Jeong Jeong-Won, Shin Dae C, Do Syn-Ho, Blanco Cesar, Klipfel Nancy E, Holmes Dennis R, Hovanessian-Larsen Linda J, Marmarelis Vasilis Z
Alfred E. Mann Institute for Biomedical Engineering, University of Southern California, 1042 W 36th Pl, DRB B21, Los Angeles, CA 90089, USA.
J Ultrasound Med. 2008 Mar;27(3):435-51. doi: 10.7863/jum.2008.27.3.435.
This study examines the tissue differentiation capability of the recently developed high-resolution ultrasonic transmission tomography (HUTT) system in the context of differentiating between benign and malignant tissue types in mastectomy specimens.
Eight mastectomy patients provided breast specimens with benign and malignant lesions. The specimens were scanned by the HUTT system with a pair of either 8- or 4-MHz transducers. Multiband HUTT images over the frequency range from 2 to 10 MHz provide characteristic profiles of frequency-dependent attenuation, termed "multiband profiles," at individual pixels. These features are classified through a novel algorithm of "segment-wise classification" that identifies the disjoint segments of various tissue types and subsequently classifies them into respective diagnostic categories using a measure of proximity to the respective multiband profile templates that have been previously obtained from reference data.
We preformed intraspecimen and interspecimen analyses of 108 slices from 8 mastectomy specimens for which "ground truth" was provided by pathology reports. The average performance indices for 2-way classification (malignant versus nonmalignant tissue) in these intraspecimen (interspecimen) specimen studies were found to be sensitivity of 81.9% (89.6%), specificity of 92.9% (92.1%), and accuracy of 89.2% (89.4%), whereas the indices for the 3-way classification were moderately lower.
The results have shown the potential of the HUTT technology for reliable differentiation of cancerous lesions from benign changes and normal tissue in mastectomy specimens using frequency-dependent ultrasound attenuation profiles.
本研究在区分乳房切除标本中良性和恶性组织类型的背景下，考察最新开发的高分辨率超声透射断层扫描（HUTT）系统的组织分化能力。
8名乳房切除患者提供了含有良性和恶性病变的乳房标本。使用一对8兆赫或4兆赫的换能器通过HUTT系统对标本进行扫描。2至10兆赫频率范围内的多波段HUTT图像在各个像素处提供了频率依赖性衰减的特征曲线，称为“多波段曲线”。这些特征通过一种新颖的“逐段分类”算法进行分类，该算法识别各种组织类型的不连续段，随后使用与先前从参考数据中获得的相应多波段曲线模板的接近度测量值将它们分类到各自的诊断类别中。
我们对8个乳房切除标本的108个切片进行了标本内和标本间分析，病理报告提供了这些标本的“真实情况”。在这些标本内（标本间）标本研究中，双向分类（恶性与非恶性组织）的平均性能指标为：敏感性81.9%（89.6%），特异性92.9%（92.1%），准确性89.2%（89.4%），而三向分类的指标略低。
结果表明，HUTT技术有潜力利用频率依赖性超声衰减曲线，在乳房切除标本中可靠地区分癌性病变与良性变化及正常组织。
