Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer

Mori, Nobuhiro; Mugikura, Shunji; Takasawa, Chiaki; Miyashita, Minoru; Shimauchi, Akiko; Ota, Hideki; Ishida, Toru; Kasajima, Atsuko; Takase, Kei; Kodama, Tetsuya; Takahashi, Satoshi

doi:10.1007/s00330-015-3847-4

Cited by 58 publications

(58 citation statements)

References 30 publications

(36 reference statements)

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“…In a recent study, Mori et al [31] found results that were concordant with our data, showing that ADC values were significantly lower in the LVI-positive group than in the negative one. They also found a significantly larger tumor size and higher axillary lymph node metastasis rate in lesions.…”

Section: Discussionsupporting

confidence: 92%

Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer

Durando

Gennaro

Cho

et al. 2016

European Journal of Radiology

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Purpose To assess the association between apparent diffusion coefficient (ADC), and histological prognostic parameters in malignant breast lesions. The ability of ADC to identify lesions with the presence of Lymphovascular invasion (LVI) in breast carcinoma was also examined. Materials and Methods This HIPAA-compliant retrospective study consisted of 212 consecutive patients with known cancers who underwent 3.0T MRI between January 2011 and 2013. In this study, a total of 126 malignant lesions in 114 women, who had undergone DWI (b-values of 0 and 1000 s/mm2) in addition to diagnostic MRI, were included. Patients with less than 0.8 cm lesions, or those who underwent neoadjuvant chemotherapy or suboptimal DW images were excluded. Classical prognostic factors [lesion size, histopathological type and grade, lymph node (LN) status and lymphovascular invasion (LVI)], molecular prognostic markers [estrogen receptor (ER), progesterone receptor (PR) and human epidermal grow factor receptor 2(HER2)] were reviewed and recorded. A region of interest (ROI) was drawn within the lesions to measure ADC values. Statistical analyses were performed by the Wilcoxon rank sum test (statistical significance at P<0.05). Adjusted p values from multiple comparison analysis were also calculated. Results This study demonstrates an inverse correlation between ADC and LVI in malignant lesions and the ability of ADC to identify aggressiveness in lesions with positive LVI. Tumor size, grade, ER, PR, HER2 and lymph node status did not impact tumor ADC value. However, tumors with LVI showed significantly lower ADC values when compared to tumors without LVI, regardless of the enhancement type, histological grade, histological type, and LN status. Conclusion Our study shows that ADC could be a potential clinical adjunct in the evaluation of prognostic factors related to malignant lesion aggressiveness such as LVI.

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Section: Discussionsupporting

confidence: 92%

Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer

Durando

Gennaro

Cho

et al. 2016

European Journal of Radiology

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“…It might be because the peritumoral‐tumoral ADC ratio, as a relative measurement of ADC, is more reliable than the peritumoral maximal ADC or tumoral ADC as an absolute measurement of ADC. Many confounding factors, including factors related to image parameters (magnetic susceptibility, spatial resolution, signal‐to‐noise ratio, b‐values, field strength, diffusion encoding, noise, fitting procedure, and channel numbers of the coil) and those related to pathophysiological features (cellular density, tissue component) of the lesions, might affect the absolute measurement of ADC despite the absence of true diffusion …”

Section: Discussionmentioning

confidence: 99%

“…DCE‐MRI is useful for evaluating tumor angiogenesis, which might be helpful for predicting lymph node metastasis, as breast cancer with higher angiogenesis has a significantly higher likelihood of presenting with regional lymph node metastasis . Regarding DWI, a previous study reported that the peritumoral‐tumoral apparent diffusion coefficient (ADC) ratio of breast cancer was associated with lymphovascular invasion, which is closely related to lymph node metastasis . In practice, clinicopathologic variables associated with lymph node metastases, such as lymphatic invasion, can only be obtained through surgery, and are thus not useful for preoperative prediction of lymph node metastases .…”

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confidence: 99%

Dynamic contrast‐enhanced and diffusion‐weighted MRI of invasive breast cancer for the prediction of sentinel lymph node status

