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Zhang L, Ning N, Liang H, Zhao S, Gao X, Liu A, Song Q, Duan X, Yang J, Xie L. The contrast-free diffusion MRI multiple index for the early prediction of pathological response to neoadjuvant chemotherapy in breast cancer. NMR IN BIOMEDICINE 2024; 37:e5176. [PMID: 38884131 DOI: 10.1002/nbm.5176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 04/21/2024] [Accepted: 04/21/2024] [Indexed: 06/18/2024]
Abstract
Early tumor response prediction can help avoid overtreatment with unnecessary chemotherapy sessions. It is important to determine whether multiple apparent diffusion coefficient indices (S index, ADC-diff) are effective in the early prediction of pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Patients with stage II and III BCs who underwent T1WI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI using a 3 T system were included. They were divided into two groups: major histological responders (MHRs, Miller-Payne G4/5) and nonmajor histological responders (nMHRs, Miller-Payne G1-3). Three b values were used for DWI to derive the S index; ADC-diff values were obtained using b = 0 and 1000 s/mm2. The different interquartile ranges of percentile S-index and ADC-diff values after treatment were calculated and compared. The assessment was performed at baseline and after two and four NAC cycles. A total of 59 patients were evaluated. There are some correlations of interquartile ranges of S-index parameters and ADC-diff values with histopathological prognostic factors (such as estrogen receptor and human epidermal growth factor receptor 2 expression, all p < 0.05), but no significant differences were found in some other interquartile ranges of S-index parameters or ADC-diff values between progesterone receptor positive and negative or for Ki-67 tumors (all P > 0.05). No differences were found in the dynamic contrast-enhanced MRI characteristics between the two groups. HER-2 expression and kurtosis of the S-index distribution were screened out as independent risk factors for predicting MHR group (p < 0.05, area under the curve (AUC) = 0.811) before NAC. After early NAC (two cycles), only the 10th percentile S index was statistically significant between the two groups (p < 0.05, AUC = 0.714). No significant differences were found in ADC-diff value at any time point of NAC between the two groups (P > 0.1). These findings demonstrate that the S-index value may be used as an early predictor of pathological response to NAC in BC; the value of ADC-diff as an imaging biomarker of NAC needs to be further confirmed by ongoing multicenter prospective trials.
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Affiliation(s)
- Lina Zhang
- PET-CT Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Ning Ning
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Hongbing Liang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Siqi Zhao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xue Gao
- Department of Pathology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Ailian Liu
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qingwei Song
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiaoyi Duan
- PET-CT Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jie Yang
- School of Public Health, Dalian Medical University, Dalian, China
| | - Lizhi Xie
- GE Healthcare, MR Research China, Beijing, China
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Chen S, Zheng B, Tang W, Ding S, Sui Y, Yu X, Zhong Z, Kong Q, Liu W, Guo Y. The longitudinal changes in multiparametric MRI during neoadjuvant chemotherapy can predict treatment response early in patients with HER2-positive breast cancer. Eur J Radiol 2024; 178:111656. [PMID: 39098252 DOI: 10.1016/j.ejrad.2024.111656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 07/17/2024] [Accepted: 07/29/2024] [Indexed: 08/06/2024]
Abstract
PURPOSE To investigate whether longitudinal changes in multiparametric MRI can predict early response to neoadjuvant chemotherapy (NAC) for HER2-positive breast cancer (BC) and to further establish quantitative models based on these features. METHODS A total of 164 HER2-positive BC patients from three centers were included. MRI was performed at baseline and after two cycles of NAC (early post-NAC). Clinicopathological characteristics were enrolled. MRI features were evaluated at baseline and early post-NAC, as well as longitudinal changes in multiparametric MRI, including changes in the largest diameter (LD) of the tumor (ΔLD), apparent diffusion coefficient (ADC) values (ΔADC), and time-signal intensity curve (TIC) (ΔTIC). The patients were divided into a training set (n = 95), an internal validation set (n = 31), and an independent external validation set (n = 38). Univariate and multivariate logistic regression analyses were used to identify the independent indicators of pCR, which were then used to establish the clinicopathologic model and combined model. The AUC was used to evaluate the predictive power of the different models and calibration curves were used to evaluate the consistency of the prediction of pCR in different models. Additionally, decision curve analysis (DCA) was employed to determine the clinical usefulness of the different models. RESULTS Two models were enrolled in this study, including the clinicopathologic model and the combined model. The LD at early post-NAC (OR=0.913, 95 % CI=0.953-0.994 p = 0.026), ΔADC (OR=1.005, 95 % CI=1.005-1.008, p = 0.007), and ΔTIC (OR=3.974, 95 % CI=1.276-12.358, p = 0.017) were identified as the best predictors of NAC response. The combined model constructed by the combination of LD at early post-NAC, ΔADC, and ΔTIC showed good predictive performance in the training set (AUC=0.87), internal validation set (AUC=0.78), and external validation set (AUC=0.79), which performed better than the clinicopathologic model in all sets. CONCLUSIONS The changes in multiparametric MRI can predict early treatment response for HER2-positive BC and may be helpful for individualized treatment planning.
