MRI to predict nipple-areola complex (NAC) involvement: An automatic method to compute the 3D distance between the NAC and tumor

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Abstract

Objectives: To assess the role in predicting nipple-areola complex (NAC) involvement of a newly developed automatic method which computes the 3D tumor-NAC distance. Patients and Methods: Ninety-nine patients scheduled to nipple sparing mastectomy (NSM) underwent magnetic resonance (MR) examination at 1.5 T, including sagittal T2w and dynamic contrast enhanced (DCE)-MR imaging. An automatic method was developed to segment the NAC and the tumor and to compute the 3D distance between them. The automatic measurement was compared with manual axial and sagittal 2D measurements. NAC involvement was defined by the presence of invasive ductal or lobular carcinoma and/or ductal carcinoma in situ or ductal intraepithelial neoplasia (DIN1c − DIN3). Results: Tumor-NAC distance was computed on 95/99 patients (25 NAC+), as three tumors were not correctly segmented (sensitivity = 97%), and 1 NAC was not detected (sensitivity = 99%). The automatic 3D distance reached the highest area under the receiver operating characteristic (ROC) curve (0.830) with respect to the manual axial (0.676), sagittal (0.664), and minimum distances (0.664). At the best cut-off point of 21 mm, the 3D distance obtained sensitivity = 72%, specificity = 80%, positive predictive value = 56%, and negative predictive value = 89%. Conclusions: This method could provide a reproducible biomarker to preoperatively select breast cancer patients candidates to NSM, thus helping surgical planning and intraoperative management of patients.

Original languageEnglish
Pages (from-to)1069-1078
Number of pages10
JournalJournal of Surgical Oncology
Volume116
Issue number8
DOIs
Publication statusPublished - Dec 15 2017

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Nipples
Neoplasms
Mastectomy
Lobular Carcinoma
Ductal Carcinoma
Carcinoma, Intraductal, Noninfiltrating
ROC Curve

Keywords

  • 3D automatic distance
  • breast cancer
  • magnetic resonance imaging
  • mastectomy
  • nipple-areola sparing
  • tumor segmentation

ASJC Scopus subject areas

  • Surgery
  • Oncology

Cite this

@article{79b4b0242f9c4e6b9566921041516387,
title = "MRI to predict nipple-areola complex (NAC) involvement: An automatic method to compute the 3D distance between the NAC and tumor",
abstract = "Objectives: To assess the role in predicting nipple-areola complex (NAC) involvement of a newly developed automatic method which computes the 3D tumor-NAC distance. Patients and Methods: Ninety-nine patients scheduled to nipple sparing mastectomy (NSM) underwent magnetic resonance (MR) examination at 1.5 T, including sagittal T2w and dynamic contrast enhanced (DCE)-MR imaging. An automatic method was developed to segment the NAC and the tumor and to compute the 3D distance between them. The automatic measurement was compared with manual axial and sagittal 2D measurements. NAC involvement was defined by the presence of invasive ductal or lobular carcinoma and/or ductal carcinoma in situ or ductal intraepithelial neoplasia (DIN1c − DIN3). Results: Tumor-NAC distance was computed on 95/99 patients (25 NAC+), as three tumors were not correctly segmented (sensitivity = 97{\%}), and 1 NAC was not detected (sensitivity = 99{\%}). The automatic 3D distance reached the highest area under the receiver operating characteristic (ROC) curve (0.830) with respect to the manual axial (0.676), sagittal (0.664), and minimum distances (0.664). At the best cut-off point of 21 mm, the 3D distance obtained sensitivity = 72{\%}, specificity = 80{\%}, positive predictive value = 56{\%}, and negative predictive value = 89{\%}. Conclusions: This method could provide a reproducible biomarker to preoperatively select breast cancer patients candidates to NSM, thus helping surgical planning and intraoperative management of patients.",
keywords = "3D automatic distance, breast cancer, magnetic resonance imaging, mastectomy, nipple-areola sparing, tumor segmentation",
author = "Valentina Giannini and Veronica Bianchi and Silvia Carabalona and Simone Mazzetti and Furio Maggiorotto and Franziska Kubatzki and Daniele Regge and Riccardo Ponzone and Laura Martincich",
year = "2017",
month = "12",
day = "15",
doi = "10.1002/jso.24788",
language = "English",
volume = "116",
pages = "1069--1078",
journal = "Journal of Surgical Oncology",
issn = "0022-4790",
publisher = "John Wiley and Sons Inc.",
number = "8",

