Publications

@article{bernardes_data-driven_2023,

title = {Data-driven adaptive needle insertion assist for transperineal prostate interventions},

author = {Mariana C. Bernardes and Pedro Moreira and Lisa Mareschal and Clare Tempany and Kemal Tuncali and Nobuhiko Hata and Junichi Tokuda},

doi = {10.1088/1361-6560/accefa},

issn = {0031-9155, 1361-6560},

year  = {2023},

date = {2023-05-01},

journal = {PHYSICS IN MEDICINE AND BIOLOGY},

volume = {68},

number = {10},

pages = {105016},

abstract = {Objective. Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150-200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients. Approach. In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not require a priori information about needle or tissue properties. The method was evaluated in experiments with both in vitro and ex vivo phantoms. Main results. The experiments in ex vivo tissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction. Significance. Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.},

note = {Num Pages: 14 

Place: Bristol 

Publisher: IoP Publishing Ltd 

Web of Science ID: WOS:000987076600001},

keywords = {biopsy, Brachytherapy, CANCER, Cryoablation, data-driven model, FEASIBILITY, Force, medical robotics, MOTION, needle insertion assist, Robot, TISSUE, transperineal prostate intervention, Ultrasound},

pubstate = {published},

tppubtype = {article}

}

@article{kobayashi_automatic_2023,

title = {Automatic segmentation of prostate and extracapsular structures in MRI to predict needle deflection in percutaneous prostate intervention},

author = {Satoshi Kobayashi and Franklin King and Nobuhiko Hata},

doi = {10.1007/s11548-022-02757-2},

issn = {1861-6410, 1861-6429},

year  = {2023},

date = {2023-03-01},

journal = {INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY},

volume = {18},

number = {3},

pages = {449–460},

abstract = {Purpose Understanding the three-dimensional anatomy of percutaneous intervention in prostate cancer is essential to avoid complications. Recently, attempts have been made to use machine learning to automate the segmentation of functional structures such as the prostate gland, rectum, and bladder. However, a paucity of material is available to segment extracapsular structures that are known to cause needle deflection during percutaneous interventions. This research aims to explore the feasibility of the automatic segmentation of prostate and extracapsular structures to predict needle deflection. Methods Using pelvic magnetic resonance imagings (MRIs), 3D U-Net was trained and optimized for the prostate and extracapsular structures (bladder, rectum, pubic bone, pelvic diaphragm muscle, bulbospongiosus muscle, bull of the penis, ischiocavernosus muscle, crus of the penis, transverse perineal muscle, obturator internus muscle, and seminal vesicle). The segmentation accuracy was validated by putting intra-procedural MRIs into the 3D U-Net to segment the prostate and extracapsular structures in the image. Then, the segmented structures were used to predict deflected needle path in in-bore MRI-guided biopsy using a model-based approach. Results The 3D U-Net yielded Dice scores to parenchymal organs (0.61-0.83), such as prostate, bladder, rectum, bulb of the penis, crus of the penis, but lower in muscle structures (0.03-0.31), except and obturator internus muscle (0.71). The 3D U-Net showed higher Dice scores for functional structures (p <0.001) and complication-related structures (p <0.001). The segmentation of extracapsular anatomies helped to predict the deflected needle path in MRI-guided prostate interventions of the prostate with the accuracy of 0.9 to 4.9 mm. Conclusion Our segmentation method using 3D U-Net provided an accurate anatomical understanding of the prostate and extracapsular structures. In addition, our method was suitable for segmenting functional and complication-related structures. Finally, 3D images of the prostate and extracapsular structures could simulate the needle pathway to predict needle deflections.},

note = {Num Pages: 12 

Place: Heidelberg 

Publisher: Springer Heidelberg 

Web of Science ID: WOS:000857906200002},

keywords = {3-D, 3D U-Net, biopsy, CANCER, Deep learning, guidance, Percutaneous intervention, Prostate, RISK, Segmentation, Ultrasound},

pubstate = {published},

tppubtype = {article}

}

@article{masaki_technical_2021,

title = {Technical Validation of Multi-Section Robotic Bronchoscope With First Person View Control for Transbronchial Biopsies of Peripheral Lung},

author = {Fumitaro Masaki and Franklin King and Takahisa Kato and Hisashi Tsukada and Yolonda Colson and Nobuhiko Hata},

