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Iima M, Kataoka M, Honda M, Le Bihan D. Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer. Korean J Radiol 2024; 25:623-633. [PMID: 38942456 PMCID: PMC11214919 DOI: 10.3348/kjr.2023.1188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 02/28/2024] [Accepted: 04/11/2024] [Indexed: 06/30/2024] Open
Abstract
This study systematically reviewed the role of diffusion-weighted imaging (DWI) in the assessment of molecular prognostic biomarkers in breast cancer, focusing on the correlation of apparent diffusion coefficient (ADC) with hormone receptor status and prognostic biomarkers. Our meta-analysis includes data from 52 studies examining ADC values in relation to estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki-67 status. The results indicated significant differences in ADC values among different receptor statuses, with ER-positive, PgR-positive, HER2-negative, and Ki-67-positive tumors having lower ADC values compared to their negative counterparts. This study also highlights the potential of advanced DWI techniques such as intravoxel incoherent motion and non-Gaussian DWI to provide additional insights beyond ADC. Despite these promising findings, the high heterogeneity among the studies underscores the need for standardized DWI protocols to improve their clinical utility in breast cancer management.
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Affiliation(s)
- Mami Iima
- Department of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine, Nagoya, Japan
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
- Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan
| | - Denis Le Bihan
- NeuroSpin, Joliot Institute, Department of Fundamental Research, Commissariat à l'Energie Atomique (CEA)-Saclay, Gif-sur-Yvette, France
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Ba R, Wang X, Zhang Z, Li Q, Sun Y, Zhang J, Wu D. Diffusion-time dependent diffusion MRI: effect of diffusion-time on microstructural mapping and prediction of prognostic features in breast cancer. Eur Radiol 2023; 33:6226-6237. [PMID: 37071169 DOI: 10.1007/s00330-023-09623-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 12/14/2022] [Accepted: 02/14/2023] [Indexed: 04/19/2023]
Abstract
OBJECTIVES This study aimed to evaluate the effect of achievable td on the accuracy of microstructural mapping based on simulation and patient experiments, and investigate the feasibility of td-dMRI in distinguishing prognostic factors in breast cancer patients. METHODS Simulation was performed using different td settings. Patients with breast cancer were enrolled prospectively between November 2020 and January 2021, who underwent oscillating and pulsed gradient encoded dMRI on a 3-T scanner using short-/long-td protocol with oscillating frequency up to 50/33 Hz. Data were fitted with a two-compartment model to estimate cell diameter (d), intracellular fraction (fin), and diffusivities. Estimated microstructural markers were used to differentiate immunohistochemical receptor status and the presence of lymph node (LN), which were correlated with histopathological measurements. RESULTS Simulation results showed that d fitted from the short-td protocol significantly reduced estimation error than those from long-td (2.07 ± 1.51% versus 3.05 ± 1.92%, p < 0.0001) while the estimation error of fin was robust to different protocols. Among a total of 37 breast cancer patients, the estimated d was significantly higher in HER2-positive and LN-positive (p < 0.05) groups compared to their negative counterparts only using the short-td protocol. Histopathological validation in a subset of 6 patients with whole slide images showed the estimated d was highly correlated with measurements from H&E staining (r = 0.84, p = 0.03) only using the short-td protocol. CONCLUSIONS The results indicated the necessity of short-td for accurate microstructural mapping in breast cancer. The current td-dMRI with a total acquisition time of 4.5 min showed its potential in the diagnosis of breast cancer. KEY POINTS • Short td is important for accurate microstructural mapping in breast cancer using the td-dMRI technique, based on simulation and histological validation. • The 4.5-min td-dMRI protocol showed potential clinical value for breast cancer, given the difference in cell diameter between HER2/LN positive and negative groups.
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Affiliation(s)
- Ruicheng Ba
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Room 525, Zhou Yiqing Building, Yuquan Campus, Hangzhou, 310027, China
| | - Xiaoxia Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Zelin Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Room 525, Zhou Yiqing Building, Yuquan Campus, Hangzhou, 310027, China
| | - Qing Li
- MR Collaborations, Siemens Healthineers Ltd., Shanghai, China
| | - Yi Sun
- MR Collaborations, Siemens Healthineers Ltd., Shanghai, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Room 525, Zhou Yiqing Building, Yuquan Campus, Hangzhou, 310027, China.
