Intravoxel incoherent motion diffusion‐weighted MRI of invasive breast cancer: Correlation with prognostic factors and kinetic features acquired with computer‐aided diagnosis

Song, Sung Eun; Cho, Kyu Ran; Seo, Bo Kyoung; Woo, Ok Hee; Park, Kyong Hwa; Son, Yo Han; Grimm, Robert

doi:10.1002/jmri.26221

Cited by 30 publications

(18 citation statements)

References 30 publications

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“…Tumor diameter and lymph node metastasis can also affect the treatment and prognosis of breast cancer. However, both in this study and previous reports 35–37 none of the aforementioned factors showed a significant correlation with derivative parameters of IVIM and APTWI, indicating that IVIM and APTWI do not have the capability to comprehensively evaluate the prognostic factors of breast cancer.…”

Section: Discussioncontrasting

confidence: 95%

“…As a result, the D value was lower than that in the group with low Ki‐67 expression. However, in other studies 27,36 no significant correlation between the D value and the expression of Ki‐67 was observed. We speculated that this discrepancy might be related to the inclusion of lesions, the selection of the b‐values for IVIM, and the delineation of the ROI.…”

Section: Discussionmentioning

confidence: 81%

“…Both PR and HER‐2 expression could significantly affect the prognosis of breast cancer; however, studies on the relationship between these two factors and the derivative parameters of IVIM and APTWI remain controversial. For example, Cho et al 12 found that PR and HER‐2 expression were closely related to D* and f values, but Song et al 36 suggested that the parameters of IVIM were not significantly correlated with the expression of PR and HER‐2. Therefore, although the results of this study showed that the expression status of PR and HER‐2 had no significant correlation with any of the parameters, it is still necessary to conduct an in‐depth study of this issue in the future.…”

Section: Discussionmentioning

confidence: 99%

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Comparative Study of Amide Proton Transfer‐Weighted Imaging and Intravoxel Incoherent Motion Imaging in Breast Cancer Diagnosis and Evaluation

Meng

Wang

Sun

et al. 2020

Magnetic Resonance Imaging

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Background Amide proton transfer‐weighted imaging (APTWI) and intravoxel incoherent motion imaging (IVIM) are valuable MRI techniques applied to cancer. Purpose To compare APTWI and IVIM in the diagnosis of benign and malignant breast lesions and to evaluate the correlations between different parameters (MTRasym [3.5 ppm], D, D*, and f) and prognostic factors for breast cancer. Study Type Retrospective. Population In all, 123 breast lesions were studied before treatment, including 58 benign lesions and 65 malignant lesions. Field Strength/Sequence Conventional MRI (T1WI, T2WI, and diffusion‐weighted imaging [DWI]), APTWI, and IVIM MRI at 3T. Assessment The magnetization transfer ratio asymmetry at 3.5 ppm (MTRasym [3.5 ppm]), diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) values were compared between the benign and malignant groups and between groups with different expression levels of prognostic factors. Statistical Tests Individual sample t‐test, χ2 test, Spearman correlation, logistic regression, and the Delong test. Results The D and MTRasym (3.5 ppm) values of the malignant group were lower than those of the benign group; however, D* and f values were higher than those of the benign group (all P < 0.05). The areas under the curve (AUCs) of D, MTRasym (3.5 ppm), D*, and f were 0.809, 0.778, 0.670, and 0.766, respectively; however, only the difference between AUC (D) and AUC (D*) was significant (Z = 2.374, P < 0.05). The D value showed a low correlation with the pathological grade and Ki‐67 expression (| r | = 0.294, 0.367); the f value showed a low correlation with estrogen receptor (ER) expression (| r | = 0.382); and the MTRasym (3.5 ppm) value showed a low correlation with pathological grade (| r | = 0.371). Data Conclusion This analysis revealed that both IVIM and APTWI could be used for the differential diagnosis of benign and malignant breast lesions, and APTWI‐derived MTRasym (3.5 ppm), IVIM‐derived D, D*, and f values showed correlations with some prognostic factors for breast cancer. Level of Evidence 2 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2020;52:1175–1186.

