Evidence map›Paper›PMID 35084081›Full record

ArticleJournal of applied clinical medical physics2022

Comparison of an in-house hybrid DIR method to NiftyReg on CBCT and CT images for head and neck cancer.

Chunling Jiang, Yuling Huang, Shenggou Ding, Xiaochang Gong, Xingxing Yuan, Shaobin Wang, Jingao Li, Yun Zhang

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Chunling JiangDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.
Yuling HuangDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.
Shenggou DingDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.
Xiaochang GongDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.
Xingxing YuanDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.
Shaobin WangMedMind Technology Co. Ltd., Beijing, P. R. China.
Jingao LiDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.
Yun ZhangDepartment of Radiation Oncology, Jiangxi Cancer Hospital of Nanchang University, Nanchang, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An in-house hybrid deformable image registration (DIR) method, which combines free-form deformation (FFD) and the viscous fluid registration method, is proposed. Its results on the planning computed tomography (CT) and the day 1 treatment cone-beam CT (CBCT) image from 68 head and neck cancer patients are compared with the results of NiftyReg, which uses B-spline FFD alone. Several similarity metrics, the target registration error (TRE) of annotated points, as well as the Dice similarity coefficient (DSC) and Hausdorff distance (HD) of the propagated organs at risk are employed to analyze their registration accuracy. According to quantitative analysis on mutual information, normalized cross-correlation, and the absolute pixel value differences, the results of the proposed DIR are more similar to the CBCT images than the NiftyReg results. Smaller TRE of the annotated points is observed in the proposed method, and the overall mean TRE for the proposed method and NiftyReg was 2.34 and 2.98 mm, respectively (p < 0.001). The mean DSC in the larynx, spinal cord, oral cavity, mandible, and parotid given by the proposed method ranged from 0.78 to 0.91, significantly higher than the NiftyReg results (ranging from 0.77 to 0.90), and the HD was significantly lower compared to NiftyReg. Furthermore, the proposed method did not suffer from unrealistic deformations as the NiftyReg did in the visual evaluation. Meanwhile, the execution time of the proposed method was much higher than NiftyReg (96.98 ± 11.88 s vs. 4.60 ± 0.49 s). In conclusion, the in-house hybrid method gave better accuracy and more stable performance than NiftyReg.

Indexed as

Head and Neck NeoplasmsRadiotherapy, Intensity-ModulatedSpiral Cone-Beam Computed TomographyAlgorithmsCone-Beam Computed TomographyHumansImage Processing, Computer-AssistedRadiotherapy Planning, Computer-AssistedTomography, X-Ray Computedcone-beam CTdeformable image registrationDice similarity coefficientfree-form registrationhead and neck cancersimilarity metricviscous fluid registration

Identifiers

PMID35084081
PMCPMC8906219

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.