Choi

Youk

Choi

et al. 2019

Magnetic Resonance Imaging

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Background Although sentinel lymph node biopsy (SLNB) is the current standard for identifying lymph metastasis in breast cancer patients, there are complications of SLNB. Purpose To evaluate preoperative dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) and diffusion‐weighted imaging (DWI) of invasive breast cancer for predicting sentinel lymph node metastasis. Study Type Retrospective. Population In all, 309 patients who underwent clinically node‐negative invasive breast cancer surgery Field Strength/Sequence 3.0T, DCE‐MRI, DWI. Assessment We collected clinicopathologic variables (age, histologic and nuclear grade, extensive intraductal carcinoma component, lymphovascular invasion, and immunohistochemical profiles) and preoperative MRI features (tumor size, background parenchymal enhancement, internal enhancement, adjacent vessel sign, whole‐breast vascularity, initial enhancement pattern, kinetic curve types, quantitative kinetic parameters, tumoral apparent diffusion coefficient [ADC], peritumoral maximal ADC, and peritumoral‐tumoral ADC ratio). Statistical Tests Multivariate logistic regressions were performed to determine independent variables associated with SLN metastasis, and the area under the receiver operating characteristic curve (AUC) was analyzed for those variables. Results 41 (13.3%) of the patients showed SLN metastasis. With MRI, tumor size (odds ratio [OR], 1.11; 95% confidence interval [CI], 1.06–1.17), heterogeneous (OR, 5.33; 95% CI, 1.71–16.58), and rim (OR, 15.54; 95% CI, 2.12–113.72) enhancement and peritumoral–tumoral ADC ratio (OR, 72.79; 95% CI, 7.15–740.82) were independently associated with SLN metastasis. Clinicopathologic variables independently associated with SLN metastasis included age (OR, 0.96; 95% CI, 0.92–0.99) and CD31 (OR, 2.90; 95% CI, 1.04–8.92). The area under the curve (AUC) of MRI features (0.80; 95% CI, 0.73–0.87) was significantly higher than for clinicopathologic variables (0.68; 95% CI, 0.60–0.77; P = 0.048) and was barely below statistical significance for combined MRI features with clinicopathologic variables (0.84; 95% CI 0.78–0.90, P = 0.057). Data Conclusion Preoperative internal enhancement on DCE‐MRI and peritumoral‐tumoral ADC ratio on DWI might be useful for predicting SLN metastasis in patients with invasive breast cancer. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:615–626.

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“…Percutaneous biopsy before surgery is insufficient when the biopsy specimen fails to provide enough information regarding the peritumoral tissue . Previous studies on breast magnetic resonance imaging (MRI) have demonstrated that a few MRI features, including adjacent vessel sign, peritumoral edema, tumor apparent diffusion coefficient (ADC), and peritumor‐to‐tumor ADC ratio are associated with LVI . However, the value of these MRI features has remained controversial.…”

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confidence: 99%

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast‐enhanced‐MRI‐based radiomics

Liu

Bao

et al. 2019

Magnetic Resonance Imaging

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Background Lymphovascular invasion (LVI) status facilitates the selection of optimal therapeutic strategy for breast cancer patients, but in clinical practice LVI status is determined in pathological specimens after resection. Purpose To explore the use of dynamic contrast‐enhanced (DCE)‐magnetic resonance imaging (MRI)‐based radiomics for preoperative prediction of LVI in invasive breast cancer. Study Type Prospective. Population Ninety training cohort patients (22 LVI‐positive and 68 LVI‐negative) and 59 validation cohort patients (22 LVI‐positive and 37 LVI‐negative) were enrolled. Field Strength/Sequence 1.5 T and 3.0 T, T1‐weighted DCE‐MRI. Assessment Axillary lymph node (ALN) status for each patient was evaluated based on MR images (defined as MRI ALN status), and DCE semiquantitative parameters of lesions were calculated. Radiomic features were extracted from the first postcontrast DCE‐MRI. A radiomics signature was constructed in the training cohort with 10‐fold cross‐validation. The independent risk factors for LVI were identified and prediction models for LVI were developed. Their prediction performances and clinical usefulness were evaluated in the validation cohort. Statistical Tests Mann–Whitney U‐test, chi‐square test, kappa statistics, least absolute shrinkage and selection operator (LASSO) regression, logistic regression, receiver operating characteristic (ROC) analysis, DeLong test, and decision curve analysis (DCA). Results Two radiomic features were selected to construct the radiomics signature. MRI ALN status (odds ratio, 10.452; P < 0.001) and the radiomics signature (odds ratio, 2.895; P = 0.031) were identified as independent risk factors for LVI. The value of the area under the curve (AUC) for a model combining both (0.763) was higher than that for MRI ALN status alone (0.665; P = 0.029) and similar to that for the radiomics signature (0.752; P = 0.857). DCA showed that the combined model added more net benefit than either feature alone. Data Conclusion The DCE‐MRI‐based radiomics signature in combination with MRI ALN status was effective in predicting the LVI status of patients with invasive breast cancer before surgery. Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:847–857.

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Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer

Cited by 58 publications

References 30 publications

Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer

Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer

Dynamic contrast‐enhanced and diffusion‐weighted MRI of invasive breast cancer for the prediction of sentinel lymph node status

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast‐enhanced‐MRI‐based radiomics

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