2023
Bernardes, Mariana C.; Moreira, Pedro; Mareschal, Lisa; Tempany, Clare; Tuncali, Kemal; Hata, Nobuhiko; Tokuda, Junichi
Data-driven adaptive needle insertion assist for transperineal prostate interventions Journal Article
In: PHYSICS IN MEDICINE AND BIOLOGY, vol. 68, no. 10, pp. 105016, 2023, ISSN: 0031-9155, 1361-6560, (Num Pages: 14 Place: Bristol Publisher: IoP Publishing Ltd Web of Science ID: WOS:000987076600001).
Abstract | Links | BibTeX | Tags: biopsy, Brachytherapy, CANCER, Cryoablation, data-driven model, FEASIBILITY, Force, medical robotics, MOTION, needle insertion assist, Robot, TISSUE, transperineal prostate intervention, Ultrasound
@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}
}
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.
Kobayashi, Satoshi; King, Franklin; Hata, Nobuhiko
Automatic segmentation of prostate and extracapsular structures in MRI to predict needle deflection in percutaneous prostate intervention Journal Article
In: INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, vol. 18, no. 3, pp. 449–460, 2023, ISSN: 1861-6410, 1861-6429, (Num Pages: 12 Place: Heidelberg Publisher: Springer Heidelberg Web of Science ID: WOS:000857906200002).
Abstract | Links | BibTeX | Tags: 3-D, 3D U-Net, biopsy, CANCER, Deep learning, guidance, Percutaneous intervention, Prostate, RISK, Segmentation, Ultrasound
@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}
}
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.
2022
Dominas, Christine; Bhagavatula, Sharath; Stover, Elizabeth; Deans, Kyle; Larocca, Cecilia; Colson, Yolanda; Peruzzi, Pierpaolo; Kibel, Adam; Hata, Nobuhiko; Tsai, Lillian; Hung, Yin; Packard, Robert; Jonas, Oliver
The Translational and Regulatory Development of an Implantable Microdevice for Multiple Drug Sensitivity Measurements in Cancer Patients Journal Article
In: IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 69, no. 1, pp. 412–421, 2022, ISSN: 0018-9294, 1558-2531, (Num Pages: 10 Place: Piscataway Publisher: Ieee-Inst Electrical Electronics Engineers Inc Web of Science ID: WOS:000733943200045).
Abstract | Links | BibTeX | Tags: Animals, Biomarkers, biomaterials, Biomedical engineering, CANCER, clinical trials, drug delivery, drug discovery, Drugs, implants, In vivo, Medical treatment, Testing, Tumor Microenvironment, Tumors
@article{dominas_translational_2022,
title = {The Translational and Regulatory Development of an Implantable Microdevice for Multiple Drug Sensitivity Measurements in Cancer Patients},
author = {Christine Dominas and Sharath Bhagavatula and Elizabeth Stover and Kyle Deans and Cecilia Larocca and Yolanda Colson and Pierpaolo Peruzzi and Adam Kibel and Nobuhiko Hata and Lillian Tsai and Yin Hung and Robert Packard and Oliver Jonas},
doi = {10.1109/TBME.2021.3096126},
issn = {0018-9294, 1558-2531},
year = {2022},
date = {2022-01-01},
journal = {IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING},
volume = {69},
number = {1},
pages = {412–421},
abstract = {Objective: The purpose of this article is to report the translational process of an implantable microdevice platform with an emphasis on the technical and engineering adaptations for patient use, regulatory advances, and successful integration into clinical workflow. Methods: We developed design adaptations for implantation and retrieval, established ongoing monitoring and testing, and facilitated regulatory advances that enabled the administration and examination of a large set of cancer therapies simultaneously in individual patients. Results: Six applications for oncology studies have successfully proceeded to patient trials, with future applications in progress. Conclusion: First-in-human translation required engineering design changes to enable implantation and retrieval that fit with existing clinical workflows, a regulatory strategy that enabled both delivery and response measurement of up to 20 agents in a single patient, and establishment of novel testing and quality control processes for a drug/device combination product without clear precedents. Significance: This manuscript provides a real-world account and roadmap on how to advance from animal proof-of-concept into the clinic, confronting the question of how to use research to benefit patients.},
