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More than just being nice: The importance of rapport to understanding

机译:不只是友善:融洽相处对理解的重要性

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Objectives: To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions. Methods: Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50-3,000 s/mm 2). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined. Results: Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p =0.017; MD, p =0.028; MK, p =0.017). ADC and MD were higher for benign (1.96± 0.41×10-3 and 2.17± 0.42×10 -3 mm2/s, respectively) than for malignant lesions (1.33± 0.18×10-3 and 1.52± 0.50×10 -3 mm2/s). MK was higher for malignant (0.61±0.27) than benign lesions (0.37±0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC,MDandMK): p =0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p =0.016). Conclusions: Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed. Key Points: ? The diffusion kurtosis model provides new information regarding breast lesions ? MD and MK are valid parameters to characterise tissue microstructure ? MK enables improved lesion differentiation ? MK is able to differentiate lesions that display similar ADC values
机译:目的:评估弥散加权成像(DWI)和弥散峰度成像(DKI)在乳腺病变的鉴别和表征中的作用。方法:36例妇女接受了包括多个b值(50-3,000 s / mm 2)的DWI序列的乳房磁共振成像(MRI)。通过病变类型和组织学亚型计算表观扩散系数(ADC),平均扩散率(MD)和平均峰度(MK)的平均值。确定了参数之间的差异和相关性。结果:发现44个病变。对于所有参数,良性和恶性病变之间存在显着差异(ADC,p = 0.017; MD,p ​​= 0.028; MK,p = 0.017)。良性病变的ADC和MD值(分别为1.96±0.41×10-3和2.17±0.42×10 -3 mm2 / s)高于恶性病变(1.33±0.18×10-3和1.52±0.50×10 -3 mm2 / s)。恶性肿瘤的MK(0.61±0.27)高于良性病变(0.37±0.18)。我们发现浸润性导管癌(IDC)和纤维腺瘤(FA)在所有参数(ADC,MD和MK)之间的差异分别为p = 0.016、0.022和0.016。 FA和纤维囊性变化(FC)仅在MK中显示差异(p = 0.016)。结论:乳腺病变中的扩散遵循非高斯分布。 MK可以区分和表征乳腺病变,从而提供有关微结构复杂性的新见解。为了确认这些结果,应该在更广泛的样本中进行进一步的研究。关键点: ?扩散峰度模型提供有关乳腺病变的新信息? MD和MK是表征组织微结构的有效参数? MK可以改善病变鉴别能力? MK能够区分显示相似ADC值的病变

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