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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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Zhao S, Li Y, Ning N, Liang H, Wu Y, Wu Q, Wang Z, Tian J, Yang J, Gao X, Liu A, Song Q, Zhang L. Association of peritumoral region features assessed on breast MRI and prognosis of breast cancer: a systematic review and meta-analysis. Eur Radiol 2024:10.1007/s00330-024-10612-y. [PMID: 38334760 DOI: 10.1007/s00330-024-10612-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 12/03/2023] [Accepted: 01/01/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Increasing attention has been given to the peritumoral region. However, conflicting findings have been reported regarding the relationship between peritumoral region features on MRI and the prognosis of breast cancer. PURPOSE To evaluate the relationship between peritumoral region features on MRI and prognosis of breast cancer. MATERIALS AND METHODS A retrospective meta-analysis of observational studies comparing either qualitative or quantitative assessments of peritumoral MRI features on breast cancer with poor prognosis and control subjects was performed for studies published till October 2022. Pooled odds ratios (ORs) or standardized mean differences and 95% confidence intervals (CIs) were estimated by using random-effects models. The heterogeneity across the studies was measured using the statistic I2. Sensitivity analyses were conducted to test this association according to different study characteristics. RESULTS Twenty-four studies comprising 1853 breast cancers of poor prognosis and 2590 control participants were included in the analysis. Peritumoral edema was associated with non-luminal breast cancers (OR=3.56; 95%CI: 2.17, 5.83; p=.000), high expression of the Ki-67 index (OR=3.70; 95%CI: 2.41, 5.70; p =.000), high histological grade (OR=5.85; 95%CI: 3.89, 8.80; p=.000), lymph node metastasis (OR=2.83; 95%CI: 1.71, 4.67; p=.000), negative expression of HR (OR=3.15; 95%CI: 2.03, 4.88; p=.000), and lymphovascular invasion (OR=1.72; 95%CI: 1.28, 2.30; p=.000). The adjacent vessel sign was associated with greater odds of breast cancer with poor prognosis (OR=2.02; 95%CI: 1.68, 2.44; p=.000). Additionally, breast cancers with poor prognosis had higher peritumor-tumor ADC ratio (SMD=0.67; 95%CI: 0.54, 0.79; p=.000) and peritumoral ADCmean (SMD=0.29; 95%CI: 0.15, 0.42; p=.000). A peritumoral region of 2-20 mm away from the margin of the tumor is recommended. CONCLUSION The presence of peritumoral edema and adjacent vessel signs, higher peritumor-tumor ADC ratio, and peritumoral ADCmean were significantly correlated with poor prognosis of breast cancer. CLINICAL RELEVANCE STATEMENT MRI features of the peritumoral region can be used as a non-invasive index for the prognostic evaluation of invasive breast cancer. KEY POINTS • Peritumoral edema was positively associated with non-luminal breast cancer, high expression of the Ki-67 index, high histological grade, lymph node metastasis, negative expression of HR, and lymphovascular invasion. • The adjacent vessel sign was associated with greater odds of breast cancers with poor prognosis. • Breast cancers with poor prognosis had higher peritumor-tumor ADC ratio and peritumoral ADCmean.
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Affiliation(s)
- Siqi Zhao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Yuanfei Li
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Ning Ning
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Hongbing Liang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Yueqi Wu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Qi Wu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Zhuo Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Jiahe Tian
- Zhongshan College of Dalian Medical University, No28 Aixian Road, Gaoxin District, Dalian, Liaoning, 116085, People's Republic of China
| | - Jie Yang
- School of Public Health, Dalian Medical University, Dalian, Liaoning Province, No. 9W. Lvshun South Road, Dalian, 116044, People's Republic of China
| | - Xue Gao
- Department of Pathology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, Liaoning, 116011, People's Republic of China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China
| | - Lina Zhang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 Zhongshan Road, Xigang District, Dalian, Liaoning, 116011, People's Republic of China.
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Nie T, Feng M, Yang K, Guo X, Yuan Z, Zhang Z, Yan G. Correlation between dynamic contrast-enhanced MRI characteristics and apparent diffusion coefficient with Ki-67-positive expression in non-mass enhancement of breast cancer. Sci Rep 2023; 13:21451. [PMID: 38052920 PMCID: PMC10698184 DOI: 10.1038/s41598-023-48445-2] [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: 08/14/2023] [Accepted: 11/27/2023] [Indexed: 12/07/2023] Open
Abstract
As a remarkably specific characteristic of breast cancer observed on magnetic resonance imaging (MRI), the association between the NME type breast cancer and prognosis, including Ki-67, necessitates comprehensive exploration. To investigate the correlation between dynamic contrast-enhanced MRI (DCE-MRI) characteristics and apparent diffusion coefficient (ADC) values with Ki-67-positive expression in NME type breast cancer. A total of 63 NME type breast cancer patients were retrospectively reviewed. Malignancies were confirmed by surgical pathology. All patients underwent DCE and diffusion-weighted imaging (DWI) before surgery. DCE-MRI characteristics, including tumor distribution, internal enhancement pattern, axillary adenopathy, and time-intensity curve types were observed. ADC values and lesion sizes were also measured. The correlation between these features and Ki-67 expression were assessed using Chi-square test, Fisher's exact test, and Spearman rank analysis. The receiver operating characteristic curve and area under the curve (AUC) was used to evaluate the diagnostic performance of Ki-67-positive expression. Regional distribution, TIC type, and ipsilateral axillary lymph node enlargement were correlated with Ki-67-positive expression (χ2 = 0.397, 0.357, and 0.357, respectively; P < 0.01). ADC value and lesion size were positively correlated with Ki-67-positive expression (rs = 0.295, 0.392; P < 0.05). The optimal threshold values for lesion size and ADC value to assess Ki-67 expression were determined to be 5.05 (AUC = 0.759) cm and 0.403 × 10-3 s/mm2 (AUC = 0.695), respectively. The best diagnosis performance was the ADC combined with lesion size (AUC = 0.791). The ADC value, lesion size, regional distribution, and TIC type in NME type breast cancer were correlated with Ki-67-positive expression. These features will aid diagnosis and treatment of NME type breast cancer.
