Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures.
Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures.
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DOI：
10.1038/s41598-021-01414-z
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发表时间：
2021-11-08
影响因子：
4.6
通讯作者：
Pogue BW
中科院分区：
文献类型：
--
作者：
Streeter SS;Hunt B;Zuurbier RA;Wells WA;Paulsen KD;Pogue BW
高切缘阳性率在肿瘤保乳手术中是一个紧迫的临床问题。体积X射线扫描正在成为一种强大的离体标本成像技术，用于分析切除边缘，但X射线缺乏非恶性和恶性纤维组织之间的对比度。在这项研究中，开发了组合的微型CT和宽场光学图像放射组学来对乳腺癌组织的恶性肿瘤进行分类，这表明X射线/光学放射组学可以改善恶性肿瘤分类。92个标准化的功能，共注册micro-CT和光学空间频域成像样本提取的54个乳腺肿瘤表现出7个组织亚型的显微组织学分析证实。当包括脂肪样本（AUC = 0.88 vs. 0.90; p值= 3.65e−11）和排除脂肪样本时，多模式特征集与单独的micro-CT相比提高了分类性能，将分类任务集中在非恶性纤维组织与恶性组织上（AUC = 0.78 vs. 0.85; p值= 9.33e−14）。将放射组学方法扩展到高维光学数据-在本研究中称为“光学组学”-为癌症检测提供了一种有前途的光学图像分析技术。放射组学特征数据和分类源代码是公开可用的。
High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.
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影响因子：
2.5
作者：
Abe, Shoko E.;Hill, Joshua S.;White, Richard L., Jr.
通讯作者：
White, Richard L., Jr.
DOI：
10.1056/nejmoa1504473
发表时间：
2015-08-06
期刊：
The New England journal of medicine
影响因子：
--
作者：
Chagpar AB;Killelea BK;Tsangaris TN;Butler M;Stavris K;Li F;Yao X;Bossuyt V;Harigopal M;Lannin DR;Pusztai L;Horowitz NR
通讯作者：
Horowitz NR
影响因子：
3.7
作者：
Cabioglu, Neslihan;Hunt, Kelly K.;Meric-Bernstam, Funda
通讯作者：
Meric-Bernstam, Funda
影响因子：
3.7
作者：
Landercasper, Jeffrey;Borgert, Andrew J.;Wilke, Lee
通讯作者：
Wilke, Lee
影响因子：
3.9
作者：
Janes, S. E. J.;Stankhe, M.;Isgar, B.
通讯作者：
Isgar, B.