Evidence map›Paper›PMID 23783063›Full record

ArticlePlastic and reconstructive surgery2013

Facial appearance transfer and persistence after three-dimensional virtual face transplantation.

Akash A Chandawarkar, J Rodrigo Diaz-Siso, Ericka M Bueno, Camille K Jania, Nathanael D Hevelone, Stuart R Lipsitz, Edward J Caterson, Srinivasan Mukundan, Bohdan Pomahac

Abstract read
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Article in Plastic and reconstructive surgery, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Facial transplantation surgery.Archives of plastic surgery · 2014
    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

9 authors.

Akash A ChandawarkarBoston, Mass. From the Division of Plastic Surgery, the Center for Surgery and Public Health, and the Division of Neuroradiology, Brigham and Women's Hospital and Harvard Medical School.
J Rodrigo Diaz-Siso
Ericka M Bueno
Camille K Jania
Nathanael D Hevelone
Stuart R Lipsitz
Edward J Caterson
Srinivasan Mukundan
Bohdan Pomahac

Funding

Virtual tool to address facial appearance transfer in face transplantationR21DE021892 · NIDCR · BRIGHAM AND WOMEN'S HOSPITAL · PI POMAHAC, BOHDAN · 2012 to 2012
$362k
NIDCR NIH HHS R21 DE021892
6 · The paper itself

Abstract

backgroundFacial appearance transfer from donor to recipient in face transplantation is a concern. Previous studies of facial appearance transfer and facial appearance persistence (preservation of the recipient's facial likeness) in face transplants simulated using two-dimensional photographic manipulations found low facial appearance transfer (2.6 percent) and high facial appearance persistence (66 percent). Three-dimensional computer simulation of complex facial transplant patterns may improve the accuracy of facial appearance transfer and facial appearance persistence estimations.

methodsThree-dimensional virtual models of human faces were generated from deidentified computed tomographic angiographs and used as "donors" or "recipients" for virtual face transplantation. Surgical planning software was used to perform 73 virtual face transplantations by creating specific facial defects (mandibular, midface, or large) in the recipient models and restoring them with allografts extracted from the donor models. Twenty independent reviewers evaluated the resemblance of each resulting posttransplant model to the donor (facial appearance transfer) and recipient (facial appearance persistence). The results were analyzed using tests for equal results with one-sample and pairwise Rao-Scott Pearson chi-square testing, correcting for clustering and multiple testing.

resultsOverall rates of facial appearance persistence and facial appearance transfer were high (69.2 percent) and low (32.4 percent), respectively. The mandibular pattern had the highest rates of facial appearance persistence and lowest rates of facial appearance transfer. Facial appearance persistence and transfer were similar across sexes.

conclusionsFacial appearance persistence is high and facial appearance transfer is low after virtual face transplantation. Appearance transfer and persistence after virtual face transplantation are more dependent on the anatomy than on the size of transplanted facial aesthetic units. This information may reassure recipients of partial face transplants and donor families.

Indexed as

Computer SimulationFacial TransplantationAdultAgedFaceFemaleHumansImaging, Three-DimensionalMaleMiddle AgedPhotographyPredictive Value of TestsYoung Adult

Identifiers

PMID23783063
PMCPMC3788837

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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.