Patient satisfaction with implant based breast reconstruction associated with implant volume and mastectomy specimen weight ratio

Woo Yeol Baek, Il Hwan Byun, Young Seok Kim, Dae Hyun Lew, Joon Jeong, Tai Suk Roh

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: Breast volume assessment is one of the most important steps during implant-based breast reconstruction because it is critical in selecting implant size. According to previous studies, there is a close relationship between the mastectomy specimen weight and resected breast volume. The aim of this study was to evaluate long-term patient satisfaction with implant-based breast reconstruction guided by the ratio of implant volume to mastectomy specimen weight. In doing so, we describe the ideal ratio for patient satisfaction. Methods: A total of 84 patients who underwent implant-based breast reconstruction for breast cancer were included in this study. The patients were grouped by the ratio of implant size to mastectomy specimen weight (group 1, <65%; group 2, 65%–75%; and group 3, > 75%). Outcome analysis was performed using a questionnaire of patient satisfaction and the desired implant size. Results: Pa tient satisfaction scores concerning the postoperative body image, size, and position of the reconstructed breast were significantly higher in group 2. The average ratio of the ideal implant volume to mastectomy specimen weight for each group was 71.9% (range, 54.5%–96.7%), with the differences across the three groups being not significant (p= 0.244). Conclusion: Since there is an increase in breast reconstruction, selecting the appropriate breast implant is undoubtedly important. Our novel technique using the ratio of implant volume to mastectomy specimen weight provides physicians a firm guide to intraoperative selection of the proper implant in reconstructive breast surgery.

Original languageEnglish
Pages (from-to)98-103
Number of pages6
JournalJournal of Breast Cancer
Volume20
Issue number1
DOIs
Publication statusPublished - 2017 Mar

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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