Beckman Laser Institute, University of California, Irvine, CA 92612, USA.
Radiology. 2010 Jan;254(1):277-84. doi: 10.1148/radiol.09082134.
To develop a near-infrared spectroscopic method to identify breast cancer biomarkers and to retrospectively determine if benign and malignant breast lesions could be distinguished by using this method.
The study was HIPAA compliant and was approved by the university institutional review board. Written informed consent was obtained. By using self-referencing differential spectroscopy (SRDS) analysis, the existence of specific spectroscopic signatures of breast lesions on images acquired by using diffuse optical spectroscopy imaging in the wavelength range (650-1000 nm) was established. The SRDS method was tested in 60 subjects (mean age, 38 years; age range, 22-74 years). There were 17 patients with benign breast tumors and 22 patients with malignant breast tumors. There were 21 control subjects.
Discrimination analysis helped separate malignant from benign tumors. A total of 40 lesions (22 malignant and 18 benign) were analyzed. Twenty were true-positive lesions, 17 were true-negative lesions, one was a false-positive lesion, and two were false-negative lesions (sensitivity, 91% [20 of 22]; specificity, 94% [17 of 18]; positive predictive value, 95% [20 of 21]; and negative predictive value, 89% [17 of 19]).
The SRDS method revealed localized tumor biomarkers specific to pathologic state.
开发一种近红外光谱方法来识别乳腺癌生物标志物,并通过该方法回顾性地确定良性和恶性乳腺病变是否可以区分。
该研究符合 HIPAA 规定,并获得了大学机构审查委员会的批准。获得了书面知情同意。通过使用自参考差示光谱 (SRDS) 分析,在波长范围 (650-1000nm) 内通过漫射光学光谱成像获得的乳腺病变图像上建立了特定光谱特征的存在。SRDS 方法在 60 名受试者(平均年龄 38 岁;年龄范围 22-74 岁)中进行了测试。其中 17 名患者患有良性乳腺肿瘤,22 名患者患有恶性乳腺肿瘤。有 21 名对照受试者。
判别分析有助于将恶性与良性肿瘤分开。共分析了 40 个病变(22 个恶性和 18 个良性)。其中 20 个为真阳性病变,17 个为真阴性病变,1 个为假阳性病变,2 个为假阴性病变(敏感性为 91%[22 个中的 20 个];特异性为 94%[18 个中的 17 个];阳性预测值为 95%[21 个中的 20 个];阴性预测值为 89%[19 个中的 17 个])。
SRDS 方法揭示了特定于病理状态的局部肿瘤生物标志物。