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多模态超声层析成像新技术检测乳腺病变。

Novel technology of multimodal ultrasound tomography detects breast lesions.

机构信息

Breast Unit, 1st Department of Propaedeutic Surgery, School of Medicine, University of Athens, Athens, Greece.

出版信息

Eur Radiol. 2013 Mar;23(3):673-83. doi: 10.1007/s00330-012-2659-z. Epub 2012 Sep 16.

Abstract

OBJECTIVES

To introduce a new three-dimensional (3D) diagnostic imaging technology, termed "multimodal ultrasonic tomography" (MUT), for the detection of breast cancer without ionising radiation or compression.

METHODS

MUT performs 3D tomography of the pendulant breast in a water-bath using transmission ultrasound in a fixed-coordinate system. Specialised electronic hardware and signal processing algorithms are used to construct multimodal images for each coronal slice, corresponding to measurements of refractivity and frequency-dependent attenuation and dispersion. In-plane pixel size is 0.25 mm × 0.25 mm and the inter-slice interval can vary from 1 to 4 mm, depending on clinical requirements. MUT imaging was performed on 25 patients ("off-label" use for research purposes only), presenting lesions with sizes >10 mm. Histopathology of biopsy samples, obtained from all patients, were used to evaluate the MUT outcomes.

RESULTS

All lesions (21 malignant and four benign) were clearly identified on the MUT images and correctly classified into benign and malignant based on their respective multimodal information. Malignant lesions generally exhibited higher values of refractivity and frequency-dependent attenuation and dispersion.

CONCLUSION

Initial clinical results confirmed the ability of MUT to detect and differentiate all suspicious lesions with sizes >10 mm discernible in mammograms of 25 female patients.

摘要

目的

介绍一种新的三维(3D)诊断成像技术,称为“多模态超声层析成像”(MUT),用于检测乳腺癌,无需电离辐射或压缩。

方法

MUT 使用固定坐标系中的透射超声在水浴中对摆动乳房进行 3D 层析成像。专门的电子硬件和信号处理算法用于为每个冠状切片构建多模态图像,对应于折射率和频率相关衰减和色散的测量。平面内像素大小为 0.25mm×0.25mm,切片间隔可根据临床要求在 1 到 4mm 之间变化。对 25 名患者(仅出于研究目的“超适应证”使用)进行了 MUT 成像,这些患者的病变大小>10mm。对所有患者获得的活检样本的组织病理学进行了评估,以评估 MUT 结果。

结果

MUT 图像上清晰显示了所有病变(21 个恶性和 4 个良性),并根据各自的多模态信息正确分类为良性和恶性。恶性病变通常表现出更高的折射率和频率相关衰减和色散值。

结论

初步临床结果证实了 MUT 检测和区分所有在 25 名女性患者的乳房 X 线照片中可辨别的大小>10mm 的可疑病变的能力。

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