This study develops an objective breast symmetry evaluation using 3-D surface imaging (Konica-Minolta V910(®) scanner) by superimposing the mirrored left breast over the right and objectively determining the mean 3-D contour difference between the 2 breast surfaces. 3 observers analyzed the evaluation protocol precision using 2 dummy models (n = 60), 10 test subjects (n = 300), clinically tested it on 30 patients (n = 900) and compared it to established 2-D measurements on 23 breast reconstructive patients using the BCCT.core software (n = 690). Mean 3-D evaluation precision, expressed as the coefficient of variation (VC), was 3.54 ± 0.18 for all human subjects without significant intra- and inter-observer differences (p > 0.05). The 3-D breast symmetry evaluation is observer independent, significantly more precise (p < 0.001) than the BCCT.core software (VC = 6.92 ± 0.88) and may play a part in an objective surgical outcome analysis after incorporation into clinical practice.
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 (ρ = 0.804) and the sternal notch to nipple distance (ρ = 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.
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