Related Experiment Video For a/LCI
Updated: Mar 11, 2026

Implementation of a Reference Interferometer for Nanodetection
Published on: April 26, 2014
Feasibility of clinical detection of cervical dysplasia using angle-resolved low coherence interferometry
Derek Ho1, Tyler K Drake1, Karen K Smith-McCune2
1Department of Biomedical Engineering, Duke University, Durham, NC.
Abstract:
This study sought to establish the feasibility of using in situ depth-resolved nuclear morphology measurements for detection of cervical dysplasia. Forty enrolled patients received routine cervical colposcopy with angle-resolved low coherence interferometry (a/LCI) measurements of nuclear morphology. a/LCI scans from 63 tissue sites were compared to histopathological analysis of co-registered biopsy specimens which were classified as benign, low-grade squamous intraepithelial lesion (LSIL), or high-grade squamous intraepithelial lesion (HSIL). Results were dichotomized as dysplastic (LSIL/HSIL) versus non-dysplastic and HSIL versus LSIL/benign to determine both accuracy and potential clinical utility of a/LCI nuclear morphology measurements. Analysis of a/LCI data was conducted using both traditional Mie theory based processing and a new hybrid algorithm that provides improved processing speed to ascertain the feasibility of real-time measurements. Analysis of depth-resolved nuclear morphology data revealed a/LCI was able to detect a significant increase in the nuclear diameter at the depth bin containing the basal layer of the epithelium for dysplastic versus non-dysplastic and HSIL versus LSIL/Benign biopsy sites (both p < 0.001). Both processing techniques resulted in high sensitivity and specificity (>0.80) in identifying dysplastic biopsies and HSIL. The hybrid algorithm demonstrated a threefold decrease in processing time at a slight cost in classification accuracy. The results demonstrate the feasibility of using a/LCI as an adjunctive clinical tool for detecting cervical dysplasia and guiding the identification of optimal biopsy sites. The faster speed from the hybrid algorithm offers a promising approach for real-time clinical analysis.
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