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. 2021 Aug 13;12(9):5597-5613.
doi: 10.1364/BOE.433346. eCollection 2021 Sep 1.

Rapid non-destructive volumetric tumor yield assessment in fresh lung core needle biopsies using polarization sensitive optical coherence tomography

Affiliations

Rapid non-destructive volumetric tumor yield assessment in fresh lung core needle biopsies using polarization sensitive optical coherence tomography

Sreyankar Nandy et al. Biomed Opt Express. .

Abstract

Adequate tumor yield in core-needle biopsy (CNB) specimens is essential in lung cancer for accurate histological diagnosis, molecular testing for therapeutic decision-making, and tumor biobanking for research. Insufficient tumor sampling in CNB is common, primarily due to inadvertent sampling of tumor-associated fibrosis or atelectatic lung, leading to repeat procedures and delayed diagnosis. Currently, there is no method for rapid, non-destructive intraprocedural assessment of CNBs. Polarization-sensitive optical coherence tomography (PS-OCT) is a high-resolution, volumetric imaging technique that has the potential to meet this clinical need. PS-OCT detects endogenous tissue properties, including birefringence from collagen, and degree of polarization uniformity (DOPU) indicative of tissue depolarization. Here, PS-OCT birefringence and DOPU measurements were used to quantify the amount of tumor, fibrosis, and normal lung parenchyma in 42 fresh, intact lung CNB specimens. PS-OCT results were compared to and validated against matched histology in a blinded assessment. Linear regression analysis showed strong correlations between PS-OCT and matched histology for quantification of tumors, fibrosis, and normal lung parenchyma in CNBs. PS-OCT distinguished CNBs with low tumor content from those with higher tumor content with high sensitivity and specificity. This study demonstrates the potential of PS-OCT as a method for rapid, non-destructive, label-free intra-procedural tumor yield assessment.

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Conflict of interest statement

LPH: Boehringer Ingelheim, Pliant Therapeutics, LX Medical, and Biogen Idec. MJS: NinePoint Medical, LX Medical.

Figures

Fig. 1.
Fig. 1.
PS-OCT quantification workflow.
Fig. 2.
Fig. 2.
Volumetric (a) structural, (b) birefringence and (c) DOPU images oriented and cut obliquely for comparison with the histopathological features in the corresponding (d) H&E and (e) trichrome sections of a CNB specimen with adenocarcinoma (T) mixed with dense fibrosis (F) and inflammation. Birefringence colormap (b, right), ranging from 0°/100 µm (no birefringence) to 65°/100 µm (high birefringence). DOPU colormap (c, right), ranging from 0 (low DOPU) to 1 (high DOPU). Corresponding (d) H&E and (e) trichrome stained histology confirms the presence of tumor and fibrosis with inflammation in the CNB specimen. Scalebars: 0.5 mm.
Fig. 3.
Fig. 3.
Volumetric a) structural, (b) birefringence and (c) DOPU images oriented and cut obliquely for comparison with the histopathological features in the corresponding (c) H&E and (d) trichrome sections CNB specimen with adenocarcinoma in the left half and fibrosis in the right half of the specimen. Inflammatory infiltrates are present throughout the specimen. Birefringence colormap (b, right), ranging from 0°/100 µm (no birefringence) to 65°/100 µm (high birefringence). DOPU colormap (c, right), ranging from 0 (low DOPU) to 1 (high DOPU). Corresponding (d) H&E and (e) trichrome stained histology confirm the presence of tumor in the left half and fibrosis in the right half of the CNB specimen. Scalebars: 0.5 mm.
Fig. 4.
Fig. 4.
Volumetric (a) structural, (b) birefringence and (c) DOPU images oriented and cut obliquely for comparison with the histopathological features in the corresponding (d) H&E and (e) trichrome sections of a CNB specimen consisting mostly of dense tumor associated fibrosis mixed with regions of inflammation. Birefringence colormap (b, right), ranging from 0°/100 µm (no birefringence) to 65°/100 µm (high birefringence). DOPU colormap (c, right), ranging from 0 (low DOPU) to 1 (high DOPU). Corresponding (d) H&E and (e) trichrome images, confirms the presence of dense tumor associated fibrosis, mixed with inflammation in the majority of the CNB specimen. Scalebars: 0.5 mm.
Fig. 5.
Fig. 5.
Volumetric (a) structural, (b) birefringence and (c) DOPU images oriented and cut obliquely for comparison with the histopathological features in the corresponding H&E and trichrome sections of a CNB specimen consisting mostly of normal lung parenchyma, which appears as a lattice-like pattern of alveoli (A), with vessels (V). The region on the far left (red arrow) contains inflammation and pigment particles. Birefringence colormap (b, right), ranging from 0°/100 µm (no birefringence) to 65°/100 µm (high birefringence). DOPU colormap (c, right), ranging from 0 (low DOPU) to 1 (high DOPU). Corresponding (d) H&E and (e) trichrome images, confirming the presence of alveolar lung parenchyma, with small amounts of collagen within the alveolar walls and surrounding vessels. Scalebars: 0.5 mm.
Fig. 6.
Fig. 6.
Quantitative PS-OCT assessment of tumor, fibrosis, and normal lung components in CNB as compared to histology. (a, c, e) Linear regression analysis demonstrated strong correlation between PS-OCT and histology for quantifying (a) tumor (r = 0.85, P < 0.001), (c) fibrosis (r = 0.9, P < 0.001) and (e) normal lung parenchyma (r = 0.89, P < 0.001). The darker shaded bands in (a, c, e) indicate the 95% confidence intervals, whereas the lighter shaded bands indicate the 95% prediction intervals. (b, d, f) Bland-Altman analysis comparing PS-OCT and histology measurements showed an overall bias of (b) 5.61% for tumor, (d) -4.37% for fibrosis and (f) 6.58% for normal lung parenchyma, respectively. The dotted lines in (b, d, f) indicate the upper and lower 95% confidence intervals.

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