Bridging Robotics and Clinical Practice Through the Iterative Development of Robotic Needle Placement
Junichi Tokuda, Ph.D.
Associate Professor of Radiology, Brigham and Women’s Hospital and Harvard Medical School

Abstract
Image guidance and robotics are transforming clinical practice, enabling precise interventions that improve patient outcomes. In this talk, I will use my research on percutaneous needle placement—an essential procedure for cancer diagnosis and treatment—as an example of how we integrate robotics research into clinical practice through an iterative process of clinical testing and fundamental research.
Percutaneous needle placement is critical for both diagnosing and treating cancer. Needle biopsies are widely performed to collect tissue samples from suspected lesions, while confirmed lesions may be treated with brachytherapy or thermal ablation using applicator needles. Accurate needle placement is essential to avoid false-negative diagnoses and ensure optimal dose distribution. As diagnostic imaging advances, clinicians can now pinpoint subregions within heterogeneous tumors with greater accuracy, increasing the demand for precision in needle placement.
Despite efforts to enhance prostate needle placement using image guidance and robotic assistance, in vivo accuracy remains a challenge due to uncertainties in needle-tissue interactions, particularly needle deviation in heterogeneous tissue. Addressing this issue requires a continuous cycle of in vivo validation and new technology development, refining both the conceptual models and technological solutions.
In this talk, I will present our approach, which moves fluidly between in vivo testing and foundational research to develop and validate new technologies. These efforts include collaborations with Johns Hopkins University and other institutions on smart shape-sensing needles, needle-guiding robots, and data-driven steering control. Additionally, I will demonstrate how modern tools such as 3D printing, open-source research software, and large language models accelerate this iterative process, allowing us to prototype, test, and refine new technologies before translating them into clinical practice.
Bio
Junichi Tokuda is a research scientist in the Department of Radiology at Brigham and Women’s Hospital (BWH) in Boston, MA, and a member of the Surgical Planning Laboratory (SPL) and the National Center for Image-Guided Therapy (NCIGT). His work focuses on developing and translating novel software and robotics technologies for image-guided interventions. At BWH, he collaborates with his colleagues on MRI-guided interventions for pelvic and abdominal organs. A strong advocate for open-source research software, he has played a pivotal role in expanding 3D Slicer—a leading open-source medical image computing platform—for surgical navigation and medical robotics applications. Recently, he has collaborated with researchers at Johns Hopkins University and Queen’s University (Kingston, ON) to integrate 3D Slicer with the Robot Operating System (ROS). He earned his B.S. in Engineering and M.S. and Ph.D. in Information Science and Technology from the University of Tokyo, Japan. He joined BWH in 2007 and is currently an Associate Professor of Radiology at Harvard Medical School.

Chulhong Kim, Ph.D.
Head of School of Convergence Science and Technology
Department Chair of Convergence IT Engineering
Program Chair of Medical Science and Engineering
Vice – Director of POSTECH-CATHOLIC BioMed Engineering
Namgo Chair Professor, Young Distinguished Professor and Mueunjae Chair Professor of Convergence IT Engineering, Electrical Engineering, Mechanical Engineering,  and Medical Science and Engineering
Director of Medical Device Innovation Center
Pohang University of Science and Technology (POSTECH)
Chief Executive Officer, Opticho, Inc

ABSTRACT:
Trans-energy imaging modalities have been significantly explored to overcome existing problems in conventional imaging modalities with respect to spatial/temporal resolutions, penetration depth, signal-to-noise ratio, contrast , and so on. Among them, photoacoustic imaging, an emerging hybrid modality that can provide strong endogenous and exogenous optical absorption contrasts with high ultrasonic spatial resolution, has overcome the fundamental depth limitation while keeping the spatial resolution. The image resolution, as well as the maximum imaging depth, is scalable with ultrasonic frequency with in the reach of diffuse photons. In this presentation, the following topics will be discussed; (1) multiscale and multiparametric trans-energy imaging systems, (2) novel deep-learning powered image processing, (3) recent clinical study results in pathology, endocrinology, oncology, cardiology, dermatology, and radiology, (4) label-free ultrafast ultrasound Doppler imaging, and (5) efforts to commercialization.