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Affiliation(s)
- Tingting Nie
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 116 Zhuodaoquan South Load, Hongshan District, Wuhan, 430079, Hubei, China
| | - Mengwei Feng
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 116 Zhuodaoquan South Load, Hongshan District, Wuhan, 430079, Hubei, China
| | - Kai Yang
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 116 Zhuodaoquan South Load, Hongshan District, Wuhan, 430079, Hubei, China
| | - Xiaofang Guo
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 116 Zhuodaoquan South Load, Hongshan District, Wuhan, 430079, Hubei, China
| | - Zilong Yuan
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 116 Zhuodaoquan South Load, Hongshan District, Wuhan, 430079, Hubei, China
| | - Zhaoxi Zhang
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 116 Zhuodaoquan South Load, Hongshan District, Wuhan, 430079, Hubei, China.
| | - Gen Yan
- Department of Radiology, the Second Affiliated Hospital of Xiamen Medical College, No 566 Shengguang Road, Jimei District, Xiamen, 361000, Fujian, China.
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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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Chen P, Zhao S, Guo W, Shao G. Dynamic contrast-enhanced magnetic resonance imaging features and apparent diffusion coefficient value of HER2-positive/HR-negative breast carcinoma. Quant Imaging Med Surg 2023; 13:4816-4825. [PMID: 37581065 PMCID: PMC10423352 DOI: 10.21037/qims-22-1318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 04/23/2023] [Indexed: 08/16/2023]
Abstract
Background According to hormone receptor (HR) status, human epidermal growth factor 2 positive (HER2+) breast carcinoma can be divided into HR- and HR+, with different treatment and prognosis. We analyzed the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings, apparent diffusion coefficient (ADC) value and the combination of DCE-MRI and ADC value of HER2+/HR- breast carcinoma. Methods Totally 259 cases (96 HR-, 163 HR+) of pathologically verified HER2+ breast carcinoma were collected. Patients underwent DCE-MRI and diffusion weighted imaging (DWI). The morphological characteristics, internal enhancement characteristics, early enhancement rate (EER), and time-signal intensity curves (TIC) were recorded, and ADC values were measured. The relationship between each feature and HER2+/HR- breast cancer was analyzed. Area under the cures (AUC) was used to compare diagnostic performance of DCE-MRI, ADC value and the combination of DCE-MRI and ADC value. Results HER2+/HR- breast cancer presented as non-mass enhancement (NME), mass with NME, whereas HER2+/HR+ breast cancer presented as mass (P<0.001). HR- cases showed a round or oval shape with circumscribed margins, whereas HR+ cases showed an irregular mass with irregular or spiculated margins (P=0.001, P=0.028). The size of the mass, the internal enhancement characteristics, EER, and TIC did not differ significantly between the two HER2+ breast carcinomas. The ADC values for HR- and HR+ breast cancers were [1.2 (1.14, 1.33)] ×10-3 mm2/s and [1.0 (0.89, 1.11)] ×10-3 mm2/s, respectively, which were statistically significant (Z=-9.119, P<0.001). The ADC value can be used for diagnosing HER2+/HR- breast carcinoma, with the threshold value of 1.095×10-3 mm2/s [negative predictive value (NPV) of 89.8%, sensitivity of 86.5% and specificity of 70.6%]. The AUCs of ADC value, DCE-MRI, and DCE-MRI combined with ADC value were 0.839, 0.689 and 0.860, respectively. AUC of the DCE-MRI combined with ADC value was significantly higher than DCE-MRI alone (P<0.0001). Conclusions The diagnostic performance of the DCE-MRI combined with ADC value was good in diagnosing HER2+/HR- breast cancers. MRI is an effective tool in diagnosing HER2+/HR- breast carcinoma, which will help select the clinical treatment plan and determine the prognosis.
