PDF(Pubmed)
Abstract：
UNASSIGNED: Mammographic architectural distortion (AD) is usually subtle and has variable presentations and causes, which poses a diagnostic challenge for breast radiologists and consequently a complex decision-making challenge for clinicians and patients. Presently, there is no reliable imaging standard to differentiate between malignant and benign ADs preoperatively. This study aimed to perform a comprehensive analysis of detailed mammographic and ultrasonographic features and clinical characteristics to enhance the diagnostic and differential efficacy for AD lesions. The findings have the potential to boost the diagnostic confidence of breast radiologists when encountering with AD lesions and could be instrumental in refining clinical management strategies for ADs.
UNASSIGNED: This retrospective study included consecutive female patients with ADs on screening or diagnostic mammography from January 6, 2015, to December 28, 2018. The patient\'s clinical data, mammographic and ultrasonographic or \"second look\" ultrasonographic findings, and pathological results were reviewed. The continuous variables were analyzed using the t-test. The categorical variables were assessed using the Chi-square test or two-tailed Fisher\'s exact test. Logistic regression analyses were conducted to evaluate potential risk factors for pathologically proven malignant ADs. Machine learning model based on multimodal clinical and imaging features was constructed using R software.
UNASSIGNED: Ultimately, 344 patients with 346 AD lesions were enrolled in the study (mean age: 47.40±10.07 years; range, 19-84 years). Of the ADs, 228 were malignant and 118 were non-malignant. Palpable AD on mammography was more likely to indicate malignancy than non-palpable AD (83.43% vs. 49.15%, P<0.001). AD associated with other mammographic findings was more likely to be malignant than pure AD (73.58% vs. 59.36%, P=0.005). Ultrasonography (US) correlates were observed in 345 of these 346 AD lesions. Among these US correlates, 63 (18.26%, 63/345) were detected by \"second look\" ultrasound. For the US correlates, the mammographic ADs that appeared as non-mass-like hypoechoic areas and masses on US were more likely to be malignant than those that appeared as other abnormalities (P<0.001). The sensitivity, specificity and diagnostic accuracy of the eXtreme Gradient Boosting (XGBoost) model based on clinical and comprehensive imaging features in differentiation of AD lesions in the validation set were 66.46%, 94.23% and 78.9%, respectively, and the AUC was 0.886 (95% confidence interval: 0.825-0.947).
UNASSIGNED: The application of mammograms-guided \"second-look\" ultrasound could enhance the detection of US correlates, particularly non-mass-like features. The comprehensive analysis based on clinical and multimodal imaging features could be beneficial in improving the diagnostic and differential efficacy for AD lesions detected on mammography and instrumental in refining clinical management strategies for ADs.
UNASSIGNED: This retrospective study included consecutive female patients with ADs on screening or diagnostic mammography from January 6, 2015, to December 28, 2018. The patient\'s clinical data, mammographic and ultrasonographic or \"second look\" ultrasonographic findings, and pathological results were reviewed. The continuous variables were analyzed using the t-test. The categorical variables were assessed using the Chi-square test or two-tailed Fisher\'s exact test. Logistic regression analyses were conducted to evaluate potential risk factors for pathologically proven malignant ADs. Machine learning model based on multimodal clinical and imaging features was constructed using R software.
UNASSIGNED: Ultimately, 344 patients with 346 AD lesions were enrolled in the study (mean age: 47.40±10.07 years; range, 19-84 years). Of the ADs, 228 were malignant and 118 were non-malignant. Palpable AD on mammography was more likely to indicate malignancy than non-palpable AD (83.43% vs. 49.15%, P<0.001). AD associated with other mammographic findings was more likely to be malignant than pure AD (73.58% vs. 59.36%, P=0.005). Ultrasonography (US) correlates were observed in 345 of these 346 AD lesions. Among these US correlates, 63 (18.26%, 63/345) were detected by \"second look\" ultrasound. For the US correlates, the mammographic ADs that appeared as non-mass-like hypoechoic areas and masses on US were more likely to be malignant than those that appeared as other abnormalities (P<0.001). The sensitivity, specificity and diagnostic accuracy of the eXtreme Gradient Boosting (XGBoost) model based on clinical and comprehensive imaging features in differentiation of AD lesions in the validation set were 66.46%, 94.23% and 78.9%, respectively, and the AUC was 0.886 (95% confidence interval: 0.825-0.947).
