Publications

2023

1. 

   Magnetic guidewire steering at ultrahigh magnetic fields

   Mehmet Efe Tiryaki, Yiğit Günsür Elmacıoğlu, and Metin Sitti

   Science Advances, 2023

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   With remote magnetic steering capabilities, magnetically actuated guidewires have proven their potential in minimally invasive medical procedures. Existing magnetic steering strategies, however, have been limited to low magnetic fields, which prevents the integration into medical systems operating at ultrahigh fields (UHF), such as magnetic resonance imaging (MRI) scanners. Here, we present magnetic guidewire design and steering strategies by elucidating the magnetic actuation principles of permanent magnets at UHF. By modeling the uniaxial magnetization behavior of permanent magnets, we outline the magnetic torque and force and demonstrate unique magnetic actuation opportunities at UHF, such as in situ remagnetization. Last, we illustrate the proposed steering principles using a magnetic guidewire composed of neodymium magnets and a fiber optic rod in a 7-Tesla preclinical MRI scanner. The developed UHF magnetic actuation framework would enable next-generation magnetic robots to operate inside MRI scanners.

   @article{tiryaki2023magnetic,
     title = {Magnetic guidewire steering at ultrahigh magnetic fields},
     author = {Tiryaki, Mehmet Efe and Elmac{\i}o{\u{g}}lu, Yi{\u{g}}it G{\"u}ns{\"u}r and Sitti, Metin},
     journal = {Science Advances},
     volume = {9},
     number = {17},
     pages = {eadg6438},
     year = {2023},
     publisher = {Science},
     url = {https://www.science.org/doi/10.1126/sciadv.adg6438},
     dimensions = {true},
   }

2. 

   MRI-powered Magnetic Miniature Capsule Robot with HIFU-controlled On-demand Drug Delivery

   Mehmet Efe Tiryaki, Fatih Doğangün, Cem Balda Dayan, and 2 more authors

   In 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023

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   Magnetic resonance imaging (MRI)-guided robotic systems offer great potential for new minimally invasive medical tools, including MRI-powered miniature robots. By re-purposing the imaging hardware of an MRI scanner, the magnetic miniature robot could be navigated into the remote part of the patient’s body without needing tethered endoscopic tools. However, state-of-art MRI-powered magnetic miniature robots have limited functionality besides navigation. Here, we propose an MRI-powered magnetic miniature capsule robot benefiting from acoustic streaming forces generated by MRI-guided high-intensity focus ultrasound (HIFU) for controlled drug release. Our design comprises a polymer capsule shell with a submillimeter-diameter drug-release hole that captures an air bubble functioning as a stopper. We use the HIFU pulse to initiate drug release by removing the air bubble once the capsule robot reaches the target location. By controlling acoustic pressure, we also regulate the drug release rate for multiple locations targeting during navigation. We demonstrated that the proposed magnetic capsule robot could travel at high speed, up to 1.13 cm/s in ex vivo porcine small intestine, and release drug to multiple target sites in a single operation, using a combination of MRI-powered actuation and HIFU-controlled release. The proposed MRI-guided microrobotic drug release system will greatly impact minimally invasive medical procedures by allowing on-demand targeted drug delivery.

   @inproceedings{tiryaki2023mri,
     title = {MRI-powered Magnetic Miniature Capsule Robot with HIFU-controlled On-demand Drug Delivery},
     author = {Tiryaki, Mehmet Efe and Do{\u{g}}ang{\"u}n, Fatih and Dayan, Cem Balda and Wrede, Paul and Sitti, Metin},
     booktitle = {2023 IEEE International Conference on Robotics and Automation (ICRA)},
     pages = {5420--5425},
     year = {2023},
     organization = {IEEE},
   }

2022

1. 

   Deep learning-based 3D magnetic microrobot tracking using 2D MR images

   Mehmet Efe Tiryaki, Sinan Ozgun Demir, and Metin Sitti

   IEEE Robotics and Automation Letters, 2022

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   Magnetic resonance imaging (MRI)-guided robots emerged as a promising tool for minimally invasive medical operations. Recently, MRI scanners have been proposed for actuating and localizing magnetic microrobots in the patient’s body using two-dimensional (2D) MR images. However, three-dimensional (3D) magnetic microrobots tracking during motion is still an untackled issue in MRI-powered microrobotics. Here, we present a deep learning-based 3D magnetic microrobot tracking method using 2D MR images during microrobot motion. The proposed method comprises a convolutional neural network (CNN) and complementary particle filter for 3D microrobot tracking. The CNN localizes the microrobot position relative to the 2D MRI slice and classifies the microrobot visibility in the MR images. First, we create an ultrasound (US) imaging-mentored MRI-based microrobot imaging and actuation system to train the CNN. Then, we trained the CNN using the MRI data generated by automated experiments using US image-based visual servoing of a microrobot with a 500μm-diameter magnetic core. We showed that the proposed CNN can localize the microrobot and classified its visibility in an in vitro environment with ±0.56 mm and 87.5% accuracy in 2D MR images, respectively. Furthermore, we demonstrated ex-vivo 3D microrobot tracking with ±1.43 mm accuracy, improving tracking accuracy by 60% compared to the previous studies. The presented tracking strategy will enable MRI-powered microrobots to be used in high-precision targeted medical applications in the future.

   @article{tiryaki2022deep,
     title = {Deep learning-based 3D magnetic microrobot tracking using 2D MR images},
     author = {Tiryaki, Mehmet Efe and Demir, Sinan Ozgun and Sitti, Metin},
     journal = {IEEE Robotics and Automation Letters},
     volume = {7},
     number = {3},
     pages = {6982--6989},
     year = {2022},
     publisher = {IEEE},
   }

2. 