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Affiliation(s)
- Siyi Chen
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
| | - Bingjie Zheng
- Department of Radiology, Henan Cancer Hospital, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 150001, China.
| | - Wenjie Tang
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
| | - Shishen Ding
- Department of Radiology, Liuzhou People's Hospital, Guangxi Medical University, Liuzhou 545006, China.
| | - Yi Sui
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
| | - Xiaomeng Yu
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
| | - Zhidan Zhong
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
| | - Qingcong Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou 510630, China.
| | - Weifeng Liu
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
| | - Yuan Guo
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, No.1 Panfu Road, Guangzhou 510180, China.
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Zhang N, Song Q, Liang H, Wang Z, Wu Q, Zhang H, Zhang L, Liu A, Wang H, Wang J, Lin L. Early prediction of pathological response to neoadjuvant chemotherapy of breast tumors: a comparative study using amide proton transfer-weighted, diffusion weighted and dynamic contrast enhanced MRI. Front Med (Lausanne) 2024; 11:1295478. [PMID: 38298813 PMCID: PMC10827983 DOI: 10.3389/fmed.2024.1295478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 01/05/2024] [Indexed: 02/02/2024] Open
Abstract
Objective To examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer. Materials In this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups. Results APT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax). Conclusion APTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment.
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Affiliation(s)
- Nan Zhang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Hongbing Liang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Zhuo Wang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Qi Wu
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Haonan Zhang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Lina Zhang
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Huali Wang
- Department of Pathology, First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Jiazheng Wang
- MSC Clinical and Technical Solutions, Philips Healthcare, Beijing, China
| | - Liangjie Lin
- MSC Clinical and Technical Solutions, Philips Healthcare, Beijing, China
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van der Hoogt KJJ, Schipper RJ, Winter-Warnars GA, Ter Beek LC, Loo CE, Mann RM, Beets-Tan RGH. Factors affecting the value of diffusion-weighted imaging for identifying breast cancer patients with pathological complete response on neoadjuvant systemic therapy: a systematic review. Insights Imaging 2021; 12:187. [PMID: 34921645 PMCID: PMC8684570 DOI: 10.1186/s13244-021-01123-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 11/06/2021] [Indexed: 12/18/2022] Open
Abstract
This review aims to identify factors causing heterogeneity in breast DWI-MRI and their impact on its value for identifying breast cancer patients with pathological complete response (pCR) on neoadjuvant systemic therapy (NST). A search was performed on PubMed until April 2020 for studies analyzing DWI for identifying breast cancer patients with pCR on NST. Technical and clinical study aspects were extracted and assessed for variability. Twenty studies representing 1455 patients/lesions were included. The studies differed with respect to study population, treatment type, DWI acquisition technique, post-processing (e.g., mono-exponential/intravoxel incoherent motion/stretched exponential modeling), and timing of follow-up studies. For the acquisition and generation of ADC-maps, various b-value combinations were used. Approaches for drawing regions of interest on longitudinal MRIs were highly variable. Biological variability due to various molecular subtypes was usually not taken into account. Moreover, definitions of pCR varied. The individual areas under the curve for the studies range from 0.50 to 0.92. However, overlapping ranges of mean/median ADC-values at pre- and/or during and/or post-NST were found for the pCR and non-pCR groups between studies. The technical, clinical, and epidemiological heterogeneity may be causal for the observed variability in the ability of DWI to predict pCR accurately. This makes implementation of DWI for pCR prediction and evaluation based on one absolute ADC threshold for all breast cancer types undesirable. Multidisciplinary consensus and appropriate clinical study design, taking biological and therapeutic variation into account, is required for obtaining standardized, reliable, and reproducible DWI measurements for pCR/non-pCR identification.
