Prediction of neoplastic progression in Barrett’s esophagus using nanoscale nuclear architecture mapping: A pilot study

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June 29, 2022
Gastrointestinal Endoscopy; 95(6):1239-1246 (2022).
P. Thota*, J. Nasibli, P. Kumar, M. R. Sanaka, A. Chak, X. Zhang, X. Liu, S. Uttam*, Y. Liu* (* Co-corresponding authors)

Background Aims: Nanoscale nuclear architecture mapping (nanoNAM), an optical coherence tomography-derived approach, is capable of detecting with nanoscale sensitivity, structural alterations in the chromatin of epithelial cell nuclei at risk for malignant transformation. Since these alterations predate the development of dysplasia, we aimed to utilize nanoNAM to identify patients with Barrett’s esophagus (BE) who progress to high grade dysplasia (HGD) or esophageal adenocarcinoma (EAC). Methods: This is a nested case control study of 46 BE patients of which 21 progressed to HGD/EAC over 3.7 (± 2.37) years (cases/progressors) and 25 patients who did not progress over 6.3 (± 3.1) years (controls/non-progressors). The archived formalin-fixed paraffin-embedded (FFPE) tissue blocks collected as part of standard clinical care at index endoscopy were used. The nanoNAM imaging was performed on a 5μm FFPE section and each nucleus was mapped to a three-dimensional (3D) depth-resolved optical path difference (3D-drOPD) nuclear representation, quantifying nanoscale-sensitive alterations in the 3D nuclear architecture of the cell. Using 3D-drOPD representation of each nucleus, twelve patient-level nanoNAM features summarizing the alterations in intrinsic nuclear architecture were computed. A risk prediction model was built incorporating nanoNAM features and clinical features. Results: A statistically significant differential-shift was observed in the drOPD cumulative distributions between progressors and non-progressors. Of the twelve nanoNAM features, six – mean-max, mean-mean, mean-median, entropy-median, entropy-entropy, entropy-skewness – showed statistically significant difference between cases and controls. NanoNAM features based prediction model identified progression in independent validation sets, with area under the receiver operating characteristic (auROC) of 80.8% ± 0.35% standard error (s.e.), with an increase to 82.54% ± 0.46% (s.e.), when combined with length of BE segment. Conclusions: NanoNAM can serve as an adjunct to histopathological evaluation of BE patients and aid in risk stratification.‍