Is the Vectra 3D Imaging System a Reliable Tool for Predicting Breast Mass?

Autor:	Wood KL; From the University of Wisconsin School of Medicine and Public Health, Madison, WI., Zoghbi Y; Division of Plastic and Reconstructive Surgery, Icahn School of Medicine at Mount Sinai, New York., Margulies IG; New York Medical College, Valhalla., Ashikari AY; Ashikari Breast Center, St John's Riverside Health System, Yonkers, NY., Jacobs J; Division of Plastic and Reconstructive Surgery, Icahn School of Medicine at Mount Sinai, New York., Salzberg CA; Division of Plastic and Reconstructive Surgery, Icahn School of Medicine at Mount Sinai, New York.
Jazyk:	angličtina
Zdroj:	Annals of plastic surgery [Ann Plast Surg] 2020 Jul; Vol. 85 (S1 Suppl 1), pp. S109-S113.
DOI:	10.1097/SAP.0000000000002333
Abstrakt:	Background: In selecting breast implants for breast reconstruction, current preoperative planning largely relies on 2-dimensional measurements, which are often limited in suboptimal accuracy and objectivity. Although the introduction of 3-dimensional imaging modalities has further improved preoperative planning, they require in-depth analysis of accuracy if they are to be considered as a standardized part of preoperative planning. Thus, the present study analyzes the reliability of the Vectra 3D Imaging System in predicting breast mass and explores potential confounding variables that may limit its accuracy. Methods: A retrospective review of 202 breasts that received direct-to-implant reconstruction by a single surgeon between February 2015 and February 2019 was conducted. Variables recorded included Vectra predicted mass (VPM; in grams), mastectomy mass (MM; in grams), ptosis grade, and body mass index (BMI). Body mass index was classified as follows: underweight (BMI < 20 kg/m), normal (20 kg/m ≤ BMI < 25 kg/m), overweight (25 kg/m ≤ BMI < 30 kg/m), and obese (BMI ≥ 30 kg/m). Cup size was approximated as follows: A and smaller (MM ≤250 g), B (250 g < MM ≤ 450 g), C (450 g < MM ≤ 600 g), and D and larger (MM ≥ 600 g). Correlation between MM and VPM was evaluated using 2-tailed Pearson correlation coefficients (r), and associated formula was derived from a linear model. Equality of variances was assessed with the Bartlett test. Correlation coefficients calculated for ptosis and BMI categories were then compared with the overall correlation coefficient. Significance was set at α = 0.05, and analyses were conducted in R 3.6.0, version 1.70. Results: There was a strong correlation between MM and VPM (R = 0.90, P < 0.0001). The following equation was derived to predict MM: [MM] = 0.8 × [VPM] + 32 (adjusted r = 0.81). The Bartlett test indicated that VPM varies significantly across cup sizes (P < 0.0001). Comparison of correlation coefficients for ptosis and BMI categories revealed a significantly reduced correlation coefficient for pseudoptosis (0.90 vs 0.75, P = 0.0425). Conclusions: The present study suggests that the reliability of Vectra in predicting breast mass varies across cup sizes and that there exists a significantly decreased association between VPM and MM among pseudoptotic breasts. These are important considerations when using this technology in surgical planning.
Databáze:	MEDLINE
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