Prospective detection of cervical dysplasia with scanning angle-resolved low coherence interferometry

Abstract

We present a prospective clinical study using angle-resolved low-coherence interferometry (a/LCI) to detect cervical dysplasia via depth resolved nuclear morphology measurements. The study, performed at the Jacobi Medical Center, compares 80 a/LCI optical biopsies taken from 20 women with histopathological tissue diagnosis of co-registered physical biopsies. A novel instrument was used for this study that enables 2D scanning across the cervix without repositioning the probe. The main study goal was to compare performance with a previous clinical a/LCI point-probe instrument [Int. J. Cancer140, 1447 (2017)] and use the same diagnostic criteria as in that study. Tissue was classified in two schemes: non-dysplastic vs. dysplastic and low-risk vs. high-risk, with the latter classification aligned with clinically actionable diagnosis. High sensitivity (non-dysplastic vs. dysplastic: 0.903, low-risk vs. high-risk: 1.000) and NPV (0.930 and 1.000 respectively) were obtained when using the previously established decision boundaries, showing the success of the scanning a/LCI instrument and reinforcing the clinical viability of a/LCI in disease detection.

Fig. 1.

A schematic of the core instrumentation for a/LCI, with Mach-Zehnder interferometer geometry. The probe tip consists of sample illumination via a PM fiber and backscattered light collection with a coherent fiber bundle [16].

Fig. 2.

Optical design for the miniaturized ROTOR. A GRIN lens G1 is butt-coupled to the a/LCI probe lens G0 and 3 mirrors RM1-RM3 form the reflective surfaces. Two identical lenses RL1 form a 4f system that prevents the beam from clipping off of RM2 and a final GRIN lens G2 is used to collimate the fields. The distinctly colored ray paths correspond to optical fields of different angles.

Fig. 3.

Visualization of probe body showing spatial orientation of components. The a/LCI probe tip is the same one as in Fig. 1, with a PM fiber for propagating the excitation beam and a fiber bundle for collecting and propagating scattered light from the sample to the a/LCI system..

Fig. 4.

Physical depictions of the probe components. (A) is a side profile of the actual probe with detachable probe tip. (B) is a 3D transparent rendering of the ROTOR.

Fig. 5.

Representations of the phantom used for scanning a/LCI validation. (A) A volumetric rendering of the four-quadrant phantom, showing location of 8 µm and 15 µm diameter polystyrene microspheres. (B) A map of the a/LCI scanpoints with an overlayed representation of the phantom quadrants in gray. (C) A white light image from the probe tip with the field of view of the instrument outlined in red. (D) A volumetric rendering of the signal intensity at the given a/LCI scanpoints [23].

Fig. 6.

Averaged a/LCI scans for each quadrant of the phantom along with corresponding a/LCI angular scattering and best fit profiles predicted from Mie theory-based ILSA [23].

Fig. 7.

(A) Representative white light image from the probe tip showing transformation zone of the cervix as well as the locations of the 36 a/LCI scanpoints in blue. (B) Representative volumetric rendering of cervix at a/LCI scanpoints in (A). Labeled points correspond to the location of the 4 a/LCI biopsy sites and the averaged nuclear diameter at each quadrant. The cervical os is visualized as a dark spot just under the 12 o’clock data point. (C) Colposcopic image with physician-annotated os outlined in yellow, transformation zone in red, and edge of ectocervix in blue.

Fig. 8.

(A) Representative depiction of patient raw a/LCI scan and (B) angle-resolved intensity profile. The pattern in (B) corresponded to a nuclear diameter value of 11 microns and a nuclear density of 1.073.

Fig. 9.

Comparison of nuclear diameter and density information between non-dysplastic and dysplastic patients.

Fig. 10.

(A) Scatter plot of nuclear diameter and density values computed from Mie theory-based ILSA, with a prospective decision line at 10.5 µm shown in blue. (B) ROC curve for histology-based classification with the prospective decision line represented in blue

Fig. 11.

Comparison of nuclear diameter and density information between low-risk and high-risk patients.

Fig. 12.

(A) Scatter plot of nuclear diameter and density values computed from Mie theory-based ILSA, with classification line shown based on linear discriminant analysis. (B) ROC curve for treatment-based classification with the prospective decision line represented in blue.