url = {https://pubmed.ncbi.nlm.nih.gov/33945467/},

doi = {10.1109/TBME.2021.3077356},

issn = {1558-2531},

year  = {2021},

date = {2021-12-01},

journal = {IEEE transactions on bio-medical engineering},

volume = {68},

number = {12},

pages = {3534–3542},

abstract = {This study aims to validate the advantage of new engineering method to maneuver multi-section robotic bronchoscope with first person view control in transbronchial biopsy. Six physician operators were recruited and tasked to operate a manual and a robotic bronchoscope to the peripheral area placed in patient-derived lung phantoms. The metrics collected were the furthest generation count of the airway the bronchoscope reached, force incurred to the phantoms, and NASA-Task Load Index. The furthest generation count of the airway the physicians reached using the manual and the robotic bronchoscopes were 6.6 textbackslashpm 1.2ˆth and 6.7 textbackslashpm 0.8ˆth. Robotic bronchoscopes successfully reached the 5th generation count into the peripheral area of the airway, while the manual bronchoscope typically failed earlier in the 3 rd generation. More force was incurred to the airway when the manual bronchoscope was used (0.24 textbackslashpm 0.20 [N]) than the robotic bronchoscope was applied (0.18 textbackslashpm 0.22 [N], p< 0.05). The manual bronchoscope imposed more physical demand than the robotic bronchoscope by NASA-TLX score (55 textbackslashpm 24 vs 19 textbackslashpm 16, p< 0.05). These results indicate that a robotic bronchoscope facilitates the advancement of the bronchoscope to the peripheral area with less physical demand to physician operators. The metrics collected in this study would expect to be used as a benchmark for the future development of robotic bronchoscopes.},

note = {Publisher: IEEE Trans Biomed Eng},

keywords = {biopsy, Bronchoscopes*, Bronchoscopy, doi:10.1109/TBME.2021.3077356, Franklin King, Fumitaro Masaki, Humans, Lung, MEDLINE, National Center for Biotechnology Information, National Institutes of Health, National Library of Medicine, NCBI, NIH, NLM, Nobuhiko Hata, Non-U.S. Gov't, pmid:33945467, PubMed Abstract, Research Support, Robotic Surgical Procedures*},

pubstate = {published},

tppubtype = {article}

}

@article{kato_robotized_2021,

title = {Robotized Catheter With Enhanced Distal Targeting for Peripheral Pulmonary Biopsy},

author = {Takahisa Kato and Franklin King and Kiyoshi Takagi and Nobuhiko Hata},

doi = {10.1109/TMECH.2020.3040314},

issn = {1083-4435, 1941-014X},

year  = {2021},

date = {2021-10-01},

journal = {IEEE-ASME TRANSACTIONS ON MECHATRONICS},

volume = {26},

number = {5},

pages = {2451–2461},

abstract = {Transbronchial biopsy with a lung catheter is more appealing with lower complication risks for peripheral pulmonary biopsy. The distal tips of the current lung catheters lack targeting capabilities, however, which prevents a physician from guiding the biopsy tools to lesions, especially those in a peribronchial location. In this study, we investigated if a robotized catheter could enhance distal targeting after passing through tortuous bronchi. We experimentally evaluated targeting accuracy and the spatial dispersion of targeting with attention to catheter shape constraints by utilizing the bronchi of a patient-derived lung phantom. This newly developed robotized catheter has an outer diameter of 3 mm and a total length of 800 mm and comprises two bending sections at the distal 30 mm length. With these two bending sections, the distal tip can be steered to peribronchial lesions followed by the targeting of multiple locations inside the lesion with controlled dispersion to improve opportunities for tissue sampling. In the experimental results, the targeting position error for a peribronchial lesion ranged from 4.6 +/- 1.2 to 7.2 +/- 3.3 mm (mean +/- STD) among the different shape constraints. As for the targeting dispersion, the shape constraints reduced dispersion ability by a maximum of 50% compared to straight reference constraints, while the dispersion was still larger than the expected minimum requirement of 1 mm. One-way analysis of variance concluded that targeting accuracy and targeting dispersion included a significant dependence on shape constraints (p < .05). This study demonstrates the feasibility of enhancing distal targeting with the proposed robotized catheter and found that bronchi shape constraints significantly affect targeting capability.},

note = {Num Pages: 11 

Place: Piscataway 

Publisher: Ieee-Inst Electrical Electronics Engineers Inc 

Web of Science ID: WOS:000707442500022},

keywords = {ABLATION, Bending, biopsy, Bronchoscopy, Catheters, Continuum robots, Design, Dexterous manipulators, LESIONS, Lung, lung biopsy, medical robotics, PLATFORM, REMOTE MAGNETIC NAVIGATION, robotized catheter, robots, SHAPE ESTIMATION, Surgery, SYSTEM, Tools, TRACKING},

pubstate = {published},

tppubtype = {article}

}

@article{shono_simulated_2020,

title = {Simulated accuracy assessment of small footprint body-mounted probe alignment device for MRI-guided cryotherapy of abdominal lesions},