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Affiliation(s)
- Kay J J van der Hoogt
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands. .,GROW School of Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands.
| | - Robert J Schipper
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Gonneke A Winter-Warnars
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Leon C Ter Beek
- Department of Medical Physics, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Claudette E Loo
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Ritse M Mann
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,GROW School of Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands.,Danish Colorectal Cancer Unit South, Institute of Regional Health Research, Vejle University Hospital, University of Southern Denmark, Odense, Denmark
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High-Resolution DWI with Simultaneous Multi-Slice Readout-Segmented Echo Planar Imaging for the Evaluation of Malignant and Benign Breast Lesions. Diagnostics (Basel) 2021; 11:diagnostics11122273. [PMID: 34943509 PMCID: PMC8700489 DOI: 10.3390/diagnostics11122273] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/29/2021] [Accepted: 11/30/2021] [Indexed: 11/19/2022] Open
Abstract
To investigate the feasibility and effectiveness of high-resolution readout-segmented echo planar imaging (rs-EPI), diffusion-weighted imaging (DWI) is used simultaneously with multi-slice (SMS) imaging (SMS rs-EPI) for the differentiation of breast malignant and benign lesions in comparison to conventional rs-EPI on a 3T MR scanner. A total of 102 patients with 113 breast lesions underwent bilateral breast MRI using a prototype SMS rs-EPI sequence and a conventional rs-EPI sequence. Subjective image quality was assessed using a 5-point Likert scale (1 = poor, 5 = excellent). Signal-to-noise ratio (SNR), lesion contrast-to-noise ratio (CNR) and apparent diffusion coefficients (ADC) value of the lesion were measured for comparison. Receiver operating characteristic curve analysis was performed to evaluate the diagnosis performance of ADC, and the corresponding area under curve (AUC) was calculated. The image quality scores in anatomic distortion, lesion conspicuity, sharpness of anatomical details and overall image quality of SMS rs-EPI were significantly higher than those of conventional rs-EPI. CNR was enhanced in the high-resolution SMS rs-EPI acquisition (6.48 ± 1.71 vs. 4.23 ± 1.49; p < 0.001). The mean ADC value was comparable in SMS rs-EPI and conventional rs-EPI (benign 1.45 × 10−3 vs. 1.43 × 10−3 mm2/s, p = 0.702; malignant 0.91 × 10−3 vs. 0.89 × 10−3 mm2/s, p = 0.076). The AUC was 0.957 in SMS rs-EPI and 0.983 in conventional rs-EPI. SMS rs-EPI technique allows for higher spatial resolution and slight reduction of scan time in comparison to conventional rs-EPI, which has potential for better differentiation between malignant and benign lesions of the breast.
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Li Z, Li J, Lu X, Qu M, Tian J, Lei J. The diagnostic performance of diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging in evaluating the pathological response of breast cancer to neoadjuvant chemotherapy: A meta-analysis. Eur J Radiol 2021; 143:109931. [PMID: 34492627 DOI: 10.1016/j.ejrad.2021.109931] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/10/2021] [Accepted: 08/18/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE To evaluate and compare the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the pathological response of breast cancer to neoadjuvant chemotherapy (NAC). METHODS We searched PubMed, EMBASE, Cochrane Library, and Web of Science systematically to identify relevant studies from inception to December 2020. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodological quality of the included studies. We extracted sufficient data to construct 2 × 2 tables and then used STATA 12.0 to perform data pooling, heterogeneity testing, meta-regression analysis and subgroup analysis. RESULTS A total of 41 articles were enrolled in this study, including 27 studies (2107 patients) on DCE-MRI and 23 studies (1321 patients) on DWI. The pooled sensitivity and specificity of DCE-MRI were 0.75 and 0.79, and the pooled sensitivity and specificity of DWI were 0.77 and 0.75. There was no significant difference in sensitivity (P = 0.598) and specificity (P = 0.218) between DCE-MRI and DWI. And meta-regression analysis showed that both magnetic field strength and the time of examination had significant effects on heterogeneity. CONCLUSIONS DWI might be a potential substitute for DCE-MRI in predicting the pathological response of breast cancer to NAC as there was no significant difference in the diagnostic performance between the two. However, considering that not all included studies directly compared the diagnostic performance of DWI and DCE-MRI in the same patients and the heterogeneity of the included studies, caution should be exercised in applying our results.
