Evidence map›Paper›PMID 39371576›Full record

ArticleIEEE robotics and automation letters2024

In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures.

Mariana C Bernardes, Pedro Moreira, Dimitri Lezcano, Lori Foley, Kemal Tuncali, Clare Tempany, Jin Seob Kim, Nobuhiko Hata, Iulian Iordachita, Junichi Tokuda

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE robotics and automation letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mariana C BernardesBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Pedro MoreiraBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Dimitri LezcanoJohns Hopkins University, Baltimore, MD 21218, USA.
Lori FoleyBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Kemal TuncaliBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Clare TempanyBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Jin Seob KimJohns Hopkins University, Baltimore, MD 21218, USA.
Nobuhiko HataBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Iulian IordachitaJohns Hopkins University, Baltimore, MD 21218, USA.
Junichi TokudaBrigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.

Funding

TRD 3 - Enabling Technologies for Intraprocedural GuidanceP41EB028741 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI Nobuhiko Hata, CLARE M TEMPANY · 2021 to 2026
$10.7M
Open Software Platform for Data-Driven Image-Guided Robotic InterventionsR01EB020667 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI DIAZ-MERCADO, YANCY, KRIEGER, AXEL · 2015 to 2024
$4.1M
Adaptive Percutaneous Prostate Interventions using Sensorized NeedleR01CA235134 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI Nobuhiko Hata, IULIAN IOAN IORDACHITA · 2019 to 2026
$3.6M
Pilot study of an implantable microdevice to test multiple drug responses in prostate cancer patientsR01CA232174 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI HATA, NOBUHIKO, JONAS, OLIVER · 2019 to 2023
$3.4M
Physician Assistance Technology in Image-guided Robotic Intervention of ProstateR01EB030539 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI HATA, NOBUHIKO, ZHANG, HAICHONG · 2021 to 2024
$2.7M
Implantable microdevices with integrated optical imaging for high-throughput in situ tumor response and drug sensitivity measurementR37CA224144 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI JONAS, OLIVER · 2018 to 2023
$2.4M
NCI NIH HHS R01 CA232174NCI NIH HHS R01 CA235134NCI NIH HHS R37 CA224144NIBIB NIH HHS P41 EB028741NIBIB NIH HHS R01 EB020667NIBIB NIH HHS R01 EB030539
6 · The paper itself

Abstract

This study addresses the targeting challenges in MRI-guided transperineal needle placement for prostate cancer (PCa) diagnosis and treatment, a procedure where accuracy is crucial for effective outcomes. We introduce a parameter-agnostic trajectory correction approach incorporating a data-driven closed-loop strategy by radial displacement and an FBG-based shape sensing to enable autonomous needle steering. In an animal study designed to emulate clinical complexity and assess MRI compatibility through a PCa mock biopsy procedure, our approach demonstrated a significant improvement in targeting accuracy (p<0.05), with mean target error of only 2.2 ± 1.9 mm on first insertion attempts, without needle reinsertions. To the best of our knowledge, this work represents the first

Indexed as

Medical Robots and SystemsSteerable Catheters/NeedlesSurgical Robotics

Identifiers

PMID39371576
PMCPMC11448709

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.