Spectral discrimination of breast pathologies in situ using spatial frequency domain imaging.
Spectral discrimination of breast pathologies in situ using spatial frequency domain imaging.
复制标题
DOI：
10.1186/bcr3455
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Wells WA
中科院分区：
文献类型：
--
作者：
Laughney AM;Krishnaswamy V;Rizzo EJ;Schwab MC;Barth RJ Jr;Cuccia DJ;Tromberg BJ;Paulsen KD;Pogue BW;Wells WA
在全国范围内，25%至50%的接受乳房肿瘤切除术进行局部管理的乳腺癌患者需要二次切除，因为残留肿瘤的持续存在。术中通过冰冻切片分析评估标本边缘在保乳手术中并没有被广泛采用。在这里，测试了一种新的乳腺原位病理学宽视场光学成像方法，以确定该系统是否可以在常规病理处理之前准确区分癌症和良性组织。空间频域成像（SFDI）被用来量化近红外（NIR）光学参数在47个乳房肿瘤切除术组织标本的表面。空间频率和波长相关的反射光谱进行参数化匹配模拟光传输。将光谱图像与组织的相邻染色切片中的组织病理学共配准，在原位成像的几何形状中切割。一个监督分类器和特征选择算法的实现，以自动判别乳腺病理和排名的贡献，每个参数的诊断。光谱参数以82%的准确度区分所有病理亚型，并以88%的准确度、高特异性（93%）和合理的灵敏度（79%）区分良性（纤维囊性疾病、纤维腺瘤）和恶性（DCIS、浸润性癌症和新辅助化疗后部分治疗的浸润性癌症）病理。虽然光谱吸收和散射功能的判别分类器的基本组成部分，散射表现出较低的方差和贡献最大的组织类型的分离。散射斜率是敏感的间质和上皮分布定量免疫组化测定。SFDI是一种新的定量成像技术，可提供特定的组织类型诊断。其平面采样和频率相关深度传感的组合在临床上是实用的，并且适合乳房手术边缘评估。本研究首次将SFDI应用于外科乳腺组织的病理鉴别。它代表了一个重要的步骤，立即离体成像手术标本，以减少与乳房肿块切除术相关的二次切除率高。
Nationally, 25% to 50% of patients undergoing lumpectomy for local management of breast cancer require a secondary excision because of the persistence of residual tumor. Intraoperative assessment of specimen margins by frozen-section analysis is not widely adopted in breast-conserving surgery. Here, a new approach to wide-field optical imaging of breast pathology in situ was tested to determine whether the system could accurately discriminate cancer from benign tissues before routine pathological processing. Spatial frequency domain imaging (SFDI) was used to quantify near-infrared (NIR) optical parameters at the surface of 47 lumpectomy tissue specimens. Spatial frequency and wavelength-dependent reflectance spectra were parameterized with matched simulations of light transport. Spectral images were co-registered to histopathology in adjacent, stained sections of the tissue, cut in the geometry imaged in situ. A supervised classifier and feature-selection algorithm were implemented to automate discrimination of breast pathologies and to rank the contribution of each parameter to a diagnosis. Spectral parameters distinguished all pathology subtypes with 82% accuracy and benign (fibrocystic disease, fibroadenoma) from malignant (DCIS, invasive cancer, and partially treated invasive cancer after neoadjuvant chemotherapy) pathologies with 88% accuracy, high specificity (93%), and reasonable sensitivity (79%). Although spectral absorption and scattering features were essential components of the discriminant classifier, scattering exhibited lower variance and contributed most to tissue-type separation. The scattering slope was sensitive to stromal and epithelial distributions measured with quantitative immunohistochemistry. SFDI is a new quantitative imaging technique that renders a specific tissue-type diagnosis. Its combination of planar sampling and frequency-dependent depth sensing is clinically pragmatic and appropriate for breast surgical-margin assessment. This study is the first to apply SFDI to pathology discrimination in surgical breast tissues. It represents an important step toward imaging surgical specimens immediately ex vivo to reduce the high rate of secondary excisions associated with breast lumpectomy procedures.
登录
查看更多内容
影响因子：
3.5
作者：
Bigio, IJ;Bown, SG;Saunders, C
通讯作者：
Saunders, C
影响因子：
5.6
作者：
FERREIRO, JA;GISVOLD, JJ;BOSTWICK, DG
通讯作者：
BOSTWICK, DG
影响因子：
3.5
作者：
Cuccia DJ;Bevilacqua F;Durkin AJ;Ayers FR;Tromberg BJ
通讯作者：
Tromberg BJ
影响因子：
82.9
作者：
Gurjar, RS;Backman, V;Feld, MS
通讯作者：
Feld, MS
影响因子：
2.4
作者：
Bogaards, A.;Sterenborg, H. J. C. M.;Lilge, L.
通讯作者：
Lilge, L.