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

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.

One-to-one registration of en-face optical coherence tomography attenuation coefficients with histology of a prostatectomy specimen.

Optical coherence tomography (OCT), enables high-resolution 3D imaging of the morphology of light scattering tissues. From the OCT signal, parameters can be extracted and related to tissue structures. One of the quantitative parameters is the attenuation coefficient; the rate at which the intensity of detected light decays in depth. To couple the quantitative parameters with the histology one-to-one registration is needed. The primary aim of this study is to validate a registration method of quantitative OCT parameters to histological tissue outcome through one-to-one registration of OCT with histology. We matched OCT images of unstained fixated prostate tissue slices with corresponding histology slides, wherein different histologic types were demarcated. Attenuation coefficients were determined by a supervised automated exponential fit (corrected for point spread function and sensitivity roll-off related signal losses) over a depth of 0.32 mm starting from 0.10 mm below the automatically detected tissue edge. Finally, the attenuation coefficients corresponding to the different tissue types of the prostate were compared. From the attenuation coefficients, we produced the squared relative residue and goodness-of-fit metric R2 . This article explains the method to perform supervised automated quantitative analysis of OCT data, and the one-to-one registration of OCT extracted quantitative data with histopathological outcomes.

Needle-based optical coherence tomography for the detection of prostate cancer: a visual and quantitative analysis in 20 patients.

Diagnostic accuracy of needle-based optical coherence tomography (OCT) for prostate cancer detection by visual and quantitative analysis is defined. 106 three-dimensional (3-D)-OCT data sets were acquired in 20 prostates after radical prostatectomy and precisely matched with pathology. OCT images were grouped per histological category. Two reviewers performed blind assessments of the OCT images. Sensitivity and specificity for malignancy detection were calculated. Quantitative analyses by automated optical attenuation coefficient calculation were performed. OCT can reliably differentiate between fat, cystic, and regular atrophy and benign glands. The overall sensitivity and specificity for malignancy detection was 79% and 88% for reviewer 1 and 88% and 81% for reviewer 2. Quantitative analysis for differentiation between stroma and malignancy showed a significant difference (4.6 mm - 1 versus 5.0 mm - 1 Mann-Whitney U-test p < 0.0001). A Kruskal-Wallis test showed a significant difference in median attenuation coefficient between stroma, inflammation, Gleason 3, and Gleason 4 (4.6, 4.1, 5.9, and 5.0 mm - 1, respectively). However, attenuation coefficient varied per patient and a related-samples Wilcoxon signed-rank test showed no significant difference per patient (p = 0.17). This study confirmed the one to one correlation of histopathology and OCT. Precise matching showed that most histological tissues categories in the prostate could be distinguished by their unique pattern in OCT images. In addition, the optical attenuation coefficient can play a role in the differentiation between stroma and malignancy; however, a per patient analysis of the optical attenuation coefficient did not show a significant difference.