   Radio Frequency Sensing-Based In Situ Temperature Measurements during Magnetic Resonance Imaging Interventional Procedures

   Mehmet Berk Bilgin, Mehmet Efe Tiryaki, Jelena Lazovic, and 1 more author

   Advanced Materials Technologies, 2022

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   Magnetic resonance imaging (MRI)-tuned radio-frequency (RF) sensors are used as a radiation-free alternative for tracking minimally invasive medical tool positions. However, in situ temperature sensing capabilities of the MRI-tuned RF sensors have not been thoroughly investigated yet. A self-resonating RF sensor capable of remote in situ temperature sensing during real-time interventional MRI is presented. The proposed RF sensor design relies on the temperature-dependent permittivity to tune or detune the resonant frequency. The sensor is tuned to match the resonant frequency of a 7 Tesla MRI (298 MHz) at body temperature, enabling a hyperintense signal in MR images. As temperature increases, the sensor detunes due to the change in the relative permittivity, and the hyperintense signal disappears in the MR image, serving as a direct visual indicator of the temperature change in real-time. In addition, the localized signal can be used for 3D position tracking of interventional medical devices. Using a 7 Tesla preclinical MRI, in vitro characterization and ex vivo feasibility of the proposed temperature sensing method are demonstrated in the clinically relevant temperature range of 36–42 °C with an accuracy of ±0.6 °C. Such RF sensors can provide safer operations in future MRI interventional procedures.

   @article{bilgin2022radio,
     title = {Radio Frequency Sensing-Based In Situ Temperature Measurements during Magnetic Resonance Imaging Interventional Procedures},
     author = {Bilgin, Mehmet Berk and Tiryaki, Mehmet Efe and Lazovic, Jelena and Sitti, Metin},
     journal = {Advanced Materials Technologies},
     volume = {7},
     number = {9},
     pages = {2101625},
     year = {2022},
     publisher = {Wiley Online Library},
   }

3. 

   Magnetic Resonance Imaging-Based Tracking and Navigation of Submillimeter-Scale Wireless Magnetic Robots

   Mehmet Efe Tiryaki, and Metin Sitti

   Advanced Intelligent Systems, 2022

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   Magnetic resonance imaging (MRI) scanners have recently been used for magnetic actuation of robots for minimally invasive medical operations. Due to MRI’s high soft-tissue selectivity, it is possible to obtain 3D images of hard-to-reach cavities in the human body, where the wireless miniature magnetic robots powered by MRI could be employed for high-precision targeted operations, such as drug delivery, stem cell therapy, and hyperthermia. However, the state-of-the-art fast magnetic robot-tracking methods in MRI are limited above millimeter-size scale, which restricts the potential target regions inside the human body. Herein, a fast 1D projection-based MRI approach that can track magnetic particles down to 300μm diameter (1.17×10−2emu) is reported. The technique reduces the trackable magnetic particle size in MRI-powered navigation fivefold compared with the previous fast-tracking methods. A closed-loop MRI-powered navigation with 0.78±0.03mm trajectory-following accuracy in millimeter-sized in vitro 2D channels and a 3D cavity setup using the tracking method is demonstrated. Furthermore, the feasibility of submillimeter magnetic robot tracking in ex vivo pig kidneys (N=2) with a 3.6±1.1mm accuracy is demonstrated. Such a fast submillimeter-scale mobile robot-tracking approach can unlock new opportunities in minimally invasive medical operations.

   @article{tiryaki2022magnetic,
     title = {Magnetic Resonance Imaging-Based Tracking and Navigation of Submillimeter-Scale Wireless Magnetic Robots},
     author = {Tiryaki, Mehmet Efe and Sitti, Metin},
     journal = {Advanced Intelligent Systems},
     volume = {4},
     number = {4},
     pages = {2100178},
     year = {2022},
     publisher = {Wiley Online Library},
   }

2020

1. 

   A realistic simulation environment for MRI-based robust control of untethered magnetic robots with intra-operational imaging

   Mehmet Efe Tiryaki, Önder Erin, and Metin Sitti

   IEEE Robotics and Automation Letters, 2020

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   Dual-use of magnetic resonance imaging (MRI) devices for robot tracking and actuation has transformed them into potential medical robotics platforms for targeted therapies and minimally invasive surgeries. In this letter, we present the dynamic simulations of an MRI-based tracking and actuation scheme, which performs intra-operational imaging while controlling untethered magnetic robots. In our realistic rigid-body simulation, we show that the robot could be controlled with a 1D projection-based position feedback while performing intra-operational echo-planar imaging (EPI). From the simulations, we observe that the velocity estimation error is the main source of the controller instability for low MRI sequence frequencies. To minimize the velocity estimation errors, we constrain the controller gains according to maximum closed-loop rates achievable for different sequence durations. Using the constrained controller in simulations, we confirm that EPI imaging could be introduced to the sequence as an intra-operational imaging method. Although the intro-operational imaging increases the position estimation error to 2.0 mm for a simulated MRI-based position sensing with a 0.6 mm Gaussian noise, it does not cause controller instability up to 128 k-space lines. With the presented approach, continuous physiological images could be acquired during medical operations while a magnetic robot is actuated and tracked inside an MRI device.

   @article{tiryaki2020realistic,
     title = {A realistic simulation environment for MRI-based robust control of untethered magnetic robots with intra-operational imaging},
     author = {Tiryaki, Mehmet Efe and Erin, {\"O}nder and Sitti, Metin},
     journal = {IEEE Robotics and Automation Letters},
     volume = {5},
     number = {3},
     pages = {4501--4508},
     year = {2020},
     publisher = {IEEE},
   }