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Section: Discussioncontrasting

confidence: 95%

Section: Discussionmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 99%

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Comparative Study of Amide Proton Transfer‐Weighted Imaging and Intravoxel Incoherent Motion Imaging in Breast Cancer Diagnosis and Evaluation

Meng

Wang

Sun

et al. 2020

Magnetic Resonance Imaging

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“…proved ADC to be a valuable noninvasive quantitative biomarker for assessing BC invasiveness ( 25 ). Agreeing with previous studies ( 26 – 29 ), our results showed that a lower ADC was associated with higher tumor malignancy, especially in TNBC patients. This phenomenon may be attributed to the high cellular density and the restriction of water molecules in malignant tumors ( 30 ).…”

Section: Discussionsupporting

confidence: 90%

Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes

et al. 2021

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ObjectivesTo assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques.MethodsA total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor, progesterone receptor, human epidermal growth factorreceptor-2 (HER-2) status, and the Ki-67 proliferation index were collected for analysis. Quantitative parameters (Ktrans, Ve, Kep), semiquantitative parameters (W-in, W-out, TTP), and apparent diffusion coefficient (ADC) values were compared in relation to breast cancer receptor status and molecular subtypes. Statistical analysis were performed to compare the parameters in the receptor status and molecular subtype groups.Multivariate analysis was performed to explore confounder-adjusted associations, and receiver operating characteristic curve analysis was used to assess the classification performance and calculate thresholds.ResultsYounger age (<49.5 years, odds ratio (OR) =0.95, P=0.004), lower Kep (<0.704,OR=0.14, P=0.044),and higher TTP (>0.629 min, OR=24.65, P=0.011) were independently associated with progesterone receptor positivity. A higher TTP (>0.585 min, OR=28.19, P=0.01) was independently associated with estrogen receptor positivity. Higher Kep (>0.892, OR=11.6, P=0.047), lower TTP (<0.582 min, OR<0.001, P=0.004), and lower ADC (<0.719 ×10-3 mm2/s, OR<0.001, P=0.048) had stronger independent associations with triple-negative breast cancer (TNBC) compared to luminal A, and those parameters could differentiate TNBC from luminal A with the highest AUC of 0.811.ConclusionsKep and TTP were independently associated with hormone receptor status. In addition, the Kep, TTP, and ADC values had stronger independent associations with TNBC than with luminal A and could be used as imaging biomarkers for differentiate TNBC from Luminal A.

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“…In the diffusional kurtosis imaging (DKI) model first proposed by Jensen et al (17), when the bvalue is high (>1000 s/mm 2 ) the diffusion of water molecules follows a non-Gaussian distribution, the DKI model is more accurate at assessing the diffusion of water molecules in a lesion (17)(18)(19). In recent years, extended DWI models based on different b-values, including IVIM and DKI, have been used for the identification of tumors in liver (20), prostate (21,22), thyroid (23) and brain (24). However, there have been few studies combining ADC, IVIM, and DKI values for use in the differentiation of benign and malignant breast lesions.…”

Section: Introductionmentioning

confidence: 99%

Application of Diffusion Weighted Imaging Techniques for Differentiating Benign and Malignant Breast Lesions

Ruan

et al. 2021

Front. Oncol.

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To explore the value of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusional kurtosis imaging (DKI) based on diffusion weighted magnetic resonance imaging (DW-MRI) in differentiating benign and malignant breast lesions. A total of 215 patients with breast lesions were prospectively collected for breast MR examination. Single exponential, IVIM, and DKI models were calculated using a series of b values. Parameters including ADC, perfusion fraction (f), tissue diffusion coefficient (D), perfusion-related incoherent microcirculation (D*), average kurtosis (MK), and average diffusivity (MD) were compared between benign and malignant lesions. ROC curves were used to analyze the optimal diagnostic threshold of each parameter, and to evaluate the diagnostic efficacy of single and combined parameters. ADC, D, MK, and MD values were significantly different between benign and malignant breast lesions (P<0.001). Among the single parameters, ADC had the highest diagnostic efficiency (sensitivity 91.45%, specificity 82.54%, accuracy 88.84%, AUC 0.915) and the best diagnostic threshold (0.983 μm2/ms). The combination of ADC and MK offered high diagnostic performance (sensitivity 90.79%, specificity 85.71%, accuracy 89.30%, AUC 0.923), but no statistically significant difference in diagnostic performance as compared with single-parameter ADC (P=0.268). The ADC, D, MK, and MD parameters have high diagnostic value in differentiating benign and malignant breast lesions, and of these individual parameters the ADC has the best diagnostic performance. Therefore, our study revealed that the use of ADC alone should be useful for differentiating between benign and malignant breast lesions, whereas the combination of MK and ADC might improve the diagnostic performance to some extent.

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Intravoxel incoherent motion diffusion‐weighted MRI of invasive breast cancer: Correlation with prognostic factors and kinetic features acquired with computer‐aided diagnosis

Cited by 30 publications

References 30 publications

Comparative Study of Amide Proton Transfer‐Weighted Imaging and Intravoxel Incoherent Motion Imaging in Breast Cancer Diagnosis and Evaluation

Comparative Study of Amide Proton Transfer‐Weighted Imaging and Intravoxel Incoherent Motion Imaging in Breast Cancer Diagnosis and Evaluation

Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes

Application of Diffusion Weighted Imaging Techniques for Differentiating Benign and Malignant Breast Lesions

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