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Yuan L, Lin X, Zhao P, Ma H, Duan S, Sun S. Correlations between DKI and DWI with Ki-67 in gastric adenocarcinoma. Acta Radiol 2023; 64:1792-1798. [PMID: 36740857 DOI: 10.1177/02841851231153035] [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] [Indexed: 02/07/2023]
Abstract
BACKGROUND Diffusion kurtosis imaging (DKI) has been applied for gastric adenocarcinoma. Correlations between its parameters and Ki-67 are unclear. PURPOSE To investigate the correlation between DKI and diffusion-weighted imaging (DWI) parameters with the Ki-67 index in gastric adenocarcinoma. MATERIAL AND METHODS A total of 54 patients with gastric adenocarcinoma were enrolled in the study and underwent DWI and DKI at 3.0-T MRI before surgery. Based on the settings of the regions of interest, the DWI and DKI parameters (including apparent diffusion coefficient [ADC], diffusion kurtosis [K], and diffusion coefficient [DK]) of each patient's gastric adenocarcinoma were measured and calculated. The participants were divided into two groups (low Ki-67 group and high Ki-67 groups). The intraclass correlation coefficient (ICC) and independent-sample t-test were used to compare differences in each parameter between two groups. Spearman's correlation coefficient was calculated to determine the correlation between Ki-67 and the parameters. Each parameter was compared using the area under the receiver operating characteristic curve. All parameters were included in the multivariate logistic regression analysis to explore the relationship between each parameter and high Ki-67 index. RESULTS ADC and DK were negatively relevant with Ki-67 and K was positively relevant with Ki-67 in gastric adenocarcinoma. ADC, DK, and K had diagnostic efficiency in differentiating the low Ki-67 group from the high Ki-67 group. A higher K value independently predicted a high Ki-67 status. CONCLUSION DWI and DKI reflected the proliferative characteristics of gastric adenocarcinoma. K was the strongest independent factor for predicting high Ki-67 status.
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Affiliation(s)
- Letian Yuan
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Xiangtao Lin
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Peng Zhao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Hui Ma
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Shuai Duan
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
| | - Shanshan Sun
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, PR China
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Zhang L, Hao J, Guo J, Zhao X, Yin X. Predicting of Ki-67 Expression Level Using Diffusion-Weighted and Synthetic Magnetic Resonance Imaging in Invasive Ductal Breast Cancer. Breast J 2023; 2023:6746326. [PMID: 37063453 PMCID: PMC10098409 DOI: 10.1155/2023/6746326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 02/26/2023] [Accepted: 03/27/2023] [Indexed: 04/18/2023]
Abstract
Objectives To investigate the association between quantitative parameters generated using synthetic magnetic resonance imaging (SyMRI) and diffusion-weighted imaging (DWI) and Ki-67 expression level in patients with invasive ductal breast cancer (IDC). Method We retrospectively reviewed the records of patients with IDC who underwent SyMRI and DWI before treatment. Precontrast and postcontrast relaxation times (T1, longitudinal; T2, transverse), proton density (PD) parameters, and apparent diffusion coefficient (ADC) values were measured in breast lesions. Univariate and multivariate regression analyses were performed to screen for statistically significant variables to differentiate the high (≥30%) and low (<30%) Ki-67 expression groups. Their performance was evaluated by receiver operating characteristic (ROC) curve analysis. Results We analyzed 97 patients. Multivariate regression analysis revealed that the high Ki-67 expression group (n = 57) had significantly higher parameters generated using SyMRI (pre-T1, p=0.001) and lower ADC values (p=0.036) compared with the low Ki-67 expression group (n = 40). Pre-T1 showed the best diagnostic performance for predicting the Ki-67 expression level in patients with invasive ductal breast cancer (areas under the ROC curve (AUC), 0.711; 95% confidence interval (CI), 0.609-0.813). Conclusions Pre-T1 could be used to predict the pretreatment Ki-67 expression level in invasive ductal breast cancer.
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Affiliation(s)
- Liying Zhang
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Jisen Hao
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Jia Guo
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Xin Zhao
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
| | - Xing Yin
- Third Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, China
