Evidence map›Paper›PMID 40762895›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

Real-time 3D US-CT fusion-based semi-automatic puncture robot system: clinical evaluation.

Masayuki Nakayama, Bo Zhang, Ryoko Kuromatsu, Masahito Nakano, Yu Noda, Takumi Kawaguchi, Qiang Li, Yuji Maekawa, Masakatsu G Fujie, Shigeki Sugano

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2025. 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. [Ultrasound technology's new application in the diagnosis and treatment of liver cancer].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026
    Review
  2. Review
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.

Masayuki NakayamaGraduate School of Creative Science and Engineering, Waseda University, Tokyo, 1698555, Japan. m_nakayama@akane.waseda.jp.ORCID http://orcid.org/0009-0001-4963-7315
Bo ZhangFuture Robotics Organization, Waseda University, Tokyo, 1620044, Japan.
Ryoko KuromatsuDivision of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Fukuoka, 8300011, Japan.
Masahito NakanoDivision of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Fukuoka, 8300011, Japan.
Yu NodaDivision of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Fukuoka, 8300011, Japan.
Takumi KawaguchiDivision of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Fukuoka, 8300011, Japan.
Qiang LiKYOSETO Co., Ltd, Tokyo, 1600023, Japan.
Yuji MaekawaKYOSETO Co., Ltd, Tokyo, 1600023, Japan.
Masakatsu G FujieFuture Robotics Organization, Waseda University, Tokyo, 1620044, Japan.
Shigeki SuganoFaculty of Science and Engineering, Waseda University, Tokyo, 1698555, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeConventional systems supporting percutaneous radiofrequency ablation (PRFA) have faced difficulties in ensuring safe and accurate puncture due to issues inherent to the medical images used and organ displacement caused by patients' respiration. To address this problem, this study proposes a semi-automatic puncture robot system that integrates real-time ultrasound (US) images with computed tomography (CT) images. The purpose of this paper is to evaluate the system's usefulness through a pilot clinical experiment involving participants.

methodsFor the clinical experiment using the proposed system, an improved U-net model based on fivefold cross-validation was constructed. Following the workflow of the proposed system, the model was trained using US images acquired from patients with robotic arms. The average Dice coefficient for the entire validation dataset was confirmed to be 0.87. Therefore, the model was implemented in the robotic system and applied to clinical experiment.

resultsA clinical experiment was conducted using the robotic system equipped with the developed AI model on five adult male and female participants. The centroid distances between the point clouds from each modality were evaluated in the 3D US-CT fusion process, assuming the blood vessel centerline represents the overall structural position. The results of the centroid distances showed a minimum value of 0.38 mm, a maximum value of 4.81 mm, and an average of 1.97 mm.

conclusionAlthough the five participants had different CP classifications and the derived US images exhibited individual variability, all centroid distances satisfied the ablation margin of 5.00 mm considered in PRFA, suggesting the potential accuracy and utility of the robotic system for puncture navigation. Additionally, the results suggested the potential generalization performance of the AI model trained with data acquired according to the robotic system's workflow.

Indexed as

Imaging, Three-DimensionalMultimodal ImagingPuncturesRobotic Surgical ProceduresTomography, X-Ray ComputedUltrasonography, InterventionalAdultFemaleHumansMalePilot ProjectsBlood vessel segmentationFusion imagingRobotic puncture systemSurgical robot

Identifiers

PMID40762895
PMCPMC12476430

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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.