author = {Naoyuki Shono and Brian Ninni and Franklin King and Takahisa Kato and Junichi Tokuda and Takahiro Fujimoto and Kemal Tuncali and Nobuhiko Hata},

doi = {10.1002/mp.14116},

issn = {0094-2405, 2473-4209},

year  = {2020},

date = {2020-06-01},

journal = {MEDICAL PHYSICS},

volume = {47},

number = {6},

pages = {2337–2349},

abstract = {Purpose Magnetic resonance imaging (MRI)-guided percutaneous cryotherapy of abdominal lesions, an established procedure, uses MRI to guide and monitor the cryoablation of lesions. Methods to precisely guide cryotherapy probes with a minimum amount of trial-and-error are yet to be established. To aid physicians in attaining precise probe alignment without trial-and-error, a body-mounted motorized cryotherapy-probe alignment device (BMCPAD) with motion compensation was clinically tested in this study. The study also compared the contribution of body motion and organ motion compensation to the guidance accuracy of a body-mounted probe alignment device. Methods The accuracy of guidance using the BMCPAD was prospectively measured during MRI-guided percutaneous cryotherapies before insertion of the probes. Clinical parameters including patient age, types of anesthesia, depths of the target, and organ sites of target were collected. By using MR images of the target organs and fiducial markers embedded in the BMCPAD, we retrospectively simulated the guidance accuracy with body motion compensation, organ motion compensation, and no compensation. The collected data were analyzed to test the impact of motion compensation on the guidance accuracy. Results Thirty-seven physical guidance of probes were prospectively recorded for sixteen completed cases. The accuracy of physical guidance using the BMCPAD was 13.4 +/- 11.1 mm. The simulated accuracy of guidance with body motion compensation, organ motion compensation, and no compensation was 2.4 +/- 2.9 mm, 2.2 +/- 1.6 mm, and 3.5 +/- 2.9 mm, respectively. Data analysis revealed that the body motion compensation and organ motion compensation individually impacted the improvement in the accuracy of simulated guidance. Moreover, the difference in the accuracy of guidance either by body motion compensation or organ motion compensation was not statistically significant. The major clinical parameters impacting the accuracy of guidance were the body and organ motions. Patient age, types of anesthesia, depths of the target, and organ sites of target did not influence the accuracy of guidance using BMCPAD. The magnitude of body surface movement and organ movement exhibited mutual statistical correlation. Conclusions The BMCPAD demonstrated guidance accuracy comparable to that of previously reported devices for CT-guided procedures. The analysis using simulated motion compensation revealed that body motion compensation and organ motion compensation individually impact the improvement in the accuracy of device-guided cryotherapy probe alignment. Considering the correlation between body and organ movements, we also determined that body motion compensation using the ring fiducial markers in the BMCPAD can be solely used to address both body and organ motions in MRI-guided cryotherapy.},

note = {Num Pages: 13 

Place: Hoboken 

Publisher: Wiley 

Web of Science ID: WOS:000521855600001},

keywords = {biopsy, Cryoablation, feasibility study, hepatic tumor, LIVER-TUMORS, MICROWAVE ABLATION, MOTION MANAGEMENT, MRI-guided intervention, needle guidance, RADIOFREQUENCY ABLATION, renal tumor, RENAL TUMORS, TRACKING},

pubstate = {published},

tppubtype = {article}

}

@article{abayazid_using_2018,

title = {Using needle orientation sensing as surrogate signal for respiratory motion estimation in percutaneous interventions},

author = {Momen Abayazid and Takahisa Kato and Stuart G. Silverman and Nobuhiko Hata},

doi = {10.1007/s11548-017-1644-z},

issn = {1861-6410, 1861-6429},

year  = {2018},

date = {2018-01-01},

journal = {INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY},

volume = {13},

number = {1},

pages = {125–133},

abstract = {Purpose To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen. Materials and methods The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time. Results The mean error of estimation of the target position ranged between 0.86 and 1.29mm. The processing maximum training and testing time was 5ms which is suitable for real-time target motion estimation using the needle position sensor. Conclusion The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.},

note = {Num Pages: 9 

Place: Heidelberg 

Publisher: Springer Heidelberg 

Web of Science ID: WOS:000419481300013},

keywords = {ABDOMINAL INTERVENTIONS, biopsy, INSERTION, Interventional radiology, Lung, Machine learning, Magnetic Resonance Imaging, MODEL, Motion compensation, percutaneous needle insertion, Radiotherapy, Respiratory motion, SYSTEM, TOMOGRAPHY, TRACKING, TUMOR MOTION},

pubstate = {published},

tppubtype = {article}

}