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Zhong M, Yang Z, Chen X, Huang R, Wang M, Fan W, Dai Z, Chen X. Readout-Segmented Echo-Planar Diffusion-Weighted MR Imaging Improves the Differentiation of Breast Cancer Receptor Statuses Compared With Conventional Diffusion-Weighted Imaging. J Magn Reson Imaging 2022; 56:691-699. [PMID: 35038210 PMCID: PMC9542110 DOI: 10.1002/jmri.28065] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/04/2022] [Accepted: 01/05/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Readout-segmented echo-planar diffusion-weighted imaging (RS-EPI) can improve image quality and signal-to-noise ratio, the resulting apparent diffusion coefficient (ADC) value acts as a more sensitive biomarker to characterize tumors. However, data regarding the differentiation of breast cancer (BC) receptor statuses using RS-EPI are limited. PURPOSE To determine whether RS-EPI improves the differentiation of receptor statuses compared with conventional single-shot (SS) EPI in breast MRI. STUDY TYPE Retrospective. POPULATION A total of 151 BC women with the mean age of 50.6 years. FIELD STRENGTH/SEQUENCE A 3 T/ RS-EPI and SS-EPI. ASSESSMENT The ADCs of the lesion and normal background tissue from the two sequences were collected by two radiologists with 15 years of experience working of breast MRI (M.H.Z. and X.F.C.), and a normalized ADC was calculated by dividing the mean ADC value of the lesion by the mean ADC value of the normal background tissue. STATISTICAL TESTS Agreement between the ADC measurements from the two sequences was assessed using the Pearson correlation coefficient and Bland-Altman plots. One-way analysis of variance, Kruskal-Wallis test, and median difference were used to compare the ADC measurements for all lesions and different receptor statuses. A P value less than 0.05 indicated a significant result. RESULTS The ADC measurements of all lesions and normal background tissues were significantly higher on RS-EPI than on SS-EPI (1.82 ± 0.33 vs. 1.55 ± 0.30 and 0.83 ± 0.11 vs. 0.79 ± 0.10). The normalized ADC was lower on RS-EPI than on SS-EPI (0.47 ± 0.11 vs. 0.53 ± 0.12, a median difference of -0.04 [95% CI: -0.256 to 0.111]). For both diffusion methods, only the ADC measurement of RS-EPI was higher for human epidermal growth factor receptor-2 (HER-2)-positive tumors than for HER-2-negative tumors (0.87 ± 0.10 vs. 0.81 ± 0.11), and this measurement was associated with HER-2 positive status (adjusted odds ratio [OR] = 654.4); however, similar results were not observed for the ADC measurement of SS-EPI (0.80 ± 0.10 vs. 0.78 ± 0.11 with P = 0.199 and adjusted OR = 0.21 with P = 0.464, respectively). DATA CONCLUSION RS-EPI can improve the distinction between HER-2-positive and HER-2-negative breast cancer, complementing the clinical application of diffusion imaging. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Minghao Zhong
- Department of Radiology, Meizhou People's HospitalMeizhou514031China
| | - Zhiqi Yang
- Department of Radiology, Meizhou People's Hospital, Meizhou, 514031 China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, 514031 China
| | - Xiaofeng Chen
- Department of Radiology, Meizhou People's HospitalMeizhou514031China
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka PopulationMeizhou514031China
| | - Ruibin Huang
- Department of RadiologyFirst Affiliated Hospital of Shantou University Medical CollegeShantou515000China
| | - Mengzhu Wang
- MR Scientific Marketing, Siemens HealthineersGuangzhou510620China
| | - Weixiong Fan
- Department of Radiology, Meizhou People's HospitalMeizhou514031China
| | - Zhuozhi Dai
- Department of Radiology, Shantou Central Hospital, Shantou, Guangdong, 515041 China
| | - Xiangguang Chen
- Guangdong Provincial Key Laboratory of Precision Medicine and Clinical Translational Research of Hakka Population, Meizhou, 514031 China
- Department of Radiology, Meizhou People's Hospital, Meizhou, 514031 China
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Dołęga-Kozierowski B, Lis M, Marszalska-Jacak H, Koziej M, Celer M, Bandyk M, Kasprzak P, Szynglarewicz B, Matkowski R. Multimodality imaging in lobular breast cancer: Differences in mammography, ultrasound, and MRI in the assessment of local tumor extent and correlation with molecular characteristics. Front Oncol 2022; 12:855519. [PMID: 36072800 PMCID: PMC9441946 DOI: 10.3389/fonc.2022.855519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 07/11/2022] [Indexed: 11/28/2022] Open
Abstract
Introduction Invasive lobular breast cancer (ILC) is a diagnostic challenge due to the diversity of morphological features. The objective of the study was to investigate the presentation and local extent of ILC using various imaging techniques and to assess the correlation between imaging and molecular profile. Materials and methods We reviewed 162 consecutive patients with ILC found on vacuum-assisted biopsy, who underwent evaluation of the lesion morphology and extent using ultrasound (US), mammography (MMG), and magnetic resonance imaging (MRI). Radiographic features were compared with ILC intrinsic subtype based on the expression of Ki-67 and estrogen, progesterone, and HER2 receptors. Results A total of 113 mass lesions and 49 non-mass enhancements (NMEs) were found in MRI. Masses were typically irregular and spiculated, showing heterogeneous contrast enhancement, diffusion restriction, and type III enhancement curve. NMEs presented mainly as the area of focal or multiregional distribution with heterogeneous or clumped contrast enhancement, diffusion restriction, and type III enhancement curve. Lesion extent significantly varied between MRI and MMG/ultrasonography (USG) (P < 0.001) but did not differ between MGF and ultrasonography (USG). The larger the ILC, the higher the disproportion when lesion extent in MRI was compared with MMG (P < 0.001) and ultrasonography (USG) (P < 0.001). In the study group, there were 97 cases of luminal A subtype (59.9%), 54 cases of luminal B HER2− (33.3%), nine cases of luminal B HER2+ (5.5%), and two cases of triple negative (1.2%). The HER2 type was not found in the study group. We did not observe any significant correlation between molecular profile and imaging. Conclusion MRI is the most effective technique for the assessment of ILC local extent, which is important for optimal treatment planning. Further studies are needed to investigate if the intrinsic subtype of ILC can be predicted by imaging features on MRI.
