En-face optical coherence tomography for the detection of cancer in prostatectomy specimens: Quantitative analysis in 20 patients.,Journal of Biophotonics

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En-face optical coherence tomography for the detection of cancer in prostatectomy specimens: Quantitative analysis in 20 patients.
Journal of Biophotonics ( IF 2.0 ) Pub Date : 2020-03-30 , DOI: 10.1002/jbio.201960105
Abel Swaan _{1,

2} , Berrend G Muller ₁ , Leah S Wilk ₂ , Mitra Almasian ₂ , Evita C H Zwartkruis ₃ , L Rence Rozendaal ₃ , Daniel M de Bruin _{1,

2} , Dirk J Faber ₂ , Ton G van Leeuwen ₂ , Marcel B van Herk _{2,

4,

5}

Affiliation

The increase histopathological evaluation of prostatectomy specimens rises the workload on pathologists. Automated histopathology systems, preferably directly on unstained specimens, would accelerate the pathology workflow. In this study, we investigate the potential of quantitative analysis of optical coherence tomography (OCT) to separate benign from malignant prostate tissue automatically. Twenty fixated prostates were cut, from which 54 slices were scanned by OCT. Quantitative OCT metrics (attenuation coefficient, residue, goodness‐of‐fit) were compared for different tissue types, annotated on the histology slides. To avoid misclassification, the poor‐quality slides, and edges of annotations were excluded. Accurate registration of OCT data with histology was achieved in 31 slices. After removing outliers, 56% of the OCT data was compared with histopathology. The quantitative data could not separate malignant from benign tissue. Logistic regression resulted in malignant detection with a sensitivity of 0.80 and a specificity of 0.34. Quantitative OCT analysis should be improved before clinical use.

中文翻译：

面对光学相干断层扫描技术检测前列腺切除术标本中的癌症：20位患者的定量分析。

对前列腺切除术标本的组织病理学评估的增加增加了病理学家的工作量。自动化的组织病理学系统（最好直接在未染色的标本上）将加速病理学工作流程。在这项研究中，我们调查了光学相干断层扫描（OCT）定量分析从良性前列腺组织自动分离良性的潜力。切下20个固定的前列腺，OCT从其中扫描了54个切片。比较了不同组织类型的定量OCT指标（衰减系数，残留物，拟合优度），并在组织学幻灯片上进行了注释。为避免分类错误，排除了质量差的幻灯片和注释的边缘。在31个切片中实现了OCT数据与组织学的准确配准。移除异常值之后，将OCT数据的56％与组织病理学进行了比较。定量数据无法将恶性肿瘤与良性组织分开。Logistic回归导致恶性检测，灵敏度为0.80，特异性为0.34。在临床使用前应改进OCT定量分析。

更新日期：2020-03-30

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