Related Experiment Video
Updated: Jun 1, 2025
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Dual-layer detector spectral computed tomography quantitative parameters for predicting pathological complete
Shaolan Guo1,2, Dandan Wang3, Qian Zhao4
1Department of Radiation Oncology Physics & Technology, Cancer Hospital of Shandong First Medical University, Jinan, China.
Background:
Breast cancer (BC) is a common cancer among women worldwide, and although the use of neoadjuvant therapy (NAT) for BC has become more widespread, there is no standardized prediction of the efficacy of NAT for BC. This study aimed to evaluate the value of quantitative parameters of dual-layer detector spectral computed tomography (DLCT) in predicting whether BC patients can achieve pathological complete response (pCR) after NAT.
Methods:
Patients who were first diagnosed with BC in Shandong Cancer Hospital and Institute and received only NAT before surgery were selected for participation in this study. All breast computed tomography (CT) imaging examinations were performed using DLCT, within 1 week before initiating NAT. The gold standard for evaluating the effect of NAT is pathologic response established at surgery. The Miller-Payne grading system was applied to assess the response to NAT. Quantitative parameters were extracted from DLCT, including CT value, normalized CT value, iodine concentration (IC), normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit (HU) curve, effective atomic number, and the normalized effective atomic number. The Mann-Whitney U test was used to compare the distribution differences of DLCT quantitative parameters between the pCR group and the non-pCR group. The diagnostic performance of the quantitative parameters was analyzed by receiver operating characteristic curve.
Results:
In the neoadjuvant chemotherapy group (n=80), compared with the non-pCR group, the slope of the spectral HU curve, IC, effective atomic number, and NIC of arterial phase in the pCR group were higher, and the difference was statistically significant (P<0.05); area under the curve (AUC): 0.768, 0.791, 0.834, and 0.770, respectively. In the neoadjuvant targeted therapy group (n=40), compared with the pCR group, the CT value, IC, effective atomic number, and NIC of the arterial phase in the non-pCR group were higher, and the difference was statistically significant (P<0.05); AUC: 0.844, 0.813, 0.802, and 0.766, respectively. There was no significant difference (P>0.05) in DLCT venous phase quantitative parameters between pCR and non-pCR in 70 patients treated with NAT.
Conclusions:
The study suggested a possibility that DLCT provided a potential tool to develop a model for predicting pCR to NAT in BC.