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Affiliation(s)
- Bartosz Dołęga-Kozierowski
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Michał Lis
- Burn and Plastic Surgery Department, Ludwik Rydygier Memorial Specialized Hospital in Krakow, Krakow, Poland
- *Correspondence: Michał Lis,
| | - Hanna Marszalska-Jacak
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Mateusz Koziej
- Department of Anatomy, Jagiellonian University Medical College, Krakow, Poland
| | - Marcin Celer
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Małgorzata Bandyk
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Piotr Kasprzak
- Breast Unit, Department of Breast Imaging, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
| | - Bartłomiej Szynglarewicz
- Breast Unit, Department of Breast Surgery, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
- Department of Oncology, Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Rafał Matkowski
- Breast Unit, Department of Breast Surgery, Lower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland
- Department of Oncology, Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
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10
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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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11
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Kazama T, Takahara T, Hashimoto J. Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review. Life (Basel) 2022; 12:life12040490. [PMID: 35454981 PMCID: PMC9028183 DOI: 10.3390/life12040490] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 02/20/2022] [Accepted: 03/08/2022] [Indexed: 12/12/2022] Open
Abstract
Magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer detection. This systematic review investigated the role of quantitative MRI features in classifying molecular subtypes of breast cancer. We performed a literature search of articles published on the application of quantitative MRI features in invasive breast cancer molecular subtype classification in PubMed from 1 January 2002 to 30 September 2021. Of the 1275 studies identified, 106 studies with a total of 12,989 patients fulfilled the inclusion criteria. Bias was assessed based using the Quality Assessment of Diagnostic Studies. All studies were case-controlled and research-based. Most studies assessed quantitative MRI features using dynamic contrast-enhanced (DCE) kinetic features and apparent diffusion coefficient (ADC) values. We present a summary of the quantitative MRI features and their correlations with breast cancer subtypes. In DCE studies, conflicting results have been reported; therefore, we performed a meta-analysis. Significant differences in the time intensity curve patterns were observed between receptor statuses. In 10 studies, including a total of 1276 lesions, the pooled difference in proportions of type Ⅲ curves (wash-out) between oestrogen receptor-positive and -negative cancers was not significant (95% confidence interval (CI): [−0.10, 0.03]). In nine studies, including a total of 1070 lesions, the pooled difference in proportions of type 3 curves between human epidermal growth factor receptor 2-positive and -negative cancers was significant (95% CI: [0.01, 0.14]). In six studies including a total of 622 lesions, the pooled difference in proportions of type 3 curves between the high and low Ki-67 groups was significant (95% CI: [0.17, 0.44]). However, the type 3 curve itself is a nonspecific finding in breast cancer. Many studies have examined the relationship between mean ADC and breast cancer subtypes; however, the ADC values overlapped significantly between subtypes. The heterogeneity of ADC using kurtosis or difference, diffusion tensor imaging parameters, and relaxation time was reported recently with promising results; however, current evidence is limited, and further studies are required to explore these potential applications.
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Affiliation(s)
- Toshiki Kazama
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara 259-1193, Japan;
- Correspondence: ; Tel.: +81-463-93-1121
| | - Taro Takahara
- Department of Biomedical Engineering, Tokai University School of Engineering, Hiratsuka 259-1207, Japan;
| | - Jun Hashimoto
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara 259-1193, Japan;
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12
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Meyer HJ, Wienke A, Surov A. Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis. Breast Care (Basel) 2022; 17:47-54. [PMID: 35355697 PMCID: PMC8914237 DOI: 10.1159/000514407] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 01/08/2021] [Indexed: 02/03/2023] Open
Abstract
Background Magnetic resonance imaging can be used to diagnose breast cancer (BC). Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Objectives This analysis aimed to compare ADC values between molecular subtypes of BC based on a large sample of patients. Method The MEDLINE library and Scopus database were screened for the associations between ADC and molecular subtypes of BC up to April 2020. The primary end point of the systematic review was the ADC value in different BC subtypes. Overall, 28 studies were included. Results The included studies comprised a total of 2,990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), luminal B in 899 (30.1%), human epidermal growth factor receptor (Her2)-enriched in 597 (20.0%), and triple-negative in 629 (21.0%). The mean ADC values of the subtypes were as follows: luminal A: 0.99 × 10-3 mm2/s (95% CI 0.94-1.04), luminal B: 0.97 × 10-3 mm2/s (95% CI 0.89-1.05), Her2-enriched: 1.02 × 10-3 mm2/s (95% CI 0.95-1.08), and triple-negative: 0.99 × 10-3 mm2/s (95% CI 0.91-1.07). Conclusions ADC values cannot be used to discriminate between molecular subtypes of BC.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany,*Hans-Jonas Meyer, Department of Diagnostic and Interventional Radiology, University of Leipzig, DE–04103 Leipzig (Germany),
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexey Surov
- Department of Radiology and Nuclear Medicine, University of Magdeburg, Magdeburg, Germany
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13
