Evidence map›Paper›PMID 34363584›Full record

ArticleInternational journal of computer assisted radiology and surgery2021

Intelligent optical diagnosis and treatment system for automated image-guided laser ablation of tumors.

Yangxi Li, Yingwei Fan, Chengquan Hu, Fan Mao, Xinran Zhang, Hongen Liao

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 32% of its field
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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. The State-of-the-Art and Perspectives of Laser Ablation for Tumor Treatment.Cyborg and bionic systems (Washington, D.C.) · 2024
    Article
  7. Review
  8. Article
  9. 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

6 authors at 2 institutions in 1 country.

Yangxi Li *Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
Yingwei Fan *Beijing Institute of Radiation Medicine, Beijing, China.
Chengquan HuDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
Fan MaoDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
Xinran ZhangDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
Hongen LiaoDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China. liao@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-3847-9347
Tsinghua University · CNBeijing Radiation Center · CN

Funding

Beijing Municipal Natural Science Foundation 7212202National Natural Science Foundation of China 81771940National Natural Science Foundation of China 81901907National Natural Science Foundation of China 82027807
6 · The paper itself

Abstract

purposeFor tumor resections near critical structures, accurate identification of tumor boundaries and maximum removal are the keys to improve surgical outcome and patient survival rate, especially in neurosurgery. In this paper, we propose an intelligent optical diagnosis and treatment system for tumor removal, with automated lesion localization and laser ablation.

methodsThe proposed system contains a laser ablation module, an optical coherence tomography (OCT) unit, and a robotic arm along with a stereo camera. The robotic arm can move the OCT sample arm and the laser ablation front-end to the suspected lesion area. The corresponding diagnosis and treatment procedures include computer-aided lesion segmentation using OCT, automated ablation planning, and laser control. The ablation process is controlled by a deflectable mirror, and a non-common-path ablation planning algorithm based on the transformation from lesion positions to mirror deflection angles is presented.

resultsPhantom and animal experiments are carried out for system verification. The robot could reach the planned position with high precision, which is approximately 1.16 mm. Tissue classification with OCT images achieves 91.7% accuracy. The error of OCT-guided automated laser ablation is approximately 0.74 mm. Experiments on mouse brain tumors show that the proposed system is capable of clearing lesions efficiently and precisely. We also conducted an ex vivo porcine brain experiment to verify the whole process of the system.

conclusionAn intelligent optical diagnosis and treatment system is proposed for tumor removal. Experimental results show that the proposed system and method are promising for precise and intelligent theranostics. Compared to conventional cancer diagnosis and treatment, the proposed system allows for automated operations monitored in real-time, with higher precision and efficiency.

Indexed as

Brain NeoplasmsLaser TherapyNeurosurgeryAnimalsHumansMiceNeurosurgical ProceduresSwineTomography, Optical CoherenceImage-guided treatmentIntelligent theranosticsLaser ablationOptical coherence tomography

Identifiers

PMID34363584
OpenAlexW3191061226

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.