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Title:

Prediction of breast resection weight in reduction mammaplasty based on 3-dimensional surface imaging.

Document type:
Journal Article
Author(s):
Eder, M; Grabhorn, A; Waldenfels, FV; Schuster, T; Papadopulos, NA; Machens, HG; Kovacs, L
Abstract:
Prediction of resection weight (RW) in reduction mammaplasty is helpful in achieving breast symmetry and in fulfilling the stringent reimbursement requirements of health insurance companies. Current breast volume estimations are largely based on surgeon's experience, which are partially unreliable and often cumbersome to obtain. Therefore, this study aims to develop a formula to predict RW based on 3D surface imaging. A total of 68 breasts were treated with bilateral T-scar, and 40 breasts were treated with bilateral or unilateral vertical-scar reduction mammaplasty. Linear distances and volume measurements were assessed 3-dimensionally preoperatively and 6 months postoperatively. Significant correlations between the RW and the calculated preoperative breast volume (? = 0.804) and the sternal notch to nipple distance (? = 0.839) were found in both techniques (P < .001). Regression equations with the RW were performed to derive prediction formulas. Surgeons may benefit from the formulas in terms of improvement in preoperative planning, dealing with insurance coverage questions, and optimizing patient consultation.
Journal title abbreviation:
Surg Innov
Year:
2013
Journal volume:
20
Journal issue:
4
Pages contribution:
356-64
Language:
eng
Fulltext / DOI:
doi:10.1177/1553350612460127
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/22983806
Print-ISSN:
1553-3506
TUM Institution:
Institut für Medizinische Statistik und Epidemiologie; Lehrstuhl für Plastische Chirurgie und Handchirurgie (Prof. Machens)
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