Purpose: Increasing interest in maintaining a positive body image following breast cancer surgery has become an important aspect of reconstruction surgery. Volume matching of the reconstructed breast to natural breasts is the most important consideration. This study aimed to explore the feasibility of using mammography with a fully automated breast volumetric software to measure the preoperative breast volume in patients with breast cancer. Methods: We evaluated patients who underwent a total mastectomy between July 2016 and February 2021. The specimen volume following total mastectomy was compared with breast volume estimates using a fully automated volumetric software (Quantra ver. 2.1.1) and 4 other previously described mammography-based prediction methods. The association between the estimates and mastectomy specimen volume was assessed using Pearson correlation and Bland-Altman analysis. Results: Sixty-six patients were included. Compared with previously described mammography-based methods, Quantra estimates were more strongly correlated with mastectomy specimen volume in the entire, fatty, and dense breast groups (r = 0.920, 0.921, and 0.915, respectively; P < 0.001). In applying Quantra estimates for measuring preoperative breast volume, we adjusted a simple equation: mastectomy specimen volume = Quantra estimate × 0.8. Conclusion Mammography with a fully automated breast volumetric software can be useful for measuring preoperative breast volume in patients with breast cancer who undergo reconstruction surgery.

Purpose: Increasing interest in maintaining a positive body image following breast cancer surgery has become an important aspect of reconstruction surgery. Volume matching of the reconstructed breast to natural breasts is the most important consideration. This study aimed to explore the feasibility of using mammography with a fully automated breast volumetric software to measure the preoperative breast volume in patients with breast cancer. Methods: We evaluated patients who underwent a total mastectomy between July 2016 and February 2021. The specimen volume following total mastectomy was compared with breast volume estimates using a fully automated volumetric software (Quantra ver. 2.1.1) and 4 other previously described mammography-based prediction methods. The association between the estimates and mastectomy specimen volume was assessed using Pearson correlation and Bland-Altman analysis. Results: Sixty-six patients were included. Compared with previously described mammography-based methods, Quantra estimates were more strongly correlated with mastectomy specimen volume in the entire, fatty, and dense breast groups (r = 0.920, 0.921, and 0.915, respectively; P < 0.001). In applying Quantra estimates for measuring preoperative breast volume, we adjusted a simple equation: mastectomy specimen volume = Quantra estimate × 0.8. Conclusion Mammography with a fully automated breast volumetric software can be useful for measuring preoperative breast volume in patients with breast cancer who undergo reconstruction surgery.