UNASSIGNED: The application of mammograms-guided \"second-look\" ultrasound could enhance the detection of US correlates, particularly non-mass-like features. The comprehensive analysis based on clinical and multimodal imaging features could be beneficial in improving the diagnostic and differential efficacy for AD lesions detected on mammography and instrumental in refining clinical management strategies for ADs.
摘要：
■乳腺摄影建筑失真（AD）通常是微妙的，并且具有可变的表现和原因，这对乳腺放射科医师提出了诊断挑战，因此对临床医生和患者提出了复杂的决策挑战。目前,术前没有可靠的影像学标准来区分恶性和良性AD.这项研究旨在对详细的乳房X线和超声特征以及临床特征进行综合分析，以提高对AD病变的诊断和鉴别功效。这些发现有可能提高乳腺放射科医师在遇到AD病变时的诊断信心，并可能有助于完善AD的临床管理策略。
■这项回顾性研究纳入了2015年1月6日至2018年12月28日连续接受筛查或诊断性乳腺X线摄影的女性患者。病人的临床资料,乳房X线摄影和超声检查或“第二次看”超声检查结果，并回顾病理结果。采用t检验对连续变量进行分析。使用卡方检验或双尾Fisher精确检验评估分类变量。进行Logistic回归分析以评估经病理证实的恶性AD的潜在危险因素。利用R软件构建基于多模态临床和影像学特征的机器学习模型。
■最终，研究纳入了344例346例AD病变患者（平均年龄：47.40±10.07岁；范围，19-84岁）。在广告中，228例为恶性，118例为非恶性。乳房X线照相术上可触及的AD比不可触及的AD更可能表明恶性肿瘤（83.43％vs.49.15%,P<0.001)。与其他乳房X线检查结果相关的AD比单纯的AD更可能是恶性的（73.58％vs.59.36%，P=0.005)。在346个AD病变中的345个中观察到超声检查（US）相关。在这些美国相关人士中，63（18.26%，63/345）通过“第二次看”超声检测到。对于美国来说，在US上表现为非肿块样低回声区和肿块的乳房X线摄影AD比表现为其他异常的AD更可能是恶性的(P<0.001).敏感性,基于临床和综合影像学特征的极限梯度提升(XGBoost)模型在验证集中鉴别AD病灶的特异性和诊断准确率为66.46%,94.23%和78.9%，分别,AUC为0.886（95%置信区间：0.825-0.947）。
■乳房X线照片引导的“第二次看”超声的应用可以增强对美国相关物的检测，特别是非块状特征。基于临床和多模态影像学特征的综合分析可能有助于提高在乳房X线摄影上发现的AD病变的诊断和鉴别功效，并有助于完善AD的临床管理策略。
■这项回顾性研究纳入了2015年1月6日至2018年12月28日连续接受筛查或诊断性乳腺X线摄影的女性患者。病人的临床资料,乳房X线摄影和超声检查或“第二次看”超声检查结果，并回顾病理结果。采用t检验对连续变量进行分析。使用卡方检验或双尾Fisher精确检验评估分类变量。进行Logistic回归分析以评估经病理证实的恶性AD的潜在危险因素。利用R软件构建基于多模态临床和影像学特征的机器学习模型。
■最终，研究纳入了344例346例AD病变患者（平均年龄：47.40±10.07岁；范围，19-84岁）。在广告中，228例为恶性，118例为非恶性。乳房X线照相术上可触及的AD比不可触及的AD更可能表明恶性肿瘤（83.43％vs.49.15%,P<0.001)。与其他乳房X线检查结果相关的AD比单纯的AD更可能是恶性的（73.58％vs.59.36%，P=0.005)。在346个AD病变中的345个中观察到超声检查（US）相关。在这些美国相关人士中，63（18.26%，63/345）通过“第二次看”超声检测到。对于美国来说，在US上表现为非肿块样低回声区和肿块的乳房X线摄影AD比表现为其他异常的AD更可能是恶性的(P<0.001).敏感性,基于临床和综合影像学特征的极限梯度提升(XGBoost)模型在验证集中鉴别AD病灶的特异性和诊断准确率为66.46%,94.23%和78.9%，分别,AUC为0.886（95%置信区间：0.825-0.947）。
■乳房X线照片引导的“第二次看”超声的应用可以增强对美国相关物的检测，特别是非块状特征。基于临床和多模态影像学特征的综合分析可能有助于提高在乳房X线摄影上发现的AD病变的诊断和鉴别功效，并有助于完善AD的临床管理策略。