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Okuma H, Sudah M, Kettunen T, Niukkanen A, Sutela A, Masarwah A, Kosma VM, Auvinen P, Mannermaa A, Vanninen R. Peritumor to tumor apparent diffusion coefficient ratio is associated with biologically more aggressive breast cancer features and correlates with the prognostication tools. PLoS One 2020; 15:e0235278. [PMID: 32584887 PMCID: PMC7316248 DOI: 10.1371/journal.pone.0235278] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 06/12/2020] [Indexed: 12/11/2022] Open
Abstract
PURPOSE The apparent diffusion coefficient (ADC) is increasingly used to characterize breast cancer. The peritumor/tumor ADC ratio is suggested to be a reliable and generally applicable index. However, its overall prognostication value remains unclear. We aimed to evaluate the associations between the peritumor/tumor ADC ratio and histopathological biomarkers and published prognostic tools in patients with invasive breast cancer. MATERIALS AND METHODS This prospective study included 88 lesions (five bilateral) in 83 patients with primary invasive breast cancer who underwent preoperative 3.0-T magnetic resonance imaging. The lowest intratumoral mean ADC value on the slice with the largest tumor cross-sectional area was designated the tumor ADC, and the highest mean ADC value on the peritumoral breast parenchymal tissue adjacent to the tumor border was designated the peritumor ADC. The peritumor/tumor ADC ratio was then calculated. The tumor and peritumor ADC values and peritumor/tumor ADC ratios were compared with histopathological parameters using an unpaired t test, and their correlations with published prognostic tools were evaluated with Pearson's correlation coefficient. RESULTS The peritumor/tumor ADC ratio was significantly associated with tumor size (p<0.001), histological grade (p = 0.005), Ki-67 index (p = 0.006), axillary-lymph-node metastasis (p = 0.001), and lymphovascular invasion (p = 0.006), but was not associated with estrogen receptor status (p = 0.931), progesterone receptor status (p = 0.160), or human epidermal growth factor receptor 2 status (p = 0.259). The peritumor/tumor ADC ratio showed moderate positive correlations with the Nottingham Prognostic Index (r = 0.498, p<0.001) and mortality predicted using PREDICT (r = 0.436, p<0.001). CONCLUSION The peritumor/tumor ADC ratio was correlated with histopathological biomarkers in patients with invasive breast cancer, showed significant correlations with published prognostic indexes, and may provide an easily applicable imaging index for the preoperative prognostic evaluation of breast cancer.
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Affiliation(s)
- Hidemi Okuma
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
- * E-mail:
| | - Mazen Sudah
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Tiia Kettunen
- Institute of Clinical Medicine, School of Medicine, Oncology, University of Eastern Finland, Kuopio, Finland
- Department of Oncology, Cancer Center, Kuopio University Hospital, Kuopio, Finland
| | - Anton Niukkanen
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Anna Sutela
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Amro Masarwah
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Veli-Matti Kosma
- Institute of Clinical Medicine, School of Medicine, Pathology and Forensic Medicine, and Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Päivi Auvinen
- Institute of Clinical Medicine, School of Medicine, Oncology, University of Eastern Finland, Kuopio, Finland
- Department of Oncology, Cancer Center, Kuopio University Hospital, Kuopio, Finland
| | - Arto Mannermaa
- Institute of Clinical Medicine, School of Medicine, Pathology and Forensic Medicine, and Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Ritva Vanninen
- Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
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14
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Diffusion-Weighted Imaging in Oncology: An Update. Cancers (Basel) 2020; 12:cancers12061493. [PMID: 32521645 PMCID: PMC7352852 DOI: 10.3390/cancers12061493] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 05/28/2020] [Accepted: 06/01/2020] [Indexed: 02/06/2023] Open
Abstract
To date, diffusion weighted imaging (DWI) is included in routine magnetic resonance imaging (MRI) protocols for several cancers. The real additive role of DWI lies in the "functional" information obtained by probing the free diffusivity of water molecules into intra and inter-cellular spaces that in tumors mainly depend on cellularity. Although DWI has not gained much space in some oncologic scenarios, this non-invasive tool is routinely used in clinical practice and still remains a hot research topic: it has been tested in almost all cancers to differentiate malignant from benign lesions, to distinguish different malignant histotypes or tumor grades, to predict and/or assess treatment responses, and to identify residual or recurrent tumors in follow-up examinations. In this review, we provide an up-to-date overview on the application of DWI in oncology.
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15
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Associations Between Apparent Diffusion Coefficient Values and the Prognostic Factors of Breast Cancer. J Comput Assist Tomogr 2019; 43:931-936. [PMID: 31738207 DOI: 10.1097/rct.0000000000000936] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Breast imaging can offer great information about breast cancer heterogeneity. The purpose of this study was to analyze the relationship between apparent diffusion coefficient (ADC) values and various prognostic factors and investigate whether ADC values are useful for breast cancer diagnosis, evaluation of treatment response, and determination of prognosis. METHODS A total of 111 cases of breast cancer were included in this study. Magnetic resonance findings were recorded according to the Breast Imaging Reporting and Data System magnetic resonance imaging lexicon. Diffusion-weighted imaging rim sign and minimum, maximum, and difference ADC values (ADCdiff) were also evaluated. RESULTS ADCdiff was related to all prognostic factors such as histological grade, Ki-67, tumor size, molecular subtype, axillary node metastasis, lymphvascular invasion, internal enhancement pattern, intratumoral high T2 signal, peritumoral edema, and diffusion-weighted imaging rim sign, whereas minimum and maximum ADC values showed variable associations. CONCLUSIONS Apparent diffusion coefficient values were shown to be correlated with many proven or possible prognostic factors of breast cancer. In particular, ADCdiff can reflect tumor heterogeneity and showed higher correlation.
