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

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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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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

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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

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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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