using three experimental cases. Experimental Case I and II evaluate the accuracy and CT-compatibility of the robot arm, respectively. In experimental Case III, the needle is steered towards 5 real targets embedded in an anthropomorphic gelatin phantom of the thorax. The mean targeting error for the 5 experiments is 1.78 ± 0.70 mm. The proposed robotic system is shown to be CT-compatible with low targeting error. Small nodule size and large needle diameter are two risk factors that can lead to complications in lung biopsy. Our results suggest that nodules larger than 5 mm in diameter can be targeted using our method which may result in lower complication rate.
    Original languageEnglish
    Pages (from-to)71-77
    Number of pages7
    JournalMedical engineering & physics
    Volume45
    DOIs
    Publication statusPublished - Jul 2017

    Fingerprint

    Electromagnetic Phenomena
    Needles
    Tomography
    Robots
    Sensors
    Biopsy
    Robotics
    Lung
    Data fusion
    Gelatin
    Punctures
    Kalman filters
    Lung Neoplasms
    Arm
    Thorax
    Mortality

    Keywords

    • Biopsy
    • Data fusion
    • Fine needle aspiration (FNA)
    • Lung cancer
    • Unscented Kalman filter

    Cite this

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    title = "Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data",
    abstract = "Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with the target is difficult and the needle tends to deflect from a straight path. In this work, we present a CT-compatible robotic system, which can both position the needle at the puncture point and also insert and rotate the needle. The robot has a remote-center-of-motion arm which is achieved through a parallel mechanism. A new needle steering scheme is also developed where CT images are fused with electromagnetic (EM) sensor data using an unscented Kalman filter. The data fusion allows us to steer the needle using the real-time EM tracker data. The robot design and the steering scheme are validated using three experimental cases. Experimental Case I and II evaluate the accuracy and CT-compatibility of the robot arm, respectively. In experimental Case III, the needle is steered towards 5 real targets embedded in an anthropomorphic gelatin phantom of the thorax. The mean targeting error for the 5 experiments is 1.78 ± 0.70 mm. The proposed robotic system is shown to be CT-compatible with low targeting error. Small nodule size and large needle diameter are two risk factors that can lead to complications in lung biopsy. Our results suggest that nodules larger than 5 mm in diameter can be targeted using our method which may result in lower complication rate.",
    keywords = "Biopsy, Data fusion, Fine needle aspiration (FNA), Lung cancer, Unscented Kalman filter",
    author = "Navid Shahriari and Wout Heerink and {van Katwijk}, Tim and Hekman, {Edsko E.G.} and Matthijs Oudkerk and Sarthak Misra",
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    language = "English",
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    pages = "71--77",
    journal = "Medical engineering & physics",
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    Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data. / Shahriari, Navid ; Heerink, Wout; van Katwijk, Tim; Hekman, Edsko E.G.; Oudkerk, Matthijs; Misra, Sarthak .

    In: Medical engineering & physics, Vol. 45, 07.2017, p. 71-77.

    Research output: Contribution to journalArticleAcademicpeer-review

    TY - JOUR

    T1 - Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data

    AU - Shahriari, Navid

    AU - Heerink, Wout

    AU - van Katwijk, Tim

    AU - Hekman, Edsko E.G.

    AU - Oudkerk, Matthijs

    AU - Misra, Sarthak

    PY - 2017/7

    Y1 - 2017/7

    N2 - Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with the target is difficult and the needle tends to deflect from a straight path. In this work, we present a CT-compatible robotic system, which can both position the needle at the puncture point and also insert and rotate the needle. The robot has a remote-center-of-motion arm which is achieved through a parallel mechanism. A new needle steering scheme is also developed where CT images are fused with electromagnetic (EM) sensor data using an unscented Kalman filter. The data fusion allows us to steer the needle using the real-time EM tracker data. The robot design and the steering scheme are validated using three experimental cases. Experimental Case I and II evaluate the accuracy and CT-compatibility of the robot arm, respectively. In experimental Case III, the needle is steered towards 5 real targets embedded in an anthropomorphic gelatin phantom of the thorax. The mean targeting error for the 5 experiments is 1.78 ± 0.70 mm. The proposed robotic system is shown to be CT-compatible with low targeting error. Small nodule size and large needle diameter are two risk factors that can lead to complications in lung biopsy. Our results suggest that nodules larger than 5 mm in diameter can be targeted using our method which may result in lower complication rate.

    AB - Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with the target is difficult and the needle tends to deflect from a straight path. In this work, we present a CT-compatible robotic system, which can both position the needle at the puncture point and also insert and rotate the needle. The robot has a remote-center-of-motion arm which is achieved through a parallel mechanism. A new needle steering scheme is also developed where CT images are fused with electromagnetic (EM) sensor data using an unscented Kalman filter. The data fusion allows us to steer the needle using the real-time EM tracker data. The robot design and the steering scheme are validated using three experimental cases. Experimental Case I and II evaluate the accuracy and CT-compatibility of the robot arm, respectively. In experimental Case III, the needle is steered towards 5 real targets embedded in an anthropomorphic gelatin phantom of the thorax. The mean targeting error for the 5 experiments is 1.78 ± 0.70 mm. The proposed robotic system is shown to be CT-compatible with low targeting error. Small nodule size and large needle diameter are two risk factors that can lead to complications in lung biopsy. Our results suggest that nodules larger than 5 mm in diameter can be targeted using our method which may result in lower complication rate.

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    KW - Data fusion

    KW - Fine needle aspiration (FNA)

    KW - Lung cancer

    KW - Unscented Kalman filter

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    DO - 10.1016/j.medengphy.2017.04.009

    M3 - Article

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    JO - Medical engineering & physics

    JF - Medical engineering & physics

    SN - 1350-4533

    ER -