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.
Prostate cancer treatment is shifting from radical to focal therapy. Instant tumor visualization on a microscopic level is crucial for clinical application of focal therapy. Optical coherence tomography (OCT) produces instant tissue visualization on a µm scale and the attenuation of OCT signal as a measure of tissue organization. The objective is to correlate qualitative and quantitative OCT analysis with histopathology.
Twenty prostates were analyzed by needle based OCT after radical prostatectomy. For precise correlation, whole mount histology slides were cut through the OCT trajectory. OCT images were classified in eight histological categories. Two reviewers independently performed assessment of the OCT images into these categories. Quantitative attenuation coefficient was used to discriminate stroma and malignant tissue. Sensitivity and specificity for detection of malignancy on OCT was calculated.
Visual analyses showed that OCT can reliably differentiate between fat, cystic and regular atrophy and benign glands. Differentiation of benign stroma and inflammation and also malignancy Gleason 3 and 4 is more difficult. Sensitivity and specificity for detection of malignancy on OCT were calculated at 77% and 75%. Quantitative analysis by means of the attenuation coefficient for differentiation between stroma and malignancy showed no significant difference (4.39 mm-1 vs. 5.31 mm-1).
Precise correlation of histology and OCT is possible and helps us to understand what we see and measure on OCT. Visual malignancy detection shows reasonable sensitivity and specificity. Our future studies focus on improving discrimination of malignancy with OCT for example by combining an extra imaging modality.
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