Evidence map›Paper›PMID 34079731›Full record

ArticleQuantitative imaging in medicine and surgery2021

Mixed reality models based on low-dose computed tomography technology in nephron-sparing surgery are better than models based on normal-dose computed tomography.

Guan Li, Zhiqiang Cao, Jinbao Wang, Xin Zhang, Longjiang Zhang, Jie Dong, Guangming Lu

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Visual extended reality tools in image-guided surgery in urology: a systematic review.European journal of nuclear medicine and molecular imaging · 2024
    Pooled it
  2. Trial
  3. Article
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  6. 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

7 authors at 5 institutions in 1 country.

Guan LiDepartment of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
Zhiqiang CaoDepartment of Urology, General Hospital of Northern Theater Command, Shenyang, China.
Jinbao WangDepartment of Radiology, General Hospital of Northern Theater Command, Shenyang, China.
Xin ZhangDepartment of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.
Longjiang ZhangDepartment of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
Jie DongDepartment of Urology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
Guangming LuDepartment of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
General Hospital of Shenyang Military Region · CNNanjing Medical University · CNChina Medical University · CNNanjing General Hospital of Nanjing Military Command · CNNanjing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNephron-sparing surgery has been widely applied in the treatment of renal tumors. Previous studies have confirmed the advantages of mixed reality technology in surgery. The study aimed to explore the optimization of mixed reality technology and its application value in nephron-sparing surgery.

methodsIn this prospective study of 150 patients with complex renal tumors (RENAL nephrometry score ≥7) who underwent nephron-sparing surgery, patients were randomly divided into Group A (the normal-dose mixed reality group, n=50), Group B (the low-dose mixed reality group, n=50), and Group C (the traditional computed tomography image group, n=50). Group A and Group C received the normal-dose computed tomography scan protocol: 120 kVp, 400 mA, and 350 mgI/mL, while Group B received the low-dose computed tomography scan protocol: 80 kVp, automatic tube current modulation, and 320 mgI/mL. All computed tomography data were transmitted to a three-dimensional visualization workstation and underwent modeling and mixed reality imaging. Two senior surgeons evaluated mixed reality quality. Objective indexes and perioperative indexes were calculated and compared.

resultsCompared with Group A, the radiation effective dose in Group B was decreased by 39.6%. The subjective scores of mixed reality quality in Group B were significantly higher than those of Group A (Z=-4.186, P<0.001). The inter-observer agreement between the two senior surgeons in mixed reality quality was excellent (K=0.840, P<0.001). The perioperative indexes showed that the mixed reality groups were significantly different from the computed tomography image group (all P<0.017). More cases underwent nephron-sparing surgery in the mixed reality groups than in the computed tomography image group (P<0.0017).

conclusionsLow-dose computed tomography technology can be effectively applied to mixed reality optimization, reducing the effective dose and improving mixed reality quality. Optimized mixed reality can significantly increase the cases of successful nephron-sparing surgery and improve perioperative indexes.

Indexed as

adherent perinephric fat (APF)computer tomographylow-doseMixed realitynephron-sparing surgery (NSS)

Identifiers

PMID34079731
PMCPMC8107318
OpenAlexW3140514129

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.