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Orguc S, Açar ÇR. Correlation of Shear-Wave Elastography and Apparent Diffusion Coefficient Values in Breast Cancer and Their Relationship with the Prognostic Factors. Diagnostics (Basel) 2022; 12:diagnostics12123021. [PMID: 36553027 PMCID: PMC9776617 DOI: 10.3390/diagnostics12123021] [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: 10/13/2022] [Revised: 11/26/2022] [Accepted: 11/30/2022] [Indexed: 12/03/2022] Open
Abstract
Background: Diffusion-weighted imaging and elastography are widely accepted methods in the evaluation of breast masses, however, there is very limited data comparing the two methods. The apparent diffusion coefficient is a measure of the diffusion of water molecules obtained by diffusion-weighted imaging as a part of breast MRI. Breast elastography is an adjunct to conventional ultrasonography, which provides a noninvasive evaluation of the stiffness of the lesion. Theoretically, increased tissue density and stiffness are related to each other. The purpose of this study is to compare MRI ADC values of the breast masses with quantitative elastography based on ultrasound shear wave measurements and to investigate their possible relation with the prognostic factors and molecular subtypes. Methods: We retrospectively evaluated histopathologically proven 147 breast lesions. The molecular classification of malignant lesions was made according to the prognostic factors. Shear wave elastography was measured in kiloPascal (kPa) units which is a quantitative measure of tissue stiffness. DWI was obtained using a 1.5-T MRI system. Results: ADC values were strongly inversely correlated with elasticity (r = −0.662, p < 0.01) according to Pearson Correlation. In our study, the cut-off value of ADC was 1.00 × 10−3 cm2/s to achieve a sensitivity of 84.6% and specificity of 75.4%, and the cut-off value of elasticity was 105.5 kPa to achieve the sensitivity of 96.3% and specificity 76.9% to discriminate between the malignant and benign breast lesions. The status of prognostic factors was not correlated with the ADC values and elasticity. Conclusions: Elasticity and ADC values are correlated. Both cannot predict the status of prognostic factors and differentiate between molecular subtypes.
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Mendez AM, Fang LK, Meriwether CH, Batasin SJ, Loubrie S, Rodríguez-Soto AE, Rakow-Penner RA. Diffusion Breast MRI: Current Standard and Emerging Techniques. Front Oncol 2022; 12:844790. [PMID: 35880168 PMCID: PMC9307963 DOI: 10.3389/fonc.2022.844790] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.
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Affiliation(s)
- Ashley M. Mendez
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Lauren K. Fang
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Claire H. Meriwether
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Summer J. Batasin
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Stéphane Loubrie
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Ana E. Rodríguez-Soto
- Department of Radiology, University of California San Diego, La Jolla, CA, United States
| | - Rebecca A. Rakow-Penner
- Department of Radiology, University of California San Diego, La Jolla, CA, United States,Department of Bioengineering, University of California San Diego, La Jolla, CA, United States,*Correspondence: Rebecca A. Rakow-Penner,
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Xue M, Che S, Tian Y, Xie L, Huang L, Zhao L, Guo N, Li J. Nomogram Based on Breast MRI and Clinicopathologic Features for Predicting Axillary Lymph Node Metastasis in Patients with Early-Stage Invasive Breast Cancer: A Retrospective Study. Clin Breast Cancer 2021; 22:e428-e437. [PMID: 34865995 DOI: 10.1016/j.clbc.2021.10.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 01/01/2023]
Abstract
INTRODUCTION To establish a nomogram for predicting axillary lymph node (ALN) involvement in patients with early-stage invasive breast cancer (BC) based on magnetic resonance imaging (MRI) features and clinicopathological characteristics. MATERIALS AND METHODS Patients with confirmed early-stage invasive BC between 03/2016 and 05/2017 were retrospectively reviewed at the National Cancer Center/Cancer Hospital. Risk factors for ALN metastasis (ALNM) were identified by univariable and multivariable logistic regression analysis. The independent risk factors were used to create a nomogram. RESULTS This study included 214 early-stage invasive BC patients, including 57 (26.6%) with positive ALNs. Tumor location (OR = 4.019, 95% CI: 1.304 -12.383, P = .015), tumor size (OR = 3.702, 95%CI: 1.517 -9.034, P = .004), multifocality (OR = 3.534, 95%CI: 1.249 -9.995, P = .017), MR-reported suspicious ALN (OR = 9.829, 95%CI: 4.132 -23.384, P <0.001), apparent diffusion coefficient (ADC) value (OR = 0.367, 95%CI: 0.158 -0.852, P = .020), and lymphovascular invasion (LVI) (OR = 3.530, 95%CI: 1.483 -8.400, P = .004) were identified as independent risk factors associated with ALNM. A nomogram was created for predicting the probability of ALNM by using these risk factors. The calibration curve of the nomogram showed that the nomogram predictions are consistent with the actual ALNM rate. The area under the curve was 0.88 (95% CI: 0.83 -0.93). The nomogram had a bootstrapped-concordance index of 0.88 and was well-calibrated. CONCLUSION The nomogram based on MRI and clinicopathologic features might be a useful tool for predicting ALNM in early-stage invasive BC and could help clinical decision-making.