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16
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Surov A, Chang YW, Li L, Martincich L, Partridge SC, Kim JY, Wienke A. Apparent diffusion coefficient cannot predict molecular subtype and lymph node metastases in invasive breast cancer: a multicenter analysis. BMC Cancer 2019; 19:1043. [PMID: 31690273 PMCID: PMC6833245 DOI: 10.1186/s12885-019-6298-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 10/27/2019] [Indexed: 12/14/2022] Open
Abstract
Background Radiological imaging plays a central role in the diagnosis of breast cancer (BC). Some studies suggest MRI techniques like diffusion weighted imaging (DWI) may provide further prognostic value by discriminating between tumors with different biologic characteristics including receptor status and molecular subtype. However, there is much contradictory reported data regarding such associations in the literature. The purpose of the present study was to provide evident data regarding relationships between quantitative apparent diffusion coefficient (ADC) values on DWI and pathologic prognostic factors in BC. Methods Data from 5 centers (661 female patients, mean age, 51.4 ± 10.5 years) were acquired. Invasive ductal carcinoma (IDC) was diagnosed in 625 patients (94.6%) and invasive lobular carcinoma in 36 cases (5.4%). Luminal A carcinomas were diagnosed in 177 patients (28.0%), luminal B carcinomas in 279 patients (44.1%), HER 2+ carcinomas in 66 cases (10.4%), and triple negative carcinomas in 111 patients (17.5%). The identified lesions were staged as T1 in 51.3%, T2 in 43.0%, T3 in 4.2%, and as T4 in 1.5% of the cases. N0 was found in 61.3%, N1 in 33.1%, N2 in 2.9%, and N3 in 2.7%. ADC values between different groups were compared using the Mann–Whitney U test and by the Kruskal-Wallis H test. The association between ADC and Ki 67 values was calculated by Spearman’s rank correlation coefficient. Results ADC values of different tumor subtypes overlapped significantly. Luminal B carcinomas had statistically significant lower ADC values compared with luminal A (p = 0.003) and HER 2+ (p = 0.007) lesions. No significant differences of ADC values were observed between luminal A, HER 2+ and triple negative tumors. There were no statistically significant differences of ADC values between different T or N stages of the tumors. Weak statistically significant correlation between ADC and Ki 67 was observed in luminal B carcinoma (r = − 0.130, p = 0.03). In luminal A, HER 2+ and triple negative tumors there were no significant correlations between ADC and Ki 67. Conclusion ADC was not able to discriminate molecular subtypes of BC, and cannot be used as a surrogate marker for disease stage or proliferation activity.
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Germany.
| | - Yun-Woo Chang
- Department of Radiology, Soonchunhyang University Hospital, 59 Daesakwan-ro, Yongsan-gu, Seoul, 140-743, Republic of Korea
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Laura Martincich
- Unit of Radiology, Institute for Cancer Research and Treatment (IRCC), Strada Provinciale 142, 10060 Candiolo, Turin, Italy
| | - Savannah C Partridge
- Department of Radiology, University of Washington, Seattle, Washington 825 Eastlake Ave. E, G2-600, Seattle, WA, 98109, USA
| | - Jin You Kim
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute 1-10, Ami-Dong, Seo-gu, Busan, 602-739, South Korea
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Magdeburger Str, 06097, Halle, Germany
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17
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Iima M, Honda M, Sigmund EE, Ohno Kishimoto A, Kataoka M, Togashi K. Diffusion MRI of the breast: Current status and future directions. J Magn Reson Imaging 2019; 52:70-90. [PMID: 31520518 DOI: 10.1002/jmri.26908] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 08/12/2019] [Indexed: 12/30/2022] Open
Abstract
Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Eric E Sigmund
- Department of Radiology, NYU Langone Health, New York, New York, USA.,Center for Advanced Imaging and Innovation (CAI2R), New York, New York, USA
| | - Ayami Ohno Kishimoto
- 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
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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18
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You C, Li J, Zhi W, Chen Y, Yang W, Gu Y, Peng W. The volumetric-tumour histogram-based analysis of intravoxel incoherent motion and non-Gaussian diffusion MRI: association with prognostic factors in HER2-positive breast cancer. J Transl Med 2019; 17:182. [PMID: 31262334 PMCID: PMC6604303 DOI: 10.1186/s12967-019-1911-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 05/08/2019] [Indexed: 12/27/2022] Open
Abstract
Background To evaluate the imaging biomarkers of human epidermal growth factor receptor 2 (HER2) positive breast cancer in comparison to other molecular subtypes and to determine the feasibility of identifying hormone receptor (HR) status and lymph node metastasis status using volumetric-tumour histogram-based analysis through intravoxel incoherent motion (IVIM) and non-Gaussian diffusion. Methods This study included 145 breast cancer patients with 148 lesions between January and November in 2018. Among the 148 lesions, 74 were confirmed to be HER2-positive. The volumetric-tumour histogram-based features were extracted from the combined IVIM and non-Gaussian diffusion model. IVIM and non-Gaussian diffusion parameters obtained from images of the subjects with different molecular prognostic biomarker statuses were compared by Student’s t test or the Mann–Whitney U test. The area under the curve (AUC), sensitivity, and specificity at the best cut-off point were reported. The Spearman correlation coefficient was calculated to analyse the correlations of clinical tumor nodule metastasis (TNM) stage and Ki67 with the IVIM and non-Gaussian diffusion parameters. Results The entropy of mean kurtosis (MK) was significantly higher in the HER2-positive group than in the HER2-negative group (p = 0.015), with an AUC of 0.629 (95% CI 0.546, 0.707), a sensitivity of 62.6%, and a specificity of 66.2%. For HR status, the MD 5th percentile was higher in the HR-positive group of HER2-positive breast cancer (p = 0.041), with an AUC of 0.643 (95% CI 0.523, 0.751), while for lymph node status, the entropy of mean diffusivity (MK) was lower in the lymph node positive group (p = 0.040), with an AUC of 0.587 (95% CI 0.504, 0.668). The clinical TNM stage and Ki67 index were correlated with several histogram parameters. Conclusion Volumetric-lesion histogram analysis of IVIM and the non-Gaussian diffusion model can be used to provide prognostic information about HER2-positive breast cancers and potentially contribute to individualized anti-HER2 targeted therapy plans . Electronic supplementary material The online version of this article (10.1186/s12967-019-1911-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Chao You
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China
| | - Jianwei Li
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Wenxiang Zhi
- Department of Ultrasound, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Yanqiong Chen
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China
| | - Wentao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University Shanghai, Shanghai, People's Republic of China
| | - Yajia Gu
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China.