note = {Num Pages: 10
Place: Piscataway
Publisher: Ieee-Inst Electrical Electronics Engineers Inc
Web of Science ID: WOS:000733943200045},
keywords = {Animals, Biomarkers, biomaterials, Biomedical engineering, CANCER, clinical trials, drug delivery, drug discovery, Drugs, implants, In vivo, Medical treatment, Testing, Tumor Microenvironment, Tumors},
pubstate = {published},
tppubtype = {article}
}
Objective: The purpose of this article is to report the translational process of an implantable microdevice platform with an emphasis on the technical and engineering adaptations for patient use, regulatory advances, and successful integration into clinical workflow. Methods: We developed design adaptations for implantation and retrieval, established ongoing monitoring and testing, and facilitated regulatory advances that enabled the administration and examination of a large set of cancer therapies simultaneously in individual patients. Results: Six applications for oncology studies have successfully proceeded to patient trials, with future applications in progress. Conclusion: First-in-human translation required engineering design changes to enable implantation and retrieval that fit with existing clinical workflows, a regulatory strategy that enabled both delivery and response measurement of up to 20 agents in a single patient, and establishment of novel testing and quality control processes for a drug/device combination product without clear precedents. Significance: This manuscript provides a real-world account and roadmap on how to advance from animal proof-of-concept into the clinic, confronting the question of how to use research to benefit patients.
2021
Banach, Artur; King, Franklin; Masaki, Fumitaro; Tsukada, Hisashi; Hata, Nobuhiko
Visually Navigated Bronchoscopy using three cycle-Consistent generative adversarial network for depth estimation Journal Article
In: MEDICAL IMAGE ANALYSIS, vol. 73, pp. 102164, 2021, ISSN: 1361-8415, 1361-8423, (Num Pages: 12 Place: Amsterdam Publisher: Elsevier Web of Science ID: WOS:000701725200004).
Abstract | Links | BibTeX | Tags: Bronchoscopy, CANCER, CT Imaging, DIAGNOSTIC BRONCHOSCOPY, guidance, GUIDED BRONCHOSCOPY, Image-guided surgery, Lung cancer, Motion tracking, NODULES, PERIPHERAL LUNG LESIONS, RECONSTRUCTION, SYSTEM, VIDEO REGISTRATION
@article{banach_visually_2021,
title = {Visually Navigated Bronchoscopy using three cycle-Consistent generative adversarial network for depth estimation},
author = {Artur Banach and Franklin King and Fumitaro Masaki and Hisashi Tsukada and Nobuhiko Hata},
doi = {10.1016/j.media.2021.102164},
issn = {1361-8415, 1361-8423},
year = {2021},
date = {2021-10-01},
journal = {MEDICAL IMAGE ANALYSIS},
volume = {73},
pages = {102164},
abstract = {[Background] Electromagnetically Navigated Bronchoscopy (ENB) is currently the state-of-the art diagnostic and interventional bronchoscopy. CT-to-body divergence is a critical hurdle in ENB, causing navigation error and ultimately limiting the clinical efficacy of diagnosis and treatment. In this study, Visually Navigated Bronchoscopy (VNB) is proposed to address the aforementioned issue of CT-to-body divergence. [Materials and Methods] We extended and validated an unsupervised learning method to generate a depth map directly from bronchoscopic images using a Three Cycle-Consistent Generative Adversarial Network (3cGAN) and registering the depth map to preprocedural CTs. We tested the working hypothesis