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Affiliation(s)
- Zhifan Li
- The first Clinical Medical College of Lanzhou University, Lanzhou 730000, China; First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Jinkui Li
- The first Clinical Medical College of Lanzhou University, Lanzhou 730000, China; First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Xingru Lu
- First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Mengmeng Qu
- The first Clinical Medical College of Lanzhou University, Lanzhou 730000, China; First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China; Key Laboratory of Evidence-based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou 730000, China.
| | - Junqiang Lei
- First Hospital of Lanzhou University, Lanzhou 730000, China.
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Duric N, Littrup P, Sak M, Li C, Chen D, Roy O, Bey-Knight L, Brem R. A Novel Marker, Based on Ultrasound Tomography, for Monitoring Early Response to Neoadjuvant Chemotherapy. JOURNAL OF BREAST IMAGING 2020; 2:569-576. [PMID: 33385161 DOI: 10.1093/jbi/wbaa084] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To evaluate the combination of tumor volume and sound speed as a potential imaging marker for assessing neoadjuvant chemotherapy (NAC) response. METHODS This study was carried out under an IRB-approved protocol (written consent required). Fourteen patients undergoing NAC for invasive breast cancer were examined with ultrasound tomography (UST) throughout their treatment. The volume (V) and the volume-averaged sound speed (VASS) of the tumors and their changes were measured for each patient. Time-dependent response curves of V and VASS were constructed individually for each patient and then as averages for the complete versus partial response groups in order to characterize differences between the two groups. Differences in group means were assessed for statistical significance using t-tests. Differences in shapes of group curves were evaluated with Kolmogorov-Smirnoff tests. RESULTS On average, tumor volume and sound speed in the partial response group showed a gradual decline in the first 60 days of treatment, while the complete response group showed a much steeper decline (P < 0.05). The shapes of the response curves of the two groups, corresponding to the entire treatment period, were also found to be significantly different (P < 0.05). Furthermore, large simultaneous drops in volume and sound speed in the first 3 weeks of treatment were characteristic only of the complete responders (P < 0.05). CONCLUSION This study demonstrates the feasibility of using UST to monitor NAC response, warranting future studies to better define the potential of UST for noninvasive, rapid identification of partial versus complete responders in women undergoing NAC.
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Affiliation(s)
- Neb Duric
- Delphinus Medical Technologies, Inc., Novi, MI.,Wayne State University, Barbara Ann Karmanos Cancer Institute, Department of Oncology, Detroit, MI
| | - Peter Littrup
- Delphinus Medical Technologies, Inc., Novi, MI.,Wayne State University, Barbara Ann Karmanos Cancer Institute, Department of Oncology, Detroit, MI
| | - Mark Sak
- Delphinus Medical Technologies, Inc., Novi, MI
| | - Cuiping Li
- Delphinus Medical Technologies, Inc., Novi, MI
| | - Di Chen
- Delphinus Medical Technologies, Inc., Novi, MI
| | - Olivier Roy
- Delphinus Medical Technologies, Inc., Novi, MI
| | - Lisa Bey-Knight
- Delphinus Medical Technologies, Inc., Novi, MI.,Wayne State University, Barbara Ann Karmanos Cancer Institute, Department of Oncology, Detroit, MI
| | - Rachel Brem
- George Washington University, Department of Radiology, Washington, DC
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