OpenIGTLink: a network communication interface for closed-loop image-guided interventions
Project Number5R01EB020667-07
Former Number2R01EB020667-04
Contact PI/Project LeaderTOKUDA, JUNICHI Other PIs
Awardee OrganizationBRIGHAM AND WOMEN'S HOSPITAL
Description
Abstract Text
Project Summary/Abstract
In this cycle of the project, we will extend OpenIGTLink software to enable individualized precision guidance,
where patient-specific characteristics are taken into account in the planning and control process for image-
guided robotic interventions (IGRI) to achieve a better clinical outcome. In particular, we will focus on improving
needle placement accuracy for IGRI of the prostate, as a simple, and yet a representative application of
individualized precision guidance. Percutaneous needle placement plays a fundamental role in both the
diagnosis and treatment of prostate cancer. Nearly one million prostate biopsies are performed annually in the
United States, where tissues are sampled from the prostate with a biopsy needle for pathological examination.
The confirmed lesions may then be focally treated with brachytherapy or thermal ablation using applicator
needles depending on clinical indications and patient preference. For those procedures, accurate needle
placement is essential to avoid false-negatives or ensure an optimal dose distribution. The demand for
accurate needle placement is growing in recent years, as clinicians are now capable of pinpointing subregions
in a heterogeneous tumor thanks to the recent progress in imaging technologies, particularly multiparametric
magnetic resonance imaging (MRI). However, the in vivo accuracies achieved by previous studies have never
matched the level of tumor subregion targeting due to needle deviation as a result of physical interaction
between the needle and the heterogeneous tissue. To address this issue, we will incorporate needle deviation
models in an IGRI system using OpenIGTLink software. Our hypothesis is that the models adapted to
individual patients will enable avoidance or compensation of needle deviation, leading to an improved in vivo
needle placement accuracy. The project comprises the following four specific aims: (Aim 1) Develop a
biomechanical model with image-based semi-automatic model generation; (Aim 2) Develop a data-driven
prediction model and hybridize with the biomechanical model; (Aim 3) Extend the IGRI platform for model-
based closed-loop control using OpenIGTLink; (Aim 4) Evaluate biomechanical, data-driven, and hybrid
models in vivo needle placement.
Public Health Relevance Statement
Project Narrative
Percutaneous needle placement plays a fundamental role in biopsy and focal ablation of prostate cancer. The
goal of this project is to develop and disseminate free open-source software named OpenIGTLink to support
advanced image-guided robot-assisted systems, where a robotic system guides a needle into the prostate
based on biomechanical, data-driven, and hybrid models that predict the tissue and needle deformation in the
patient during insertion. We expect that the accurate prediction will enable individualized planning and control
for robot-assisted needle placement and improve accuracy biopsy and focal ablation.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AblationAddressAnatomyAnimal ModelBiomechanicsBiopsyBrachytherapyCharacteristicsClinicalClinical DataCommunicationCompensationComputer softwareCore BiopsyDataDiagnosisDoseElementsEnsureFeedbackGenerationsGoalsHybridsImageImaging technologyInterventionLesionMachine LearningMagnetic Resonance ImagingMalignant neoplasm of prostateMedicalMethodsModelingNamesNeedle biopsy procedureNeedlesOutcomePathologicPatient PreferencesPatientsPhysiciansPlayPopulationPositioning AttributeProceduresProcessProstateProstate AblationProstate Cancer therapyRoboticsRoleStructure of base of prostateSystemSystems IntegrationTestingThermal Ablation TherapyTissue ModelTissue SampleTissuesTrainingUnited StatesUpdateWorkbiomechanical modelclinical practicedata-driven modelimage guidedimage guided interventionimprovedin vivoin vivo Modelindividual patientmachine learning modelopen sourcepredictive modelingprospectiveprostate biopsyreal-time imagesrobot assistancerobot controlrobotic systemsimulationsoftware developmenttumor
National Institute of Biomedical Imaging and Bioengineering
CFDA Code
286
DUNS Number
030811269
UEI
QN6MS4VN7BD1
Project Start Date
01-July-2015
Project End Date
31-January-2026
Budget Start Date
01-February-2024
Budget End Date
31-January-2026
Project Funding Information for 2024
Total Funding
$635,108
Direct Costs
$533,127
Indirect Costs
$101,981
Year
Funding IC
FY Total Cost by IC
2024
National Institute of Biomedical Imaging and Bioengineering
$635,108
Year
Funding IC
FY Total Cost by IC
Sub Projects
No Sub Projects information available for 5R01EB020667-07
Publications
Publications are associated with projects, but cannot be identified with any particular year of the project or fiscal year of funding. This is due to the continuous and cumulative nature of knowledge generation across the life of a project and the sometimes long and variable publishing timeline. Similarly, for multi-component projects, publications are associated with the parent core project and not with individual sub-projects.
No Publications available for 5R01EB020667-07
Patents
No Patents information available for 5R01EB020667-07
Outcomes
The Project Outcomes shown here are displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed are those of the PI and do not necessarily reflect the views of the National Institutes of Health. NIH has not endorsed the content below.
No Outcomes available for 5R01EB020667-07
Clinical Studies
No Clinical Studies information available for 5R01EB020667-07
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History
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