that the proposed VNB can be integrated to the navigated bronchoscopic system based on 3D Slicer, and accurately register bronchoscopic images to pre-procedural CTs to navigate transbronchial biopsies. The quantitative metrics to asses the hypothesis we set was Absolute Tracking Error (ATE) of the tracking and the Target Registration Error (TRE) of the total navigation system. We validated our method on phantoms produced from the pre-procedural CTs of five patients who underwent ENB and on two ex-vivo pig lung specimens. [Results] The ATE using 3cGAN was 6.2 +/-2.9 [mm]. The ATE of 3cGAN was statistically significantly lower than that of cGAN, particularly in the trachea and lobar bronchus (p < 0.001). The TRE of the proposed method had a range of 11.7 to 40.5 [mm]. The TRE computed by 3cGAN was statistically significantly smaller than those computed by cGAN in two of the five cases enrolled (p < 0.05). [Conclusion] VNB, using 3cGAN to generate the depth maps was technically and clinically feasible. While the accuracy of tracking by cGAN was acceptable, the TRE warrants further investigation and improvement. (c) 2021 Elsevier B.V. All rights reserved.},
note = {Num Pages: 12
Place: Amsterdam
Publisher: Elsevier
Web of Science ID: WOS:000701725200004},
keywords = {Bronchoscopy, CANCER, CT Imaging, DIAGNOSTIC BRONCHOSCOPY, guidance, GUIDED BRONCHOSCOPY, Image-guided surgery, Lung cancer, Motion tracking, NODULES, PERIPHERAL LUNG LESIONS, RECONSTRUCTION, SYSTEM, VIDEO REGISTRATION},
pubstate = {published},
tppubtype = {article}
}
[Background] Electromagnetically Navigated Bronchoscopy (ENB) is currently the state-of-the art diagnostic and interventional bronchoscopy. CT-to-body divergence is a critical hurdle in ENB, causing navigation error and ultimately limiting the clinical efficacy of diagnosis and treatment. In this study, Visually Navigated Bronchoscopy (VNB) is proposed to address the aforementioned issue of CT-to-body divergence. [Materials and Methods] We extended and validated an unsupervised learning method to generate a depth map directly from bronchoscopic images using a Three Cycle-Consistent Generative Adversarial Network (3cGAN) and registering the depth map to preprocedural CTs. We tested the working hypothesis that the proposed VNB can be integrated to the navigated bronchoscopic system based on 3D Slicer, and accurately register bronchoscopic images to pre-procedural CTs to navigate transbronchial biopsies. The quantitative metrics to asses the hypothesis we set was Absolute Tracking Error (ATE) of the tracking and the Target Registration Error (TRE) of the total navigation system. We validated our method on phantoms produced from the pre-procedural CTs of five patients who underwent ENB and on two ex-vivo pig lung specimens. [Results] The ATE using 3cGAN was 6.2 +/-2.9 [mm]. The ATE of 3cGAN was statistically significantly lower than that of cGAN, particularly in the trachea and lobar bronchus (p < 0.001). The TRE of the proposed method had a range of 11.7 to 40.5 [mm]. The TRE computed by 3cGAN was statistically significantly smaller than those computed by cGAN in two of the five cases enrolled (p < 0.05). [Conclusion] VNB, using 3cGAN to generate the depth maps was technically and clinically feasible. While the accuracy of tracking by cGAN was acceptable, the TRE warrants further investigation and improvement. (c) 2021 Elsevier B.V. All rights reserved.
2019
Dupourque, Lenny; Masaki, Fumitaro; Colson, Yolonda L.; Kato, Takahisa; Hata, Nobuhiko
Transbronchial biopsy catheter enhanced by a multisection continuum robot with follow-the-leader motion Journal Article
In: INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, vol. 14, no. 11, pp. 2021–2029, 2019, ISSN: 1861-6410, 1861-6429, (Num Pages: 9 Place: Heidelberg Publisher: Springer Heidelberg Web of Science ID: WOS:000496030000019).
