The utility of diffusion-weighted imaging for differentiation of phyllodes tumor from fibroadenoma and breast cancer

Fang, Jinzhi; Zhang, Yuzhong; Li, Ruifeng; Liang, Lanlan; Yu, Jie; Hu, Ziqi; Zhou, Lingling; Liu, Renwei

doi:10.3389/fonc.2023.938189

Cited by 2 publications

(1 citation statement)

References 32 publications

(38 reference statements)

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“…This result is consistent with the finding of McDonald et al ( 22 ), who concluded that ADC mean is a simple and sufficient biomarker and is able to improve the diagnostic ability of breast MRI compared to complex ADC measurement methods. Recently, the value of ADC min in diagnosing breast cancer has aroused the attention of some scholars ( 23 - 25 ). ADC min values represent the highest cellular area composed of tumor stroma.…”

Section: Discussionmentioning

confidence: 99%

Quantitative apparent diffusion coefficient metrics for MRI-only suspicious breast lesions: any added clinical value?

Li,

Wang,

Gao

et al. 2023

Quant Imaging Med Surg

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Background Suspicious breast lesions [Breast Imaging Reporting and Data System (BI-RADS) category 4 or 5] detected only by magnetic resonance imaging (MRI) and invisible on other initial imaging modalities (MRI-only lesions) are usually small and poorly characterized in previous literature, thus making diagnosis and management difficult. This study aimed to investigate the clinical significance of quantitative apparent diffusion coefficient (ADC) metrics derived from conventional diffusion-weighted imaging (DWI) on evaluating MRI-only lesions. Methods A total of 90 suspicious MRI-only lesions were evaluated, including 51 malignant and 39 benign lesions. Morphological and kinetic characteristics of all lesions (termed BI-RADS parameters) were described according to the BI-RADS lexicon on dynamic contrast-enhanced (DCE) imaging. Minimum, maximum, and mean ADC values (ADC min , ADC max , ADC mean ) were obtained by measuring the ADC map of DWI. ADC heterogeneity was then obtained by the following formula: ADC heterogeneity = (ADC max − ADC min )/ADC mean . Diagnostic performance of these parameters was assessed and compared using the receiver operating characteristic (ROC) curve. Results Of the 90 MRI-only lesions, there were 45 masses and 45 non-mass lesions. Among BI-RADS parameters, only two different kinetic patterns were significantly different between benign and malignant groups (P=0.005 and P<0.001, respectively). The area under the ROC curve (AUC) of combined significant ADC parameters (ADC min , ADC mean , and ADC max , all P≤0.001) was significantly higher than that of the two different kinetic patterns (P=0.006 for both). For MRI-only masses, only ADC mean and ADC max , among all BI-RADS and ADC parameters, had diagnostic value (combined AUC =0.833). For non-mass lesions, size, distribution, ADC min , and ADC mean were significantly different between benign and malignant groups (P=0.004, P<0.001, P=0.001, and P<0.001, respectively). In addition, ADC mean had the highest diagnostic performance among all ADC parameters, regardless of mass or non-mass (AUC =0.825 and 0.812, respectively). ADC heterogeneity showed no significant differences, no matter in mass or non-mass groups (P=0.62 and 0.43, respectively). Conclusions In differentiating MRI-only suspicious lesions, quantitative ADC metrics generally performed better than BI-RADS parameters, and ADC mean is still the best ADC parameter to distinguish MRI-only lesions.

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Section: Discussionmentioning

confidence: 99%