Evidence map›Paper›PMID 39387846›Full record

ArticleMedical physics2025

Multi-stage automatic and rapid ablation and needle trajectory planning method for CT-guided percutaneous liver tumor ablation.

Shengwei Li, Fanyu Zhou, Yumeng Zhang, Sheng Xu, Yufeng Wang, Lin Cheng, Zhixin Bie, Bin Li, Xiao-Guang Li

Abstract read
In one paragraph

Article in Medical physics, 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
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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

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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.

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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

9 authors.

Shengwei LiMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-9067-6826
Fanyu ZhouResearch and Development Center, Hygea Medical Technology Co., Ltd., Beijing, China.
Yumeng ZhangResearch and Development Center, Hygea Medical Technology Co., Ltd., Beijing, China.
Sheng XuMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Yufeng WangMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Lin ChengMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Zhixin BieMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Bin LiMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Xiao-Guang LiMinimally Invasive Tumor Therapy Center, Beijing Hospital, National Center of Gerontology Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-3345-1313

Funding

National High Level Hospital Clinical Research Funding BJ-2022-106
6 · The paper itself

Abstract

backgroundComputer-assisted planning methods have increasingly contributed to preoperative ablation planning; however, these methods cannot automatically obtain the final optimal solution within a short time and are rarely validated in practice, greatly limiting their clinical applicability. PURPOSE: We aimed to propose a full-automatic multi-stage ablation and needle trajectory planning method for CT-guided percutaneous liver ablation to attain the final optimal plans under multiple clinical constraints rapidly.

methodsOur proposed method integrates the ablation zone planning fulfilling complete tumor coverage and critical structure avoidance while reaching a trade-off between ablation number and healthy tissue damage, and needle trajectory planning under multiple clinical constraints. Our needle trajectory planning determines feasible skin entry regions based on hard constraints, where the multi-objective optimization (MOO) considering soft constraints is performed using the Pareto Optimality and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods for the final optimal solution. The performance of our proposed method was evaluated on 30 tumors of various characteristics from 23 patients and clinically validated in five clinical cases.

resultsOur proposed method achieved 99.8% treatment zone coverage and 40.5% ablation efficiency without involving critical structures, and completely satisfied multiple clinical constraints in all needle trajectory planning results. The average planning time was 23.6 s for tumors of different sizes. All the plans were considered clinically acceptable by the doctors' evaluation. Our method achieved complete tumor coverage without complications in clinical case validation.

conclusionOur proposed planning method can generate a final optimal plan satisfying multiple clinical constraints within a short time, potentially facilitating preoperative planning for hepatic tumor ablation.

Indexed as

Ablation TechniquesLiver NeoplasmsSurgery, Computer-AssistedTomography, X-Ray ComputedAutomationHumansNeedlesTime Factorscomputer‐assisted ablation planningliver tumorneedle trajectory planning

Identifiers

PMID39387846
PMCPMC11700007

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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.