Abstract | Links | BibTeX | Tags: Bronchoscopy, CANCER, COMPUTED-TOMOGRAPHY, Continuum robots, diagnosis, lung biopsy, Multisection robot, NAVIGATION BRONCHOSCOPY, NODULE, Surgical robotics
@article{dupourque_transbronchial_2019,
title = {Transbronchial biopsy catheter enhanced by a multisection continuum robot with follow-the-leader motion},
author = {Lenny Dupourque and Fumitaro Masaki and Yolonda L. Colson and Takahisa Kato and Nobuhiko Hata},
doi = {10.1007/s11548-019-02017-w},
issn = {1861-6410, 1861-6429},
year = {2019},
date = {2019-11-01},
journal = {INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY},
volume = {14},
number = {11},
pages = {2021–2029},
abstract = {Purpose Current manual catheters for transbronchial biopsy in the lung lack a steering ability, which hampers a physician's ability to reach nodules in the peripheral lung. The objective of this paper is to design and build a multisection robot with a follow-the-leader motion and compare the performance of the conventional catheter and our robotic catheter in the right main and right segmental lobar bronchus. Methods A three-section continuum robot with an outer diameter of 3 mm was developed. Each section includes one anchored wire and two driving wires made of stainless steel. Follow-the-leader control is implemented using a joystick for a physician to control the distal section of the robot, while the subsequent two sections follow the controlled distal section. Results The robotic catheter deviated from the preplanned approach path by less than the manual catheter did (robotic Conclusion This study demonstrated an improvement in the maneuverability for the robotic catheter. In addition to a greater aptitude for reaching a peripheral area of the lung, these findings suggest that the designated target in a peripheral area can be reached with less trauma to the bronchi wall.},
note = {Num Pages: 9
Place: Heidelberg
Publisher: Springer Heidelberg
Web of Science ID: WOS:000496030000019},
keywords = {Bronchoscopy, CANCER, COMPUTED-TOMOGRAPHY, Continuum robots, diagnosis, lung biopsy, Multisection robot, NAVIGATION BRONCHOSCOPY, NODULE, Surgical robotics},
pubstate = {published},
tppubtype = {article}
}
Purpose Current manual catheters for transbronchial biopsy in the lung lack a steering ability, which hampers a physician’s ability to reach nodules in the peripheral lung. The objective of this paper is to design and build a multisection robot with a follow-the-leader motion and compare the performance of the conventional catheter and our robotic catheter in the right main and right segmental lobar bronchus. Methods A three-section continuum robot with an outer diameter of 3 mm was developed. Each section includes one anchored wire and two driving wires made of stainless steel. Follow-the-leader control is implemented using a joystick for a physician to control the distal section of the robot, while the subsequent two sections follow the controlled distal section. Results The robotic catheter deviated from the preplanned approach path by less than the manual catheter did (robotic Conclusion This study demonstrated an improvement in the maneuverability for the robotic catheter. In addition to a greater aptitude for reaching a peripheral area of the lung, these findings suggest that the designated target in a peripheral area can be reached with less trauma to the bronchi wall.
2018
Moreira, Pedro; Patel, Niravkumar; Wartenberg, Marek; Li, Gang; Tuncali, Kemal; Heffter, Tamas; Burdette, Everette C.; Iordachita, Iulian; Fischer, Gregory S.; Hata, Nobuhiko; Tempany, Clare M.; Tokuda, Junichi
Evaluation of robot-assisted MRI-guided prostate biopsy: needle path analysis during clinical trials Journal Article
In: PHYSICS IN MEDICINE AND BIOLOGY, vol. 63, no. 20, pp. 20NT02, 2018, ISSN: 0031-9155, 1361-6560, (Num Pages: 9 Place: Bristol Publisher: IoP Publishing Ltd Web of Science ID: WOS:000448103100002).