}

TY - JOUR

T1 - MRI to predict nipple-areola complex (NAC) involvement

T2 - An automatic method to compute the 3D distance between the NAC and tumor

AU - Giannini, Valentina

AU - Bianchi, Veronica

AU - Carabalona, Silvia

AU - Mazzetti, Simone

AU - Maggiorotto, Furio

AU - Kubatzki, Franziska

AU - Regge, Daniele

AU - Ponzone, Riccardo

AU - Martincich, Laura

PY - 2017/12/15

Y1 - 2017/12/15

N2 - Objectives: To assess the role in predicting nipple-areola complex (NAC) involvement of a newly developed automatic method which computes the 3D tumor-NAC distance. Patients and Methods: Ninety-nine patients scheduled to nipple sparing mastectomy (NSM) underwent magnetic resonance (MR) examination at 1.5 T, including sagittal T2w and dynamic contrast enhanced (DCE)-MR imaging. An automatic method was developed to segment the NAC and the tumor and to compute the 3D distance between them. The automatic measurement was compared with manual axial and sagittal 2D measurements. NAC involvement was defined by the presence of invasive ductal or lobular carcinoma and/or ductal carcinoma in situ or ductal intraepithelial neoplasia (DIN1c − DIN3). Results: Tumor-NAC distance was computed on 95/99 patients (25 NAC+), as three tumors were not correctly segmented (sensitivity = 97%), and 1 NAC was not detected (sensitivity = 99%). The automatic 3D distance reached the highest area under the receiver operating characteristic (ROC) curve (0.830) with respect to the manual axial (0.676), sagittal (0.664), and minimum distances (0.664). At the best cut-off point of 21 mm, the 3D distance obtained sensitivity = 72%, specificity = 80%, positive predictive value = 56%, and negative predictive value = 89%. Conclusions: This method could provide a reproducible biomarker to preoperatively select breast cancer patients candidates to NSM, thus helping surgical planning and intraoperative management of patients.

AB - Objectives: To assess the role in predicting nipple-areola complex (NAC) involvement of a newly developed automatic method which computes the 3D tumor-NAC distance. Patients and Methods: Ninety-nine patients scheduled to nipple sparing mastectomy (NSM) underwent magnetic resonance (MR) examination at 1.5 T, including sagittal T2w and dynamic contrast enhanced (DCE)-MR imaging. An automatic method was developed to segment the NAC and the tumor and to compute the 3D distance between them. The automatic measurement was compared with manual axial and sagittal 2D measurements. NAC involvement was defined by the presence of invasive ductal or lobular carcinoma and/or ductal carcinoma in situ or ductal intraepithelial neoplasia (DIN1c − DIN3). Results: Tumor-NAC distance was computed on 95/99 patients (25 NAC+), as three tumors were not correctly segmented (sensitivity = 97%), and 1 NAC was not detected (sensitivity = 99%). The automatic 3D distance reached the highest area under the receiver operating characteristic (ROC) curve (0.830) with respect to the manual axial (0.676), sagittal (0.664), and minimum distances (0.664). At the best cut-off point of 21 mm, the 3D distance obtained sensitivity = 72%, specificity = 80%, positive predictive value = 56%, and negative predictive value = 89%. Conclusions: This method could provide a reproducible biomarker to preoperatively select breast cancer patients candidates to NSM, thus helping surgical planning and intraoperative management of patients.

KW - 3D automatic distance

KW - breast cancer

KW - magnetic resonance imaging

KW - mastectomy

KW - nipple-areola sparing

KW - tumor segmentation

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U2 - 10.1002/jso.24788

DO - 10.1002/jso.24788

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VL - 116

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EP - 1078

JO - Journal of Surgical Oncology

JF - Journal of Surgical Oncology

SN - 0022-4790

IS - 8

ER -