| | - Weijun Peng
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China.
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Abstract
In the current era of breast imaging, magnetic resonance imaging (MRI) has an important role. To get its specificity better, some supporting or cooperative tools might be needed. The search for new methods continues and non-contrast MRI trials are seen. With the shorter and easier acquisition, no need for contrast material, diffusion-weighted (DW)-MRI could be the best collaborator. This pictorial review aims to give an overview of the DW-MRI of the breast by means of a set of specially selected cases.
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Affiliation(s)
- Irmak Durur-Subasi
- University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Clinic of Radiology, Ankara, Turkey.
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Surov A, Clauser P, Chang YW, Li L, Martincich L, Partridge SC, Kim JY, Meyer HJ, Wienke A. Can diffusion-weighted imaging predict tumor grade and expression of Ki-67 in breast cancer? A multicenter analysis. Breast Cancer Res 2018; 20:58. [PMID: 29921323 PMCID: PMC6011203 DOI: 10.1186/s13058-018-0991-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 05/18/2018] [Indexed: 01/24/2023] Open
Abstract
Background Numerous studies have analyzed associations between apparent diffusion coefficient (ADC) and histopathological features such as Ki-67 proliferation index in breast cancer (BC), with mixed results. The purpose of this study was to perform a multicenter analysis to determine relationships between ADC and expression of Ki-67 and tumor grade in BC. Methods For this study, data from six centers were acquired. The sample comprises 870 patients (all female; mean age, 52.6 ± 10.8 years). In every case, breast magnetic resonance imaging with diffusion-weighted imaging was performed. The comparison of ADC values in groups was performed by Mann-Whitney U test where the p values are adjusted for multiple testing (Bonferroni correction). The association between ADC and Ki-67 values was calculated by Spearman’s rank correlation coefficient. Sensitivity, specificity, negative and positive predictive values, accuracy, and AUC were calculated for the diagnostic procedures. ADC thresholds were chosen to maximize the Youden index. Results Overall, data of 870 patients were acquired for this study. The mean ADC value of the tumors was 0.98 ± 0.22 × 10− 3 mm2 s− 1. ROC analysis showed that it is impossible to differentiate high/moderate grade tumors from grade 1 lesions using ADC values. Youden index identified a threshold ADC value of 1.03 with a sensitivity of 56.2% and specificity of 67.9%. The positive predictive value was 18.2%, and the negative predictive value was 92.4%. The level of the Ki-67 proliferation index was available for 845 patients. The mean value was 12.33 ± 21.77%. ADC correlated with weak statistical significant with expression of Ki-67 (p = − 0.202, p < 0.001). ROC analysis was performed to distinguish tumors with high proliferative potential from tumors with low expression of Ki-67 using ADC values. Youden index identified a threshold ADC value of 0.91 (sensitivity 64%, specificity 50%, positive predictive value 67.7%, negative predictive value 45.0%). Conclusions ADC cannot be used as a surrogate marker for proliferation activity and/or for tumor grade in breast cancer.
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstrasse 20, 04103, Leipzig, Germany.
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Währinger Gürtel, 18-20 1090, Vienna, Austria
| | - Yun-Woo Chang
- Department of Radiology, Soonchunhyang University Hospital, 59 Daesakwan-ro, Yongsan-gu, Seoul, 140-743, Republic of Korea
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Laura Martincich
- Unit of Radiology, Institute for Cancer Research and Treatment of Candiolo (IRCC), Strada Provinciale 142, 10060 Candiolo, Turin, Italy
| | - Savannah C Partridge
- Department of Radiology, University of Washington, 825 Eastlake Avenue E, G2-600, Seattle, WA, 98109, USA
| | - Jin You Kim
- Department of Radiology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Korea
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Liebigstrasse 20, 04103, Leipzig, Germany
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Magdeburger Strasse, 06097, Halle, Germany
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