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Affiliation(s)
- Mei Xue
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shunan Che
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuan Tian
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | | | - Liling Huang
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Liyun Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ning Guo
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jing Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Chen Y, Wang J, Zhang X, Yang W, Chen H, Bao B, Qiu Y, Tian L. Correlation between apparent diffusion coefficient and pathological characteristics of patients with invasive breast cancer. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:143. [PMID: 33569445 PMCID: PMC7867890 DOI: 10.21037/atm-20-7746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Background There is insufficient research on the correlation between the apparent diffusion coefficient and clinicopathological characteristics of breast cancer patients. The present study is to investigate the correlation between the apparent diffusion coefficient and pathological characteristics of patients with invasive breast cancer. Methods From January 2019 to September 2020, 122 cases of invasive breast cancer and 21 cases of benign tumors were retrospectively enrolled. The apparent diffusion coefficient was compared between the two groups, and the correlation between the apparent diffusion coefficient and the pathological characteristics of the patients with invasive breast cancer were analyzed. Results Compared with the benign tumor group, the apparent diffusion coefficient in the invasive breast cancer group was significantly lower (0.89±0.17 vs. 1.47±0.27 10−3 mm2/s, P=0.000). Using the apparent diffusion coefficient to diagnose patients with invasive breast cancer, the area under receiver operating characteristic (ROC) curve was 0.966±0.021 [95% confidence interval (CI): 0.924–1.000, P=0.000], and the best diagnostic cut-off value was 1.16 (10−3 mm2/s), with sensitivity and specificity of 0.905 and 0.902, respectively. The apparent diffusion coefficient was used to diagnose vascular tumor thrombus in patients with invasive breast cancer. The area under the ROC curve was 0.641±0.068 (95% CI: 0.508–0.774, P=0.047), and the best diagnostic threshold was 0.835 (10−3 mm2/s), with sensitivity and specificity of 0.676 and 0.650, respectively. The apparent diffusion coefficient in patients with high expression of Ki-67 (%) was significantly reduced (0.87±0.17 vs. 1.00±0.16 10−3 mm2/s, P=0.000). The apparent diffusion coefficient was not significantly correlated with age, menopause, lesion size, estrogen receptor, progesterone receptor, or lymph node metastasis in patients with invasive breast cancer (P>0.05). Conclusions In patients with invasive breast cancer the apparent diffusion coefficient was significantly reduced. It was able to differentiate invasive breast cancer and vascular tumor thrombus, and was also related to Ki-67 (%) high expression.
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Affiliation(s)
- Yuhui Chen
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jiandong Wang
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xiuxiu Zhang
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wuyao Yang
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hongye Chen
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Baoshi Bao
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yue Qiu
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Lin Tian
- Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
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Maric J, Boban J, Ivkovic-Kapicl T, Djilas D, Vucaj-Cirilovic V, Bogdanovic-Stojanovic D. Differentiation of Breast Lesions and Distinguishing Their Histological Subtypes Using Diffusion-Weighted Imaging and ADC Values. Front Oncol 2020; 10:332. [PMID: 32232007 PMCID: PMC7083136 DOI: 10.3389/fonc.2020.00332] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 02/25/2020] [Indexed: 12/11/2022] Open
Abstract
Diffusion-weighted imaging (DWI) has not been well explored in differentiation of malignant from benign breast lesions. The aims of this study were to examine the role of apparent diffusion coefficient (ADC) values in differentiation of malignant from benign tumors and distinguishing histological subtypes of malignant lesions, and to determine correlations between ADC values and breast tumors structure. This cohort-study included 174 female patients who underwent contrast-enhanced breast MR examination on a 3T scanner and were divided into two groups: patient group (114 patients with proven tumors) and control group (60 healthy patients). One-hundred-thirty-nine lesions (67 malignant and 72 benign) were detected and pathohistologically analyzed. Differences between variables were tested using chi-square test; correlations were determined using Pearson's correlation test. For determination of cut off values for diagnostic potential, Receiver Operating Characteristic curves were constructed. Statistical significance was set at p < 0.05. Mean ADC values were significantly lower in malignant compared to benign lesions (0.68 × 10-3mm2/s vs. 1.12 × 10-3mm2/s, p < 0.001). The cut off value of ADC for benign lesions was 0.792 × 10-3mm2/s (sensitivity 98.6%, specificity 65.7%), and for malignant 0.993 × 10-3mm2/s (98.5, 80.6%). There were no significant correlations between malignant lesion subtypes and ADC values. DWI is a clinically useful tool for differentiation of malignant from benign lesions based on mean ADC values. The cut off value for benign lesions was higher than reported recently, due to high amount of fibrosis in included benign lesions. Finally, ADC values might have implications in determination of the biological nature of the malignant lesions.
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Affiliation(s)
- Jelena Maric
- General Hospital "Sveti Vračevi", Bijeljina, Bosnia and Herzegovina
| | - Jasmina Boban
- Faculty of Medicine Novi Sad, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
| | - Tatjana Ivkovic-Kapicl
- Faculty of Medicine Novi Sad, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
| | - Dragana Djilas
- Faculty of Medicine Novi Sad, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
| | - Viktorija Vucaj-Cirilovic
- Faculty of Medicine Novi Sad, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
| | - Dragana Bogdanovic-Stojanovic
- Faculty of Medicine Novi Sad, University of Novi Sad, Novi Sad, Serbia.,Center for Diagnostic Imaging, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia.,Department for Pathology, Oncology Institute of Vojvodina, Sremska Kamenica, Serbia
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