Evidence map›Paper›PMID 31002326›Full record

ArticleJAMA network open2019

Comparison of 3-Dimensional and Augmented Reality Kidney Models With Conventional Imaging Data in the Preoperative Assessment of Children With Wilms Tumors.

Lianne M Wellens, Jene Meulstee, Cornelis P van de Ven, C E J Terwisscha van Scheltinga, Annemieke S Littooij, Marry M van den Heuvel-Eibrink, Marta Fiocco, Anne C Rios, Thomas Maal, Marc H W A Wijnen

Abstract readComparative Study
In one paragraph

Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. The role of Pediatric Surgery in childhood cancer.Revista da Associacao Medica Brasileira (1992) · 2024
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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

10 authors.

Lianne M WellensDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Jene MeulsteeRadboud University Medical Center, Nijmegen, the Netherlands.
Cornelis P van de VenDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
C E J Terwisscha van ScheltingaDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Annemieke S LittooijDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Marry M van den Heuvel-EibrinkDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Marta FioccoDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Anne C RiosDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Thomas MaalRadboud University Medical Center, Nijmegen, the Netherlands.
Marc H W A WijnenDepartment of Pediatric Surgery, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Nephron-sparing surgery can be considered in well-defined cases of unilateral and bilateral Wilms tumors, but the surgical procedure can be very challenging for the pediatric surgeon to perform. Objective: To assess the added value of personalized 3-dimensional (3-D) kidney models derived from conventional imaging data to enhance preoperative surgical planning. Design, Setting, and Participants: In a survey study, the conventional imaging data of 10 Dutch children with Wilms tumors were converted to 3-D prints and augmented reality (AR) holograms and a panel of pediatric oncology surgeons (n = 7) assessed the quality of the different imaging methods during preoperative evaluation. Kidney models were created with 3-D printing and AR using a mixed reality headset for visualization. Main Outcomes and Measures: Differences in the assessment of 4 anatomical structures (tumor, arteries, veins, and urinary collecting structures) using questionnaires. A Likert scale measured differences between the imaging methods, with scores ranging from 1 (completely disagree) to 5 (completely agree). Results: Of the 10 patients, 7 were girls, and the mean (SD) age was 3.7 (1.7) years. Compared with conventional imaging, the 3-D print and the AR hologram models were evaluated by the surgeons to be superior for all anatomical structures: tumor (median scores for conventional imaging, 4.07; interquartile range [IQR], 3.62-4.15 vs 3-D print, 4.67; IQR, 4.14-4.71; P = .008 and AR hologram, 4.71; IQR, 4.26-4.75; P = .002); arteries (conventional imaging, 3.62; IQR, 3.43-3.93 vs 3-D print, 4.54; IQR, 4.32-4.71; P = .002 and AR hologram, 4.83; IQR, 4.64-4.86; P < .001), veins (conventional imaging, 3.46; IQR 3.39-3.62 vs 3-D print, 4.50; IQR, 4.39-4.68; P < .001 and AR hologram, 4.83; IQR, 4.71-4.86; P < .001), and urinary collecting structures (conventional imaging, 2.76; IQR, 2.42-3.00 vs 3-D print, 3.86; IQR, 3.64-4.39; P < .001 and AR hologram, 4.00; IQR, 3.93-4.58; P < .001). There were no differences in anatomical assessment between the two 3-D techniques (the 3-D print and AR hologram). Conclusions and Relevance: In this study, the 3-D kidney models were associated with improved anatomical understanding among the surgeons and can be helpful in future preoperative planning of nephron-sparing surgery for Wilms tumors. These models may be considered as a supplementary visualization in clinical care.

Indexed as

Augmented RealityModels, AnatomicPrinting, Three-DimensionalChild, PreschoolFemaleHolographyHumansKidney NeoplasmsMalePreoperative PeriodWilms Tumor

Identifiers

PMID31002326
PMCPMC6481457

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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.