BIO:

Dr. Chulhong Kim studied for his Ph.D. degree under Prof. Lihong Wang at Washington University in St. Louis. He currently holds Namgo Chair Professorship, Young Distinguished Professorship, and Mueunjae Chair Professorship of School of Convergence Science and Technology (Head), Convergence IT Engineering (Department Chair), Electrical Engineering, Mechanical Engineering, and Medical Science and Engineering (Program Chair) at Pohang University of Science and Technology in Republic of Korea. He is the Director of Medical Device Innovation Center supported by Ministry of Education and the Vice-Director of POSTECH-CATHOLIC BioMed Engineering. He is also the Chief Executive Officer of Opticho Inc., a spinoff company to commercialize preclinical and clinical photoacoustic imaging systems. He was the recipients of the 2022 Korean Presidential Award from Ministry of SMEs and Startups, the Science and Technology Award of the Month for December 2021 by the Korean Minister of Science and ICT, the LINA+50 Creative Innovation Award, the 2020-2021 IEEE EMBS Distinguished Lecturer, the 2017 IEEE EMBS Early Career Achievement Award, the 2017 KAST Young Scientist Award, etc. He has published 253 peer-reviewed journal articles (Nature and Science portfolio journals, PNAS, Chemical Reviews, Radiology, IEEE Transactions, etc). His Google Scholar h-index and citations have reached 78 and over 19,900, respectively. His group’s works have been selected for the 1st positions of the USenhance and TDSC-ABUS Challenges in the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), the 2022/2025 Photoacoustics Journal and TomoWave Best Paper Award and Seno Medical Best Paper Award Finalists continuously in Photons Plus Ultrasound Conference (Photonics West, SPIE), the 2020 Hitachi High-tech Best Presentation Award in High Speed Imaging and Spectroscopy Conference (Photonics West, SPIE), and the 2020 Microscopy Today Innovation Award. He has currently served as a Section Editor of Photoacoustics Journal (premier journal in the field), an Associate Editor of IEEE T. Medical Imaging and IEEE T. Biomedical Engineering, and a Topical Editor-in-Chief of IEEE ACCESS, and an Editorial Board Member of Biomedical Engineering Letters, etc. He is also elected as a member of the National Academy of Engineering of Korea (NAEK) and Young Korean Academy of Science and Technology (Y-KAST). He is a Fellow of the IEEE, SPIE, OPTICA, and AIMBE.

Abstract:

Robotic systems have markedly extended human capabilities in sensing, interacting, manipulating, and transforming the world around us. The design of miniaturized and versatile robots on the scale of tens or a few micrometers would enable access throughout the human body, paving the way for procedures at the cellular level and offering localized diagnosis and treatment with unprecedented precision and efficiency. However, unlike large scale robots, the development of microrobots also faces challenges in locomotion, manufacturing, control, and intelligence. This presentation will discuss our recent efforts to overcome these challenges using innovative engineering techniques and material designs to create miniaturized machines with adaptive locomotion and biomedical functions. I will first discuss the fundamental challenges of nanoscale locomotion and demonstrate how our bio-inspired designs tackle these issues through untethered magnetic nanorobots that achieve efficient locomotion and collective control. Next, I will highlight our development of self-propelled microrockets, which represent a breakthrough in microrobot-based disease treatment within the gastrointestinal tract of living animals. Finally, I will present our advancements using innovative soft materials, from liquid crystal elastomers to hyperelastic hydrogels, to make miniaturized robots with highly adaptive locomotion and transformation. Together, these innovations lay the groundwork for a new era of precision medicine driven by miniaturized machines and robots.

Bio:

Dr. Jinxing Li is an Assistant Professor in the Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering at Michigan State University. His research is centered on advancing microrobotics and neural interfaces to address critical challenges in healthcare. He joined MSU in 2021 as part of the university’s Global Impact Initiative from Stanford University, where he conducted postdoctoral research on engineering soft materials for robotics and brain-machine interfaces. Dr. Li earned his Ph.D. in NanoEngineering at UC San Diego, focusing on engineering nanomaterials as micro/nanorobots for therapeutic applications. He was also a visiting scholar at Nokia Bell Labs, working on responsive biomaterials for telemedicine. Dr. Li received his M.S. from Fudan University and B.S. from Huazhong University of Science and Technology, both in Electrical Engineering. He is the recipient of the NSF CAREER Award, ARPA-E IGNIITE Award, NIH Trailblazer Award, and the MIT Technology Review Innovators Under 35.