Abstract | Links | BibTeX | Tags: Accuracy, bore prostate biopsy, CANCER, guidance, needle deflection, needle path analysis, robot-assisted biopsy, SYSTEM
@article{moreira_evaluation_2018,
title = {Evaluation of robot-assisted MRI-guided prostate biopsy: needle path analysis during clinical trials},
author = {Pedro Moreira and Niravkumar Patel and Marek Wartenberg and Gang Li and Kemal Tuncali and Tamas Heffter and Everette C. Burdette and Iulian Iordachita and Gregory S. Fischer and Nobuhiko Hata and Clare M. Tempany and Junichi Tokuda},
doi = {10.1088/1361-6560/aae214},
issn = {0031-9155, 1361-6560},
year = {2018},
date = {2018-10-01},
journal = {PHYSICS IN MEDICINE AND BIOLOGY},
volume = {63},
number = {20},
pages = {20NT02},
abstract = {While the interaction between a needle and the surrounding tissue is known to cause a significant targeting error in prostate biopsy leading to false-negative results, few studies have demonstrated how it impacts in the actual procedure. We performed a pilot study on robot-assisted MRI-guided prostate biopsy with an emphasis on the in-depth analysis of the needle-tissue interaction in vivo. The data were acquired during in-bore transperineal prostate biopsies in patients using a 4 degrees-of-freedom (DoF) MRI-compatible robot. The anatomical structures in the pelvic area and the needle path were reconstructed from MR images, and quantitatively analyzed. We analyzed each structure individually and also proposed a mathematical model to investigate the influence of those structures in the targeting error using the mixed-model regression. The median targeting error in 188 insertions (27 patients) was 6.3 mm. Both the individual anatomical structure analysis and the mixed-model analysis showed that the deviation resulted from the contact between the needle and the skin as the main source of error. On contrary, needle bending inside the tissue (expressed as needle curvature) did not vary among insertions with targeting errors above and below the average. The analysis indicated that insertions crossing the bulbospongiosus presented a targeting error lower than the average. The mixed-model analysis demonstrated that the distance between the needle guide and the patient skin, the deviation at the entry point, and the path length inside the pelvic diaphragm had a statistically significant contribution to the targeting error (p < 0.05). Our results indicate that the errors associated with the elastic contact between the needle and the skin were more prominent than the needle bending along the insertion. Our findings will help to improve the preoperative planning of transperineal prostate biopsies.},
note = {Num Pages: 9
Place: Bristol
Publisher: IoP Publishing Ltd
Web of Science ID: WOS:000448103100002},
keywords = {Accuracy, bore prostate biopsy, CANCER, guidance, needle deflection, needle path analysis, robot-assisted biopsy, SYSTEM},
pubstate = {published},
tppubtype = {article}
}
While the interaction between a needle and the surrounding tissue is known to cause a significant targeting error in prostate biopsy leading to false-negative results, few studies have demonstrated how it impacts in the actual procedure. We performed a pilot study on robot-assisted MRI-guided prostate biopsy with an emphasis on the in-depth analysis of the needle-tissue interaction in vivo. The data were acquired during in-bore transperineal prostate biopsies in patients using a 4 degrees-of-freedom (DoF) MRI-compatible robot. The anatomical structures in the pelvic area and the needle path were reconstructed from MR images, and quantitatively analyzed. We analyzed each structure individually and also proposed a mathematical model to investigate the influence of those structures in the targeting error using the mixed-model regression. The median targeting error in 188 insertions (27 patients) was 6.3 mm. Both the individual anatomical structure analysis and the mixed-model analysis showed that the deviation resulted from the contact between the needle and the skin as the main source of error. On contrary, needle bending inside the tissue (expressed as needle curvature) did not vary among insertions with targeting errors above and below the average. The analysis indicated that insertions crossing the bulbospongiosus presented a targeting error lower than the average. The mixed-model analysis demonstrated that the distance between the needle guide and the patient skin, the deviation at the entry point, and the path length inside the pelvic diaphragm had a statistically significant contribution to the targeting error (p < 0.05). Our results indicate that the errors associated with the elastic contact between the needle and the skin were more prominent than the needle bending along the insertion. Our findings will help to improve the preoperative planning of transperineal prostate biopsies.