Ni He1, Yao-Pan Wu2, Yanan Kong3, Ning Lv4, Zhi-Mei Huang5, Sheng Li6, Yue Wang7, Zhi-Jun Geng8, Pei-Hong Wu9, Wei-Dong Wei10. 1. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: heni@sysucc.org.cn. 2. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: 61684754@qq.com. 3. Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: kongyn@sysucc.org.cn. 4. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: lvning@sysucc.org.cn. 5. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: zhimeih_2015@163.com. 6. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: shengl_2015@163.com. 7. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: yuew_2015@163.com. 8. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: Zhi-jung_2015@163.com. 9. Department of Medical Imaging and Image-guided Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: 409109980@qq.com. 10. Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China. Electronic address: weiweid@mail.sysu.edu.cn.
Abstract
PURPOSE: Breast cone-beam computed tomography (BCBCT) is a flat-panel detector (FPD)-based X-ray imaging system that provides high-quality images of the breast. The purpose of this study was to investigate the ability to detect breast abnormalities using non-contrast BCBCT and contrast-enhanced BCBCT (BCBCT and CE-BCBCT) compared to ultrasound (US) and digital mammography (MG). MATERIALS AND METHODS: A prospective study was performed from May 2012 to August 2014. Ninety-two patients (172 lesions) underwent BCBCT alone, and 120 patients (270 lesions) underwent BCBCT and CE-BCBCT, all the patients underwent US and MG. RESULTS: Cancer diagnosis was confirmed pathologically in 102 patients (110 lesions). BCBCT identified 97 of 110 malignant lesions, whereas 93 malignant lesions were identified using MG and US. The areas under the receiver operating curves (AUCs) for breast cancer diagnosis were 0.861 (BCBCT), 0.856 (US), and 0.829 (MG). CE-BCBCT improved cancer diagnostic sensitivity by 20.3% (78.4-98.7%). The AUC values were 0.869 (CE-BCBCT), 0.846 (BCBCT), 0.834 (US), and 0.782 (MG). CONCLUSION: In this preliminary study, BCBCT was found to accurately identify malignant breast lesions in a diagnostic setting. CE-BCBCT provided additional information and improved cancer diagnosis in style c or d breasts compared to the use of BCBCT, US, or MG alone.
PURPOSE: Breast cone-beam computed tomography (BCBCT) is a flat-panel detector (FPD)-based X-ray imaging system that provides high-quality images of the breast. The purpose of this study was to investigate the ability to detect breast abnormalities using non-contrast BCBCT and contrast-enhanced BCBCT (BCBCT and CE-BCBCT) compared to ultrasound (US) and digital mammography (MG). MATERIALS AND METHODS: A prospective study was performed from May 2012 to August 2014. Ninety-two patients (172 lesions) underwent BCBCT alone, and 120 patients (270 lesions) underwent BCBCT and CE-BCBCT, all the patients underwent US and MG. RESULTS:Cancer diagnosis was confirmed pathologically in 102 patients (110 lesions). BCBCT identified 97 of 110 malignant lesions, whereas 93 malignant lesions were identified using MG and US. The areas under the receiver operating curves (AUCs) for breast cancer diagnosis were 0.861 (BCBCT), 0.856 (US), and 0.829 (MG). CE-BCBCT improved cancer diagnostic sensitivity by 20.3% (78.4-98.7%). The AUC values were 0.869 (CE-BCBCT), 0.846 (BCBCT), 0.834 (US), and 0.782 (MG). CONCLUSION: In this preliminary study, BCBCT was found to accurately identify malignant breast lesions in a diagnostic setting. CE-BCBCT provided additional information and improved cancer diagnosis in style c or d breasts compared to the use of BCBCT, US, or MG alone.
Authors: Seyedamir Tavakoli Taba; Patrycja Baran; Yakov I Nesterets; Serena Pacile; Susanne Wienbeck; Christian Dullin; Konstantin Pavlov; Anton Maksimenko; Darren Lockie; Sheridan C Mayo; Harry M Quiney; Diego Dreossi; Fulvia Arfelli; Giuliana Tromba; Sarah Lewis; Timur E Gureyev; Patrick C Brennan Journal: Eur Radiol Date: 2020-01-23 Impact factor: 5.315
Authors: Jann Wieler; Nicole Berger; Thomas Frauenfelder; Magda Marcon; Andreas Boss Journal: Medicine (Baltimore) Date: 2021-05-07 Impact factor: 1.889